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The following hypothetical situation was written by University of Michigan Law School student Joe Hillman. This blog post is to serve as an issue spotter with which our readers should please feel free to engage. Comments or subsequent blog post submissions regarding this issue spotter may address any relevant type of law or policy.

Imagine a very farfetched hypothetical. Let’s say the year is 2035 and you, a proud resident of Arizona, have purchased an autonomous vehicle with SAE Level 3 autonomous capabilities, meaning the vehicle will occasionally need you to take control and drive. While buying the car from the Delaware-incorporated company Alset, you sign an enforceable, albeit boilerplate, contract that contains a choice-of-law clause requiring the application of Delaware law to any contractual dispute. Alset is headquartered in Texas but has effectively lobbied the government of the smaller Delaware to adopt more “flexible” contract law for nationwide technology companies.

In 2037, President Pete Buttigieg signed into law the Umbrella National Autonomous Vehicle Organizations are Devious and Bear Liability Everywhere (UNAVOIDABLE) Act, which among other things, makes autonomous vehicle manufacturers liable for damages caused by an SAE Level 3 vehicle when the driver fails to retake control of their car. Accordingly, Alset’s insurance rate goes up. To lower their premiums, Alset decides to remotely shut off all SAE Level 3 vehicles, which violates their contract with you, their dear customer. You sue Alset for breach of contract in the Superior Court of Arizona. Alset does not object to the forum but calls upon the Superior Court to apply Delaware as the choice-of-law clause in the contract dictates. The 2030 amendments to Delaware’s contract law provide that “a sale contract may be voided if a change in federal regulation makes enforcement impractical to one or more parties.” That statute has always been construed liberally. What are the legal implications or unanswered questions of the aforementioned scenario?

Two infrastructure projects in South Asia were built on the promises of East Asian trading partners and on extensive lines of credit. Though both are characterized by extensive delays, why is one celebrated as an important step forward towards infrastructure modernization, and the other derided as “debt-trap diplomacy”? In Gujarat, India’s preparations for a high-speed train project to connect Ahmedabad and Mumbai are well underway, albeit significantly delayed, based on a debt agreement between Japan and India. Approximately 2,000 miles away, across the Palk Strait, the completion of the Hambantota International Port, financed by commercial loans from Chinese-owned banks, led to consternation when those loans could not be repaid. Much has been written about the Hambantota port – both as a curse and a boon for Sri Lanka. This essay adds to the conversation by comparing and contrasting it with India’s bullet train project. This essay explores the contours of both deals, highlighting the differences in debt terms, political rhetoric surrounding the projects, and their foreign policy implications.  

Debt Terms 

The debt terms of both projects highlight important differences. Japan offered India “a soft loan” of 79,00,00 crore rupees (103 billion USD), approximately 80% of the project, on the favorable interest rate of 0.1%, allowing for a 50-year tenure, and a 15-year moratorium period. The port, however, was built on a “$307 million, 15-year commercial loan with a four-year grace period” and a 6.3% interest rate. The lines of credit for both projects drew both domestic and international attention. The low interest rate that Japan offered to India has been repeatedly highlighted by Prime Minister Modi as a political achievement. In contrast, the high interest rates offered by China are cited as the primary reason for Sri Lanka’s subsequent default on the port, leading to an eventual sale of controlling equity and a 99-year lease on the port. 

Political Rhetoric and Foreign Policy Motivations  

For both countries, the infrastructure projects were, at their inceptions, viewed as straightforward wins. Even when infrastructure projects are delayed and above-budget, as with both the train and port, they serve a different goal: supporting malleable political promises. Politicians are inherently myopic; their promises are characterized by the ebbs and flows of election cycles. In contrast, infrastructure and transportation projects are distinguished by their multi-year plans.

In India, the bullet train was incorporated into Modi’s signature Make In India campaign, and it is unsurprising the line was built to connect Ahmedabad in his native state of Gujarat with Mumbai, India’s biggest financial center. At the inauguration of the train’s construction, he spoke about “his own Ahmedabad.” There are questions too, about whether these projects are needed or essential at all – serving to boost GDP measures and political aspirations, but not contributing to true development. Mahendra Rajapaksa, Prime Minister of Sri Lanka, was born in Hambantota, and building the port there fulfilled his earlier campaign promises about development. In Sri Lanka, the port project outlasted the government that promised to repay the debt. The bullet train may do the same. The next scheduled general election in India (to elect the federal government) is May 2024, and the latest estimate for a fully operational project is October 2028.

Both projects tap into narratives about modernization and economic progress. Speeches made during the inauguration of construction in Ahmedabad spoke about the role trains had played in Japan’s economic progress. The Hambantota port was seen as crucial in terms of both foreign policy and economics, allowing Sri Lanka to more closely align itself with China in opposition to India. The port was also seen as crucial to an image of an advanced maritime economy. Criticisms of both projects point to their lack of commitment to true inclusive development. For example, the India-Japan deal leaves open the question of whether crucial technology transfers are included. Delays in the project can also be attributed to protests by farmers whose lands were appropriated for the project. Similar issues plagued the Hambantota port, which saw frequent violent protests during its construction.  

Conclusion

The story of India’s train and Sri Lanka’s port poses important questions for cross-sovereign-financed infrastructure projects, particularly in low- and middle-income economies. Since the Indian project is far younger than Sri Lanka’s, and is separated by Japan’s comparatively less expansionist foreign policy as compared to China, it remains to be seen whether these differences will lead to success. These projects are particularly ill-suited to the political process because they outlast election cycles, and leave nations holding the bill long after the politicians who promised repayment have moved on. 

Across the country, a number of  transit systems are looking to redefine what it means to take public transportation through facilitating cost-reduction or free transit programs. These programs may contribute to a reduction in pollution and benefit low-income riders by making transportation less expensive and more reliable. Cities in Massachusetts, such as Lawrence, Brockton, and Worcester, have already provided fare-free bus service on certain lines, with Lawrence saying that the trial program is working effectively. 

In Boston’s mayoral race, public transportation was aptly a key issue of interest. Once heralded as the site of the first subway system in the country, Boston’s transportation landscape often equates to lengthy delays, traffic jams, irreplaceably old T cars, and transportation fatigue. Boston’s average city-area driver may spend up to 60 hours in commuter traffic per year. The MBTA has a 7 billion dollar repair backlog, which is unsurprising given the frequency in which reports of fires, the threat of rising seas, and structural issues are found in the news. This figure also mimics the national transit investment backlog of 176 billion dollars predicted by the American Society of Civil Engineers. And this was before the COVID-19 pandemic changed the city’s dynamic. Whether the decline in transportation is due to the booming nature of the city or the lack of investment in infrastructure, it is hard to say. However, it is apparent to many that the current transportation regime is unsustainable. Given the growth of the city, and the increases in the number of jobs that are expected to rise, transportation reform is needed to usher in the city of tomorrow. 

Boston’s situation is not unique. Many big cities in the country are struggling with revitalizing their public transit regimes in a way that is actually viable and efficient for those who need it. While foundational change would likely require a cultural shift towards a great sense of importance for the use of public transportation, the Boston mayoral race provided an interesting occasion to discuss the policies behind free-fare transit, the current financial apparatuses regarding the MBTA, and the question of target ridership. Michelle Wu, the first woman and person of color to be elected mayor of Boston, was inaugurated as mayor on November 16, 2021 following a successful campaign in which she used the catchy slogan “Free the T.” Through this discussion, Wu advocated for starting by making buses free and then incrementally proceeding to make public transportation free in its entirety. Opponents, like former acting mayor Kim Janey, advocated for waiving fares on the line 28 bus, which runs from Mattapan to Roxbury along Dorchester Avenue. Many of the mayoral candidates rightly recognized that access to public transit is an economic justice, racial justice, and social justice issue, but they differ on the way in which this issue can be combated. Anna Essaibi George recommended that essential workers, students, and senior individuals should have free or discounted transit fares, whereas John Barros felt that specific bus lines should be made freely available to low-income passengers. Andrea Campbell supported structural overhaul in the sense that communities should be created where day to day needs can be found within 15 minutes. There was skepticism by residents and political opponents alike about the viability of a free-fare transit program for MBTA buses given that this would equate to a reduction in $60 million in yearly revenue. 

Now that Michelle Wu has won, Boston communities and invested parties are interested in seeing how mass transit is able to change in the city. Until 2021, the Fiscal and Management Control Board controlled transportation reform, with responsibilities including “addressing a lack of long-term vision and strategy, customer focus and accountability to the Government and Legislature.” They have now been replaced by the MBTA, Board of Directors who will be critical in shaping the transportation system of the future. At the beginning of his first term, Governor Charlie Baker brought together a panel of experts who were tasked to provide recommendations on Boston’s public transportation system. While a panel of this nature has not happened since, it may be useful in recruiting outside sources to add to the current MBTA leadership as well as to discuss funding opportunities for improvements. Mayor Wu regularly takes the T herself, noting that it gives her a personal sense of how the systems are operating and their struggles with consistency and regular maintenance. 

If there are to be impactful reforms of the public transportation system in Boston, the critical question is how they will be financed. According to news sources, the MBTA has historically relied on one-time state and federal funds to address maintenance issues. In 2019 and 2020, ticket sales approximately consisted of about a third of the MBTA’s revenue, which begs the question of whether a decrease in this revenue without alternatives would exacerbate the MBTA’s financial concerns. Funding alternatives could include “a local option sales or property tax, or new taxes on fuel providers and ride-hailing services.” However, some scholars suggest that what is really needed is a reliable flow of investment in transportation infrastructure through Congress. This would be similar to infrastructure assistance that States received through the March 2020 CARES Act, but on a consistent basis. 

Representative Ayanna Pressley and Senator Ed Markey of Massachusetts proposed the Freedom to Move Act, explicitly acknowledging the vital nature of public transportation, and the problems with MBTA’s proposed cutbacks on service. This legislation would create a $5 billion dollar grant program to offset fare revenues for transit agencies, but this would likely need to be expanded to effectively mitigate the loss of revenue from free transit. This act is seeking to address transit equity gaps through the goal of improving the quality and safety of transportation service, particularly in low-income and historically underserved communities. This legislation would be impactful but its scope would mean that dollars for cities’ improvements would have to be allocated fairly and hopefully supplemented over time. 

Opponents to a free transit regime argue that attempting to do so would be a fiscal nightmare given the current financial struggles of the public transit system. On the other hand, fare collection and policing is a significant cost for transit systems, which would be completely alleviated if free transit were to exist. However, there is the question of whether free-transit is really an effective solution to the problems of mass transit or rather that the most significant problem is reliable and efficient service, requiring significant system upgrades. This is most pronounced in the sense that if an unreliable bus costs $1.50, and then becomes unreliable but free, the free ticket won’t change the structural concerns with arriving at a particular place at a specific time. This is particularly pertinent for those individuals who rely on public transportation to arrive at their place of employment in a timely fashion. While some opponents to free transit advocate for service improvements and reduced fares for lower-income earners, some supporters of free transit argue for a model with incremental changes, focusing on expanding free transit access gradually over time to defray the costs of improvements.
After analyzing the debates surrounding free public transit, the question becomes how Mayor Wu will strategize to meet one of her campaign goals in freeing the T. As of her first day in office, Mayor Wu launched “a two-year, fare-free program for three popular bus routes  – all of which serve predominantly low-income, nonwhite communities.” This is seemingly to grow momentum for a larger-scale initiative in the future. However, the difficulty is always in the details, and Massachusetts bureaucracy means that the mayor of Boston will not have the necessary power to expand to free-transit without the Commonwealth of Massachusetts’ backing (the state legislature) and the MBTA Board of Directors. In fact, her current program was negotiated as a part of a deal with the MBTA to use COVID-19 relief funding for these efforts. It is hard to say whether cautious optimism is appropriate for Boston with the election of Mayor Wu. While some individuals note that the lack of a consistent stream of income for transportation issues makes significant improvements unlikely, others are more optimistic in the sense that Mayor Wu’s election and catchy slogan may have mobilized voters to be a voice for transportation. What is certain is that transportation reform is necessary, and it is encouraging to see a Boston mayor who recognizes the immediacy of these efforts and strives for a better future for public transit.

Let’s talk about the stigma of the bus. Public transit in the United States is not particularly robust or well-funded compared to its European or Asian counterparts. The American bus system in particular is stigmatized; Americans associate the bus with poverty, crime, and filth. This stigma is not entirely unwarranted, but it has created a self-fulfilling prophecy of sorts. About 40% of buses in the U.S. are in disrepair. 

In Los Angeles, for example, the bus system is painfully underfunded but is in desperate need of a revamp, which has created a cycle of neglect and a decline in middle class users leading to a $861.9 million federal bailout in 2020. Though Los Angeles transit has been in rough shape for a while, the pandemic has sped up the problem since city and county governments temporarily suspended the bus fare, which has been referenced as America’s largest free transit experiment.

Some frequent complaints about the public bus systems are that it is inconvenient, unreliable, unsafe, inaccessible, inefficient, and has poor network integration with other modes of transportation such as the train or micromobility. Moreover, these problems do not impact all communities equally. Continuing with the Los Angeles example, 92% of users are people of color and users had a median income of $12,000 in 2012 and $17,000 in 2019. For readers who are doing the math, not only is $17,000 well below the poverty line, but it’s insidious when compared to the increased cost of living in the city. Coupled with the fact that the bus is in worse shape than other modes of local transportation, it is clear that low-income nonwhite people have worse access to transportation on average and the horrific bus infrastructure is partially to blame.

So, what do we do about the bad reputation of the bus? This question may be related to two blogs the Journal of Law and Mobility has posted recently. On December 23, I wrote about the role of recreation transportation in inspiring creative technology. Then on February 8, Research Editor Namjun Park wrote a blog about clean energy credits and electric vehicles (EVs). It may sound outlandish, but perhaps this is an example of recreation transportation inspiring new ideas about our daily mobility needs, and electrification is a piece of that puzzle.

Though recreation, EVs, and decrepit infrastructure sound like three different ideas, each touches on something important about the bus: the transportation industry has been buzzing about electrifying buses, and people love a “fun” bus. Even the above-linked article from The Atlantic mentions “bus lines of the ‘party’ variety”. Is it possible that electrifying public buses and somehow making the busing experience more enjoyable could increase ridership in a meaningful way? Is it even reasonable to assume that increasing bus ridership is a net positive for public transit? Though it is outside the scope of this blog, it may be important to consider bus fare and what LA’s accidental free transit experiment means for the future of accessible transit as bus fares generally contributes to the infrastructure budget.

First of all, electrifying buses may be a successful strategy for a few reasons. The cleanliness, accessibility, reliability, and network integration complaints could be reduced when new electric buses are introduced and the current units are replaced. With the passage of the recent Bipartisan Infrastructure Law, the United States has $89.9 billion (yes, with a ‘B’!) guaranteed funding for public transit projects over the next five years, which is long overdue considering the Biden Administration estimates there are 24,000 buses in the U.S. in need of replacement. Relatedly, the Biden Administration has placed particular emphasis on electrification as EVs after Biden’s lofty campaign promises regarding the climate crisis and manufacturing jobs. Aside from being politically flashy, electric buses can help combat environmental injustice, which disproportionately impacts poor communities of color; offers a smoother and quieter ride for users, which may promote ridership; and will eventually have lower operating costs than diesel buses, which justifies permanently eliminating bus fare to promote accessibility. 

If revamping and replacing the old, rundown buses with new EV technology does not increase ridership, perhaps local governments must also make the ride more enjoyable for the user. The Atlantic may have mentioned party buses in jest, but the concept has gained popularity in recent years. It seems that people love to watch TV, play video games, socialize, make coffee, or enjoy a cocktail while they are mobile. But the transportation industry has known this for a long time– one of the many appeals of automation has been using time in the car to do productive or recreational activities while the car drives itself. The allure of doing so is relevant to those who rely on public transportation as well. Although arguably those who use the bus have an opportunity to enjoy their coffee or watch a movie on the way to work unlike those who currently drive their own car, the chaos and dilapidation of American public infrastructure is certainly not luxurious. It would be disingenuous to suggest that riding the bus in LA is more relaxing or prestigious than driving one’s own vehicle simply because people on the bus have time to safely watch Netflix on their phones. 

The intersection of all these thoughts forces us to consider whether the stigma around the bus ultimately implies that those who rely on the least expensive means of transportation are simply less deserving of leisure than those who will be able to afford a fully automated vehicle. On the other hand, maybe cities could not eliminate the bus fare if we started advocating for televisions and mini bars to be installed in public buses. The value of a free, accessible bus system for communities with a tight budget certainly outweighs the excitement of making every bus a party bus.

I cannot help thinking, however, there must be a reasonable middle ground. The idea of having luxury options on a free bus is not completely farfetched; we already have movies, video games, lattes, and cocktails for purchase on planes– why not the bus, too? Perhaps there is a way of including optional creature comforts at bus stops or even on the bus itself. If the Bipartisan Infrastructure Bill is truly going to provide for electric buses, why not install televisions in the back of the seat as we already have for decades in airplanes and allow users to choose to pay a few dollars for use? Could we not provide the option to buy a coffee at the bus stop while waiting? Could the proceeds of these luxuries not be collected in an infrastructure account the way traditional bus fare has been for decades? 

As a lawyer, I will not agonize myself (or the reader) by analyzing the tortious nightmare of making every public bus a true party bus, however I will maintain that there could be a feasible way to abolish bus fare while simultaneously making the bus a more pleasant experience for those who have the privilege of choosing to drive their own car. I believe the recent infrastructure legislation, though still not enough money to completely solve the transportation crisis in the U.S., may offer momentum to chip away at the bus stigma. If we can make the bus a cleaner, more reliable, and dare I say even fun experience, maybe ridership would increase so greatly that the inherent value of investing tax dollars in free transit will become undeniable.

As we electrify buses, perhaps every public bus could be a bit more like a party bus. 

This blog is the first in a series about electric vehicles (EVs) in various forms of public and private means of transportation, as well as the unanswered legal and policy questions surrounding electrification. More posts about EVs will follow.

CLEAN ENERGY CREDITS 

            The terms “clean energy credit” or “renewable credit” are used often; but they can refer to different things in different contexts: a tax credit obtained through investment in qualified renewables ventures; or a renewable energy certificate (REC)—generated through producing energy via renewable methods of producing zero-emissions products like electric vehicles (EVs)—that can be sold as a separate commodity to other entities.

TAX CREDITS

            There are a number of federal programs that subsidize investment into renewable energy, but the most famous is contained in the Internal Revenue Code § 30D and can be used by purchasers of “Qualified Plug-in Electric Drive Motor Vehicles” (which include passenger vehicles and light trucks) to offset their tax liability. Each purchaser may subtract $7,500 from his tax liability; when 200,000 units of the qualified vehicles have been sold, the tax credit is gradually reduced quarter-by-quarter until the sixth following quarter, when the credit available to purchasers of each such vehicle is reduced to zero. This federal subsidy program has been crucial in attracting customers to auto manufacturers like Tesla, functioning as a de facto rebate program. 30D was utilized in marketing Teslas to the extent that during Tesla’s tax-credit phase-out period (2018-2020), the company went so far as to guarantee reimbursement to customers if manufacturing delays placed deliveries into reduced-credit quarters and caused purchasers to be eligible for less than the full $7,500 in credits. 

RECs 

            Renewable energy certificates (RECs) are different from renewable tax credits. They are creations of state law, being parts of larger state-enacted climate-change initiatives called Renewable Portfolio Standards (RPS.) These standards are commitments to have a certain percentage or a certain amount of a state’s power production come from renewable sources. For example, the Michigan RPS stipulates that 15% of the state’s power production will be renewably produced by 2021. Renewable usually means something like wind, solar, or other ostensibly clean sources. Currently, 37 states have enacted an RPS or less stringent renewable portfolio “goals.” There are currently no federal RPSs, although they have been proposed over the years in Congress.

            Today, RECs are common parts of RPS policies. In most states, power producers—that generate power from renewable sources more than they are required to by the state’s RPS—may either trade or sell RECs to other parties that may not be meeting their own RPS requirements. Each REC represents one megawatt-hour (MWh) of electricity generated from a renewable energy source. Virtually all RPS programs allow energy producers to unbundle RECs from corresponding renewably-produced electricity and thus to collect double revenue streams. This is meant to funnel capital into the renewable energy sector. Caselaw over the past decade has solidified RECs not merely as ancillary proof-of-work aspects of renewably generated electricity, but as commodities separately generated in the process of renewable power generation. This form of RECs—personal property voluntarily unbundle-able from renewably-generated electricity—has been recognized by many government and nongovernmental organizations, including the Environmental Protection Agency, Department of Energy, Federal Trade Commission, the Climate Registry, the CDP (formerly Carbon Disclosure Project), and Center for Resource Solutions. Most states today have opted to impose “home grown” requirements as well on RECs utilized by entities to comply with in-state RPS standards.

AUTO INDUSTRY

            Today, RECs are granted not only to power producers, but to auto manufacturers. Zero Emission Vehicle (ZEV) programs implemented in California and a handful of other states (Colorado, Connecticut, Maine, Maryland, Massachusetts, New Jersey, New York, Oregon, Rhode Island, Vermont, Washington) grant RECs to auto manufacturers that produce and sell qualifying “zero-emissions” automobiles. Just as in states with RPSs in which RECs are earned and sold by renewable power generators, states with ZEV programs award ZEV credits to manufacturers based on the type and range of the qualifying vehicle sold. Credits are awarded not only for pure EVs (ZEVs), but Transitional Zero Emission Vehicles (TZEVs) as well, which include plug-in hybrids. ZEV credits are worth more than TZEVs, and more credits are earned for selling vehicles with longer ranges. And because of the aforementioned “home grown” requirements of most RPSs, ZEV credits cannot be applied out-of-state to assist in compliance with other states’ RPS requirements; which is why many EVs like the Fiat 500e, VW e-Golf, Hyundai Kona EV, and Kia Soul EV are sold new only in states with ZEV programs.

            There is no consensus among regulators, industry groups, or scholars as to how much RECs are aiding in efforts to transition the world to greener economic habits. However, some private-sector entities have benefited massively from RECs, especially ZEV credits.   

            Tesla has been the most high-profile utilizer of renewable energy certificates in the automotive space. In addition to their use of the IRC § 30D tax credit to market their automobiles, they have also reaped enormous benefits from selling ZEV credits. Their annual Form 10-K filing says: “We earn tradable credits in the operation of our business under various regulations related to zero-emission vehicles (“ZEVs”), greenhouse gas, fuel economy, renewable energy and clean fuel. We sell these credits to other regulated entities who can use the credits to comply with emission standards, renewable energy procurement standards and other regulatory requirements.”

            The 10-K’s Revenue by source section that disaggregates revenue by major source shows that sales of ZEV credits (“automotive regulatory credits”) brought Tesla $419MM, $594MM, and $1.58B of revenue in years 2018, 2019, and 2020, respectively. Tesla, however, showed a profit (positive net income) for the first time in 2020. Tesla showed a net loss of $976MM and $862MM in years 2018 and 2019, respectively; and showed a profit of $721MM in 2020. As a result, market analysts and commentators have noted since that Tesla’s recent profitability is purely attributable to the sale of regulatory credits, without the $1.58B in regulatory-credit-sale revenue, they would not have ended 2020 with $721MM in profit. 

            Short traders Michael Burry (who was the subject of Michael Lewis’s book The Big Short and the movie based on it) have taken large short positions against Tesla, reasoning that a balance sheet sustained by regulatory artifice cannot be sustainable. On the analyst side, commentators like Tim Benson at RealClearEnergy have painted depressing pictures about ZEV programs’ effects on the auto industry’s progression toward EVs. Benson writes that automakers are effectively given two choices: buy ZEV credits from Tesla to fulfill regulatory requirements, or spend billions on EV R&D and maybe one day fulfill regulatory requirements by EV sales. They have mostly chosen to delay EV R&D, instead opting to buy hundreds of millions of ZEV credits from Tesla—because it’s the cheaper option. So ZEV programs have mostly amounted to direct wealth transfers from incumbent auto manufacturers to Tesla. A question we should now ask is whether this arrangement is actually aiding in our societal transition to renewable energy sources and whether the opportunity or transaction costs make the arrangement worth it.

            To start, energy credits systems such as ZEV credits are undeniably spurring investment into renewables. Enterprises focused on renewable energy production and zero-emissions products like EVs have more capital in their coffers than they otherwise would have. If we assume that zero-emissions vehicles like Teslas are truly zero-emissions products (by ignoring the environmental effects of mining required to build EV components such as batteries, nonrenewable power used along every stage of the production process, etc.), then it would seem to be a good thing that an EV market is flourishing as a result of Tesla becoming profitable and staying in business. However, the next (and more important) analytic step is one of costs and benefits. If auto manufacturers other than Tesla were not effectively held hostage by the ZEV credit system and forced to fork over hundreds of millions to Tesla, and if instead they had more of a real choice to invest that money in renewables technology would we maybe be farther along on our journey to a world powered by renewables?

            The empirical data we have so far is worrying, but not dispositive as to the counterfactual question above. The National Renewable Energy Laboratory (NREL) has been tracking voluntary procurements of renewable energy since the 1990s; according to them, the purchase and use of unbundled RECs has grown by over 60 million MWhs between 2010 and 2020. 

            In 2020, sales of unbundled RECs comprised 44.97% of all purchases of renewable energy. Assuming that regulatorily unnecessary purchases of green power did not happen (in other words, no entity purchased more renewable power than they were required to by RPSs), it means that almost half of all RPS requirements imposed on polluters were satisfied using RECs. We can conclude that a corresponding amount of capital was transferred to the renewables sector; however, we can also conclude that RPSs across states had only half the effect they sought in aggregate, because while more renewable energy was produced and purchased than before, only half of RPS requirements was satisfied using actual energy; the other half was satisfied by using an artifice of regulation—RECs.

            In sum: unbundled RECs have become a reality in the regulation of electric utilities and automotive manufacturers; they are undeniably contributing to increased investment in renewables technologies and enterprises; but it remains to be seen whether permitting unbundled RECs to be used to comply with climate initiatives like RPSs is the best—most effective and efficient—arrangement we could have.  

Are you familiar with SAE J3016, the recommended practice that defines, among many other terms, the widely (mis)cited levels of driving automation? You can be! You could read one of the many purported (and often erroneous) summaries of it. You could read my short gloss on it. Or you could read the actual current document by downloading it for free from SAE’s website. Go ahead. I’ll wait.

Let me know when you reach the part about the minimal risk condition (MRC). It’s on page 15 and 38—but don’t skip ahead. After all, you don’t want to miss the important parts about failure mitigation strategy and fallback on page 10. Knowing that “ODD” refers to “operational design domain” will help shortly. Also, all those “deprecated terms” are fun. Okay, ready?

So, as you have now read, MRC is basically where a vehicle stops (and what the vehicle does while stopped) “when a given trip cannot or should not be continued.” At levels 4 and 5, the automated driving system (ADS) rather than the human driver is expected to achieve an MRC.

Years ago, I made two proposals for more clearly defining MRC. The first proposal was to develop a hierarchy of conditions that, depending on circumstances, might potentially qualify as “minimal risk”: stopping in place, in an active lane of traffic, on a narrow shoulder, on a wide shoulder, in a parking lot, in front of a hospital emergency department, and so forth. Happily, there is some progress on this.

My second proposal involved rethinking the relationship between the MRC and the automated driving system (ADS). The current version of J3016 explains that the “characteristics of automated achievement of a minimal risk condition at Levels 4 and 5 will vary according to the type and extent of the system failure, the ODD (if any) for the ADS feature in question, and the particular operating conditions when the system failure or ODD exit occurs.”

My proposal: J3016 should instead define both “attainable MRC” and “expected MRC,” where:

  • “Minimal risk condition” is a vehicle state that reduces the risk of crash when a given trip cannot or should not be completed.
  • Attainable MRC (AMRC) is that state that can be achieved given constraints in the ADS, in the rest of the vehicle, and in the driving environment.
  • Expected MRC (EMRC) is that state that should be achieved given constraints in the rest of the vehicle (excluding the ADS) and in the driving environment—but not in the ADS.

Whereas “attainable MRC” corresponds to how “MRC” is currently defined in J3016, “expected MRC” corresponds to how MRC is often used both outside and even inside J3016.

The key difference is that the EMRC is a function of the vehicle and the driving environment—but not a function of the ADS itself. In other words, the EMRC is a stable condition that is reasonable for the instant vehicle in its instant environment regardless of the intended capability or the current functionality of the instant ADS. If a level 4 feature (more on this in a moment) cannot achieve this EMRC, then it has failed. This does not mean that the ADS should just drive the vehicle off a cliff: It should still attempt to reduce risk, but the resulting AMRC is unlikely to be as safe as the EMRC.

Let’s get concrete. (AC or PCC? Bad joke. Sorry.) A vehicle that stops on a wide shoulder (outside of an active travel lane) with its emergency flashers engaged has reached an MRC as this term is generally understood. The present difficulty comes not from potential MRCs that are more ambitious (such as returning to a maintenance depot) but from potential MRCs that are less ambitious.

In particular: Can being stopped in an active travel lane constitute a minimal risk condition? This is where distinguishing between AMRC and EMRC can help. Consider three examples, each featuring a level 4 feature:

First, if the vehicle’s driveshaft suddenly breaks in heavy traffic, then it may be physically impossible for the vehicle to reach a shoulder. In this case, stopping in an active travel lane (while engaging the emergency flashers and calling for help) could constitute both the AMRC and the EMRC. This is the best thing that a functional ADS could do under the vehicular and environmental circumstances (the EMRC), and this ADS can actually do it (the AMRC).

Second, if a blizzard or crash suddenly renders a narrow roadway impassible for conventional and automated vehicles alike, then it may again be physically impossible for the vehicle to safely reach a shoulder. In this case as well, stopping in the active travel lane (while engaging the emergency flashers and calling for help) could constitute both the AMRC and the EMRC. Again, this is the best thing that a functional ADS could do under the vehicular and environmental circumstances (the EMRC), and this ADS can actually do it (the AMRC).

The third example is where my proposal departs from J3016. If an ADS loses critical sensors in a deer strike, then it may be unable to detect whether the vehicle has a clear path from its current travel lane to the shoulder. In that case, stopping in the active travel lane (while engaging the emergency flashers and calling for help) could constitute the AMRC, because it might indeed be the best that the ADS can do under the circumstances.

In this case, however, the EMRC would be stopping on the shoulder rather than in the active travel lane. The AMRC and EMRC differ in this case because the inability to reach a shoulder is due to an ADS constraint rather than to a constraint in the rest of the vehicle or in the driving environment. In short, the ADS itself has failed. This is not necessarily a condemnation of the ADS (although in many of the common hypotheticals a lack of sufficient redundancy may indeed be a shortcoming) but, rather, a recognition that the ADS was unable to effectively position an otherwise functional vehicle in the given driving environment.

We can analogize these three examples to human driving—at least to a point. A human driver might stop in an active travel lane if a driveshaft breaks or a blizzard makes the road impassable. They might also stop in the active travel lane if they suffer a heart attack or are blinded in a deer strike—but only because humans cannot be designed to perform any differently. In contrast, automated driving systems are being designed to accommodate adverse incidents ranging from software malfunction to hardware loss. Again, this is not necessarily a condemnation of the ADS: Functional safety analysis is based on imperfection rather than perfection. But the inevitability—and even the potential acceptability—of that occasional failure does not negate the failure.

Indeed, J3016 has another term—”failure mitigation strategy”—to describe a vehicle’s response to such a failure. Its definition, however, emphasizes that failure mitigation is exclusively a vehicle function rather than an ADS function. And so here I would distinguish between failure mitigation undertaken by a partially incapacitated ADS (which is within J3016’s scope) and failure mitigation undertaken by a vehicle in the event of a fully incapacitated ADS (which, while beyond J3016’s scope, is certainly within the scope of automated driving design and regulation).

This distinction highlights a big disadvantage to my proposal: Drawing a line between an ADS and the rest of the vehicle is tricky both in theory and in practice. For example, is a brake actuator part of the ADS? Does the answer depend on whether the actuator would also be present in a conventional vehicle? What if the class of vehicle is designed rather than retrofitted for driving automation such that all its systems are closely integrated? As the current definition of failure mitigation strategy illustrates, however, J3016 already draws this line. And, conceptually, this line reinforces the potentially helpful notion of an ADS as analogous to a human driver who drives—or, in the language of J3016, “performs the dynamic driving task” for—the vehicle.

There are, fortunately, some advantages to my proposal.

First, defining EMRC independent of ADS design enables the specification (inside or outside J3016) of a basic floor for this concept: When a trip cannot or should not be completed, then the EMRC entails stopping outside of an active travel lane unless the vehicle (excluding its ADS) or the driving environment prevents this. This is true whether the human driver (at or below level 3) or the ADS (at or above level 4) is expected to achieve this EMRC.

Second, because EMRC is not dependent on ADS design, the EMRC for a poorly designed ADS is not less than the EMRC for a well-designed ADS. If an ADS lacks an adequate backup power supply, then loss of primary power does not affect what the EMRC requires but instead affects whether the ADS can actually meet that expectation.

Third, this floor more clearly distinguishes automated driving levels 3 and 4. An ADS developer that describes an automated driving feature as level 4 promises that the ADS will reliably achieve this EMRC. Again, the failure to meet that expectation does not necessarily warrant condemnation or imply misclassification—but this failure is still a failure. In contrast, an ADS developer that describes a feature as level 3 does not promise that the ADS will reliably achieve this EMRC, which is why human fallback is necessary. If a human does not resume actively driving, a level 3 feature may still try to minimize risk but is not expected to achieve the EMRC.

Without this floor, however, the definition of level 4 becomes tautological. If MRC is merely whatever state the given ADS can achieve under its current circumstances, then the ADS always achieves that MRC. But this is the very definition of level 4, which means that level 3 simply ceases to exist. To put this more concretely: Stopping in an active travel lane is the MRC for an ADS that, by virtue of its own design limitations, necessarily stops only in its current travel lane. An ADS that reliably brings its vehicle to a stop—any stop—when a human does not resume actively driving is therefore level 4. And yet the quintessential example of level 3 has long been a feature that, upon a human driver’s failure to resume actively driving, at least stops the vehicle but does not consistently move it to the shoulder.

Distinguishing EMRC and AMRC fixes this. The EMRC is the same regardless of the level of automation, and the difference is where the expectation falls: At level 3 the human driver is expected to achieve the EMRC, and at level 4 the ADS is expected to achieve the EMRC.

In this way, EMRC more correctly aligns with how J3016 itself currently uses the term “minimal risk condition” to distinguish an ADS that may need a human driver to achieve an acceptable level of risk (i.e., level 3) from an ADS that does not (i.e., level 4).

AMRC, in contrast, would correspond to how J3016 currently defines “minimal risk condition.” This is useful in other ways. For example, it is important to know that stopping in an active travel lane may be the AMRC of a level 3 feature in the absence of human intervention or of a level 4 feature in the presence of a catastrophic malfunction. While EMRC is used to define, AMRC can be used to describe.

Yes, this is complicated. And J3016 is criticized for being complicated enough already. But this is a complicated topic. While public-facing summaries can and should be simplified, the underlying technical definitions need the nuance that credibility and utility demand.

(As an aside: I also recognize that J3016 is long and complicated largely because of level 3. But removing level 3 from the document because it is complex and controversial makes no more sense than removing certain words from a dictionary because they too are complex and controversial. Love it or hate it, level 3 represents a design that some automakers are pursuing. We need terms and concepts with which to discuss and debate it.)

Language matters. In a prior revision, the J3016 authors appropriately recognized the difference between individuals (e.g., “dispatchers”) and companies (e.g., “dispatching entities”). And I hope that the next version also recognizes the difference between a feature’s aspirational level of automation and its functional level of automation—a difference with legal significance. But these are topics for future posts and publications.

And so until then: Automated driving systems never die; they just fallback.

This blog is the forth in a series about facial recognition software in various forms of public and private means of transportation, as well as the greater public policy concerns of facial recognition tools. More posts about the relationship between transportation technology, FRS, and fundamental rights will follow.

As we wrote on October 27th, one of the primary dangers of facial recognition software (FRS) is its impact on the freedom of assembly guaranteed by the First Amendment. FRS is another example of the importance of mobility and surveillance to democratic freedom. Scholars have long emphasized that increased mobility via greater transport options provides an ex ante boost to personal freedom, whereas the electronic or physical marks left by transport can give rise to surveillance and control, which provides an ex post decline in freedom. Thus, while greater mobility can be a boon to democratic liberty, the consequent greater potential surveillance of movement using that transport can counteract that by suppressing the freedom of assembly and association. Therefore, it is crucial to the future of democracy and our constitutional rights that leaders in the mobility space remain aware of potential chilling effects on protected First Amendment activity.

At its zenith, FRS can fuel a surveillance state where the government can locate and identify its citizens, and use those tools to shape every aspect of public life. For years, the Chinese government has used this technology to track and surveille nearly all of its 1.4 billion citizens. If that is not scary enough, the regime has utilized the technology in its genocidal campaign to control, incarcerate, and destroy the Uighurs.

Of course, it’s difficult to imagine this type of situation in the US. However, surveillance  during transportation and in public places is already a fact of life for many Americans; FRS is already a tool used by the Detroit, Chicago, and Pittsburgh police departments. 

A stone’s throw from us at the Law & Mobility Program, Project Green Light Detroit (PGL) is a public-private program by which local businesses set up cameras with video-feeds viewable in real-time by the DPD. The goal is to improve neighborhood safety by speeding up police response times to at-risk locations (inside and outside liquor stores, gas stations, restaurants, medical clinics, and houses of worship). Some of these video cameras may also be connected to a face surveillance system, enabling them to record not only what is happening at a given location, but who is at that location at any given moment. Touting the program’s effectiveness, DPD reports that violent crime has been reduced 23% year-to-date at all sites and 48% at the original 8 sites compared to 2015. However, some commentators cast doubt on the program’s promise, citing research that mass surveillance programs like this generally have only mixed impact if increased in scale.

Moreover, the existence of this capacity to monitor people while they travel through their days may also chill legitimate and valuable speech, running afoul of the First Amendment. Surveillance enables the state to see who citizens associate with and the speech they make or even plan to make. The Supreme Court has found that such requirements to disclose speech and assembly may create an unnecessary risk of discouraging speech, and thus are often unconstitutionally vague and overbroad. Ams. for Prosperity Found. v. Bonta, 141 S. Ct. 2373, 2388 (2021). Such state actions that can indirectly chill speech trigger exacting scrutiny, which requires the policy be narrowly tailored to a sufficiently important governmental interest, although the policy need not necessarily be the least restrictive means of promoting that interest. Id. at 2383-84. In Bonta, the Supreme Court found that California compelling charitable organizations’ disclosure of their Schedule Bs in order to investigate charitable misconduct was facially unconstitutional. Id. at 2378. The court found that the law was essentially “a dragnet for sensitive donor information from tens of thousands of charities each year, even though that information will become relevant in only a small number of cases,” there were alternative ways to investigate fraud, and thus the program mostly just made fraud investigations easier and more convenient by keeping the Schedule B information close at hand. Id. at 2387.

In a constitutional challenge, PGL may run into similar problems to California’s disclosure requirements. The program can be characterized as indiscriminate surveillance not narrowly tailored to the interest of crime prevention, since there are many alternative ways to report or show incidents of crime without real-time video-feeds. The interest in faster police response times may even be characterized as administrative in nature, and that argument may become stronger if the aforementioned concerns about effectiveness of the program as it scales up come true. Such a constitutional challenge is becoming more likely, as FRS receives more scrutiny for its impact on civil rights from commentators and activists. For instance, a Michigan man recently filed a federal lawsuit against the DPD for wrongfully arresting and jailing him based on flawed and racially biased FRS, and civil rights organizations have petitioned the government to prevent using FRS. PGL has already been put to use on disfavored speech; in summer 2020, the media reported allegations that PGL was used on crowds of Black Lives Matter protestors to identify people not social distancing and fine them for violating the governor’s health order, and to identify those with questionable immigration status.

Besides the legal issues, FRS programs like PGL may face resistance from the communities they are supposed to serve. FRS does not just identify criminals; it identifies all people. Thus, PGL not only allows the DPD to identify a mugger outside a liquor store, it also allows the government to watch people in deeply personal moments where they expect privacy, such as going to pray at a house of worship, obtain an abortion at a medical clinic, or receive counseling at a drug rehabilitation center. Protests have been mounted against PGL, and surveys of 130 residents of three cities(Detroit, Los Angeles, and Charlotte) indicated that these people want to be seen but not watched, and expressed discomfort with FRS due to intrusion on their privacy. Therefore, installing FRS in our transportation networks may contribute to making our daily lives safer, but also provides great power that may not only run afoul of constitutional freedoms but also disquiet people’s notions of privacy.

Recreation transportation is an entire industry. We seek different and exciting forms of transportation all the time, and often it’s just for fun. Whether it’s ATVs, jet skis, horseback riding, biking, or walking around a new city to see the sights, transportation is part of all of our recreational activities. This blog will explore how amusement parks design transportation systems, how transportation throughout American amusement parks as a microcosm of innovative transportation policy, and if any lessons can be learned by society from amusement park transportation for implementing new transportation technologies. 

Earlier this year, Vox published an article about how the story of amusement parks is the story of America. Many American amusement parks were inspired by the World’s Columbian Exposition of 1893. For the sake of context, the 1893 World’s Fair was specifically organized to celebrate the 400th anniversary of Christopher Columbus’s voyage and eventual ravaging of North and South America, not the culture of Colombia as the term “World’s Fair” might suggest to many people. The fair was held in Chicago in no small part because Chicago was accessible by railroad. 

The focal point of the Columbian exposition was the White City, which was a huge exhibit of buildings depicting an interesting and (at the time) futuristic community obsessed with transportation, electricity, manufacturing, and living on the go. With all the white and gold structures showcasing technologically advanced processes, “[t]he Columbian Exposition, like the amusement parks and theme parks it inspired, was inspired by the America for which its people longed, not necessarily the America they encountered”.

Amusement parks are a unique recreational experience because they offer an opportunity for people to test their individual limits in a safe, confined, and regulated environment. It’s a form of entertainment that requires participation by those seeking amusement. Margaret King, the director of the Center for Cultural Studies and Analysis, stated, “Theme parks are all about us…. It’s the museum of us, of America. It’s a distillation of the qualities we most value and like about ourselves. [Visiting the Disney Parks] is like going back to your hometown. It’s the hometown that is shared by everyone in the country”. This explanation is eerily similar to how Americans describe driving a car.

This blog has previously considered how to make transportation more equitable, so it is important to briefly note that this feeling of Disney World being the hometown of all Americans is far from reality. Racism, elitism, and exclusion are at the heart of many American pastimes, including visiting amusement parks. Race, Riots, and Roller Coasters by Victoria W. Wolcott explores the history of amusement parks prohibiting Black patrons and the subsequent civil rights initiatives. 

Walt Disney has been accused of being a violent antisemite and passionate racist. Although there is no single example of Disney being a bigot and many claim he was a “product of his time”, it is undoubtable that Disney’s legacy has inspired modern conversations about problematic imagery in the parks. (Though specific attractions are outside the scope of this blog, I encourage any readers who are interested to read a few newspaper articles about the Splash Mountain controversy). Likewise, transportation inequality is an undertone of innovation even when the technology’s inspiration is fanciful. 

Circling back to what amusement parks mean for recreation transportation, the most iconic example may be the Disney monorail. Before Walt Disney’s death in 1966, Disney dreamed of building a city of tomorrow full of futuristic transportation called Project X, which eventually became EPCOT (Experimental Prototype Community of Tomorrow). When Disney World was being constructed in central Florida, transportation infrastructure became a bit more complicated than its California predecessor, Disneyland (which was the first ever American monorail), because the parking lot and the Magic Kingdom park were separated by a lake. Though a boat was probably the obvious choice (and a boat exists today), Disney felt the pressure to deliver an exciting, innovative transportation experience on a monorail. 

Before Project X could be actualized, Disney died and “EPCOT Died Ten Minutes After Walt’s Body Cooled” as newspapers headlined.  On his deathbed, Disney cautioned his successors to make use of the lake so the purpose of the monorail could be to make people feel like they were leaving their real life behind as they were transported into the amusement park. 

Believe it or not, the monorail system in Las Vegas is the same as the one in Disney as the city contacted Bombardier Transportation to build an identical system to the one in Orlando. All this to say that the monorail concept is clearly beloved by vacationers and recreation companies.

If everybody loves the monorail because it’s such an efficient, enjoyable way to travel, why do we not have a larger scale version of the monorail to serve communities’ daily needs when they’re not on vacation? Well, first of all, building the monorail was not as simple as it might seem, even though Disney already owned the land. Difficult construction will never be made easier by a densely populated urban center, for example; adding a monorail in the middle of San Francisco would be quite the feat. 

While there are monorails that operate outside the wonderland of recreational settings, most of those monorails are located in urban centers throughout Asia and can only seat a couple dozen people at a time. Additionally, because a monorail is only a single track, it is difficult for users to switch tracks. For short lines, the monorail works but is not ideal for complicated, city-wide commutes. 

Maybe more importantly, transportation agencies do not like systems that are more expensive than they are useful. A monorail, as stated before, is only one track that runs circularly. For large cities, it makes much more sense to invest in a large, multitrack fleet train. (In all fairness, we still don’t see enough trains in the United States, but that is a different blog). It is more efficient and cost effective to maintain traditional buses or multitrack train fleets that have the same maintenance needs, rather than several single track monorails with different nuances. 

The ultimate question is whether the concept of the monorail would serve the general public’s transportation needs, or if the monorail is best suited for recreational services. The Infrastructure Investment and Jobs Act (known as the Infrastructure Bill or IIJA) approportioned $1.2 trillion to repair and reimagine the deteriorating American infrastructure. This includes $39 billion for modernizing public transit and $66 billion for railways. 

The idea of these two earmarks is to modernize infrastructure, improve accessibility, service Amtrak in the Northeast corridor, and bring rail services to the rest of the country. While the Disney monorail has long been a symbol of Tomorrowland, Walt Disney’s original concept of futuristic transportation is ironically outdated. By nature, tomorrow becomes today which becomes yesterday. The monorail that Walt Disney imagined, which became an iconic symbol of leisure and whimsy, is not necessarily the modern transit system the IIJA is meant to inspire.

Because of the aforementioned shortcomings of monorails, maybe a monorail system is not worth trying to force into typical American infrastructure after the hardfought IIJA has brought some hope back to the transportation industry. A monorail may serve its purpose in Las Vegas and Disney World, but perhaps it is not innovative enough for daily life. However, transportation recreation is valuable for the joy it brings vacationers, even if its utility probably ends with the thrill of escaping reality. 

One thing is for certain: transportation innovation and amusement parks clearly have a long, intertwined history beginning with the Columbian Exposition of 1893. Its clean, white city full of futuristic transportation concepts that inspired amusement parks to become a place where we can live in the future and the past at the same time. Recreation transportation is an opportunity to experience the excitement of innovation even when that innovation isn’t practical because it gets us excited about all the potential of transportation.

Five years to the day after I criticized Uber for testing its self-proclaimed “self-driving” vehicles on California roads without complying with the testing requirements of California’s automated driving law, I find myself criticizing Tesla for testing its self-proclaimed “full self-driving” vehicles on California roads without complying with the testing requirements of California’s automated driving law.

As I emphasized in 2016, California’s rules for “autonomous technology” necessarily apply to inchoate automated driving systems that, in the interest of safety, still use human drivers during on-road testing. “Autonomous vehicles testing with a driver” may be an oxymoron, but as a matter of legislative intent it cannot be a null set.

There is even a way to mortar the longstanding linguistic loophole in California’s legislation: Automated driving systems undergoing development arguably have the “capability to drive a vehicle without the active physical control or monitoring by a human operator” even though they do not yet have the demonstrated capability to do so safely. Hence the human driver.

(An imperfect analogy: Some kids can drive vehicles, but it’s less clear they can do so safely.)

When supervised by that (adult) human driver, these nascent systems function like the advanced driver assistance features available in many vehicles today: They merely work unless and until they don’t. This is why I distinguish between the aspirational level (what the developer hopes its system can eventually achieve) and the functional level (what the developer assumes its system can currently achieve).

(SAE J3016, the source for the (in)famous levels of driving automation, similarly notes that “it is incorrect to classify” an automated driving feature as a driver assistance feature “simply because on-road testing requires” driver supervision. The version of J3016 referenced in regulations issued by the California Department of Motor Vehicles does not contain this language, but subsequent versions do.)

The second part of my analysis has developed as Tesla’s engineering and marketing have become more aggressive.

Back in 2016, I distinguished Uber’s AVs from Tesla’s Autopilot. While Uber’s AVs were clearly on the automated-driving side of a blurry line, the same was not necessarily true of Tesla’s Autopilot:

In some ways, the two are similar: In both cases, a human driver is (supposed to be) closely supervising the performance of the driving automation system and intervening when appropriate, and in both cases the developer is collecting data to further develop its system with a view toward a higher level of automation.

In other ways, however, Uber and Tesla diverge. Uber calls its vehicles self-driving; Tesla does not. Uber’s test vehicles are on roads for the express purpose of developing and demonstrating its technologies; Tesla’s production vehicles are on roads principally because their occupants want to go somewhere.

Like Uber then, Tesla now uses the term “self-driving.” And not just self-driving: full self-driving. (This may have pushed Waymo to call its vehicles “fully driverless“—a term that is questionable and yet still far more defensible. Perhaps “fully” is the English language’s new “very.”)

Tesla’s use of “FSD” is, shall we say, very misleading. After all, its “full self-driving” cars still need human drivers. In a letter to the California DMV, the company characterized “FSD” as a level two driver assistance feature. And I agree, to a point: “FSD” is functionally a driver assistance system. For safety reasons, it clearly requires supervision by an attentive human driver.

At the same time, “FSD” is aspirationally an automated driving system. The name unequivocally communicates Tesla’s goal for development, and the company’s “beta” qualifier communicates the stage of that development. Tesla intends for its “full self-driving” to become, well, “full self-driving,” and its limited beta release is a key step in that process.

And so while Tesla’s vehicles are still on roads principally because their occupants want to go somewhere, “FSD” is on a select few of those vehicles because Tesla wants to further develop—we might say “test”—it. In the words of Tesla’s CEO: “It is impossible to test all hardware configs in all conditions with internal QA, hence public beta.”

Tesla’s instructions to its select beta testers show that Tesla is enlisting them in this testing. Since the beta software “may do the wrong thing at the worst time,” drivers should “always keep your hands on the wheel and pay extra attention to the road. Do not become complacent…. Use Full Self-Driving in limited Beta only if you will pay constant attention to the road, and be prepared to act immediately….”

California’s legislature envisions a similar role for the test drivers of “autonomous vehicles”: They “shall be seated in the driver’s seat, monitoring the safe operation of the autonomous vehicle, and capable of taking over immediate manual control of the autonomous vehicle in the event of an autonomous technology failure or other emergency.” These drivers, by the way, can be “employees, contractors, or other persons designated by the manufacturer of the autonomous technology.”

Putting this all together:

  1. Tesla is developing an automated driving system that it calls “full self-driving.”
  2. Tesla’s development process involves testing “beta” versions of “FSD” on public roads.
  3. Tesla carries out this testing at least in part through a select group of designated customers.
  4. Tesla instructs these customers to carefully supervise the operation of “FSD.”

Tesla’s “FSD” has the “capability to drive a vehicle without the active physical control or monitoring by a human operator,” but it does not yet have the capability to do so safely. Hence the human drivers. And the testing. On public roads. In California. For which the state has a specific law. That Tesla is not following.

As I’ve repeatedly noted, the line between testing and deployment is not clear—and is only getting fuzzier in light of over-the-air updates, beta releases, pilot projects, and commercial demonstrations. Over the last decade, California’s DMV has performed admirably in fashioning rules, and even refashioning itself, to do what the state’s legislature told it to do. The issues that it now faces with Tesla’s “FSD” are especially challenging and unavoidably contentious.

But what is increasingly clear is that Tesla is testing its inchoate automated driving system on California roads. And so it is reasonable—and indeed prudent—for California’s DMV to require Tesla to follow the same rules that apply to every other company testing an automated driving system.

This blog post is written by Akshaya Kapoor, who is a fourth year student in the B.B.A LL.B (Hons.) Programme at the Jindal Global Law School (O.P. Jindal Global University, Sonipat, Haryana, India).

From an International Law perspective, the Vienna Convention on Road Traffic of 1968, which is an international agreement binding over 70 States to uniform traffic legislations, mandates that the driver must be in control of the car at all times. To account for changing trends, the treaty was amended first in 2014 and thereafter in 2016 allowing for automated driving technologies so long as such systems could be overridden or switched off by the driver. Consequently, SAE level 5 vehicles are still impermissible because of the abovementioned prerequisite. That said, several countries have formulated unique regulations for the testing and operation of AVs in their pursuit of embracing the automated future. Admittedly, India is still lacking as against its western counterparts.

One of the largest in the world, the Indian automotive sector contributes a whopping 7.1% to its GDP, in addition to creating jobs, exports and bringing FDI into the nation. Only recently, even Tesla Motors entered the Indian market. However, the country neither has any AV-specific legislations nor is the existing framework very AV friendly or ready. The Motor Vehicles Act, 1988 (“Act”) and its adjoining rules are the principal legislation governing transportation and operation of automobiles in India. The Act does not permit any form of transportation without a human operator. Although the draft Motor Vehicles (Amendment) Bill of 2017 had proposed AV testing, it is pending assent till date. The bigger problem is the apportionment of liability. Currently, the claimant is awarded compensation from the defendant for death or permanent disablement arising out of a road accident, based on the principle of ‘no fault liability’. Being a welfare legislation, the Act ensures the victim receives statutory relief irrespective of contributory neglect or default. 

However, with AVs it will be very difficult to gauge and assess liability going by the aforementioned formula. An accident involving a driverless car may be caused by various reasons such as design and manufacturing defects, software malfunctions and hacking. In such scenarios, the manufacturer or the relevant third-party must be held liable for compensation rather than the owner/operator. Reference can also be made to The Consumer Protection Act, 2019. As per the provision on product liability therein, the manufacturer would be liable to compensate for a faulty product or any deficiencies in service. However, clarifications on the legal personality of AI and whether the technology is a product or a service would be needed. Apart from this, provisions in the Act regarding licensing, testing, and vehicle registration would also require an overhaul. To deal with data protection and cybersecurity, the scope of Section 66 of The Information Technology Act, 2000 (Computer Related Offences) would have to be enlarged to account for AI systems in AVs. 

Keeping aside the legislative hurdles, India faces several grassroot issues as well. Firstly, the country has poor road and transport infrastructure. Secondly, discussions on AI in the automobile industry are in a nascent stage. NITI Aayog’s policy paper titled “National Strategy for Artificial Intelligence”, merely provides that the existing legislations would require sector-specific system considerations, without mentioning the contours. More importantly, Mr. Nitin Gadkari, the Hon’ble Road Transport and Highway Minister, has explicitly declared that he shall not permit fully autonomous vehicles in India. Reason being AVs would lead to unemployment of lakhs of drivers and automotive workers. All these roadblocks make AVs a distant pipe dream in India.

Innovation and technology can be termed as a necessary evil to human progress. The game-changing abilities of AV technology have been discussed at length. On the downside, the transition into the driverless future would be laden with cultural, ethical, social and legal challenges. To develop comprehensive and fair legislations, central governments must collaborate with technology companies and automakers. As a starting point, reliance can be placed on recommendations of the U.S. DOT and the EU Parliamentary assembly, which propose for protecting and promoting core ethical principles of transparency, justice, responsibility, safety and privacy in all AI-related laws.

As for India, insurance, contract and motor vehicle legislations would need serious reconsideration. Furthermore, the country must work on its transport infrastructure besides gauging public interest. Inspiration can be taken from the models in the U.S. and UK to deal with the liability aspect. While employment concerns seem to be another major obstacle, technological advancements can be viewed as an alternative opening to more skilled jobs in the country. Notwithstanding government policy, manufacturers must continue harnessing AI, albeit responsibly. 

This blog post is the third in a series about facial recognition software in various forms of public and private means of transportation, as well as the greater public policy concerns of facial recognition tools. More posts about the relationship between transportation technology, FRS, and modern slavery will follow.

Racism in America has been ingrained for many years now. Though we have come a long way, our history with racism is still very much present in the inner workings of our society, especially when it comes to technology and transportation. So how has the history of our country encouraged tech racism in transportation? In her book Dark Matters: On the Surveillance of Blackness, Professor Simone Brown demonstrates that we can trace the emergence of surveillance technologies and practices back to the trans-Atlantic slave trade

Early surveillance in this country began in the 18th century with the “lantern laws.” Simply put, Black, mixed-race, and Indigenous people carried candle lanterns while walking in the streets after dark and not in the company of a white person so slaves could be easily identified. The “lantern laws” were a prime example of earlier supervisory technology. If these laws were broken, they came with punishments. Not only was this a form of early surveillance, but it was a form of control. The “lantern laws” made it possible for the Black body to be controlled and helped to maintain racial boundaries

In the 1950s and 60s, government surveillance programs like the FBI’s “COINTELPRO” targeted Black people, and it was a systematic attempt to spy on and dispute activists in the name of “national security.” However, recently we have learned that the FBI surveillance program targets so-called “Black Identity Extremists.” Put simply, race plays a major factor in a policy terms such as “Black Identity Extremist” because the FBI attempts to define a movement where none exists. Essentially, a group of Black individuals who are connecting ideologically is considered a threat because they are Black.

We can see how past laws and practices connect to present times. Today, police surveillance cameras are disproportionately installed in Black and Brown neighborhoods to keep a constant watch. Along with the disproportionate rate at which Black and Brown communities are watched, the ACLU says there are additional ways in which the government could misuse cameras including voyeuristic purposes, which have targeted women; spied on and harassed political activists; and even intended criminal purposes. Governmental surveillance programs have been the most recent in a string of periodic public debates around domestic spying. 

Racial bias is a significant factor when it comes to facial recognition technology in transportation, especially when in use by law enforcement agencies. Black people are incarcerated at more than five times the rate of white people. Black people receive harsher prison sentences, Black people are more likely to be held on bail during pretrial procedures, and Black people are dying disproportionately at the hands of the police. Racial biases are still very much present when it comes to the technology that law enforcement agencies use to aid in arrest. 

To start, technology itself can be racially biased. According to Joy Buolamwini and Timnit Gebru, based on their 2018 study, they have brought to the forefront in their research how algorithms can be racist. For example, law enforcement uses digital technology for surveillance and predicting crime on the theory that it will make law enforcement more accurate, efficient, and effective. But digital technology such as facial recognition can be used as a tool for racial bias, not effective policing.

This technology can be beneficial in theory, but when people of color are being misidentified at disproportionate rates, we must reconsider the algorithms and the purpose behind facial recognition. People of color are misclassified over a third of the time, while white people rarely suffer from these mistakes. For example, Joy Buolamwini and Timnit Gebru’s 2018study found that the datasets used to identify people were overwhelmingly composed of lighter-skinned people. Black women are misidentified approximately 35% of the time versus the 0.8% of white men who are misidentified. Additionally, in 2019, a national study of over 100 facial recognition algorithms found that they did not work well on Black and Asian faces.

With many software business models increasingly relying on facial recognition tech, the error-prone algorithms exacerbate the already-pervasive racial biases towards people of color. Moreover, false matches lead to a bigger problem, such as mass incarceration. All it takes is one false match, which can lead to lengthy interrogations, being placed on a watch list by police, dangerous police encounters, false arrest, or worse, wrongful convictions. A false match can come from nearly anything. For example, in New Jersey, Nijeer Parks was arrested for a crime he did not commit based on a bad face recognition match. This bad facial recognition came from the police comparing Mr. Parks New Jersey state ID with a fake Tennessee driver’s license left by the perpetrator.

There is more of a risk factor for people like Mr. Parks, who has a prior criminal record because facial recognition software is often tied into mugshot databases. This amplifies racism further because when a person is arrested and their mugshot is taken by law enforcement, it’s saved in the database. Since people of color are arrested at a higher rate for minor crimes, their faces are more likely to be stored in the databases, which increases the odds of identification and other errors.

Law enforcement agencies and the justice system across the board need to consider that machines can be wrong. Just like humans, algorithms are infallible. For example, recent studies have documented subjective flaws in eyewitness identification of suspects, and those same weaknesses in human judgment can affect the use of facial recognition technologies. There is a human and algorithmic error, but the error rates slip into the design and “training” process when algorithms are tested. Simply put, the NIST tests for differential error rates over different parts of the population show substantial error-rate variations for certain races. As mentioned before, if there are millions of examples of white men in a database and only two Black women, the algorithms will have difficulty distinguishing the faces of Black women. It is not the lack of data training, but the software is less likely to identify features from certain kinds of faces.

Although groups are trying to make surveillance technology better for people of color, we must look at our history as a country, especially regarding tech racism in transportation. Looking back on the “lantern laws” and now facial recognition, government agencies like law enforcement agencies and the FBI are allowed to deploy invasive face surveillance technologies against Black and Brown communities merely for existing. Additionally, racial bias in law enforcement agencies can inform emerging technologies and carry over into the transportation sector. This intersection may be most obvious when we think of interactions such as traffic stops.

There are less obvious connections between systemic racism and FRS in transportation, including access to transportation or failure to recognize pedestrians or riders. Racial disparities within FRS that are used in personal vehicles, rideshares, buses, or trains are not only unfair and unequal, but they are also unsafe. Tech racism could mean that nonwhite people (namely Black people) are locked out of their vehicles, unable to start their vehicles, hit by buses, unidentified by automatic train doors, or unnoticed by safety features such as fatigue prevention at higher rates than white people.

 The Transportation Security Administration has been testing facial recognition technology at airports across the country and expects it to become a preferred method to verify a passenger’s identity. However, according to the National Institute of Standards and Technology, facial recognition software showed a higher rate of incorrect matches between Asian and Black people than white people, even with airport surveillance. The research clearly shows that technology in transportation has had its most significant impacts on people of color who are already dealing with transportation disadvantages. Therefore, if the technology used for transportation continues to reinforce human biases, this will perpetuate inequality as a result.

Facial recognition is a powerful tool for technology. It can have significant implications in criminal justice and everyday life, but we must build a more equitable face recognition landscape. The inequities are being addressed. Algorithms can train diverse and representative datasets, photos within the databases can be made more equitable, and regular and ethical auditing is possible, especially when it comes to skin tone. Though racial bias in facial recognition technology is being addressed, the question remains, should facial recognition technology be banned? There is a historical precedent for technology being used to survey movements of the Black population. Facial technology relies on the data that developers feed it, who are disproportionately white.

This blog post is the second in a series about facial recognition software in various forms of public and private means of transportation, as well as the greater public policy concerns of facial recognition tools. More posts about the relationship between transportation technology, FRS, and modern slavery will follow.

Volume II: Beginning to Think about Modern Slavery and Human Trafficking

This blog post is the next in our series about facial recognition software (FRS) in transportation technology. This time, we will begin considering whether facial recognition software can be a meaningful tool for combatting modern slavery and human trafficking. The two most pressing questions regarding this topic are: first, is FRS an impactful tool in combating slavery and trafficking and, second, what are the relevant slavery risks?

Before we begin to think about either of these questions, let’s think about what slavery and trafficking mean in the context of transportation technology. It is important to understand that there is disagreement among experts about the best working definitions of slavery and trafficking. The definitions we will use here are not absolute. When we use the term “modern slavery”, we are generally talking about the exploitation of humans for personal or financial gain using deceit, force, or abuse of a person’s vulnerability. Modern slavery could be in the production of our clothing, manufacturing of our cars, harvesting of our food, or in forced sex work, for example. Human trafficking, though often conflated with modern slavery, is defined by the United Nations as “transportation, transfer, harbouring or receipt of people through force, fraud or deception, with the aim of exploiting them for profit”.

Turning to the effectiveness of FRS, the short answer is that FRS has helped identify and rescue survivors of slavery and trafficking. There are tools such as Spotlight, which use image processing to scan missing persons’ photographs and search through databases of online sex ads. Spotlight is owned and operated by Thorn, which is an organization that seeks to use technology to promote safety. Thorn focuses primarily on combatting child sex trafficking and child pornography.

Spotlight has helped identify victims 60% faster than searches that do not include FRS and has identified over 17,000 missing children since 2016. The idea is that sex work is often advertised online, and Spotlight is able to match photographs of sex workers with photos in databases of missing persons to identify which ads include children. In the case of adults, such FRS services could identify people who may be participating against their will based on who has been reported missing.

Hypothetically, using FRS in different means of transportation could help identify missing persons more quickly because recognition could occur during transit rather than after a person has already been forced to perform labor or has been advertised for sex online. Additionally, as society moves towards automation, victims of modern slavery and human trafficking will have less and less contact with other humans during transportation who may have otherwise been able to identify a problem. Consequently, FRS could not only replace that safety net, but also do so more quickly and accurately. However, this hypothesis assumes many things about the technology, such as which database the FRS uses, how the images in that database are collected, the accuracy of the analysis, and the ability to intervene. 

Thorn has partnered with Amazon Rekognition to power Spotlight as it has become a tool for law enforcement agencies. Frankly, this partnership is the first consideration of our second question. Because the implementation of FRS in the transportation sector for this purpose is speculative at this point, it is important to consider the relevant risks to vulnerable communities.

This is where things get complicated. Amazon has a long history of serious allegations about abusing employees ranging from labor law violations at best to modern slavery at worst. These claims include factory and warehouse employees urinating in bottles during their shifts because they were discouraged (or even not permitted) to use the restroom. Reports also note at least one person dying of heat exhaustion and dehydration. 

Amazon’s alleged treatment of its employees is troubling because it creates a difficult dynamic; actors who have contributed positively to the fight against slavery and trafficking may also be participants in these egregious practices. Modern slavery and human trafficking are so prominent that an estimated 40 million people are currently enslaved, and almost every individual consumes goods or services produced by slave labor. Each of us has a slavery footprintbecause many companies upon which we rely have slavery somewhere in their supply chain. But what does all of this mean for the impact and risks associated with facial recognition in vehicles?

Truthfully, upticks in slavery have been deeply correlated with every major transportation innovation from roads to ships to rubber tiresVolkswagenPorscheGeneral MotorsMercedes-Bens, and BMW each capitalized on the Holocaust by producing wartime material for Nazi Germany or utilizing forced labor from concentration camps. These are concepts that will be explored further in later blogs. For now, the important question is what does the dark history of these companies have to do with using FRS in different modes of transportation?

Well, put simply, FRS in various modes of transportation could be a great tool to combat modern slavery and human trafficking, but there will be obstacles related to public opinion, the right to privacy, technology racism, agency rulemaking, and legislative drafting. Relatedly, the issue of unethical labor practices by technology and car companies may leave a poor taste in the mouths of consumers who could be left wondering if investing in FRS is simply a public relations stunt when thousands of workers have historically been exploited at the hands of the very same companies. 

For this reason, transparency will be important from both private companies as well as municipalities interested in implementing FRS in public transportation. It is also important to note that most of the aforementioned companies have not only become more transparent about their role in the Holocaust, but also paid reparations (see thisVolkswagen example). 

This point is important because by pointing out this complicated dynamic of entities that have facilitated and now want to combat slavery and trafficking, we are not embarking on a witch hunt to find hypocrites, but rather shedding light on the very complicated web of how modern slavery that has touched nearly every facet of society. Recognizing this relationship does not mean those entities cannot be part of the solution, but it does mean we must anticipate some standoffishness from the public, particularly affected communities, and should be used as something of a lesson about the potential role of the private sector in fostering a solution.

We will address potential legal avenues throughout this series, but one option is federal legislation. Federal human trafficking laws and regulations are nothing new in the United States and date back to The Mann Act of 1910 (which was problematic in its own right, but the beginning of this story nonetheless). The Victims of Trafficking and Violence Prevention Act (TVPA) has been reauthorized three times since it was originally passed in 2000, and was expanded upon in 2005 and 2008 in light of more available research, including technological advancements and the power of the internet era.

State and federal agencies could also regulate FRS as a tool to combat slavery and trafficking. Many federal agencies have invested in FRS studies for various purposes, including a Department of Transportation study on eye tracking to gauge the safety of commercial drivers, train conductors, and air traffic controllers. Interestingly, the Department of Transportation has also proudly led the Transportation Leaders Against Trafficking initiative for nearly a decade. The purpose of the initiative is to connect transportation and travel industry leaders to maximize the industry’s impact on trafficking through training, public outreach, funding, and pledges, meaning the relationship between executive agencies, legislatures, and industry is clear. All three are working to develop FRS, combat slavery and trafficking, and implement transportation technology; it is time for these seemingly unrelated initiatives to overlap.

This blog is merely here to introduce the complicated intersection between transportation technology, FRS, and modern slavery. Various perspectives and further analyses of the legal history and potential legal solutions will follow.

This blog post is the first in a series about facial recognition software in various forms of public and private means of transportation, as well as the greater public policy concerns of facial recognition tools.

Volume I: An Introduction

What is the point of facial recognition software in vehicles? For that matter, what is facial recognition software? We use it to unlock our iPhones and tag our loved ones in photos on social media, but facial recognition software can also serve a variety of functional purposes throughout society, such as identifying suspects of violent crime or survivors of modern slavery. One of the most sensational questions surrounding facial recognition software in vehicles is how we can protect individuals’ privacy.

Facial recognition software is a form of biometric security. It is used to determine people’s identity using their faces from photos, videos, or even real time. Put simply, a camera scans the face and, once the face is detected, the software begins to analyze the image. Analysis converts the image to data based on the person’s facial features; think of this as turning the face into a type of equation. The software then tries to find a match by comparing the face to images in a database.

Though the technology may make people uneasy, it is important to conceptualize that this technology has been public for a while. Mercedes-Benz first introduced the Mercedes-Benz User Experience (MBUX) at the beginning of 2018, which is considered one of the most comprehensive automaker-created infotainment centers to date. Among other features that enhance the driver experience, MBUX includes facial recognition that senses the driver’s fatigue or discomfort, in which case the system will change the music or climate control features to prevent falling asleep behind the wheel. 

MBUX also has a voice recognition feature called “Hey Mercedes”, which is very similar to the in-home listening devices such as Alexa and can help drivers dial a phone call or input a destination into the navigation system without removing their hands from the steering wheel. Jaguar Land Rover has been using facial recognition since 2019 to similarly read driver fatigue with the ultimate goal of implementing machine learning to track the driver’s alertness and patterns of discomfort. 

In addition to personal vehicles, facial recognition software may be used to monitor rideshare vehicles to offer a safer experience. Uber has already been using facial recognition to determine if drivers were wearing their masks throughout the pandemic. The Uber app previously used facial recognition to identify the driver before each ride began, and the mask verification was an extension of that feature. Experts have also talked extensively about the potential safety benefits of facial recognition on public transportation. Companies such as FaceFirst aim to use facial recognition on or around public transit to identify domestic terrorists, child abductors, missing persons, survivors of modern slavery and human trafficking, people on ‘Do Not Fly’ lists, and deter petty theft. 

All of this is to say that facial recognition software in vehicles may be used to create a safer and more comfortable transportation experience. But what are some potential concerns of facial recognition technology, and how do we reconcile those concerns with some of the potential benefits? 

It is impossible to explain the huge variety of concerns people have about introducing more facial recognition, but one major concern is data breaching. Clearview AI, for example, is a facial recognition software company that touts itself as “the world’s largest facial network”, which currently sells its product to law enforcement agencies to “generate high-quality investigative leads”. Last year, Clearview was breached by hackers who were able to obtain access to about 3 billion images (some of which were scraped from social media which is a distinct violation of most social media platforms’ terms of service). This instance has raised serious concerns about how individual’s photos are obtained, how the images are stored, and who has access to those images.

A second concern is racism. Tech racism is a very large topic that certainly deserves its own blog post. As an overview, it is important to note that facial surveillance is largely used by law enforcement agencies, which is already a dynamic loaded withracial bias. Joy Buolamwini and Timnit Gebru’s 2018 research concluded that facial recognition software misidentifies Black women approximately 35% of the time but only misidentified white men 0.8% of the time. A false match can result in a wrongful arrest, a wrongful conviction, or even violence. Moreover, facial recognition used by police rely on mugshots databases for identification, which exacerbates racist policing patterns of the past because Black people are the most likely to be arrested due to over-policing. Because Black people are disproportionately likely to have mugshots in existing databases, current facial recognition software being used by law enforcement is more likely to get a match for Black faces. Coupled with the fact that the software is less likely to correctly identify Black features, the disproportionately high number of Black mugshots in the databases ensures that Black people are matched more frequently with less accuracy. This could especially be a problem for instances of traffic stops and crowd control.

Finally, there are many unanswered constitutional questions about the right to privacy and freedom of assembly. A handful of police departments, including Pittsburg law enforcement, have used facial recognition software to scan crowds of protesters to identify who in the crowd has outstanding warrants and arrest them accordingly. On Last Week Tonight, John Oliver described this practice as “the most insidious way” to prevent people from exercising their First Amendment right to assemble freely. Moreover, there are countless privacy questions about facial recognition in public spaces, including rideshare services and public transit that remain unanswered. Ultimately, people may not want to be under surveillance when using public or private means of transportation for a variety of reasons, and public policy will have to reflect the balance to be had between intelligence and privacy.

The aforementioned uses and concerns are far too abundant to address in a single blog post. As such, this blog post will be the first in a series of pieces that consider the role of facial recognition software in transportation technology and how we can reconcile its incredible potential as a safety tool and the relevant civil rights issues. In this series, we will seek to parse out some of the nuances of facial recognition software in privately owned vehicles, rideshares, and public transportation to consider how to best implement the technology widely.

Among the institutions and industries that took a big hit during the pandemic was mass transit, both financially and reputationally aspects. IFinancially, income sources for mass transit have plunged, since state and local income tax revenue has decreased due to uncertain market conditions, and fare revenue has dropped precipitously because transit ridership fell by 79% nationally as a result of the pandemic and lockdowns. Transit programs have also lost valuable social capital; the belief that mass transit is unsafe and unsanitary has skyrocketed since March 2020 (as evidenced by public surveys in the US and New Zealand), and experts project that these beliefs may be durable and outlast the pandemic. Thus, this drain on mass transit’s resources may be long-lasting, and poses a serious danger to mass transit’s future. 

In choosing how to proceed, leaders in the transportation space may have to prioritize which values are most important to them: public health, technological advancement, or political prowessdimensions. Evidence regarding the impact of lockdowns of mass transit on people’s daily lives, focusing on urban and suburban communities, emphasizes that the pandemic’s impacts have fallen most heavily on socioeconomically disadvantaged populations. Therefore, the political considerations of social justice and equity should have a central place in the planning of mass transit in cities and suburbs going forward, since these are the primary populations affected.

Although ridership of mass transit declined across the board, it declined the least in areas with more “essential” jobs and lower percentages of white, educated, and high-income individuals. Thus, public transit remains most relevant to the lives of people with lower socioeconomic status and with jobs that were deemed “essential” during lockdowns. As researchers have written, this research suggests that the inevitable adjustments to public transit should be based on socioeconomic qualities, and keep a higher level of services in areas with higher concentrations of vulnerable people. This policy implication is further bolstered by research finding that women and disabled people’s access to essential services (grocery shopping, commuting to work, and taking care of or supporting family) were disproportionately affected by the pandemic’s impact on mass transit. Furthermore, somewhat ironically, the public health measures of the pandemic resulted in many people deferring or forgoing essential services like healthcare because of difficulties traveling to the location of healthcare, especially if they are non-white, disabled or low-income. 

The research seems to clearly show that the pandemic had its greatest impacts on people already dealing with transport disadvantage: people of color, disabled people, poor people, and service workers. Therefore, in planning for the future of mass transit, leaders should prioritize the needs and concerns of these populations over and above economic and technological considerations. This only makes sense as a matter of political economy, because these are the people using these resources.

The Law and Mobility Project is eager to announce the beginning of a new thematic initiative. For the next two years, the Project will focus on the relationship between transportation technology and modern slavery. Specifically, the Project will consider how transportation technology can be used as a tool to combat modern slavery and human trafficking.

Ultimately, the Project seeks to analyze how transportation technologies can be used to combat exploitation by addressing systemic failures. One of the goals of the Project is to consider how to successfully implement transportation technology into society in a way that helps (rather than harms) populations who have historically experienced less access to transportation and have been systemically vulnerable to trafficking and modern slavery.

We are striving to make the Project a principal resource for scholarship, discussion, and examination. To be as holistic as possible, the Project will aim to address transportation law and policy issues from the perspective of different communities. Because this topic is very complex, the Project seeks to use an interdisciplinary approach to identify opportunities in a variety of fields.

In addition to the Journal of Law and Mobility, the Project will include blog posts, speakers series, and a reference guide to identify obstacles and share possible solutions as new transportation technology is implemented throughout society. In the second year of the human trafficking concept, the Project will host a conference to discuss the relevant legal questions and build a repertoire of meaningful resources. 

We will be looking to answer a series of questions, such as: How can CAVs create greater mobility access for marginalized communities? How can we use historical lessons about transportation technology and slavery to implement CAVs in the most ethical way possible? How will new transportation technology support marginalized people’s ability to move in dignified ways? What are some unanswered social challenges that new transportation technologies will create, and how can we try to get ahead of unknown obstacles? 

Although we will be examining how transportation technology can be used to combat modern slavery and human trafficking, we will continue to make the Project a resource for a wide variety of transportation technology topics in addition to our new focus.

Relevant areas of specialization might include disability rights, the rights of sex workers, racial justice, urban development, technology law, employment law, legislative drafting, environmental justice, products liability, transportation law, or administrative law. We are also interested in connecting with those who work in engineering, software development, and other fields related to the development of transportation technology. This list is far from exhaustive. 

We are eager to connect with you about fields that have not been listed to foster a richer, more comprehensive analysis of the challenges and opportunities presented by transportation technologies. Please let us know how we may be of assistance for your transportation technology work.

We are looking for expertise in relevant areas of law and technology in addition to other disciplines. If you are interested in sharing resources or collaborating with the Law and Mobility Project as a specialist in any adjacent field, please reach out at LawandMobility@umich.edu

If you have an article to submit for potential publication in the Journal of Law and Mobility, please submit your work here

Although we are looking for articles for the journal, we are also interested in compiling multimedia materials such as blog posts, Q&As, video interviews, or any other format that may be of interest to you. Please reach out to us if there is another format that may best showcase your work — we are happy to help facilitate a variety of creative resources.

As someone who has thought about cybersecurity for some time, including in previous posts on this blog, the recent events around the hack of the Colonial Pipeline has been front of mind, and not just because I live in Washington, D.C., where gas stations have been running out of fuel. The incident is yet another dramatic demonstration of how cyberattacks can cause serious real-world damage. As more and more of our transportation system becomes connected to computer networks (both vehicles and infrastructure) cybersecurity is becoming just as important issue as the physical safety and security of our roads and vehicles.  

Government Response

The Colonial Pipeline attack comes at a time when the Biden Administration and Congress have both turned their attention to cybersecurity. In the House, lawmakers have proposed $500 million in funding to help state and local governments protect themselves from cyberattacks, while other legislators have been discussing laws that require companies to report cyberattacks they suffer to the government and the public. Such rules would give the government greater insight into attacks and allow them to better coordinate responses when cybercriminals attack more than one company or industry. Making attacks public would also give the public a better idea of how the companies they patronize are protecting their data and products. At the same time, President Biden signed an executive order that will require all software sold to the federal government to meet set security standards. Given the sheer amount of buying power the U.S. government has, that means consumers will also likely benefit from the order, as companies up security in their products to make them competitive for government purchase.

The Colonial attack will also put more scrutiny on the Transportation Security Administration (this is the same TSA that confiscates your water bottles at the airport). While the U.S. Department of Transportation oversees the regulation of pipelines (via the Pipeline and Hazardous Materials Safety Administration), the TSA (part of the Department of Homeland Security) is tasked with helping pipeline owners protect their infrastructure from cyberattacks. In a 2018 report the government’s General Accounting Office (GAO) released a report on weaknesses in the TSA’s pipeline security efforts, including cybersecurity. As the fallout from the Colonial attack continues, the TSA’s infrastructure security will no doubt face some tough questions.

Issues for Transportation Technology Overall

Pipelines are far from the only part of our transportation system that is at risk of being hacked. Last June automaker Honda’s internal network was compromised, leading the company’s factories across the globe to shut down for a day or more. Journalists and hackers alike have shown how a vehicle’s onboard computers can be compromised in a number of ways. More recently, the European Union Agency for Cybersecurity issued a report that identified autonomous vehicles as “highly vulnerable to a wide range of attacks.” The complexity of AVs (and driver assistance systems) and the myriad of computer systems within them is part of why they make a tempting target. Issues also arise as vehicles become more networked – meaning a failure to connect to an outside server can limit a car’s capabilities, as has been reported with some Teslas at times. As AVs and connected vehicles of all kinds proliferate, along with connected infrastructure, the number of failure points or avenues of attack multiple, something that will keep engineers up for years to come.

One good thing that may come from the Colonial Pipeline incident is the centering of cybersecurity in our discussions over infrastructure and transportation. Especially as the White House and lawmakers continue to negotiate a potentially massive investment in infrastructure, addressing the cybersecurity ramifications will be vital. Likewise, the current surface transportation reauthorization (a bill that funds the U.S. DOT and highway projects) will expire on September 30, giving Congress a second opportunity to include cybersecurity issues into the greater transportation policy discussion.

Last year I wrote about Uber and Lyft’s battle against a California law that required them to treat their drivers as employees, rather than contractors. Then, in November, California voters passed Prop. 22, which exempted app-based drivers from that law, something Claire covered in detail. Two recent actions from the Biden Administration, which has positioned itself as pro-worker and pro-organized labor, indicate that the fight over how to classify gig workers is far from over, and that the administration will throw their weight toward increasing the rights of gig workers. These actions come as Uber, Lyft, and other emerging transportation companies reckon with their labor practices overall, amid a changing atmosphere as we emerge from COVID lockdown.

Administration Moves

Last week the Department of Labor withdrew a Trump-era proposed rule change governing the definition of “independent contractor.” The Trump Administration’s proposed change would have deemphasized a number of factors that are used in deciding a worker’s classification, which would have weighted considerations toward classifying workers as independent contractors. By pulling the rule before it can go into effect, the existing rule, with six factors for consideration, remains in use under the Fair Labor Standards Act. This move comes in the same week in which the Secretary of Labor, Marty Walsh, voiced his support for gig workers being considered as employees and receiving benefits, like health insurance, in “a lot of cases.” While that’s far from a definitive course of action, when combined with the regulatory changes, the Secretary’s words indicate the Federal government will be paying attention to the classification fight going forward and is putting its weight behind pro-worker options. I’ll also note that in March Uber announced it will categorize its UK drivers (which total more than 70,000) as employees, bringing them into compliance with a recent court decision – meaning Uber is facing labor changes on both sides of the Atlantic.

Uber and Lyft Need Drivers

While Uber and Lyft gird themselves for possible regulatory changes, they are also dealing with a shortage of drivers. In 2020 COVID lockdowns and the continued threat of the virus (along with the threat of monstrous customers…) cratered demand for rideshares, leading many drivers to move on from ridesharing. Now, with demand for rides growing as the world opens back up, both companies find themselves in need of more drivers and having to turn to financial incentives to recruit them. On the ground the shortage has raised prices and increased wait times for users.

At the same time as they have been recruiting more human drivers, both Uber and Lyft have purged their in-house development of automated vehicles. In December, Uber sold its automation efforts over to automated vehicle developer Aurora for roughly $4 billion. Then last month Lyft offloaded it’s automation program to a Toyota subsidiary for $550 million. For a long time the conventional wisdom was that the end-goal of the ridesharing companies was to automate their fleets and escape from having to deal with human employees (or contractors). Yet given that automation is still years away from widespread deployment and that only a few major corporations can afford the long term development costs of AVs, it seems Lyft and Uber are cutting their losses. That said, if they can survive COVID losses and changing demands, I’m sure they’ll be first in line to buy production AVs.

Emerging Tech and Emerging Labor Issues

Of course, Uber and Lyft are far from the only transportation-tech related companies with labor issues that have become apparent over the past year. Last year, as grocery deliveries exploded in popularity, Amazon drivers were coming up with unique ways of ensuring they got a crack at incoming orders – hanging their phones from trees as close to a Whole Foods as possible. The idea was that by leaving phones closer to the building they would be the first to be offered a delivery job via the gig-app Amazon Flex. Depending on your point of view this is either ingenious, or demonstrative of the gig economy pitting workers against each other. More recently Amazon has taken flack for making the delivery drivers who operate Amazon branded vans (yet are wait for it… contractors…) sign biometric consent forms. The forms give Amazon permission to use cameras and sensors to monitor drivers “100%” of the time they are working, in the name of safety, as the system can give audio alerts to drivers in real time. I can’t imagine that an AI-enabled camera that can yell corrections at you as you drive is anyone’s ideal boss, but here we are.

The gig economy is clearly not going away anytime soon, even if some gig jobs become automated. And now there is momentum for dealing with the employment issues around these companies and their platforms. Just where that momentum takes the labor market, and how it may change the relationship between platforms and workers, remains to be seen.

Last week I wrote about how a recent crash in Texas is illustrative of a serious issue with Tesla’s Autopilot feature. As a refresher, Autopilot is an advanced driver-assistance system (ADAS), meaning it can take over a number of driving tasks and help protect drivers, but a human is supposed to remain focused on the driving task. Failures within the Autopilot system have contributed to several fatal accidents, and Tesla drivers have at times abused the system, using it to operate their vehicle while sleeping, or when they were passed out due to drinking. But these incidents shine a light on bigger problems with Autopilot and ADAS systems in general – problems of public perception in regards to the capabilities of these systems and the lack of regulation dealing with them.

Public Perception

The first consideration in regards to Autopilot and the rest of ADAS/AV development is the question of the public’s perception of Autopilot and just what the technology can actually do. While some of these incidents are no doubt caused by drivers intentionally pushing the limits of the Autopilot system, others are likely cases of “mode confusion” – something previously seen in fighter pilots. Fighter aircraft can have multiple different modes of automation, and to prevent confusion pilots are highly trained to understand the capabilities and limits of each mode available in a given aircraft. The same is not true for drivers, especially when marketing materials and manuals are unclear or make a vehicle out to be more autonomous than it really is. Indeed, a German court recently found that Tesla’s claims about Autopilot were misleading, in a suit brought by a watchdog organization (of which several German automakers are members…). Indeed, the name “Autopilot” seems tailor-made to confuse consumers, though Tesla founder (and soon to be Saturday Night Live host?) claims the name is apt, as aircraft autopilot systems always require supervision. While that may be true, one does wonder how many Tesla owners or potential Tesla owners are up on aircraft operation procedures.

The issue is compounded by Tesla’s introduction of further automation technology and software, including what they call “Full Self-Driving” (FSD). While Tesla’s website and their manuals do state that a driver must be “fully attentive” the danger of confusion is clear (enough that the California DMV, which regulates AVs in that state, had to press Tesla to explain just what FSD did and why Tesla believed the DMV shouldn’t regulate it like other AV systems. It also doesn’t help that the systems in place to monitor drivers using Autopilot can rather easily be tricked, meaning that it’s extremely likely some drivers are intentionally circumventing the vehicle’s safeguards.

Problems for AV and ADAS development and deployment arise if Tesla’s incidents become the face these systems to the public. Tesla has a well-earned image as an innovative company, having pushed the electric vehicle market into a new era, and Autopilot is almost certainly preventing accidents when used properly, just as other ADAS systems do. But if all that cuts into the public consciousness is high profile abuses and deadly accidents, that could set back public trust of automation and harm the industry overall.

Lack of Regulation

There is a very important piece of the puzzle left to talk about – the government’s role in regulating Autopilot and vehicle automation overall. Much has been discussed in this blog about the lack of overall AV regulation, and ADAS has fallen into the same situation – namely the technology is out on the road while safety regulations remain in the draft folder. As I mentioned last week, the National Transportation Safety Board (NTSB), in its 2019 investigation of an Autopilot-related crash, took to task the government’s primary vehicle safety regulator, the National Highway Traffic Safety Administration (NHTSA), for failing to generate clear ADAS safety rules. During the Trump administration, NHTSA remained extremely hands off on generating new rules or regulations regarding ADAS. In 2016, Obama-era NHTSA regulators had indicated that “predictable abuse” could be considered a potential defect in an automated system, which could have flagged Autopilot misuse, but that guidance wasn’t followed up. It remains to be seen if the Biden administration will pivot back toward regulating automation, but given that ADAS accidents continue to occur and garner a lot of attention, they may be unable to ignore it for long. For now, state-level regulators can attempt to fill the gap, as seen in the California DMV emails linked above, but their power is limited when compared to the federal government.

It’s hard to tell how all of this will end. Tesla seems uninterested in pulling back and testing their automation systems in more controlled environments (as other automakers do), and instead continues to push out updates and new tech to the public. Perhaps that level of bravado is to be expected from a company that made its name in challenging the existing paradigm, but that doesn’t excuse the fact that the Federal government has yet to step in and lay down clear rules on ADAS systems. For the sake of the promising safety-benefits of ADAS and automation overall those rules are needed soon, not only to protect the public, but to ensure confidence in these emerging technologies – something that would be to the benefit Tesla and other automakers.

P.S. – I’ll leave you with this – a perfect illustration of absurdity of how vehicle features are named.


By Matthew Wansley*


Human drivers are a menace to public health. In 2019, 36,096 Americans were killed in motor vehicle crashes, and an estimated 2.74 million Americans were injured. Most crashes aren’t “accidents.” The National Highway Traffic Safety Administration estimates that driver error is the critical reason for 94% of crashes. The deployment of autonomous vehicles (AVs)—likely in the form of robotaxis—will make transportation safer. AVs will cause fewer crashes than conventional vehicles (CVs) because software won’t make the kinds of errors that drivers make. AVs won’t drive drunk, get drowsy, or be distracted. They won’t speed, run red lights, or follow other vehicles too closely. They will drive cautiously and patiently. AVs will consistently drive like the safest human drivers drive at their best.

But AVs could be even safer, I argue in a forthcoming article, The End of Accidents (forthcoming in the U.C. Davis Law Review). AVs could be designed not only to avoid causing their own errors, but also to reduce the consequences of errors by human drivers, cyclists, and pedestrians. AVs can monitor their surroundings better and react more quickly than human drivers. AV technology has the potential to make better predictions and better decisions than humans can. AVs could be designed to anticipate when other road users will drive, bike, or walk unsafely and to prevent those errors from leading to crashes or make unavoidable crashes less severe. As long as AVs share the roads with humans, improving AV technology’s capability to mitigate the consequences of human error will save lives.

Liability rules will influence how much AV companies invest in developing safer technology. Existing products liability law creates insufficient incentives for safety because AV companies can reduce their liability for a crash by showing that the plaintiff was comparatively negligent. A comparative negligence defense will be a powerful liability shield because the kinds of errors that human drivers make—violating traffic laws and driving impaired—are the kinds of errors that human jurors recognize as negligence. A liability regime with a comparative negligence defense only creates incentives for AV companies to develop behaviors that AV technology has already mastered: driving at the speed limit, observing traffic signals, and maintaining a safe following distance. It won’t push AV companies to develop software that can reliably anticipate human error and take evasive action.

Data from real-world AV testing shows that AVs are rarely causing crashes but are failing to avoid plausibly preventable crashes. In October 2020, the leading AV company, Waymo, released a report of every contact between its prototype robotaxis and other vehicles, bicycles, or pedestrians during its 6.1 million miles of autonomous driving in 2019. At the current stage of testing, Waymo’s AVs usually have a backup driver behind the wheel, ready to take over manual control if necessary. Waymo’s report includes every actual contact during autonomous operation and every contact that would have happened, according to Waymo’s simulation software, if the backup driver hadn’t taken over manual control. If the report is reliable, almost every contact in the 6.1 million miles involved human error. In fact, in most cases, it’s not even arguable that the AV made an error that contributed to the contact.

Waymo’s report also reveals, however, that its AVs sometimes fail to avoid plausibly preventable crashes caused by human error. Consider the scenario depicted below. Late one night in 2019, a Waymo AV was travelling in the left lane of a divided road in the suburbs of Phoenix. A CV was traveling in the wrong direction in the right lane veering towards the AV. The backup driver took over manual control. According to Waymo’s simulation, if the backup driver hadn’t taken over, the CV would have crashed head-on into the AV. The force of the collision would have caused the AV’s airbag to deploy. The AV would have braked, but not swerved out of the way. The CV’s driver likely wouldn’t have swerved out of the way either because the driver was likely “significantly impaired or fatigued.”

Head-On Collision from Waymo Report

Waymo doesn’t clarify whether its backup driver was able to avoid a crash. But it’s quite possible that the backup driver was able to avoid it. Evolution has armed humans with a powerful survival instinct. The backup driver should have had room for evasive maneuvers on the wide suburban road late at night. Yet Waymo’s AV software—software that would drive 6.1 million miles without causing a crash that same year—wouldn’t have prevented an apparently preventable head-on collision.

Consider the simulated crash from a liability perspective. Suppose there had been no backup driver, and the vehicles collided. Assume, consistent with the report, that the driver of the CV was drunk. Would the drunk driver prevail against Waymo in a lawsuit? Almost certainly not. The question itself sounds absurd. Drunk driving that results in a crash is negligence per se. Waymo’s comparative negligence defense would dispose of the case. Because Waymo would avoid liability for the crash, it would have little incentive to develop technology that could prevent a similar crash in the future.

Now consider the same simulated crash from a social welfare perspective. Would the social benefits of technology that could prevent a crash like this exceed the cost of development? Likely yes. Drunk driving is common. Drivers, impaired or not, sometimes drive in the wrong direction. AV technology’s ability to monitor the environment more consistently and react more quickly gives AVs advantages over CVs in responding to impaired drivers. If AV companies invest in developing better behavior prediction and decision-making capabilities, they could design AVs that would dramatically reduce the social costs of drunk driving. AVs could become superhuman defensive drivers, preventing not only crashes like this one but also crashes that now seem unpreventable.

Investments in developing safer AV software will be highly cost-effective because the software will be deployed at scale. When an AV company develops code that enables its AVs to prevent a crash in a certain kind of traffic scenario—and doesn’t make them less safe in other scenarios—it will add the new code to the software that runs on all the AVs in its fleet. The improved code will prevent a crash every time one of the company’s AVs encounters a similar traffic scenario for the rest of history. As engineers change jobs or share ideas, the fix will spill over to other AV companies’ fleets. From a social welfare perspective, the return on investments in developing safer AV technology will be tremendous.

AV companies will only develop AV technology’s full crash prevention potential if they internalize the costs of all preventable crashes. But determining which crashes could be efficiently prevented with yet-to-be developed AV technology would be exceedingly difficult for jurors, judges or regulators. AV technology may achieve safety gains not just by mimicking the behavior of an expert human driver but by exhibiting emergent behavior—behavior that would seem alien to a human observer. The better approach is to treat all crashes involving AVs as potentially preventable. In The End of Accidents, I defend a system of absolute liability for AV companies that I call “contact responsibility.” Under contact responsibility, AV companies would pay for the costs of all crashes in which their AVs come into contact with other vehicles, persons, or property unless they could show that the party seeking payment intentionally caused the crash. No crash involving an AV would be considered an accident.[1]

Contact responsibility would align the private financial incentives of AV companies more closely with public safety. AV companies will collect massive amounts of data on driver, cyclist, and pedestrian behavior as their fleets of AVs passively record their surroundings. Contact responsibility will push AV companies to sift through that data to find opportunities to prevent crashes efficiently. In many cases, the solution will be developing safer technology. If a company’s AVs are frequently being hit in intersections by CVs that run red lights, the company might develop software that can more reliably predict when CVs won’t stop at traffic signals. In other cases, the solution may be deploying AVs differently. The company might plan routes for its robotaxis that avoid especially dangerous roads at certain times of day. In still other cases, the solution may be political. The company might use its money to lobby for protected bike lanes, mandatory ignition interlocks, or the development of a vehicle-to-vehicle communication network.

Contact responsibility might sound radical because it would insulate human drivers from tort liability for crashes they cause negligently or even recklessly. One might worry that this would create a moral hazard risk. But liability plays at most a modest role in deterring unsafe driving. Human drivers tend to cause crashes by breaking traffic laws and driving impaired. Under contact responsibility, the civil and criminal penalties for those violations would continue to provide deterrence. Drivers would also still face liability for crashes with other CVs, cyclists, and pedestrians. They would still face the possibility that their insurers would raise their premiums after a crash with an AV, even though they weren’t held liable, because the crash indicated they had a higher risk of crashing with a CV. Most importantly, drivers would still want to avoid the risk of injuring themselves or others. Contact responsibility wouldn’t diminish those deterrents. It would simply target liability incentives where they will be most useful: AV companies’ investment decisions.

In recent years, several scholars have proposed reforms to adapt tort law to crashes involving AVs.[2] The debate has yielded valuable insights, but it has been conducted almost entirely from the armchair. Now that data on AV safety performance is publicly available, it’s possible to make more informed predictions about the real-world consequences of different liability rules. The data suggest that AV crashes will follow a predictable pattern. AVs will rarely cause crashes. But they will fail to avoid plausibly preventable crashes caused by other road users. Therefore, it’s critical for liability reform to address whether AV companies will be responsible when a negligent or reckless human driver causes a crash with an AV. Scholars who have considered the issue of comparative negligence have advocated retaining some form of the defense.[3] In fact, the leading reform proposal expressly rejects AV company responsibility for “injury caused by the egregious negligence of a CV driver, coupled with minimal causal involvement by the [AV].”[4] I argue that absolving AV companies from responsibility for those injuries would be a mistake. Contact responsibility is the only liability regime that will unlock AV technology’s full crash prevention potential.


[1] For crashes between AVs, I endorse Steven Shavell’s “strict liability to the state” proposal. See Steven Shavell, On the Redesign of Accident Liability for the World of Autonomous Vehicles 2 (Harvard Law Sch. John M. Olin Ctr., Discussion Paper No. 1014, 2019), http://www.law.harvard.edu/programs/olin_center/papers/pdf/Shavell_1014.pdf.

[2] See generally Kenneth S. Abraham & Robert L. Rabin, Automated Vehicles and Manufacturer Responsibility for Accidents: A New Legal Regime for a New Era, 105 Va. L. Rev. 127 (2019); Mark A. Geistfeld, A Roadmap for Autonomous Vehicles: State Tort Liability, Automobile Insurance, and Federal Safety Regulation, 105 Calif. L. Rev. 1611 (2017); Kyle D. Logue, The Deterrence Case for Comprehensive Automaker Enterprise Liability, 2019 J. L. & Mobility 1; Bryant Walker Smith, Automated Driving and Product Liability, 2017 Mich. St. L. Rev. 1;David C. Vladeck, Machines Without Principals: Liability Rules and Artificial Intelligence, 89 Wash. L. Rev. 117 (2014).

[3] See, e.g., Mark A. Lemley & Bryan Casey, Remedies for Robots, 86 U. Chi. L. Rev. 1311, 1383 (2019).

[4] Abraham & Rabin, supra note 2, at 167.


* Matthew Wansley researches venture capital law and risk regulation as an Assistant Professor of Law at the Benjamin N. Cardozo School of Law. Prior to joining the Cardozo faculty, he was the General Counsel of nuTonomy Inc., an autonomous vehicle startup, and a Climenko Fellow and Lecturer on Law at Harvard Law School. He clerked for the Hon. Scott Matheson on the U.S. Court of Appeals for the Tenth Circuit and the Hon. Edgardo Ramos on the U.S. District Court for the Southern District of New York.

Earlier this month, two Texas men died when the Tesla Model S they were traveling in crashed into a tree. However, just what led to the crash remains a point of contention between authorities and Tesla itself. The police have said that one passenger was found in the front passenger-side seat, while the other was in the back – meaning at the time of the accident, there was no one in the driver’s seat. That would indicate that the vehicle’s “Autopilot” advanced safety system was active, though last week Tesla CEO Elon Musk claimed that the company had data indicated the system was not in use at the time of the accident. The investigation is ongoing, and local police have said they will subpoena Tesla to obtain the vehicle data in question.

If the Texas case does turn out to have involved the Autopilot feature, it will be far from the first. In May of 2016, a Florida driver was killed when his Tesla, in Autopilot mode, crashed into the side of a semi-truck. The National Highway Traffic Safety Administration (NHTSA) investigation into that incident found no evidence of defects in the Tesla system, placing responsibility primarily on the driver, who wasn’t paying attention to the road while the vehicle operated under Autopilot. The National Transportation Safety Board (NTSB), on the other hand, put more of the blame on Tesla for allowing the driver to misuse the Autopilot features – i.e. that the system didn’t disengage when being used outside of its recommended limits. Then Secretary of Transportation Anthony Foxx echoed this when he made a point to say that automakers like Tesla had a responsibility to insure consumers understand the limits of driver assistance systems. In March 2018, a California man was killed when his Tesla Model X SUV crashed into a highway safety barrier, leading to a NTSB investigation and a lawsuit from the driver’s family. A third driver died in a 2019 accident while Autopilot was enabled, this time again in Florida.

At issue here is not only the safety of the Autopilot technology, but also the way it has been marketed, and the willingness of drivers to push the system beyond its capabilities. At its core, Autopilot is an advanced driver-assistance system (ADAS), meaning it can take over a number of driving tasks and help protect drivers, but a human is supposed to remain focused on the driving task. Over the years Tesla has upgraded their vehicle’s software to recognize things like stoplights and stop signs, starting with beta tests and then making their way into every Tesla on the road that is capable of supporting the update (though there have been humorous issues with these roll outs – like vehicles confusing Burger King signs for stop signs). In late 2020, Tesla rolled out a “Full Self-Driving” update to select vehicles, which expanded autopilot’s operational domain to local streets (previously it was only useable on highways).

The NTSB has taken Tesla to task over Autopilot not only for the aforementioned 2016 crash, but also for a 2018 crash were a Tesla ran into the back of a stopped fire truck (no one was hurt). In that incident, Autopilot had been engaged for 13 minutes before the crash, and the driver had been distracted by their breakfast coffee and bagel. In its investigation of the 2019 Florida crash, the NTSB again cited Tesla’s failure to ensure Autopilot couldn’t be used in situations outside of its designed domain, and pointed to NHTSA’s failure to generate clear safety rules for ADAS technologies. In other cases Autopilot has continued to operate while a driver sleeps, or was passed out due to drinking (requiring police officers to use their cars to force the vehicle to a stop).

What remains in question is the ability of Tesla vehicles to monitor human drivers and keep them engaged in the driving process. A recent Consumer Reports test illustrates how easy it can be to trick the existing monitoring system and even allow a driver to slip into the passenger seat while in motion. Tesla’s system for testing driver interaction is via the steering wheel, while some other automaker systems, like GM’s Super Cruise, use more direct observation via eye tracking cameras.  It’s clear there is an issue with Autopilot that needs further investigation, but what have governments done in reaction to these issues, beyond the NTSB reports we noted? And what issues are raised by the way Tesla has marketed Autopilot to consumers? I’ll explore both of those issues in my next post.  

Last week, Claire wrote about how Fourth Amendment precedents and facial recognition technologies could allow law enforcement to use AVs and other camera-equipped transportation technologies as a means of surveillance. In that post she mentioned the case of Robert Julian-Borchak Williams, who last year was arrested by the Detroit Police Department based on faulty facial recognition evidence. The same day Claire’s post went up, law students from Michigan Law’s Civil Rights Litigation Initiative, along with the Michigan ACLU, sued the City of Detroit in Federal court for false arrest and imprisonment in violation of Mr. Williams’ rights under the US Constitution and the Constitution of the State of Michigan.

Given the growing use of facial recognition technology by law enforcement (including in the pursuit of the January 6th insurrectionists) cases of misidentification and wrongful arrests like Mr. Williams’ will no doubt continue to occur. Indeed, there is longstanding concern about facial recognition systems misidentifying people of color – due in large part to their designer’s failure to use diverse datasets (i.e. diverse faces) in the training data used to teach the system how to recognize faces. Beyond the digital era camera technology itself has built in biases, as it was long calibrated to better capture white skin tones. As cameras become more ubiquitous in our vehicles (including cameras monitoring the driver) issues of facial recognition will continue to collide with the emerging transportation technologies we regularly discuss here.

With all of that in mind, let’s turn to a recent case in Massachusetts that gives us a good example of how vehicle camera data can be used in a criminal investigation. On December 28, 2020, Martin Luther King, Jr. Presbyterian Church, a predominantly Black church in Springfield, MA, was destroyed by arson. Last week, the U.S. Department of Justice brought charges against a 44 year old Maine man, Dushko Vulchev, for the destruction of the church. Just how was the FBI able to identify Mr. Vulchev as a suspect, you ask? Thanks to video footage from a Tesla vehicle parked near the church on the night of the fire. When Mr. Vulchev damaged (and later stole) the Tesla’s tires, the vehicle used its onboard cameras to record him in clean, clear footage (you can see the photos in this Gizmodo post on the case). Tesla vehicles are equipped with a number of cameras and a feature called “Sentry Mode,” which remains turned on even when the vehicle is parked and otherwise inactive. If the vehicle is damaged, or a “severe threat” is detected, the car alarm will activate and the vehicle’s owner will be able to download video of the incident beginning 10 minutes before the threat was detected. In this case, this video footage was instrumental in identifying Mr. Vulchev and placing him near the church on the night of the fire.

While the FBI didn’t use facial recognition software in this case (as far as we know), it still illustrates how the quantity and quality of vehicle generated material will continue to be of interest in future investigations. How long before law enforcement proactively seeks video footage from any vehicle near a crime scene, even if that vehicle was otherwise uninvolved? If more OEM’s turn to Tesla’s camera-based security features, could we face a feature where every car on the block becomes a potential “witness?” Further, what happens when the data they produce is fed into faulty facial recognition software like the one that misidentified Mr. Williams? We live in an era of ever-more recording and our vehicles may soon be just another device watching our every move, whether are aware of it or not.  

In light of the 2021 Law and Mobility Conference’s focus on equity, the Journal of Law & Mobility Blog will publish a series of blog posts surveying the civil rights issues with connected and autonomous vehicle development in the U.S. This is the fourth and final part of the AV & Civil Rights series. Part 1 focuses on Title VI of the Civil Rights Act. Part 2 focuses on the Americans with Disabilities Act. Part 3 focuses on Title II of the Civil Rights Act.

Your data says a lot about you, and widescale adoption of connected and automated vehicles (AVs) will create mountains of data that says even more. Based on location data alone, AV companies may know where you live, where you work, what you like to do in your free time, who you hang out with, and possibly even your religious and political beliefs. And, again, this is just based on location data; AV companies will also have extensive records of your biometric and financial information. Overall, AVs can provide constant and near-comprehensive surveillance. So what happens when the government gets access to surveillance collected by private companies and relies on it in criminal investigations?

This was the real-life nightmare of Robert Julian-Borchak Williams, a Black man in the Detroit area who was arrested and charged for a crime that he didn’t commit. A facial recognition algorithm employed by the Detroit Police Department matched his face to a surveillance image from a robbery. Williams is known as the first person arrested as the result of a bad algorithm.

As of fall 2020, at least 360 police departments use facial recognition technologies, 24 use automated data analysis tools, and 26 use predictive policing measures, which aim to identify crimes before they happen by relying on historical data (which has been shown to be racially discriminatory and ineffective). Over 1,000 police departments use surveillance drones, which were deployed to track down and arrest Black Lives Matter protestors last summer. If AVs become a part of this network of technologies, this surveillance will become even more invasive, particularly for Black passengers and pedestrians that both police and artificial intelligence tend to manifest bias towards.

This trend of warrantless surveillance is constitutionally dubious. The Fourth Amendment protects U.S. persons from “unreasonable searches and seizures” without a warrant. Courts have considered surveillance to be an “unreasonable search or seizure” if it invades a reasonable expectation of privacy. The scope of Fourth Amendment protections was narrowed in United States v. Miller and Smith v. Maryland, where the Supreme Court held that there is no reasonable expectation of privacy if information is purposefully provided to third parties. In these cases, the Court held that the government could obtain bank records and transactional phone call data without a warrant because that information was consensually relayed to third parties (namely, bank and phone companies). However, this third party doctrine was abrogated in 2015 in United States v. Carpenter, when the Supreme Court held that a warrant was required to collect over four and half months’ worth of cell-site location information (CSLI) for the defendant, a robbery suspect. The Court noted that, if third party doctrine were applied to CSLI, “[o]nly the few without cell phones could escape . . . tireless and absolute surveillance.”

The Carpenter framework could be applied to AVs, based on the potential comprehensiveness of AV surveillance; the intimate information that AV surveillance could reveal; how cheap it would be for the government to rely on AV for both ongoing and retrospective surveillance; and the questionable level of voluntariness through which AV users would “provide” their information to companies. Thus, the application of the Carpenter framework to AV by judges is one way to avoid the incorporation of AVs into the surveillance state. On the legislative side, we could see a comprehensive federal privacy bill soon. However, policing is squarely in the state and local purview, and it is hard to say how much a federal law could reach into these surveillance issues as both a legal and a practical matter.

States like California and Virginia already have comprehensive privacy laws on the books that protect consumers with certain rights, including the right to know what data is being collected about them by large, private companies, and the right to opt out of the sale of personal information by these companies. However, government and nonprofit entities are explicitly exempt from these laws. Moving forward, privacy laws should include protection from government overreach, not just corporate overreach.

AV companies can certainly take action as well. Around the time of the Williams arrest, Amazon, Microsoft, and IBM announced that they would pause or stop offering their facial recognition data to law enforcement. These moves were largely symbolic, as police mostly rely on companies that are not household names for their data. In the AV context, company policies against warrantless surveillance and partnerships with law enforcement could provide users with some peace of mind.

Throughout my Civil Rights Series, I have emphasized the importance of data transparency so that agencies like the Department of Justice’s Civil Rights Division can easily track and investigate discriminatory impacts of AVs. “Transparency,” however, cannot be a mechanism for extending the surveillance state to these vehicles. Our increasingly connected and data-driven transportation systems cannot throw our privacy rights under the (connected and automated) bus.

By Christopher Chorzepa and Phillip Washburn


Week 2 of the 2021 Law and Mobility Conference opened with a discussion, moderated by C. Ndu Ozor, focusing on a variety of topics: inequalities and equity issues in our transportation system, how to prevent new transportation tech from exacerbating these issues, and how new tech can potentially help correct injustices. 

Dr. Regan F. Patterson began the panel by highlighting that automobile-dominated systems have destructive impacts on Black people and communities, and that we must explicitly consider impacts on racial violence during the transition to other technologies. Dr. Patterson highlighted how cars are frequent sites of violence against Black people, as seen in the interactions between police and George Floyd, Sandra Bland, and countless others. Citing pieces by Tamika Butler and Brentin Mock, Dr. Patterson stressed that policymakers and developers of shared electric and automated vehicles (SEAVs) must explicitly think about whether this technology can make transportation safer for Black people and diminish racial violence. 

Sadly, transportation planning has long not accomplished these goals. It has been used as a tool of oppression, deliberately targeting Black communities. Highway construction destroyed Black neighborhoods and placed heavily trafficked highways closer to communities of color, resulting in environmental justice concerns due to high levels of emissions contributing to poor health outcomes. Further, Dr. Patterson framed climate change as a racial justice concern, since its impacts fall unevenly on the most vulnerable communities. She expressed a desire for a transportation system that reduces Black harm, affirms Black life, and ensures livable Black futures.

Dr. David Rojas-Rueda focused on how transportation policies and technologies shape public health. Dr. Rojas said that emerging transportation technologies should consider impacts on human health, focusing on how they impact urban design (surroundings and ability to get places affects health), human behavior (physical activity affects health), disease, and mortality from accidents. Examining micromobility, Dr. Rojas found that substitution to e-scooters — from bikes, public transit, or cars — may result in different impacts on health based on the current transportation composition of the city. 

In Atlanta, substitution to e-scooters was harmful because of increased risk of traffic fatalities and reduced physical activity. In contrast, it was beneficial in Portland because e-scooters were associated with fewer traffic incidents. Examining SEAVs, Dr. Rojas said that human health impacts will vary based on how we handle the transition. He highlighted that SEAVs might affect health by increasing autonomy of those who cannot drive (children, elderly, and disabled folks), reducing road deaths and injuries (although this would result in reduced organ donations), present presently unknown risks from increased exposure to electromagnetic fields, reducing stress from driving (but potentially increase stress through time spent working while commuting), and increasing use of alcohol and drugs (through reduced need for designated drivers). Dr. Rojas emphasized that we need to prioritize the deployment of SEAVs in low-income areas because road injuries and deaths tend to be more common in disadvantaged areas, and these communities have traditionally been underserved by transportation planning. Thus, the increased autonomy and reduced risk of road accidents from SEAVs would greatly benefit human health in disadvantaged neighborhoods.

Robin Chase stressed two problems: (1) there is an “unseen fifty percent” of the population that does not have access to safe and reliable transportation because they do not have a driver’s license or access to a car, or they do not have the money to gain access to a car or other form of transportation; and (2) whereas we used to have a background reality of a right to mobility, we have now made it safer to cross the ocean in a plane than to cross the road in an automobile, so that the unseen fifty percent is now unable to move without being subjected to high risk of injury or death. 

Ms. Chase proposed that we fix these problems by increasing access to shared mobility. She added that shared mobility would also have equity benefits, since using shared mobility would increase physical activity (putting a dent in the obesity epidemic, which disproportionately affects BIPOC), reduce the volume of traffic accidents (which also disproportionately affects BIPOC), and reduce emissions (climate change disproportionately affects BIPOC). Thus, she proposed that the government shift spending priorities away from SEAVs to public transit. Ms. Chase finished her presentation stressing the equity benefits derived from the implementation of emerging transportation technology while emphasizing the potential abuse for user data surveillance purposes assembled from digitized travel.

In discussion, the panelists highlighted that transportation inequities often exacerbate housing and employment inequities, and stressed that transportation and housing must be planned together to achieve the best outcomes for racial, health, and economic equity. Dr. Patterson noted that transit systems have often been used to facilitate gentrification and suburbanization, and stressed that there needs to be a solution like van-pooling services to get between housing centers and transit hubs to deal with these problems. 

The panelists agreed that disadvantaged communities need to be prioritized during transportation planning because transit improvements need to benefit everyone, not just affluent communities. Because public transit is used more intensively than SEAVs, government spending priorities need to shift if we want to do the most good for the most people. To that end, the panelists set a goal of allowing poor and Black people to safely live car-independent lives, rather than our current focus on providing subsidies to already rich people. For instance, we provide tax incentives to put solar panels on your home (benefitting homeowners) and buy an electric vehicle (benefitting car-owners).

The final issue considered by the panelists was how much startups and smaller companies should be regulated to pursue equity goals. Dr. Patterson stated that equity needs to be inserted into business models from the beginning because it traditionally has been ignored and led to inequitable outcomes. Otherwise, biased outcomes can be programmed into automated systems. Dr. Patterson firmly believed that switching course mid-stream is not feasible, and equity needs to be a primary consideration at the outset. Further, Dr. Rojas felt that policymaking should be proactive and made in an interdisciplinary function, incorporating equity and innovation concerns.

On the other hand, Ms. Chase felt that there should be a two-tiered regulation scheme with more onerous equity regulations for large companies and less red tape for startups. Ms. Chase emphasized that part of the problem faced by transportation startups is that they are not financially rewarded for their positive externalities on equity, while cars do not have to pay for the emissions, parking, and road damage they cause. Thus, she stated that companies with low volume and slim profit margins should receive less regulation so that they may grow and innovate. 

The question of when the government should require companies meet certain transportation goals is an important one. Soft-regulation can foster innovation, but may leave blind spots that persist past initial stages. Early and consistent regulation may end some startups before the get going, but would ensure the companies that survive have the right goals. Regardless of when it enters the stage, it is important that equity be part of all transit solutions.

In light of the 2021 Law and Mobility Conference’s focus on equity, the Journal of Law & Mobility Blog will publish a series of blog posts surveying the civil rights issues with connected and autonomous vehicle development in the U.S. This is the third part of the AV & Civil Rights series. Part 1 focuses on Title VI of the Civil Rights Act. Part 2 focuses on the Americans with Disabilities Act. Part 4 focuses on the Fourth Amendment.

As Bryan Casey discussed in Title 2.0: Discrimination Law in a Data-Driven Society, there are a growing number of studies that indicate racial disparities in wait times, ride cancellation rates, and availability for rideshares and delivery services like Uber, Lyft, and GrubHub. Given that, for the most part, humans are behind the wheel in these cars, these disparities are the aggregate result of both conscious and unconscious biases. Drivers can choose where they pick up passengers, meaning that neighborhoods associated with marginalized demographics have less cars available at any given moment. Drivers may see a passenger’s name and decline that passenger based on assumptions about their race. The passenger rating system is also a challenge. Drivers may—again, consciously or unconsciously—be more judgmental of a black passenger than a white passenger when rating them between 1 and 5 at the end of a ride. Ratings can undermine users’ ability to nab a car quickly and can even get users kicked off of platforms.

As Uber and other companies transition to connected and automated vehicles (AV), they have promoted the artificial intelligence (AI) that these vehicles will rely on as the solution to what they frame as a very human problem of bias. However, as growing numbers of studies are showing, AI can be just as discriminatory as people. After all, people with biases make machines and program algorithms, which in turn learn from people in the world, who also have biases. As the Wall Street Journal recently reported, “AI systems have been shown to be less accurate at identifying the faces of dark-skinned women, to give women lower credit-card limits than their husbands, and to be more likely to incorrectly predict that Black defendants will commit future crimes than whites.” And when AI is discriminatory, this can manifest on a broader scale than when it is just one discriminatory person behind a wheel. Accordingly, switching from human drivers to computer drivers will not end transportation access issues based on racial disparate impact, absent a concerted effort by AV companies, and perhaps by the government, to fight algorithmic discrimination.

Where does the law enter for this type of discrimination? It isn’t clear.

Title II of the Civil Rights Act of 1964 broadly mandates that all people in the U.S., regardless of “race, color, religion, or national origin,” are entitled to “full and equal enjoyment” of places of public accommodation, which are defined as any establishments that affect interstate commerce. Access to transportation undoubtedly affects participation in interstate commerce. And yet, as Casey reported, “[i]t is unclear whether Title II covers conventional cabs, much less emerging algorithmic transportation models,” including rideshare systems that have explicitly resisted categorization as public accommodations. It also remains unclear whether discrimination claims based on statistical evidence of race discrimination are cognizable under Title II, particularly given the judiciary’s increasing reluctance to remedy state and private action with a discriminatory impact, rather than clear evidence of racially discriminatory intent.

Professor Casey advocated updates to Title II as one manner to combat discrimination in rideshares. Particularly, Congress should clarify that the statute cognizes statistically based claims and that it covers “data-driven” transportation models. This is not unheard of; the Fair Housing Act covers disparate impact. Since we published Title 2.0, there have not been any litigation or policy updates in this area.

Accordingly, it will likely be up to AV companies themselves to ensure that people are not denied the benefit of access to AV on the basis of their race (or gender, socioeconomic status, or disability, for that matter) because of discriminatory algorithms. Experts have suggested reforms including frequent inventories of discriminatory impact of AI, adjusting data sets to better represent marginalized groups, reworking data to account for discriminatory impacts, and, if none of these steps work, adjusting results to affirmatively represent more groups. At a minimum, transparency is key for both the government and concerned individuals to assess whether AV has a discriminatory impact, and any data or findings should be widely published and shared by these companies.

Despite the downfalls of today’s rideshares discussed above, black users have still praised this technology as easier than hailing a cab on the street. In that way, AVs still have the opportunity to be another step towards transportation equity.

The 2021 Law and Mobility Conference opened with a panel, moderated by Emily Frascaroli, that set out to begin answering three questions: What are emerging transportation technologies? What is the legal landscape surrounding these technologies? What are some challenges that these technologies face, in terms of both gaining popular use and promoting transportation equity?

Nira Pandya presented on the legal landscape of connected and automated vehicles (AV). The current legal landscape of AV falls into three buckets: federal law, nonbinding federal agency guidance, and state law. On the federal level, there is no comprehensive federal AV legislation. On the regulatory side, the Department of Transportation has promulgated nonbinding regulatory guidance to encourage collaboration, transparency, and integration of AVs into existing transportation systems, but there are no binding regulations on any aspect of AVs. Meanwhile, at least 29 states and D.C. have enacted AV-related legislation or executive orders, creating a varying and uncertain landscape for AVs throughout the U.S. Moving forward, the Biden administration seems generally committed to the development of innovative transportation technology and has appointed leaders whose backgrounds align well with this goal.

Jennifer A. Dukarski presented on data, a key driver of mobility. Data is already ubiquitous in our transportation technology, from conventional vehicles’ navigation and diagnostic systems to the account and payment systems for scooter shares. Data will only become more frequently and invasively collected as our transportation system becomes more connected and automated. Yet the U.S. lacks comprehensive federal legislation for data privacy, all the while there is a dearth of regulations and legislation at both the state and federal levels that restrict how transportation companies can use our data. States such as California have developed broad, cross-cutting data privacy laws, and leaders in the field speculate that federal data privacy legislation could be introduced as soon as this fall.

Bryant Walker Smith discussed how emerging transportation must focus on both technology and the law being means to serve social needs such as increased transportation safety and equity, rather than ends in themselves. He outlined the safe systems approach, which focuses on both the vehicle and infrastructure aspects of transportation being designed to maximize social goals, such as safety, through design and policy.

A contentious issue with emerging transportation that the panelists highlighted was the reality that the companies creating transportation technology will, for better or worse, be driving the regulation of this technology. In this vein, one of the challenges of promoting transportation equity through policy or otherwise is weighing just how much pressure to put on AV companies to solve social injustices. Are we striving for equity in AV because it is better than striving for equity in more traditional modes of transportation, or are we doing this just because it is more convenient than dismantling the inequities built into our current transportation system? Given that transportation inequity is tied to a variety of broad and overlapping historical policies – housing, insurance, and urban development, to name a few – how much pressure can we really place on an AV or scooter company to resolve these social problems?

Finally, in describing the challenges to widespread adoption of emerging transportation technology, the panelists converged on the importance of transparency and uniformity.  For transportation systems like AV to work, the technology needs to be seamless, which will be challenging in the absence of a comprehensive federal framework. Promoting transparency from AV manufacturers about safety, data, and equity issues will be essential in developing consumer trust. This trust will then serve two purposes: getting more people on board with using these technologies and getting more people to advocate for their elected officials to pass good policies regulating these technologies.

The panel wrapped up with brief discussions of a National Highway Traffic Safety Administration (NHTSA) advanced notice of proposed rulemaking on a “Framework for Automated Driving System Safety” – which has had its comment period extended to April 1 – and of spectrum issues with connected vehicles.

In light of the 2021 Law and Mobility Conference’s focus on equity, the Journal of Law & Mobility Blog will publish a series of blog posts surveying the civil rights issues with connected and autonomous vehicle development in the U.S. This is the second part of the AV & Civil Rights series. Part 1 focuses on Title VI of the Civil Rights Act. Part 3 focuses on Title II of the Civil Rights Act. Part 4 focuses on the Fourth Amendment.

Leaders in the autonomous vehicle (AV) industry have promoted AVs as the gateway to transportation equity by providing people who are unable to drive due to age or disability with the freedoms of a car. Nearly every AV company is already experimenting with accessibility features. Waymo and Cruise are trying out braille and other features to assist blind users. Nissan has virtual reality avatars that may provide comfort and assistance to passengers with disabilities. May Mobility’s shuttle deploys a wheelchair ramp. However, federal law has mandated that transportation be accessible to everyone for over three decades, and this goal is still far from being realized. Can AVs really be different?

A 2017 survey by the Department of Transportation found that an estimated 25.5 million people in the U.S. have disabilities that make traveling outside of the home challenging. Further, more than 3.5 million Americans with travel-limiting disabilities are unable to leave their homes at all. As our population continues to age, these numbers will only increase. This lack of access to transportation has devastating impacts. Disabled people experience depression at a rate four times higher than the U.S. population as a whole, undoubtedly due in part to isolation. From an economic standpoint, mitigating transportation obstacles for disabled people would create employment opportunities for 2 million people with disabilities and save $19 billion annually from missed medical appointments.

Per federal law, transportation is not supposed to be this inaccessible. The Americans with Disabilities Act (ADA) broadly mandates that both government and privately owned public transportation be accessible to people with disabilities. On the ground, inaccessibility has persisted, due in part to massive loopholes in the statute. The ADA does not apply to rail transit systems constructed prior to 1990, meaning that improved accessibility has been largely voluntary, and inadequate, for systems such as the New York subway. The ADA both mandates that buses have accessibility features and requires paratransit services to be available wherever there are fixed-route buses, but where inaccessible bus stops require door-to-door services. However, these services require reservation up to 48 hours in advance, and they are up to ten times more expensive per trip than fixed-route bus fare.

The ADA gets even messier for privately owned auto transportation systems. The statute does not require taxi services to purchase accessible vehicles, which makes hailing an accessible cab nearly impossible in many parts of the U.S. Ride shares have even further complicated this murky scheme. It also remains unclear whether the ADA covers ridesharing platforms at all, although a recent lawsuit against Uber may finally force a court to answer this question.

Regardless of whether the ADA will reach AV fleets, widespread mobility issues for Americans with disabilities in our current transportation system means that the statute will not do nearly enough on its own to promote accessibility for all. Even the experimentation with accessibility features that I detailed earlier will not be enough. AV will not be fully accessible unless it is uniformly accessible, and disability rights advocates are already worried that AV companies are striving for specialization at the expense of similar or identical accessibility features across all fleets.

The best way to ensure uniform accessibility for emerging transportation would probably be through sweeping federal legislation. This seems unlikely to happen any time soon, and in the meantime uniform accessibility will be left to AV companies themselves. AV companies have the opportunity to make AV transportation radically accessible from the start by accounting for mobility, visual, auditory, memory, and intellectual impairments in their design across competing fleets and geographic regions. This is the only way to ensure that the next transportation revolution does not leave our most vulnerable community members behind.

In light of the 2021 Law and Mobility Conference’s focus on equity, the Journal of Law & Mobility Blog will publish a series of blog posts surveying the civil rights issues with connected and autonomous vehicle development in the U.S. This is the first part of the AV & Civil Rights series. Part 2 focuses on the Americans with Disabilities Act. Part 3 focuses on Title II of the Civil Rights Act. Part 4 focuses on the Fourth Amendment.

Road planning has never been value-neutral. From Detroit’s 8 Mile Road to West Baltimore’s “road to nowhere,” infrastructure has been used both intentionally and unintentionally to further marginalize communities of color, and particularly Black communities. As the Biden administration hopes to move forward with sizable infrastructure investments, including potential investment in infrastructure for autonomous vehicles (AV), proposals to build new roads and refurbish existing ones will arise. Both federal and local policymakers must avoid repeating racist automotive infrastructure decisions of the past.

Both before and after the civil rights movement, one of the mechanisms through which segregation and white supremacy were, and continue to be, perpetuated is through urban planning. Federally backed mortgages and other services were unavailable in communities that were evaluated as “insecure” during the early and mid-20th century, meaning that these redlined areas were left blighted as developers looked to development in wealthier, whiter neighborhoods and suburbs. The advent of urban sprawl focused federal transportation infrastructure resources to expressways designed to decrease congestion for suburban commuters to city centers, which often meant that these roads were built right through formerly thriving black neighborhoods, displacing homes and businesses and forcing those who remained to deal with increased pollution and noise. Even public transportation became increasingly geared toward the comfort of white, suburban riders instead of the working class people of color that tend to depend on it. Take the express train, literally designed to skip through entire city neighborhoods and block access for local riders.  

Some environmental and racial justice advocates have turned to civil rights law to attempt to right some of these wrongs. Title VI of the Civil Rights Act of 1964 prohibits discrimination on the basis of race, color, and national origin in programs receiving federal financial assistance, which constitute the majority of infrastructure projects. The statute allows affected communities to file both federal lawsuits and administrative complaints, which equip federal agencies like the Department of Transportation to initiate fund termination proceedings or refer matters to the Department of Justice for other legal action.  However, in Alexander v. Sandoval, the Supreme Court dealt a devastating blow to Title VI by interpreting the statute to require discriminatory intent, rather than discriminatory impact alone, to prove discrimination. Essentially, the holding in Alexander v. Sandoval has eliminated the private cause of action for discriminatory infrastructure and left enforcement up to federal agencies.

On the administrative side, the Biden administration has provided a glimmer of hope for the utility of Title VI. The Federal Highway Administration recently asked Texas’ transportation department to halt construction on an I-45 expansion project after community members filed a Title VI complaint citing concerns about pollution and displacement. The project would impact Harris County, Texas, which has large Black and Latinx populations. Time will tell whether the pause and investigation will yield the result that the community members sought in this complaint, and whether it will serve as precedent for similar actions.

Overall, while impacted communities may use Title VI to stall projects, the best way to ensure that any future infrastructure that facilitates the AV revolution does not violate civil rights is to ensure equitable access to construction decision-making and emerging transportation itself. AV developers cannot tout equity while failing to acknowledge that infrastructure built for cars has had a devastating impact, which may continue without road planning that moves marginalized voices to the center.

2020-21 Has Revealed Problems in Supply Chains and Distribution

The various crises of the past year have disrupted many industries, and transportation logistics is no exception. The pandemic has demonstrated the fragility of our supply chains, as logistics providers have been overwhelmed and overworked and businesses have been faced with long delays and uneven availability of important products. Further, we have grown increasingly aware of the importance of supply chains to consumers’ everyday lives, perhaps most memorably when we were all desperate to find toilet paper a year ago. More seriously, the integrity of our supply chains is having literally life-or-death consequences for hundreds of thousands of people in the realm of medical supplies. Since the beginning stages of the pandemic, we were confronted with our supply chains’ inability to deliver adequate amounts of testing kits, PPE, and pharmaceuticals. Recently, the government invoked the Defense Production Act (DPA) to put higher priority on the Covid-19 vaccine in the supply chain. Even after the pandemic’s impacts are no longer felt so strongly in our supply chains, extreme weather events will likely continue to disrupt distribution, as just happened in Texas.

The Promise of AVs to Remedy Transportation Logistics’ Woes

While government actions like the DPA may be positive developments in our present moment, the recently revealed defects in our supply chains will require more than temporary band-aids enacted in reaction to crises. Amidst the disorder in our current supply chains, entrepreneurs and industry professionals see an opportunity for emerging technologies to make our supply chains more reliable, efficient, and better able to foresee and cope with future disruptions. Industry commentators especially highlight the potential of autonomous vehicles for their potential to remove the human factor that has proven so vulnerable in the pandemic. In contrast to people, AV systems can run 24/7, are not subject to 14-day quarantines, and will never exacerbate the already worrisome long-standing driver shortage due to illness. Thus, AV systems could provide the transportation logistics industry the efficiency and reliability that consumers so badly need during emergencies like the coronavirus crisis. Experts in government and industry have long  recognized that increasing automation in the trucking industry would have these advantages, as well as the added benefits of cost savings, reduced congestion, increased energy efficiency, and improved road safety.

Obstacles to AV Implementation: Disparate Regulations

While companies like TuSimple, Aurora and Waymo are already making progress on autonomous freight routes in the US and elsewhere, they are charging ahead without much coordinated help on the governmental level. One of the main challenges for these companies are the conflicting standards they face when traveling between states, since no preempting federal legislation has been passed and state regulations remain a disparate patchwork. Analysts have noted the “sheer divergence of law” between state and local governments, and leaders in government and industry have been discussing the need to harmonize the AV regulatory regime for years.

Some key areas of variance in state laws are: whether or not AVs are exempted from follow-too-closely statutes (which effectively prohibit automated platooning), definitions of automation, and whether or not a human operator is required. For instance, during TuSimple’s planned AV route from Phoenix to Houston, the company would have to pass through New Mexico, which lags behind neighboring states in terms of AV-enabling legislation (their state legislature is currently working on a bill that would authorize AV testing and platooning, while Arizona and Texas have authorized driverless testing for years).

This patchwork poses an obvious problem for long-haul trucking across state lines, thus hindering  AV technology’s potential as a solution to the aforementioned supply chain issues.

Removing Roadblocks

If the federal government wants to be proactive in helping the private sector resolve supply chain problems with innovation in the AV space, it should set about harmonizing local regulations. Government leaders have repeatedly stated that they aim to “promote regulatory consistency among State, local, tribal and territorial, and international laws and regulations so that AVs can operate seamlessly nationwide and internationally.” Continuing to dialogue with industry leaders and utilizing the resources of the Department of Transportation and the National Highway Traffic Safety Administration to coordinate between state and local governments will be crucial to fostering innovation with smart regulation. Another avenue is federal preemption, which could be targeted at specific areas of conflicting regulations which stifle innovation in and implementation of AV tech, like follow-too-closely statutes. Of course, new regulations should be designed in concert with industry leaders and with plenty of time for public comment, the same way rulemaking and research have been conducted to this point.

If the federal government remains inactive and allows the conflicting patchwork of state regulations to persist, industry commentators have suggested that AV stakeholders in the private sector have an alternative method to harmonize regulations: legal challenges under the Commerce Clause. Dormant Commerce Clause doctrine holds that because Congress has the power to regulate interstate commerce, states are constitutionally barred from actions that discriminate against or unduly burden foreign commerce, even in the absence of federal regulation. The foundational case of Hunt v. Washington State Apple Advertising Commission provided the relevant test for facially neutral laws that have discriminatory impact: the state law is unconstitutional if it either (a) has a hidden protectionist purpose or (b) the burden on foreign commerce outweighs the local benefits. AV stakeholders may have a workable argument that conflicting regulations between states put an undue burden on interstate commerce that outweighs any local benefits.

These kinds of litigations have occurred in the commercial trucking industry before. Legal professionals have compared potential challenges by AV stakeholders to Consolidated Freightways Corporation’s successful challenge to Iowa’s statutory prohibition on the use of 65-foot double-trailer trucks, even though these trucks were permitted in surrounding states and studies showed that the illegal vehicles were no less safe than the legal ones. The burden on the trucking company’s ability to engage in interstate commerce was large enough and the local safety benefits were small and unsubstantiated enough to overcome the strong presumption of validity imputed to local safety measures.

Applying this legal doctrine to conflicting AV regulations seems like a logical extension. For instance, follow-too-closely statutes in states like Kansas could be held invalid as applied to AV commercial trucks if courts are satisfied that they unduly burden the flow of commerce by preventing platooning (which researchers say should reduce congestion, increase energy efficiency, and provide more efficient business models) and insufficiently serve the local interests of highway safety that they are designed to further (studies show that platooning actually improves road safety). Some legal observers even suggest that states’ omissions to act on AV-enabling legislation should be scrutinized for burdening innovation and commerce with regulatory uncertainty.

Therefore, while the current legislative patchwork poses an obstacle to technological innovation and the promise it holds for commercial freighting, AV leaders have multiple ways in which to pursue a more hospitable regulatory environment. Working together with lawmakers to coordinate across jurisdictions rather than working against them in litigation may be a more efficient way forward, and more enticing to an industry that would rather not provoke legislators’ ire. However, the legal doctrine seems to be on the side of promoting AV innovation here, and is a tool ready to be picked up if necessary. Regulators would be wise to start paying closer attention to the need to harmonize regulations, as the last year has made unmistakably clear that our supply chains need improvement, and technological disruption looks to be a promising solution.

During the holiday season, news outlets reported that Apple is working on adding electric self-driving cars to its repertoire of products and services. Apple is using the codename “Project Titan” for its electric vehicle that is expected to have fully autonomous capabilities. Like a present with a big red bow on it, the secret surrounding Project Titan was itching to be unwrapped. Apple has yet to disclose the news itself; however, sources familiar with the project revealed details of the new vehicle that could be entering the market as early as 2024.

At this time, there are no vehicles available for purchase in the U.S. that are equipped with Automated Driving Systems (ADS). ADS describes level 3-5 motor vehicles with driving automation systems that perform part or all of the dynamic driving task (DDT) on a sustained basis. At levels 3-5 of automation, a person is not considered to be driving the vehicle when the automated driving features are engaged. If Apple releases a fully-autonomous vehicle, it has the potential to be the first available for purchase in U.S.

Sources reported that Apple is setting itself apart from competitors by using an innovative monocell battery design. This type of layout bulks up the individual cells in the battery and frees up space inside the battery pack by eliminating the need for pouches and modules to hold battery materials. There are also talks of Apple using a lithium iron phosphate (LFP) battery, which is less prone to overheating than other types of batteries. In more recent news, it was reported that Apple is actively searching for a supplier for lidar sensors for its vehicle. By acting as the eyes that allow a car’s computer to see its surroundings, lidar sensors play a key role in the autonomous part of the Apple Car. The majority of autonomous vehicles use lidar sensors; however, Apple is specifically seeking lidar sensors that will still be considered cutting-edge years from now.

While most of Project Titan remains secret, patent applications filed by Apple provides additional insight as to what features the car may include. Apple’s patents describe several technological advancements including an “intelligent” window-tinting system that responds to external weather conditions, a new way to send alerts using a system for enhancing situational awareness, and an augmented virtual display using a virtual reality system to help reduce motion sickness in passengers.

Fully autonomous vehicles are getting closer to being road ready, but the self-driving technology and the laws surrounding the use of these vehicles are in need of further development. The U.S. Department of Transportation (U.S. DOT) has decided to pay closer attention to automation and preparing for the future of transportation. The U.S. DOT’s fundamental focus is to create the safest, most efficient and modern transportation system in the world. Recognizing that automated vehicles align with their focus, on January 11, 2021, the U.S. DOT released the Automated Vehicles Comprehensive Plan (“Comprehensive Plan”) to understand and respond to the opportunities and challenges presented by ADS. To achieve the U.S. DOT’s vision for ADS, the Comprehensive Plan outlines three goals: promote collaboration and transparency, modernize the regulatory environment, and prepare the transportation system for the safe integration of automated vehicles.

Creating a regulatory scheme to integrate automated vehicles alongside regular vehicles is no small task. Currently, there are no national standards for automated vehicles. However, states are free to enact their own legislation regarding the use of such vehicles within their borders, and 29 states and D.C. have done so. The Comprehensive Plan states:

“The U.S. Government will modernize or eliminate outdated regulations that unnecessarily impede the development of AVs—or that do not address critical safety, mobility, and accessibility needs—to encourage a consistent regulatory and operational environment. In doing so, it will promote regulatory consistency among State, local, tribal and territorial, and international laws and regulations so that AVs can operate seamlessly nationwide and internationally. “

Automated Vehicles Comprehensive Plan

While the law often lags behind technological innovation, it should not “unnecessarily impede” it, as stated above. The Comprehensive Plan is a step in the right direction for Apple, the several other companies developing automated vehicles, and for the public soon to be driving, or riding, in them.

Several articles have been written over the past two years regarding shared micromobility electric scooters’ environmental impact. Some of the more phenomenal headlines were hyper-critical of electric scooters:

            Electric Scooters Aren’t Quite As Climate-Friendly As We Thought;

            Sorry, Scooters Aren’t So Climate-Friendly After All;

            Study: Electric Scooters Increase Carbon Emissions In Most Cases.

The report cited to support these assertions is one out of North Carolina State University with a similarly eye-catching title: “Are E-Scooters Polluters? The Environmental Impacts Of Shared Dockless Electric Scooters.” The study found that the greenhouse gas emissions associated with e-scooters were derived from four primary sources. The two largest impact categories — materials & manufacturing and collection & distribution emissions — accounted for over 90 percent of emissions. The two remaining categories were the transportation to the U.S. (most scooters are manufactured in China) and the actual emissions from scooter use and maintenance.

To me, that life cycle assessment is encouraging because scooter companies can reduce those two largest categories through practices on through production and operational changes. The truth of the environmental impact of electric scooters ultimately rests on the answer to a few simple questions:

  1. How are electric scooters manufactured?
  2. How long is the use-life of an electric scooter?
  3. What types of trips are electric scooters replacing?
  4. How are electric scooters collected, charged, and distributed?

These questions are interrelated and address overlapping issues. The answers are important for the future success of shared micromobility scooters as part of a mixed-transportation system. High on the list of goals that cities have set that they hope micromobility can help them reach are reduced traffic congestion and reduced emissions.

How are electric scooters manufactured?

This part of the life cycle of scooters may be difficult for cities to internalize and pressure scooter companies to change. Since the scooters are manufactured in China, and the raw materials are sourced outside the U.S., the immediate emission effects are not internalized in the United States. The direct effects are brought to bear in China and at the communities containing the mines for component materials. The component materials of a typical electric scooter include an aluminum frame (6.0kg), steel parts (1.4 kg), a lithium-ion battery (1.2 kg), an electric motor (1.2 kg), and tires with tubing (0.83 kg). Fifty percent of the emissions associated with electric scooters come from procuring the materials and manufacturing the actual scooter.

One way to reduce the emissions per passenger mile driven is to use the parts of decommissioned scooters to refurbish and extend other electric scooters’ lives. This will extend the parts’ life and reduce the need to procure and manufacture brand new scooters with new raw materials. Most of the scooter parts can be recycled if they cannot be reused in other scooters.  Uber has committed to recycling 90 percent of used spare parts from their “Jump” line of micromobility bikes and scooters. In the future, major micromobility providers should commit to using more recycled raw materials and components and to recycling the parts of e-scooters after they have outlived their working days. We cannot let what happened to bicycles in China happen to electric scooters in the United States.

How long is the life of an electric scooter?

Closely tied to the question of what goes into an electric scooter is: how long do scooters stay on the road? The longer a scooter can remain operational, the lower the average emissions per passenger miles traveled due to the sizeable portion of emissions being created up-front from materials and manufacturing. The less time a scooter is operating on the street, the higher the emissions per passenger mile traveled. When companies first distributed scooters around the U.S., the average life cycle was between one and three months. This short life was due in part to scooters being destroyed, thrown in rivers, and generally abused as they descended on cities, in addition to the expected wear and tear from everyday use. Over time, the scooters being manufactured and distributed have been made to be more durable and long-lasting. However, this can create a tradeoff with manufacturing emissions: to make more durable scooters that enjoy a longer street-life, more durable materials, and more energy must go into manufacturing, creating more emissions. If vehicles can last for two years before being decommissioned, the average per passenger-mile traveled is decreased by roughly 30 percent, according to the NCSU study. The tradeoff between increasing manufacturing inputs to extend the life of scooters is beneficial. Micromobility providers should continue spending resources developing more robust scooters that will need less maintenance and can remain in circulation longer to drive down average emissions continually. This solution should be supplemented by reusing parts, as discussed above. Using parts from older scooters to extend scooters’ lives on the street should be a priority for cities and micromobility companies. 

What trips are electric scooters replacing?

The benefits of electric scooters on transportation sector emissions depend mostly on what other transportation methods are being displaced. Suppose scooter trips only displace trips that otherwise would have been walking. In that case, scooters will never be an emission reducing solution. If e-scooters are only replacing automobile trips, scooters would always reduce net transportation emissions even at the current life cycle emissions assessment. Replacing ride-sharing and automobile trips decreases emissions (although this may not remain true as ride-hailing providers shift to using only zero-emission vehicles). Replacing what would otherwise be walking, bicycling, or public transportation trips results in more emissions from the transportation sector.

Several cities have studied this question during their scooter pilot programs. Chicago reported 43 percent of scooter trips replaced a trip that would have used ride-sharing service or personal vehicle. Thirty percent would have been walking trips, and 15 percent would have used public transportation. Portland found that 34 percent of local riders and 48 percent of visitors took an e-scooter instead of using a ride-hailing service or driving a personal vehicle. However, the city also reported that 42 percent would have walked or biked. Suppose scooters continue to and increasingly replace personal vehicle and ride-sharing trips. In that case, they will successfully help cities meet their goals of reducing traffic congestion and transportation emissions. However, in Ann Arbor, data shared by scooter companies has shown that scooters are not serving to replace vehicle trips or as the touted first-last mile solution. They are overwhelmingly replacing trips that otherwise would all be on foot: trips between on-campus academic buildings. This widespread use for scooters in college towns is an occurrence cities will need to address to meet their goals.

How are electric scooters collected, charged, and distributed?

Scooter companies approach collection, charging, and distribution in similar ways with minor variations. They employ people (either as employees or independent contractors) to drive around and collect scooters, take them somewhere (a central charging location or their home) to be charged overnight, and then use those people to drive around in the morning to redistribute the scooters. Cities often have requirements for the starting balance of scooters across the city to provide equitable access to communities underserved by public transportation. The additional miles driven by personal vehicles to find scooters, take them to be charged, and redistribute them in the morning accounted for 43 percent of scooters’ emissions impact.

There are several ways to address this enormous source of emissions. One method would require micromobility companies to make a similar move to Lyft: require their “chargers” (as Spin calls them) to drive an electric vehicle (or at least highly fuel-efficient cars) to reduce emissions from driving around. However, this would limit the number of people eligible to work in these roles, but that will change as electric vehicle models become more ubiquitous in the market this decade. Another solution is to minimize the distance between where scooters are picked up and dropped off. This may require greater segmentation or creating grids for collection and drop off.

The solution I like best requires investment and partnership between cities and scooter companies: installing public charging and storage corrals, and develop a reward charging program. At the entrances to metro stations, near bike-share drop-off areas, and other areas where morning demand is highest, scooter companies can work with cities to install corrals where scooters can be deposited and plugged into installed chargers. By sharing demand and usage data, scooter companies and cities can determine the best morning distribution locations and work in partnership to build central hubs for charging and collection.

Instead of hiring or contracting with vehicle drivers to pick up dozens of scooters, scooter companies should create rewards programs that incentivize users to drop off low-battery scooters at this location and plug them in to be charged. There will still be a need for drivers for scooters with bone-dry batteries. Still, users can relocate scooters with 10-20 percent juice to a charging corral at the end of a day in exchange for a free ride credit for later use. With the invigoration of reward and competition type apps, micromobility companies could incorporate features that “gamify” charging on foot instead of driving around in a vehicle.

Where we go from here

The conversation around the emissions associated with shared micromobility scooters needs to be reshaped. The industry has already come a long way since the first days of descending on cities like locusts. Cities are integrating scooters into their transit options; People have accepted them and approve of them; Scooters have great potential to reshape transportation. By adopting some of the suggestions I’ve proposed above, electric scooter companies can put to rest the idea that they aren’t a part of the solution to reduce the transportation sector’s emissions.

The first week and a half of the Biden administration has seen a flurry of activity: thirty executive orders and actions were taken in the first three days alone, with new announcements every day this week as well. Three of the earliest orders touched transportation and energy issues: an order promoting COVID-19 safety in domestic and international travel, an order to rejoin the Paris Climate Agreement, and an order that will block a permit for the Keystone XL pipeline and direct agencies to review more than 100 Trump executive actions on the environment.

Biden has nominated for Transportation Secretary Pete Buttigieg, who emphasized infrastructure in his campaign for the Democratic candidacy and touted a $21 million investment in “Smart Streets” to revitalize downtown South Bend as the city’s mayor. Biden has nominated as Secretary of Energy Jennifer Granholm, who, since serving as Michigan’s governor, has maintained a focus on renewable energy development, and, particularly, the electrification of American cars.

Among Biden’s most expensive proposals is his sweeping $1.7 trillion plan to tackle climate change. Biden’s executive orders on climate and the environment will freeze new oil and gas leases on federal lands; conserve at least 30% of federal lands and oceans by 2030; double wind energy production by 2030; and establish an interagency climate task force; all with a goal of achieving net-zero carbon emissions by 2050.

With climate, infrastructure, and clean energy jobs as guiding focuses, here is a preliminary view of the transportation policies that we can expect from the Biden Administration:

Electric Vehicles and Fuel Efficiency

Biden’s “Plan for a Clean Energy Revolution” includes a $400 billion investment in clean energy and innovation. A significant part of this plan is working toward the widespread use of electric vehicles.

Automakers expect a push for a new agreement to raise average fuel economy standards across fleets, which will require them to sell more electric vehicles. Under Trump’s standards, they would have had to show 1.5% fleetwide fuel economy increases from 2022-2025, which had been lowered from the 4.7% standard of the Obama Administration. There are currently around twenty fully electric vehicles for sale in the US, with many more expected to pop up in the next few years, including electric pickup truck models from GM, Ford, and Fiat Chrysler. Ford has pledged $11 billion to introduce a variety of new EVs, while GM has committed $27 billion to electric powertrains, vehicles, and autonomous systems through 2025.

On the manufacturing side, Biden hopes to make the U.S. a leader in electric vehicle production, with a goal of creating 1 million new jobs in the auto sector. On the consumer side, he has floated plans to offer rebates for consumers to replace conventional cars with electric vehicles. He has pledged to add 550,000 charging stations across the US.

Biden also plans to electrify the government fleet. In 2019 there were 645,000 civilian, military, and post office vehicles in the federal government’s fleet. Fulfilling this goal will create jobs in the industry, accomplish net-zero transportation-related carbon emissions for the federal government, and provide long-needed updates for postal workers. In anticipation of this plan, part of GM’s electric and autonomous vehicle investment will be in its defense unit, which relaunched in 2017.

Infrastructure

For decades, infrastructure development and maintenance has been synonymous with road funding. Attempting to break away from this pattern, Biden’s $2 trillion “Build Back Better” plan includes development goals for transit and power; upgrading and weatherizing buildings; constructing sustainable homes; innovating clean energy technology; streamlining agriculture; and expanding internet access.

Nicknamed “Amtrak Joe,” Biden’s infrastructure plan includes “sparking the second great railroad revolution.” He plans to work with Amtrak and private freight companies to electrify their fleets. Biden is also aiming to invest in quality public transportation in the roughly 315 American municipalities with populations of more than 100,000 by 2030.

Biden’s plan to expand broadband internet or wireless broadband via 5G also targets transportation and climate change by supporting a transition to remote work.  

An advisor to Biden recently announced that the Administration believes an infrastructure bill of up to $2 trillion is possible within Biden’s first 100 days. Absent legislation, the administration can still shape approximately $1 billion in Department of Transportation grants to promote this agenda; the Trump administration focused on road projects encouraging car travel with these grants.

Autonomous Vehicles

The Trump administration took a purposefully hands-off approach to regulating autonomous vehicles (AV). The National Highway Transportation Administration (NHTSA) promulgated voluntary guidance, which contained twelve safety elements for testing. Of the 66 companies with permits to test these vehicles in California, only 32 submitted these self-assessment reports, and not all of those were rigorous.

While there is not an explicit Biden plan on autonomous vehicles, Buttigieg’s infrastructure plan during his run included reassembling the Advisory Committee on Automation in Transportation, which Trump secretary Elaine Chao had disbanded, and proposing that NHTSA take on a strong federal role for the regulation and oversight of AV safety. A request for comments on AV safety in the waning days of the Trump Administration could be a jumping-off point for these plans.

Granholm has expressed concerns about the labor implications of AV, which could also shape the Biden Administration’s AV policies.

Micromobility

When campaigning, Biden promised to help cities “invest in infrastructure for pedestrians, cyclists, and riders of e-scooters and other micromobility vehicles.” The Biden Administration may therefore account for micromobility as part of is transportation and infrastructure policies.

One development in Congress in this area is the bipartisan Bicycle Commuter Act of 2021, which was recently introduced into the House. The Act would bring back and strengthen an expired pre-tax benefit program for bike commuters, increasing the benefit and ensuring that cyclists could be eligible for other transit coverage. This could be a starting point on micromobility.

Environmental Justice

The early actions of the Biden Administration demonstrate a focus on environmental justice unparalleled by any previous president. On Wednesday it was reported that Biden will sign an executive order establishing an interagency council on environmental justice, an office of health and climate equity in the Department of Health and Human Services, and an office of environmental justice at the Department of Justice. These orders will double down on the promises of a Clinton executive order to ensure that environmental justice considerations are a part of all federal projects. Biden’s clean energy plan includes a goal to support the health and wellbeing of those who have been impacted by fossil fuels, including advocating for new jobs in renewable energy in oil and gas towns. Biden’s infrastructure plan includes a goal of “disadvantaged communities” receiving 40% of the benefits of government spending on energy efficiency.

Accordingly, any of the Biden Administration’s transportation policies may need to account for disproportionate impacts on marginalized communities in the U.S.

Overall, achieving low carbon emissions, investing in sustainable infrastructure, and promoting environmental justice will be the central concerns of the Biden administration that will drive its transportation policy. While there is little in the way of specific policy on AV and micromobility, we are likely to see increased research and regulation in these and other emerging transportation areas.

By Vanessa Casado Pérez*


When we think of transportation, we hardly ever think of sidewalks, albeit they are transportation corridors as much as roads or highways. Managing sidewalk space is not easy. There are multiple uses competing for this public space, as it is even called “our last commons.” The rights over sidewalks are murky, and their governance is often fragmented and suffering from lack of planning. The public has a right of way over them and walks on them. Hospitality and retail do business on them by installing terraces, announcing their latest sales on a blackboard, or by alluring passersby with wonderful window displays. Homeless people sleep on them.

COVID-19 has exacerbated the conflict between uses. On the one hand, our sidewalks are too narrow to social distance while walking on them even in the absence of street furniture or businesses. On the other, restaurants and bars have taken over the sidewalk as a lifeblood of their business. The latter makes the competition between users even more acute as pedestrians see their space reduced, something particularly challenging for those with disabilities. Where possible, local authorities have transformed parking spots as space for terraces, taking parklets to a whole new level, to expand sidewalks. Making parking more difficult may increase congestion due to people circling around trying to find a spot in the short term, but it may discourage driving in the long term. Expanding the sidewalk by reducing space for cars is an interesting move as normally what we see is shifting road problems to the sidewalk without carefully considering the impacts on the latter.  

Two such cases of shifting road congestion to the sidewalk are micromoblity devices and delivery robots. Both solve the last mile problem. Our roads are often congested. Some commuters waste more than a hundred hours a year in traffic. Vehicles emit greenhouse gases and local pollutants, which contribute to climate change and harm our health. There is no single recipe to mitigate our dependency on cars and reduce emissions. But often, an ingredient is public transportation. Public transportation can be inconvenient if it does not take you door to door as your private vehicle will. Finding an emissions-free way to fill the last mile gap between the public transit stop and your place of work or home is paramount. A successful way to do so are shared bikes or scooters systems. Beyond bikes docked on parking spots, there have been scooters or bikes scattered on the sidewalk in cities across the United States. These micromobility devices have taken a hit during the pandemic as there were fewer commuters and shared transportation was perceived as a contagion risk. However, the consulting firm McKinsey predicts that scooter and shared bike companies may recover as those micromobility devices are less risky than public transportation, can adapt to social distancing and hygiene requirements in the medium term, and in the long run cities are likely to discourage the use of private vehicles.[1]

Another new user of our sidewalks are delivery robots. Our demand for home delivery of goods has skyrocketed in recent years too, but, in contrast to micromobility devices, it has accelerated during recent lockdowns. The problem for delivery companies is the last mile, which is particularly costly. The last mile is also socially costly as vehicles parking and stopping add to congestion and pollution. While there have been advances in self-driving delivery vehicles, recently delivery robots have been deployed in university campuses or some neighborhoods to solve this last mile problem. A van arrives to a neighborhood, and the Serves (Postmates), Scouts (Amazon), or Relays (Savioke) decamp to deliver our food or our latest online impulse purchase. There are concerns related to privacy and job loss but also related to the use of sidewalks. Sidewalks are shared spaces. People with disabilities have had problematic encounters with those robots. Others have played pranks on them. But they, jointly with scooters, are a new private use of a shared resource: sidewalks. Reducing pollution is a step forward, but moving congestion from the road to the sidewalk benefiting both private companies and drivers is just another example of the disregard for pedestrians.[2]

Our sidewalks are home to pedestrians window-shopping, neighbors walking their dogs, blackboards with the latest addition to a restaurant’s menu, homeless individuals, terraces, and a long etcetera. Scooters are an additional obstacle to fluid mobility. While scooters are not allowed to be ridden on the sidewalk, they are left on it, often scattered, making it hard for those using the public right of way to walk on the, often narrow, sidewalk. Delivery robots, on the other hand, are circulating, and perhaps we can consider them as using the public right of way. But still, they also help illustrate that the space in our last commons, sidewalks, is scarce, both physically -because they are narrow- and as a result of regulation -because ordinances allow for multiple private uses of it. COVID-19 lockdowns have made it even scarcer as people made their sidewalks their gyms or social outlets and restaurants have transformed them into dining rooms. But even before cities have regulated what uses are acceptable on a sidewalk—for example, some cities ban food vendors—, or have discouraged certain uses—such as sleeping on benches by designing benches with individual seats that impede lying down.

Like with other gig economy innovations, scooters or robots have asked forgiveness instead of permission, but cities have moved to regulate them. For scooters, some cities did sign agreements that were quite lucrative. For delivery robots, state and local authorities are wrestling for the authority to regulate them. Some cities want to ban them, while state authorities seem more accommodating. Often, monetary compensation for the city is the solution. Fees do not solve the problem that space occupied by scooters or delivery robots is not occupied by the public; that while we accept these devices, we do not allow homeless people to station themselves on the street even if they have nowhere to go. Allowing scooters and delivery robots on our sidewalks is the nth illustration monetization and privatization of the sidewalk, a public space. In the cases of micromobility and delivery devices, privatization also benefits the public at large by reducing emissions because these devices reduce the need for automobiles. The conflict between uses remains though. While here is no straightforward solution to the incompatibility of uses, widening our sidewalks would mitigate scarcity and mitigate the conflicts. Widening the sidewalk may imply reclaiming space now granted to cars, further discouraging the use of private vehicles and, thus, further reducing emissions. Widening sidewalks may ensure that the public’s right of way has a clear path without so many obstacles, but it will not make all uses and users welcome. The decision of whether a city accepts homeless people or delivery robots, which will also reduce the number of delivery jobs, is a political one.


[1] Cities have more incentives than ever to want to reduce air pollution. Beyond the problems caused by smog, higher levels of air pollution have bene linked to worse coronavirus outcomes.

Maria A. Zoran, Roxana S. Savastru, Dan M. Savastru, & Marina N. Tautan, Assessing the Relationship Between Surface Levels of PM2.5 and PM10 Particulate Matter Impact on COVID-19 in Milan,  Italy, 738 Sci. Total Env’t 139825 (2020); Leonardo Setti, Fabrizio Passarini, Gianluigi De Gennaro, , Pierluigi Barbieri, , Maria Grazia Perrone, Andrea Piazzalunga, Massimo Borelli, Jolanda Palmisani, Alessia Di Gilio, Prisco Piscitelli, & Alessandro Miani, The Potential Role of Particulate Matter in the Spreading of COVID-19 in Northern Italy: First Evidence-Based Research Hypotheses, Health Scis. Preprint (Apr. 17, 2020),https://www.medrxiv.org/content/10.1101/2020.04.11.20061713v1.full.pdf.

[2] Vanessa Casado Perez, Reclaiming the Sidewalk, Iowa L. Rev. (forthcoming 2021) (on file with author), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3747436.

For an account of how our laws have benefitted cars, see Gregory H. Shill, Should Law Subsidize Driving?, 95 N.Y.U. L. Rev. 498, 551 (2020), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3345366.


* Vanessa Casado Pérez is an Associate Professor at Texas A&M School of Law and a Research Associate Professor at Texas A&M Department of Agricultural  Economics. Her scholarship focuses on public property and natural resources law. She is affiliated with the Bill Lane Center for the American West at Stanford University.

In several publications, she explores the role of property rights in the management of scarce natural resources and urban public property spaces. She has published in, among others, Southern California Law Review, Iowa Law Review, Florida State Law Review,  the NYU Environmental Law Journal, or the California Journal of Public Policy. 

Prior to joining Texas A&M, Professor Casado Perez was Teaching Fellow of the LL.M. Program in Environmental Law & Policy and Lecturer in Law at Stanford Law School. She holds an LLB, a BA in Economics, and an LLM from Universitat Pompeu Fabra in Barcelona, where she is from. She also holds an LLM from the University of Chicago Law School and a JSD from NYU School of Law.

In a New York Times article published this past Sunday, Ben Fried, a spokesman for TransitCenter, a transportation advocacy group, described mass transit systems across the country as being in “existential peril” due to continued financial issues caused by the COVID-19 pandemic. Since the pandemic exploded into American cities in the spring, the disruption to mass transit has been visible in a number of ways. In April, New York’s subway system, which has been operating 24/7 for decades, moved to shut down from 1 am to 5 am, to allow for cleaning (though subway cars, at least, may be safer than other forms of transit, as they have air flow that can diminish the amount of viral particles in the air). Shutdowns, reduced services, and budget cuts are widespread across mass transit systems, and transit employees have faced continued danger of viral exposure and death. In March, Jason Hargrove, a Detroit bus driver, posted a video from his bus after a passenger coughed on him, and just a week after the video went up, he died from COVID. Back in New York, by September 100 members of Transit Workers Union Local 100 had died of the disease, while D.C.’s Metro got “lucky” and lost its first employee in August.

While their employees face physical danger, the transit systems themselves are also threatened. In June, New York’s MTA projected $10.3 billion in losses over the next two years – and warned that could lead to service cuts and fare hikes. In July San Francisco’s Muni suggested it will lose a majority of its’ bus lines to budget cuts. This month D.C.’s Metro put out a proposed budget that pushes the wait between trains up to 15-30 minutes, ends weekend subway service, and cuts half the agency’s bus lines. But while such measures may keep the systems afloat, they run the risk of further degrading mass transit and leading to a potential “death spiral.” The concern is that while service cuts will save money and allow transit systems to continue operating, those same cuts will drive down usage. Think about it – if the subway only comes every 30 minutes, are you more or less likely to use it for your commute? That could lead to further revenue declines, even as the world begins to open up again post-pandemic. Reductions in service are already hurting vulnerable populations, as it makes it harder for essential workers to get to their still-open workplaces and limits the ability of low income and disabled individuals to obtain food and medicine. In a report, advocacy group Transportation for America showed that the burden of transit cuts will fall disproportionally on minority communities, based on a model reflecting 50% reductions in service. Mass transit within cities and regions is not the only thing at risk – Amtrak has, at times during the pandemic, had 10% of their usual ridership, leading to possible cuts across the nation. Amtrak is an important means of connecting rural communities – who could lose their only non-automobile connection to the outside world.

So what can be done to save mass transit? In May, the U.S. House of Representatives passed a relief bill that included $15 billion for transit systems, but even if that had passed into law it would have been a bandage, not a cure. Federal money will be necessary, and the incoming Biden administration would seem inclined to give it – but whether it can get through a likely divided Congress remains to be seen. Without that money, however, it is hard to see how transit agencies can avoid service cuts and pull themselves out of the death spiral…

P.S. Mass transit is far from the only part of the transportation system desperate for funds. State departments of transportation are seeing less income from tolls and gas taxes, since fewer people are traveling. Pennsylvania’s department, for example, ran out of cash in late November, and was seeking legislative approval to borrow $600 million to keep their projects functioning.

In the midst of a tumultuous election week, app-based driving platforms Lyft and Uber are celebrating a victory in California. Voters there passed Prop 22, which classifies app-based drivers as independent contractors for employment and tax purposes. The initiative carves out an exception to Assembly Bill 5 (AB5), which had classified these drivers as employees. The initiative passed by a significant margin, with 58.4% of Californians voting yes and 41.6% voting no as of this writing. Prop 22 will have significant implications for the rights of a growing number of workers who rely on these apps for both part-time and full-time employment, as well as for policy mobilization opportunities for tech companies.

The Path to Prop 22

Over a third of American adults participate in some sort of gig work, including millions who drive for Uber or Lyft, or both. The labor rights implications for the gig economy have been a concern from the outset, and have become increasingly prescient as the popularity of working for these companies has grown. Particularly relevant in the midst of the COVID-19 pandemic, independent contractors typically do not qualify for unemployment insurance, paid time off, or employer-based health benefits.

In the fall of 2019, California’s state legislature took on the gig economy by passing AB5. AB5 codified and expanded a California Supreme Court decision that held that the vast majority of the workforce is comprised of employees, not independent contractors, and that the burden is on the employer to prove that employees are independent contractors by applying a three-part legal test. “Factor 2” of this test provides that independent contractors perform service “outside the usual course” of business for the employer. This is where gig companies struggle to maintain workers’ independent contractor status.

AB5 was immediately controversial, as reflected by the variety of carveouts included both in the Bill and a subsequent amending bill, AB2257, which exempted nearly 100 types of businesses and workers from the law prior to Prop 22. Companies like Lyft, Uber, and DoorDash remained non-exempt, leading to legal battles. Uber and Lyft even threatened to cease operations in California as a result of the enforcement of AB5, as we have recently discussed.

Enter Prop 22. The ballot initiative classifies app-based drivers as independent contractors, not employees or agents, when certain conditions are met that resemble the policies of Uber and Lyft: no set work hours, no required assignments, no restrictions on working for other app-based driving companies, and no restrictions on having other employment. The initiative requires the approval of seven eighths of the California legislature to amend the policies in Prop 22, meaning that this scheme—designed by ride-share companies, for ride-share companies—could, essentially, be permanently entrenched.

Prop 22 also guarantees benefits to certain drivers across ride-sharing platforms: a wage equivalent of 120% of California’s minimum wage and a healthcare subsidy. The health benefit, however, only applies to drivers who work 25 or more hours per week, measured in “engaged time” spent picking up and transporting passengers. Many drivers spend more than one third of their shift waiting for passengers, meaning that, to reap these healthcare benefits, drivers need to work nearly 40 hours per week. The wage benefit also only applies to engaged time. One study estimates that, accounting for waiting time and costs, the minimum wage for app-based drivers under Prop 22 will be closer to $5.64 per hour, well below California’s minimum wage.

Lyft and Uber poured over $200 million into the “Yes on Prop 22” campaign, making it the most expensive ballot initiative in California’s history. The companies have also spurred controversy for using their apps to urge their armies of drivers and riders to support the initiative. While a smattering of unions and labor organizers pushed back against Prop 22, there was no comparable cash flow or targeted mobilization on the other side: opponents raised only $20 million.

What does Prop 22 mean for emerging transportation?

California has always been a trendsetter in the transportation industry. There are more registered vehicles in California than in any other individual state, and two of Uber’s largest markets are in San Francisco and Los Angeles. Unsurprisingly, this victory in California has led to reports that Lyft and Uber are already looking to pass similar laws in other states.

The success of Prop 22 will, at the very least, send a signal to other jurisdictions that passing laws similar to AB5 will lead to a concerted backlash. New Jersey, Massachusetts, New York, and Illinois are among states that have considered legislation that would classify many independent contractors as employees. Even prior to Prop 22, the tumultuous path of AB5 demonstrated the tricky business of using a one-size-fits-all approach to regulating labor and employment in the gig economy, which encompasses a broad swath of fields and income levels. The fact that millions of California voters were mobilized in support of this initiative sends an even stronger signal.

Perhaps an even more fascinating (and jarring) element of the Prop 22 story is the corporatization of California’s ballot initiative process, which allows companies to skirt around legislators, regulators, and courts to implement laws useful to their margins. California’s ballot initiative process is one of the most relaxed in the nation, which various corporations used this election cycle to promote multimillion dollar campaigns directly to voters. It is clear that Uber and Lyft, which have experienced steep drops in revenue throughout 2020, will spare no expense in fighting laws meant to guarantee employment benefits to their drivers. To illustrate, advertisements funded by Lyft framed Prop 22 as a worker’s rights bill, highlighting the benefits that are secured by Prop 22 (without mentioning hour requirements, of course) and claiming that maintaining the status quo of AB5 would end ride share services in California as they exist today (which would only happen if Lyft decided not to pay up to comply with the law).

Even the CEO of Uber has expressed that ride-sharing apps are failing their drivers, advocating for creative policy solutions to give these workers flexible benefits. This is not what Prop 22 does, instead shutting down policymaking and entrenching a path that will allow Uber and Lyft to, essentially, continue operating the way that they always have. It will be interesting to see whether, and how, this model of mobilization will be transferred to other transportation issues.

By Emily Kortright & Lucy Johnston-Walsh*


Children and young adults who are involved with the foster care system face multiple barriers to transportation, particularly in remote areas of the country with limited public transport options.  Recent changes in federal and state laws now allow children to remain in foster care beyond age 18 up to age 21, with a goal of providing these young adults with the opportunity to develop independent living skills.  As a greater number of older youth may choose to remain involved with foster care, there will be increasing demands for transportation to places of work and education.  Youth residing in suburban or rural areas have unique challenges due to lack of public transportation. Unfortunately, foster youth frequently experience many legal challenges in obtaining their drivers’ licenses, purchasing a car and obtaining insurance.  Foster care provider organizations (both governmental and private) often express fears of liability related to allowing a foster youth to drive.  

New and emerging forms of transportation may provide potential solutions, but – as always – with advancements in technology come challenges in implementation. Just as mass transit is unavailable, micromobility is largely inaccessible for foster youth in remote locations. Bikes, scooters, and other means of bike-lane-occupying transit have provided cost-effective, footprint reducing options for residents of cities around the world. However, micromobility options are often impractical to implement in suburban and rural locations where most trips are more than a few miles. Micromobility for foster children in urban areas presents its own slew of concerns such as risk of accidents and injuries, lack of supervision, and determination of appropriate age of usage.

Ridesharing apps have become some of the most pervasive and visible technological advancements in mobility; however, combined with the lack of available cars in non-urban areas, they do not provide the advantages to foster children that they do to the general population. Many foster children do not even have access to smart phones and cellular data. Also, Uber and Lyft drivers cannot be properly vetted to ensure the safety of the children, and often have restrictions related to unaccompanied minors. State laws and policies place appropriate safety restrictions on who may transport foster youth, and often the list includes only caseworkers, biological parents and/or foster parents, or residential facility staff. Unless special permission is given by the court or parents, it would be challenging to approve any rideshare driver.  Moreover, waiting for a rideshare driver to become available and arrive could be problematic for youth who have time commitments relating to jobs or appointments.

Companies such as HopSkipDrive, Kango, VanGo and Zum seek to provide ridesharing services to children in a safe manner, vetting drivers through extensive interviews, background checks, and certification processes, and implementing real-time monitoring systems. Los Angeles-based HopSkipDrive, has even focused its outreach on foster youth, expanding to Las Vegas and partnering with Clark County Child Welfare Services. However, these services are not widespread, often require scheduling in advance, and the extensive vetting process for drivers means that the cost of each ride tends to be even higher than most ridesharing apps. Even extensive security measures cannot completely shield children from the risks of assault and kidnapping that ridesharing apps present. In February of 2020, HopSkipDrive was suspended in Las Vegas when a driver was charged with unlawful contact with a minor and luring a child, despite having an approved criminal record and background check.

According to a new report, 1 in 10 vehicles will be fully automated by 2030, with robo-taxis comprising a significant portion of the market. While contracts with agencies that provide robo-taxi services could provide a convenient solution for foster youth, the possibility of fully automated vehicles means that even semi-autonomous cars will still require some manner of control by a human driver. This presents similar challenges as ridesharing. Furthermore, the newness of the technology will likely mean higher costs, accessibility that is limited to cities and wealthier areas, higher risks, and lower public trust – all crucial factors that the foster care system considers when dealing with the transportation of youth.

Even if the aforementioned options were easily accessible to foster youth, all of them could prove to be cost-prohibitive. Child welfare agencies operate on strict budgets, allocating money only for necessities. Foster parents are also likely on tight budgets and may have a hard time justifying the expense of transportation technology. Even if a child has access to a smart phone to order an Uber, he or she most likely does not have the money to spare. Children in urban areas may have access to micromobility, but if they do not have the money to pay for it, it is of little use. Children in suburban or rural areas may find the cost prohibits them from even owning a bike or scooter. If such technology is deemed necessary, various bureaucratic hoops remain when deciding who will pay for such expenses.

Despite these safety and budgetary considerations, technology should still be harnessed to address many of the transportation barriers that foster youth face. Technology must be adapted to better suit the unique situations of the foster youth population.  For instance, individuals with connections to child protection services (i.e. caseworkers, foster parents, Court Appointed Special Advocates, etc.) could volunteer to act as on-call drivers, providing rides to youth in the foster care system. Safety concerns could be limited by keeping drivers within the pool of individuals who have already been approved. For older youth and those in less rural areas, micromobility programs could be created specifically for foster children, in which scooters and bikes could be donated or purchased specifically for their usage. Additionally, as a far-out solution, contracts between counties and fully automated vehicles could prove to be the ultimate solution once the technology has become more pervasive and affordable. It must not be taken for granted that technology automatically benefits all populations and individuals equally; the unique challenges of foster youth mean that we must provide them with unique solutions.

Sources:


* Lucy Johnston-Walsh is a Clinical Professor and Director of the Children’s Advocacy Clinic at Penn State Dickinson Law in Carlisle, Pennsylvania. Emily Kortright is a certified legal intern in the Children’s Advocacy Clinic and JD candidate. The Children’s Advocacy Clinic is an experiential learning program for law students. The Clinic receives court appointments to represent children who are involved with the foster care system. Many clinic clients have been negatively impacted by transportation barrriers.

This year we have tried our best to keep up with all of the ways that the COVID-19 pandemic continues to challenge our transportation system – though with so much news on so many fronts that is often a losing battle. This past summer I moved from Ann Arbor to Washington, D.C. and last week I made a return trip to Michigan for some work that had to be completed on campus. Having crossed the eastern part of the U.S. twice now, I have been relieved to see the vast majority of travelers using mask when in public rest stops in Maryland, Pennsylvania, and Ohio – I saw maybe on noncompliant person the entire trip. In reflection on my travels, I want to use today’s blog to present a grab-bag of COVID stories from the past few months that I hadn’t had a chance to feature yet.

How COVID Changed Driving Behavior

All the way back in March, Phil noted in a blog post how COVID-related lockdowns shifted traffic and pollution levels in the U.S. For some people the pandemic has become an excuse to indulge their leadfoot. From January to August the Iowa State Patrol saw a 101% increase in the number of tickets for speeding 100 mph above the speed limit, and a 75% increase in tickets for drivers speeding 25 mph over the limit. Likewise, between March and August the California Highway patrol saw a similar 100% increase in tickets for speeding 100 mph over the limit, with other states reporting extreme speeding ticket increases as well. Some of this could be due to emptier roads inviting speed demons, combined with reductions in the number of officers on the road due to the pandemic.

Earlier in the year, the pandemic lockdowns and travel reductions did benefit one population – wildlife. Over the spring, when lockdowns were at their height and travel at record lows, California reported a 21% reduction in roadkill, while Idaho reported a 38% reduction and Maine a 44% fall. For a while it appeared that human roadway deaths would also fall as travel reduced – from March to May New York City went a record 58 days without a pedestrian fatality. Yet as time has gone on, the number of roadway fatalities has started to climb, or at least have not fallen comparable to reductions in travel. Looking at New York City again, while the number of vehicle miles driven in the city was down 40% between January and June of this year, the number of road fatalities only dropped 10%. Nationwide, while the total number of deaths on the road dropped 5%, the number of deaths per 100 million vehicle miles traveled actually rose from 1.02 in 2019 to 1.15 in 2020. Indeed July 2020 motor-vehicle fatality estimates saw an 11% increase over 2019.  Could it be that the drivers still on the road are the most dangerous? Could the increased number of speeders be goosing the number of deaths?

Ridesharing Continues to Take a Hit

In August I touched on the major ridership drops facing Uber and Lyft, as part of a blog post discussing the companies’ challenge to a new California law requiring them to treat their drivers as employees, rather than contractors. What I didn’t touch on was how those services and their drivers that are operating in the pandemic reacted to the health crisis. It wasn’t until May that Uber started requiring drivers to wear masks, though now they require both drivers and passengers to take selfies pre-ride to prove all parties are masked up, though in the case of riders the photos are only necessary if the rider was previously flagged for not wearing a mask. Uber has also supplied public health officials with usage data to assist with contract tracing. The company reported that in the first half of 2020 they received 560 data requests globally from public health departments, up from just 10 such requests in the entirety of 2019.

As cities and regions have opened back up, Uber ridership has been reportedly up in cities like New York, while still collapsed in San Francisco and LA. Given that nearly a quarter of the company’s rides from 2019 came from NYC, LA, SF, Chicago, and London, reduced demand on the west coast could be a major issue for them – even if the increased demand for takeout benefits their delivery service, UberEats (though delivery apps have proven to be less than profitable, even during the pandemic…).

Disinfecting Mobility

Another issue that has come to the forefront during the COVID crisis is how to clean vehicles and spaces to reduce the spread of illness. For mass transit half the battle is getting people to social distance and wear masks. In New York more than 170 transit workers have been assaulted while trying to enforce mask requirements, with 95% of those attacks taking place on buses. Meanwhile, companies like AV developer Voyage have adopted new tech to help keep their vehicles clean, which in Voyage’s case meant adopting ultraviolet lighting systems that sterilize their robotaxis in between passengers. In May, Ford rolled out new software for police vehicles they produce that uses the vehicle’s own heating system to bring the internal temperature in the car beyond 133 degrees Fahrenheit for 15 minutes, to disinfect high touch areas. In both of these cases the cleaning technology is dangerous to humans, meaning it’s unlikely to be rolled out to the average consumer. New mobility tech like drones have also been repurposed to help fight COVID, with a drone-based system being used to spray disinfectant in Atlanta’s Mercedes-Benz Stadium, which has been reopened for NFL games (though the number of fans that will actually be allowed in is unknown…).

That’s enough for today, though of course going forward we’ll continue to explore the many ways the ongoing crisis can challenge our transportation system – including upcoming looks at the future of rail and air travel.

Micromobility usage was at an all-time high before March 2020. The culmination of decades of growth and industry involvement in the United States resulted in nearly 350 million rides taken on shared bikes and scooters since 2010. The National Association of City Transportation Officials (NACTO) reported this astounding statistic in their Shared Micromobility in the U.S.: 2019 report.

In 2019, more than 134 million shared trips were taken, 60% higher than trips taken in 2018. NACTO reported the average trip in 2019 was 11-12 minutes, covering a distance of 1-1.5 miles. These numbers are significant because they represent trips that may otherwise have been taken by car. 46% of all U.S. car trips are under 3 miles. Replacing short vehicle trips with micromobility trips helps decrease carbon consumption. It can also increase access to new forms of transportation for low socioeconomic status and minority communities in cities.

However, micromobility in cities can and should be doing better. The adoption rates for Capital Bikeshare, a cheap and widely available bike-sharing service in Washington, D.C., is significantly lower among the Black and African-American population than among the White population. This is surprising at first when you consider that micromobility enjoys a positive perception from diverse groups of people.

However, positive perception does not always translate into access. Micromobility needs to be made widely available to all populations in the cities in which they operate. Many bike and scooter sharing services are dockless, and thus can be left almost anywhere. Many scooter companies rely on contract workers to pick up scooters at night when the batteries are dead, charge them overnight at their residence, and redistribute the scooters in the morning. This method allows the scooter companies to rebalance their fleet, and direct where scooters are first released in the morning, and how many scooters are dropped off in each area.

Logically, companies have figured out where scooters are ridden the most. They have access to incredible real-time demand and use data. But this can lead to a feedback loop. Suppose early micromobility adopters are predominately white, male, and young. In that case, scooters will be placed where that demographic is likely to find them first in the morning. In cities where scooter numbers have a firm cap, access to scooters is a zero-sum game for things like early morning work commutes or grocery runs.

One solution to the access problem is having cities work with micromobility companies to ensure scooters’ placement is not only profitable but equitable. Scooters should be located in all communities, not merely in ones that have shown early to use micromobility most frequently. These goals can be accomplished by cities working directly with the providers to access the data and share public-private goals. It could also be done by working with unbiased third-parties to make recommendations for what policies will make micromobility systems most widely available.

Something the current pandemic has provided micromobility companies is a different picture. The NACTO report found that micromobility usage in cities was utilized at higher rates when made free to essential workers. The most-used Citi bike stations were at hospitals in April. Black workers are disproportionally found among essential workers, and essential workers’ utilizing micromobility systems revealed new commuter patterns. The pandemic may provide a picture of what access should look like while simultaneously exposing micromobility systems to underserved communities as cheap and viable transportation options. There is clearly work to be done, and the information is out there. It is time to put the information to use.

This blog post kicks off a month of coverage focused on micromobility – check back tomorrow for a new journal article on micromobility laws nationwide!

A few weeks ago I wrote about how COVID-19 has disrupted the ridesharing industry, with Lyft and Uber struggling to find their place in our changing world. Those same disruptions have sent ripples through the various bikeshare and e-scooter services that make up the micromobility industry, though that segment of the greater mobility ecosystem may be better positioned to continue functioning during the ongoing pandemic.

First, the bad news – earlier in the pandemic, both Lime and Bird, major e-scooter operators, laid off staff, with Lime shedding 13% of its workforce and Bird laying off a full 30%. Part of this was due to the companies suspending some service in the face of the pandemic. In May, a huge number of bikes owned by JUMP, a Lime-owned dockless bikeshare service, were shown being destroyed in videos posted to social media.

Yet at the same time as those JUMP bikes were being destroyed, the U.S. found itself in the middle of a major bicycle shortage. Even now, months into the pandemic, bike producers are struggling to keep up with demand, though industry leaders acknowledge that they were very lucky to dodge the business losses they originally had feared as the pandemic began. Bicycles represent a convenient means of mobility, and as city dwellers sought to avoid public transit, they turned to their bikes to get them where they need to go. Indeed, in New York City, bike riding increased over 50% across the city’s bridges in March as the weather improved. Likewise, also in March, the city’s docked bikeshare, Citi Bike, saw a 67% increase in demand.

That last number is very interesting to me – even at some of the darkest points of New York’s outbreak, people were still flocking to use bikeshare. Indeed, of all the modes of mobility, micromobility seems the most pandemic-proof. To ride carefully all you really need to do is wipe the scooter or bike’s handlebars down, or generously sanitize/wash your hands after your ride. One company, Wheels, has even released rentable e-bikes with self-cleaning handlebars! And, of course, don’t forget your mask, which frankly could improve the ride experience as it shields your face from the wind. I’ll admit that other than my car, a Spin scooter is the only form of transportation I’ve used since the pandemic began – and I would consider myself more paranoid about COVID exposure than the majority of people.

Across the globe cycling and micromobility are a vital lifeline for people to traverse cities, and have proven to be more resilient than other modes of transport in the face of disasters – as seen in the 2017 Mexico City earthquake. I’ve written in the past about how cities are changing in the face of the pandemic, and stronger investment in the infrastructure to support micromobility and cycling needs to be a part of those changes.

So what can the micromobility industry itself do to encourage consumers to use their services, especially those who can’t afford for get their hands on a bike of their own? As often is the case in the mobility space (or at least our coverage of the space…) Michigan offers a potential path forward. At the end of June, the City of Detroit announced a new pilot program to connect essential workers with affordable e-bikes and scooters. In this case, two micromobility providers, Spin and MoGo, along with GM, leased scooters and e-bikes to the employees of hospitals, grocery stores, pharmacies, and manufactures – but only to those employees living within 6 miles of their workplace. Here, micromobility companies are getting their vehicles into the hands of people who need them the most – and giving them a reliable new way to get to work. While far from a full solution to the companies’ woes, it shows that they can reach customers while also providing a public service.

Like many industries, the automated vehicle industry faced setbacks due to this year’s many COVID-19 related local and regional lockdowns. In the spring, as the first wave of the virus spread, many companies had to stop testing to protect the human safety drivers and, in the case of Bay Area companies, follow local “shelter in place” orders. One partial exception to the rule was Waymo, which has been testing fully automated vehicles without safety drivers in Arizona, was able to keep some of those fully automated vehicles operating, since there were no drivers involved.

Beyond shutting down on-the-road testing, the AV industry has seen other COVID-related fallout. Due to the pandemic Ford delayed the launch of their robotaxi service to 2022, while GM’s Cruise unit laid off 8% of their staff in May. Yet desire to invest in the AV industry appears to remain strong. Zoox, which had (at least temporary) laid off its safety drivers in April, was bought by Amazon in June. Over the summer companies have begun to announce new testing sites – with Aurora testing automated semis and cars in Dallas-Fort Worth, and a Chinese AV developer, AutoX, launching a test around PayPal’s headquarters in San Jose, CA. Closer to home, Russian AV developer Yandex announced it would begin testing in Ann Arbor, their first test in the US, while May Mobility’s AV service in Grand Rapids will resume service at the end of August.

Indeed, two other developments in Michigan show that AV and mobility-related work is still an important focus, even during periods of major upheaval. In July the state of Michigan launched the Office of Future Mobility and Electrification, which is led by the “chief mobility officer.” The office’s structure and mission is based off work done by Detroit’s Office of Mobility Innovation – and hopes to recreate that office’s success at a state level. Part of the office’s mission will be to consolidate the work of 135 different councils, boards, and commissions spread out across 17 state agencies and departments – all of which have been working on some element of mobility. Earlier this month a second major announcement pointed to just how dedicated the state seems to be toward new mobility tech. On August 13th, a public-private partnership, named “CAVNUE,” was announced, with its goal being the creation of a 40-mile long testing corridor between Detroit and Ann Arbor. The corridor would be designed for testing both connected and automated vehicles as well as infrastructure. If this project is successful, it would be a major boon for the many companies in Southeast Michigan – and would signal a move to greater public testing of emerging mobility technology beyond more controlled environments like MCity.  

One lesson of the past year has been that the future can change very quickly, making rosy predictions of future AV successes harder to believe than in “the before time.” But these developments seem to show the AV industry finding its way forward. The future promise (and challenge) of AVs hasn’t diminished, even in our rapidly changing present.

Last week I discussed the California Superior Court decision that ruled that under California law Uber and Lyft must classify their ridesharing drivers as employees, rather than independent contractors. In response to that ruling, both companies had threatened to shut down service across the state. Yesterday, an appeals court issued a stay on that ruling, allowing both companies to continue operations, “pending resolution” of their appeal of the initial order. As I mentioned in my last blog post, the rideshare giant’s strategy currently appears to be “run out the clock,” until the November election, when California voters will decide on Proposition 22, which would establish a new classification for drivers. So for now those Californians who are willing to brave getting into a rideshare will be able to do so – while Uber and Lyft also explore more creative solutions, in case Prop 22 doesn’t pass.

Also on Thursday, another court case tied to Uber was just starting. Federal prosecutors in San Francisco filed criminal charges against Uber’s former security chief, Joe Sullivan. Sullivan is charged with two felony counts for failing to disclose a 2016 Uber data breach to federal investigators who were investigating similar earlier incidents that had occurred in 2014. In the 2016 incident, an outside hacker was paid $100,000 by Uber after the hacker revealed they had acquired access to the information of 57 million riders and drivers. Beyond the payment, Uber faced further criticism for failing to reveal the incident for a full year. Two of the hackers involved later plead guilty to charges related to the hack, and they are both awaiting federal sentencing. In 2018 Uber paid $148 million to settle a suit brought by state attorneys general related to the hack, while the FTC expanded a previous data breach settlement in reaction to the incident. Beyond the lack of transparency (to the public and law enforcement) Uber’s major misstep, at least in my view, is the payment itself. While many companies, Uber included, sponsor “bug bounties,” where outside security researchers are rewarded for reporting security flaws in a company’s products, this payment fell outside of that structure. Rather, it seems more like a ransom payment to less than scrupulous hackers. While Uber is far from the only company to have faced data breaches (or to have paid off hackers), this case should be a wake-up call for all mobility companies – a reminder that they have to be very careful with the customer data they are collecting, least they fall prey to a data breach, and, just as importantly, when a breach occurs, they have to face it with transparency, both to the public and investigators.  

The third Uber-related this month involves another former Uber employee, Anthony Levandowski, who was sentenced to 18 months in prison for stealing automated vehicle trade secrets from Google. In 2016, Levandowski left Google’s automated vehicle project to start his own AV tech company, which was in turn acquired by Uber. Levandowski was accused of downloading thousands of Google files related to AVs before he left, leading to a suit between Google’s Waymo and Uber, which was settled for roughly $250 million. There are a lot more details involved in the case, but it highlights some of the many challenges Uber, and the mobility industry at large, face.

Mobility and AVs are a huge business, with a lot of pressure to deliver products and receive high valuations in from investors and IPOs. That can incentivize misbehavior, whether it be stealing intellectual property or concealing data breaches. Given how central mobility technologies are to people’s daily lives, the public deserves to be able to trust the companies developing and deploying those technologies – something undermined by cases like these.

This week a California Superior Court ruled that transportation network company (“TNC”) titans Uber and Lyft have to classify drivers as employees, rather than independent contractors. The suit, spearheaded by the state’s Attorney General, sought to bring the two ride-sharing companies into compliance with Assembly Bill 5 (“AB 5”), which reclassified an array of “gig economy” workers as employees. When gig economy workers are reclassified as employees, they gain access to minimum wage requirements, overtime and sick leave, workers’ comp, disability insurance, and (importantly, in the COVID-19 era) unemployment insurance. Given those added benefits, employees can cost a company 20 to 30 percent more than an independent contractor, which is in part fueling opposition to bill and the ruling.

The decision comes after months of COVID-19 related disruptions that have cratered the ridesharing services at the core of Lyft and Uber’s business models. Lyft has reported a 61% revenue drop in the second-quarter of 2020, though it also reported an uptick in ridership in July. Uber reported a 75% drop in US ridership over April, May, and June of this year. Various lockdowns contributed to that drop – indeed, according to Uber’s own reports, nearly a quarter of its entire business comes from four US metro areas – NYC, Chicago, LA, San Francisco – along with its London operations. While the company has claimed encouraging signs from markets in nations like New Zealand, where the virus is under control, it remains to be seen if that success can be replicated in the US, where the virus is still spreading. In May, Uber announced two rounds of layoffs, cutting roughly 25% of its workforce (around 6,700 people), while Lyft cut 20% of its workforce in April.

Uber’s precarious financial situation makes its response to the Superior Court ruling all the more interesting – toying with a potential state-wide shutdown of their services, a least temporarily. In an interview, Uber CEO Dara Khosrowshahi indicated that if the company’s appeal of this week’s ruling fails, Uber may have to shut down service as they adjust to the new rules – with reductions in service outside major markets upon the service’s reactivation. That shutdown period also times out with the November election, where California voters will decide on Proposition 22, which would exempt ridesharing drivers from being classified as employers under AB 5. In a New York Times op-ed, Khosrowshahi has proposed a “third way” between employee and independent contractor. This system would require all gig economy companies to establish funds to give their workers cash payments to be used for benefits, with payouts based on the hours worked. By requiring all gig companies to pay in, individuals working for multiple companies at the same time remain covered as they switch from app to app. In response to this proposal, critics point out that Uber could already establish such a system, at least for their own drivers, if it wanted to.

California is far from the only place where ridesharing companies are being pushed to change the relationship the companies have with their drivers. In June, Seattle passed a law requiring paid sick time for TNC drivers during the COVID-19 crisis (the leave requirement would expire 180 days after the crisis has ended…). The Seattle bill grants one paid day of leave for every 30 calendar days worked (either full or part time). In Washington, D.C., a Lyft driver has challenged the company’s lack of sick days, arguing drivers should be classified as employees under city law. Indeed, as the pandemic spread workers across the nation have spoken up about the difficulty of obtaining any sick leave from gig economy companies, even when they showed symptoms of COVID-19.

Unemployment insurance has been a major focus in these disputes, especially as drivers have been unable to work due to lockdowns or COVID-related reductions in demand. Traditionally, when drivers are classified as independent contractors, they lose the ability to claim unemployment, as their “employer” doesn’t pay into the system. At the start of the COVID crisis, Congress set up a separate unemployment fund for self-employed workers, though that fund ran out at the end of July. Even while the funds were available,  however, many gig workers had a hard time obtaining them, as existing state unemployment systems struggled to adapt to new rules while being slammed with claims from millions of people newly out of work. In California, the issues surrounding Assembly Bill 5 complicated the process, as the Federal funds were marked for people classified as independent contractors, which, thanks to AB 5, now did not include many gig workers. Drivers in New York, frustrated at their inability to obtain unemployment funds sued the state government, and have won, at initially, building their arguments off two earlier rulings that deemed gig workers eligible for unemployment benefits. Part of the disputes in both California and New York involve the lack of earnings data for drivers, which the state needs to calculate their unemployment eligibility, with a lawyer for the State of New York accusing Lyft and Uber of “playing games” to prevent turning over said data. Elsewhere, the Pennsylvania Supreme Court ruled on a similar case – finding that an Uber driver was not “self-employed” for the purposes of unemployment benefits, while the Massachusetts A.G. has also recently brought suit to reclassify Uber and Lyft drivers as employees.

As the pandemic drags on, it’s hard to know what will happen next. The shortfalls of the current system have been made manifest – something clearly needs to change. Perhaps that could come in the form of Uber’s proposed “third way,” but such a system would need to be much better defined than it is now to prove it could offer a level of benefits comparable to those offered to employees. At the same time, if gig workers are to be counted as full employees, could that limit the entry of new gig companies? The massive growth of companies like Uber and Lyft was fueled in part by the cost savings that came from using independent contractors. Could new companies hope to cut into existing or new markets while also providing greater employee benefits?

For now, I’d say it’s more important to focus on the existing problem. Uber and Lyft are sophisticated technology companies, and both should be more than able to adapt their system to make their drivers employees. Given the COVID-19 related reductions in demand, the time seems right for them to make that change everywhere, not just in California. After all, according to their own plans, Uber won’t be dealing with human drivers forever, so future employee expenses will supposedly reduce with time. And while the pandemic may have harmed Uber’s ridesharing, it has helped grow its delivery service, UberEats. Even if automated vehicles replace gig drivers, they will be less able to replace workers for services like TaskRabbit or Instacart, where human labor is still central. And with expanded government-based safety nets seemingly a distant possibility, for the time being, workers will still need employer-based benefits of one form or another. Just as ridesharing companies disrupted the way people move through the world, it seems the time is right to disrupt the relationship between those companies and drivers that form the core of the TNC workforce.

An IBM report released earlier this month revealed some significant changes in consumer sentiment and public willingness to use certain mobility methods as a result of COVID-19. The study polled more than 25,000 adults during the month of April. Of the respondents that regularly used buses, subways, or trains: 20 percent said they no longer would utilize those options; an additional 28 percent said they would use public transportation less often. 17 percent of people surveyed said they will use their personal vehicle more; 25 percent of that 17 percent said it will be their exclusive method of transportation going forward.

Consumer perception of public transportation and the ways we move has shifted dramatically in just three short months. These results indicate that a significant number of U.S. consumers intend to drastically change the ways they travel in the aftermath of COVID-19. If these sentiments remain in place in the coming years, the decrease in public transportation ridership would mean decreased fee collections, which can lead to several options for cities to fund public transportation, including (1) an increase in ridership fees, (2) an increase in general tax revenue devoted to public transportation, or (3) a decrease in service offerings. All of these options are undesirable, especially in cities where private vehicle ownership is low, and many workers may have no option other than public transportation. The cities with the largest annual ridership numbers for subway or metro are New York City, Washington D.C., Chicago, Boston, and the San Francisco Bay Area.

City

Annual Metro/ Subway ridership (2019)

Population
(2018 Estimates)

Percent of Households without a vehicle (2016)

New York, NY

2,274 Million

8,398,748

54.4%

Washington, D.C.

237 Million

702,455

37.3%

Chicago

218 Million

2,705,994

27.5%

Boston

152 Million

694,583

33.8%

San Francisco

123 Million

883,305

29.9%

Removing 20 percent of public transportation riders completely and decreasing the usage of nearly 30 percent more would be financially catastrophic for any city transit authority. In 2019, the New York MTA brought in nearly $17 Billion. The current decrease in ridership (down 74 percent) has already required the MTA to seek billions in aid from the federal government and led to a first-ever decrease in working hours to sanitize trains overnight. A sustained decrease of more than 30 percent of rides per year would require a systemic overhaul of the metro system or some other drastic measures.

While some respondents indicated they will use their personal vehicles more, it is clear that in cities where public transportation is most utilized, many people do not have access to a personal vehicle. This will place a difficult decision on many underserved and minority communities: return to using public transportation and face an elevated risk of potential infection, struggle to find a job closer to home to avoid transportation, or save for a personal vehicle to avoid public transportation. Owning a vehicle in major cities can be prohibitively expensive for low-income households, and affordable parking can be nearly impossible to find. As transit authorities raise prices to compensate for lost riders, more riders may depart as the cost of ridership becomes too high for their budget. This could lead to a death spiral for public transportation. These systems simply cannot sustain 90 percent ridership decreases.

The same IBM survey also found that the decision to buy a personal vehicle after COVID-19 was “greatly” influenced by a constraint on their personal finances for more than 33 percent of respondents. 25 percent said they would hold off on buying a vehicle for more than 6 months. So for many people who wish to stop using public transportation, there is no safe and affordable option immediately available. Some may point to rideshare services as a safer alternative to the cramped quarters of public transportation. But according to the survey, of the respondents who used rideshare apps and services already, more than 50 percent said they would use the services less, or stop entirely. Uber and Lyft are going to see an incredible drop off in ridership; Uber and Lyft both halted their carpooling services in March. Uber trips were already down 70 percent in some cities in March. These numbers are sure to increase, and the companies will recover financially due to the increase in demand for UberEats during this crisis. However, the surge in ridership seen in recent years will take many years to reach 2019 peaks.

Finally, the IBM survey also asked about working from home, a topic I wrote about at the end of March.  Around 40 percent of respondents indicated they feel strongly that their employer should provide employees the option to opt-in to remote working from home going forward. 75 percent indicated they would like to continue working from home at least occasionally, and more than 50 percent indicated they would like working from home to be their primary work method. Perhaps companies will heed the desires of their employees. It is unlikely that many companies will offer the “work from home, forever” option that Twitter and Facebook have provided. But almost certainly we will see an increase in the ability of employees to work from home, now that their ability to do so has been demonstrated. Especially in cities like New York and San Francisco where the annual cost of office space is more than $13,000 per employee. If more tech companies follow Facebook’s lead and allow many employees to work remotely forever, we may even see housing prices start to decrease in some select areas and a further decrease in public transportation ridership in cities like San Francisco.

Mobility is going to change immensely once this crisis is over, whenever that may be. Public transportation must be overhauled in its current processes and operations if it hopes to regain public confidence and achieve ridership numbers anywhere near 2019 levels during the next decade.

As the COVID-19 pandemic continues and our memories of the “before time” feel ever more distant, some have begun to wonder how this crisis and its aftermath could change how and where people live. Will people abandon expensive and dense major cities for smaller cities, suburbs or even small towns? On the one hand, I’ll admit that living in a small city like Ann Arbor has made weathering the lock down rather easy, which could lead credence to these ideas. Personally, I’ve had no issues finding supplies, or taking a walk without running into too many other people (though my apartment building’s shared laundry rooms are now a fraught location). Of course, Ann Arbor, a wealthy, educated college town with excellent access to medical care has a lot of resources other cities do not, so it may not be the best example.

Alternatively, there are those who argue our cities won’t actually change that much post-COVID-19, and there are even ways that the outbreak could make cities better (with the proper investment). Cities have survived disease outbreaks for millennia, and given that so much of our economy, culture, and infrastructure is built around cities it would be hard to seismically shift to some other model of living. Yet the economic upheaval that the pandemic has ushered in will no doubt influence where and how people live, and could last a good deal longer than the disease itself.

So what changes are well already seeing in cities, and what could that indicate about where we’re heading? In a number of cities, including New York, Seattle, and Oakland, are closing streets to open up more space for pedestrians and cyclists. Streets could also be closed to provide more outdoor space for restaurants, to help them reopen while preserving some measure of social distancing. New Zealand has gone as far as to make such street alterations national policy. Cities and towns in that nation are able to apply for funding to immediately expand sidewalks and modify streets, with the national government covering 90% of the cost. Some suggest these closures and modifications should be permanent – that we should take this opportunity to create more walkable and bikeable cities now, when we have the chance. In many ways these modified streets are similar to proposals for automated vehicle (“AV”) dominated cities. Supporters believe that wide adoption and deployment of AVs would mean more streets could have one lane of traffic in each direction, with the extra space turned over to alternative uses. The current demands of social distancing dovetail with those ideas – could cities use the current crisis to prepare themselves for an autonomous future? Given the difficulty of building new infrastructure, it may not be a bad idea to get ahead of the curve.

As noted by Phillip in a post earlier in the crisis, another effect of the global lockdown has been improved environmental conditions in cities around the globe. In India, for example, where cities have significant pollution problems, massive reductions in travel have led to clear skies. For the first time, we are seeing clear examples of what cleaner energy production could bring (pun intended). Such improvements could lead residents to demand continued reductions in emissions even after this crisis passes. These and other changes made to cities in the short term to cope with lockdowns and social distancing could dictate the future of urban design, but only if governments and citizens are willing to adopt them and protect them from being undone once the crisis passes.

P.S. Those of you who are interested in buying a bike to help navigate the new socially-distanced world may run into an issue – just like masks, cleaning supplies, and toilet paper, bikes are now becoming a scarce resource in some places.

For the past two years, the purpose of this blog and the Law and Mobility Program has been to peak around the corner and see what’s next. We have explored the legal and policy ramifications of emerging transportation technologies and tried to figure out how those technologies, be they automated vehicles, e-scooters, delivery drones, or even flying cars, will fit into our existing transportation and legal systems.

As it has with so many aspects of our lives, the COVID-19 pandemic has complicated our ability to look forward – the world to come is harder to predict. How close to “normal” will we get without a vaccine or treatment? If a significant portion of the workforce moves to remote work (Twitter, for example, is going to a permanent remote work option), what does that mean for our transportation system? Will people retreat from large, dense cities? As the pandemic disrupts state and local budgets, what will happen to transportation budgets? Right now, there are no clear answers.

Going forward, this blog and the Law and Mobility Program will remain focused on the future, with a keen eye on today. We will still explore new technologies and their ramifications, while also seeking a better understanding of how the current crisis is altering the mobility landscape. Later today we’ll publish the first of a series of blog posts dealing with some of the specific disruptions and changes that are already occurring. We hope you’ll enjoy these posts and, as always, invite you to join us in the conversation by submitting posts of your own – outside blog post submissions (of 500-1,000 words) are always welcome at JLMsubmissions@umich.edu (all submissions are evaluated for publication by our staff).

Up to now, the way forward for roadways-based, commercial automated mobility remained somewhat of a mystery. Surely, we would not see AVs in the hand of individual owners anytime soon – too expensive. “Robotaxi” fleets commanded by the likes of Uber and Lyft seemed the most plausible option. There was, at least in appearance, a business case and that most industry players seemed to be putting their efforts towards an automated version of common passenger cars.

Over the course of 2019, the landscape slowly but steadily changed: public authorities started to worry more about safety and the prospects of seeing fleets of “robotaxis” beyond the roads of Arizona, Nevada or California seemed remote. This is how automated shuttles found their way to the front of the race towards a viable business model and a large-scale commercial deployment.

Many now mock these slow-moving “bread loafs,” ridiculing their low speed and unenviable looks. However, some of these comments appear slightly disingenuous. The point of the shuttles is not “to persuade people to abandon traditional cars with steering wheels and the freedom to ride solo.” I don’t see any of these shuttles driving me back home to Montreal from Ann Arbor (a 600 miles/1000km straight line). But I see them strolling around campuses or across airport terminals. The kind of places where I don’t quite care about the good looks of whatever is carrying me around, and also the kind of place where I wouldn’t take my car to anyway. There might be much to say about how certain electric vehicles marketed directly to the end-user failed because of their unappealing design, but I don’t plan to buy a shuttle anytime soon.

Looks aside, these automated “turtles” have a major upside that the “hare” of, say, Tesla (looking at you, Model 3!) may not dispose of. Something which happens to be at the top of the agenda these days: safety. While notoriously hard to define in the automated mobility context (what does safety actually imply? When would an AV be safe?) removing speed from the equation immediately takes us into a safer territory; public authorities become less concerned, and more collaborative, agreeing to fund early deployment projects. Conversely, scooters irked a lot of municipal governments because they go too fast (among other things). As a result, there was little public appetite for scooters and operators were forced to withdraw, losing their license or failing to become commercially viable.

As a result, it is the safe vein that various industry players decided to tap. Our turtles are indeed slow, with a top speed of 25mph, usually staying in the range of 15 to 20 mph. This is no surprise: that is the speed after which braking means moving forward several dozen if not hundreds of feet. Within that lower bracket, however, a vehicle can stop in a distance of about two cars (not counting reaction time) and avoid transforming a collision into a fatality. Hence, it goes without saying that such shuttles are only suitable for local transportation. But why phrase that as an only? Local transportation is equally important. Such shuttles are also suitable for pedestrian environments. Outside of the US, pedestrians have their place on the road – and many, many roads, across the globe, are mostly pedestrian. Finally, they can also be usefully deployed in certain closed environments, notably airports. In many places, however, deployment of such shuttles on roadways might require some additional work – creation of lanes or changes to existing lanes – in order to accommodate their presence. Yet the same observation can also be made for “robotaxis,” however, and the adaptations required there may be much more substantial. The limited applications of automated shuttles may be what, ultimately, makes them less appealing than our Tesla Model 3 and its promises of freedom.

Overall, turtle shuttles appear closer to a marginal development from widely used rail-based automated driving systems, rather than a paradigm shift. That might precisely be what makes them a good gateway towards more automation in our mobility systems; there is wisdom in believing that we will have a better grasp of the challenges of automated mobility by actually deploying and using such systems, but it is not written anywhere that we need to break things to do so.

It feels like much longer than two months ago that I first wrote about the coronavirus, Covid-19. At the time of my first blog post on the subject, the world had just witnessed China quarantine more than 50 million people in four weeks. The United States is now under conditions that significantly exceed that number. As of March 26th, more than 20 U.S. states have imposed either statewide orders, or partial orders, for residents to stay at home and shelter in place. Currently, more than 196 million citizens are being urged to stay at home. Social Distancing, Zoom, and Flatten the Curve have become household names and phrases overnight. As I write this, millions of citizens are entering their second or third week of working from home.

As the United States reckons with this outbreak’s severity and we learn to live at a distance, it is crucial to reflect on the unintended secondary effects that have become apparent from en masse “work from home” (“WFH”). Perhaps we can learn something. Perhaps it is just refreshing to note them. Perhaps it could provide inspiration for solutions to many problems we are already facing or will one day face.

Traffic Reductions

Traffic in various cities across the world has decreased dramatically. With millions of people working from home for the foreseeable future, there are fewer cars on the road during traditional rush hour peaks. Traffic in Chicago is moving as much as 60% faster; traffic in Los Angeles is moving 35% more quickly than usual.  8am LA rush hour traffic was flowing around 60 miles per hour, while it typically dips down to 30 mph. Roughly the same increase in speed was measured during the evening commute hour.

Pollution Reduction

A decrease in rush hour traffic was an easily predicted effect of mass-quarantining. One unintended side effect is the sharp decrease in pollution over major cities. There has been a severe downturn in Nitrogen Dioxide (“NO2“) — a significant pollutant released from the burning of fossil fuels — over Los Angeles, Seattle, and New York. The same significant drop in NO2 has been seen over China around Wuhan, Shanghai, and Beijing.

This decrease in pollution and an increase in traffic speeds reflect the anticipated benefits of autonomous vehicles. One of the benefits of AVs is the decrease in emissions that come from daily commutes. Most autonomous vehicle manufacturers and testers use electric vehicles because the electrical power the advanced computer systems draw exceeds the capacity of most car batteries. An increase in electric vehicles on the roads will decrease fossil fuels being burned while driving, which would likely lead to a reduction in pollutants (like NO2) over concentrated areas over roadways.

Another benefit of AVs is the decrease in traffic time. Vehicles the communicate with other vehicles (“V2V”) or that communicate with infrastructure (“V2I”) will, over time, allow for fewer slowdowns and higher average driving speeds. Because vehicles can communicate when they are slowing down, speeding up, turning, exiting, etc. the flow of highway traffic will become smoother as fewer interruptions cause human drivers to hit the breaks or come to a standstill. AVs that platoon in synchronization can also increase traffic speeds.

One of the much-touted benefits of autonomous vehicles is the increased productivity that a driver can experience by freeing up their attention and hands from needing to drive and monitor their vehicle. Although not to the same scale, faster traffic speeds from increased WFH translates into less time wasted on a commute and more time with family and at work. The same is true of WFH; my daily commute has changed from a 15-minute walk to the law school to a 15-second walk from the kitchen up to my desk. 

One metric I am interested in seeing after the Covid-19 social distancing and en masse WFH is worker productivity while working from home. If workers are similarly (or more) productive when working from home, we could see an uptick in companies allowing employees to WFH weekly, or even on an unlimited basis (subject to approval of some sort). Similarly, if some of the benefits that AVs seek to bring — decreased traffic, reduced pollution, increased productivity — can be achieved through en masse WFH, should AV proponents, and others interested in these benefits, be advocating for more WFH in other contexts? Companies could even use WFH to advertise their “green” efforts, by touting the number of driven miles and pollutants they eliminate annually by requiring employees to WFH periodically.

If we anticipate future events like Covid-19, where social distancing becomes crucial, keeping WFH skills sharp may become a necessity. Allowing or requiring workers to stay home one or more days per week could be a method to keep those skills sharp: being productive at home, efficient communication online, and keeping in contact with employees and supervisors. As this crisis continues to unfold, it is essential to remember that this round of social distancing will not last forever. As a country, we will emerge from this crisis changed. How we change is interesting to project, but it is similarly essential to aid in preventing future problems and adapting future solutions.

Last week, the United States declined to sign the “Stockholm Declaration,” an international agreement to set targets for reducing road fatalities. The reason given for not signing the declaration was the U.S.’s objection to items within the document that referenced climate change, equity, gender equality, and other issues. For context, here is the paragraph they are referencing:

[Signatories resolve to] “[a]ddress the connections between road safety, mental and physical health, development, education, equity, gender equality, sustainable cities, environment and climate change, as well as the social determinants of safety and the interdependence between the different [Sustainable Development Goals (“SDGs”)], recalling that the SDGs and targets are integrated and indivisible;”

This is an abdication of responsibility on the part of the American government, and ignores the real social, economic, and climate issues that are deeply tied to transportation. This piece is the first in a series, in which I will touch on how transportation, especially the emerging mobility technologies we usually cover, are entwined with issues that the current Administration sees as beyond the scope of road safety. This is not meant to be an exhaustive list, but rather a few examples offered as proof of the complexity of the issues. For today we’ll consider the environmental issues that are tied to road safety.

Road Safety and the Environment

Much has been made of how CAVs and other new mobility technologies can reduce greenhouse emissions via electrification of transportation and gained efficiencies through coordination between vehicles and infrastructure. The pursuit of safer roads via CAV deployment is also the pursuit of “greener” roads. This is especially important in the face of a recent study that found the use of rideshares like Lyft and Uber are increasing emissions – by an estimated 69%. The study found that rideshare usage shifted trips that would have been undertaken by mass transit, biking, or walking. Any discussion of the future of road safety, especially in cities, will have to include discussions of ridesharing, and how to better integrate biking, walking, and things like micro-mobility services into our streets, an integration that has important environmental implications.

The deployment of electric vehicles, something that appears to be a goal of major auto manufacturers, is another area in which road safety and the environment meet. To start with, these vehicles reduce overall vehicle emissions, which themselves are a health hazard. While not traditionally part of the road safety discussion, recent studies have shown that outdoor air pollution reduces the average life expectancy world-wide by almost 3 years. Including emissions in the safety conversation is especially important as vehicles are now the largest carbon producers.

Electric vehicles have other positive safety features – their large batteries, for example, make them less likely to roll over in an accident. On the other hand, electric vehicles traveling at low speeds can be harder for pedestrians and others to hear. In response, NHTSA has now mandated that EVs be equipped to generate artificial sound to warn those around them.

These are just a few ways in which environmental issues cross over into road safety, as recognized by the signatories to the Stockholm Declaration, and it is imperative the U.S. government take them into consideration rather than dismissing them outright.

The California DMV recently released several 2019 reports from companies piloting self-driving vehicles in California. Under state law, all companies actively testing autonomous vehicles on California public roads must disclose the number of miles driven and how often human drivers were required to retake control from the autonomous vehicle. Retaking control is known as “disengagement.” The DMV defines disengagements as:

“[D]eactivation of the autonomous mode when a failure of the autonomous technology is detected or when the safe operation of the vehicle requires that the autonomous vehicle test driver disengage the autonomous mode and take immediate manual control of the vehicle.”

Because of the proprietary nature of autonomous vehicle testing, data is not often publicly released;  this is one of the few areas where progress data is made publicly available. The 60 companies actively testing in California cumulatively traveled 2.88 million miles in 2019. The table below reports the various figures for some of the major testers in California.

Company Vehicles Active in CA Miles Driven in 2019 Engagements Engagements per 1,000 miles Average Miles Between Engagements
Waymo 153 1.45 Million 110 0.076 13,219
GM Cruise 233 831,040 68 0.082 12,221
Apple 66 7,544 64 8.48 118
Lyft 20 42,930 1,667 38.83 26
Aurora ? 13,429 142 10.57 95
Nuro 33 68,762 34 0.494 2,024
Pony.ai 22 174,845 27 0.154 6,493
Baidu 4 108,300 6 0.055 18,181
Tesla 0 0 0 0 0

What these numbers make clear is that there are several contenders who have made significant progress in the autonomous vehicle space, and there are some contenders which are not yet so competitive. Companies like Waymo, GM Cruise, and Baidu (which also tests extensively in China) have made incredible progress in decreasing the frequency at which a driver must engage with an automated vehicle. Others, like Apple, Lyft, and Aurora, while making progress, are nowhere near as sophisticated in avoiding engagements yet. Noticeably Tesla, the manufacturer frequently in the news for its “Autopilot” feature, does not test on public roads in California. The company says it conducts tests via simulation, on private test tracks, public roads around the world, and “shadow-tests” by collecting anonymized data from its customers during normal driving operations.

What these numbers seem to illustrate is that the autonomous vehicle industry is not all on par, as many often believe. It is often said that Henry Ford did not conceive the idea of an automobile; he perfected it. Similarly, companies like Waymo or GM may be the first to perfect autonomous vehicles, and gain an incredible market advantage once they do so. They are striving to be the Ford’s in this space, while others look like they’re still manufacturing carriages. However, despite these impressive numbers from a select few, the companies themselves think these metrics “do[] not provide relevant insights” (per Waymo) and that the idea that they give any “meaningful insight . . . is a myth” (per GM Cruise).

Why are the head and shoulder leaders on these metrics saying that they provide very little indication of progress on the technology? Disengagement reports may not be the best way for these companies to build trust and credibility in their products. They are only transparent in that they provide some data with no detail or context.

I was having a conversation about these disengagement numbers with a colleague* this week, and the topic of driver distraction arose. In the CA tests, the driver is constantly alert. Once these vehicles are in use for the general public, a notification to engage may not be effective if the driver is distracted. One reason these numbers do not provide particularly useful information is that for the metrics to be useful, at least two things must be true:

  • If the vehicle does not indicate it needs to disengage, no technical errors have been made; and
  • The driver is paying attention and can quickly engage when necessary.

In California testing, the drivers behind the vehicle are always alert and ready to take over. They may take over when the vehicle indicates they must, because of a malfunction or poor conditions. The driver can also engage when the vehicle has done something incorrectly, yet does not indicate that the driver needs to take over. This could include veering into a lane or failing to recognize a pedestrian.

One of the allures of autonomous vehicles is that a driver may not need to be 100 percent engaged for the vehicle to function correctly. However, current technology has not yet achieved this  result, as reiterated this past week by the National Transportation Safety Board (NTSB). The NTSB is an independent federal agency, which lacks enforcement power, but makes recommendations which are considered thorough and are taken seriously by policymakers.

The NTSB put forward many findings on Tuesday, February 25th regarding a Tesla crash that killed a California driver in March 2018. (A synopsis of the NTSB report and findings can be found here.) The facts of the crash involved driver of a Tesla in Autopilot mode, which struck a barrier between the highway and a left exit lane. NTSB found that the Tesla briefly lost sight of the lines marking the highway lane, and started to follow the right-most lane marker of the exit lane (because of fading on the highway lines) caused the vehicle to enter the “gore area.” This same action had apparently occurred several times in this exact vehicle, but the driver on previous trips was paying attention and was able to correct the vehicle. This time, the driver was playing a mobile game and did not correct the vehicle, causing the crash. Here was how NTSB presented three of their findings:

The Tesla’s Autopilot lane-keeping assist system steered the sport utility vehicle to the left into the neutral area of the gore, without providing an alert to the driver, due to limitations of the Tesla Autopilot vision system’s processing software to accurately maintain the appropriate lane of travel. (emphasis added)

The driver did not take corrective action when the Tesla’s Autopilot lane-keeping assist system steered the vehicle into the gore area, nor did he take evasive action to avoid the collision with the crash attenuator, most likely due to distraction by a cell phone game application. (emphasis added)

The Tesla Autopilot system did not provide an effective means of monitoring the driver’s level of engagement with the driving task.

Here we see a combined failure of both (1) and (2) presented above, combined with an inability to adequately monitor driver engagement. The vehicle took an action which it assumed to be correct, and thus did not notify the driver to take over. This combined with the driver not paying attention, failing to notice the need to disengage, and resulted in the crash. This tragic accident highlights that the AV industry still has many areas to improve before higher SAE level vehicles are ready for mass adoption. (The ADAS on the Tesla was SAE Level 2)

As I discussed last week, the federal Department of Transportation has taken a rather hands-off approach to regulation of automated vehicles, preferring to issue guidance rather than mandatory regulations. The  National Transportation Safety Board (NTSB) criticized this approach in their Tesla crash findings. The NTSB wrote that there has been “ Insufficient Federal Oversight of Partial Driving Automation Systems.”

The US Department of Transportation and the National Highway Traffic Safety Administration (NHTSA) have taken a nonregulatory approach to automated vehicle safety. NHTSA plans to address the safety of partial driving automation systems through enforcement and a surveillance program that identifies safety-related defect trends in design or performance. This strategy must address the risk of foreseeable misuse of automation and include a forward-looking risk analysis.

Because the NTSB lacks enforcement power, it cannot compel industry actors or other government agencies to take any action. It can only perform investigations and make recommendations. NTSB Chairman Robert Sumwalt had much to say regarding distracted driving, the AV industry, and the lack of government regulations in the hearing on Tuesday, February 25th.

“In this crash we saw an over-reliance on technology, we saw distraction, we saw a lack of policy prohibiting cell phone use while driving, and we saw infrastructure failures, which, when combined, led to this tragic loss,”

“Industry keeps implementing technology in such a way that people can get injured or killed . . . [I]f you own a car with partial automation, you do not own a self-driving car. Don’t pretend that you do.”

“This kind of points out two things to me. These semi-autonomous vehicles can lead drivers to be complacent, highly complacent, about their systems. And it also points out that smartphones manipulating them can be so addictive that people aren’t going to put them down,”

Chairman Sumwalt is right to be frustrated. The DOT and NHTSA have not regulated the AV industry, or ADAS as they should. Tragic accidents like this can be avoided through a variety of solutions; better monitors of driver engagement than torque-sensing steering wheels, lock-out functions for cell-phones when driving, stricter advertising and warning regulation by companies offering ADAS. Progress is being made in the AV industry, and automated vehicles are getting smarter and safer every day. But incidents like this that combine a failure of technology, regulation, and consumer use, do not instill public confidence in this incredible technology that will be beneficial to society. It only highlights how much farther we still have to go.

*I would like to thank Fiona Mulroe for the inspiration to take this approach to the disengagement report

In January of this year, the United States Department of Transportation and the National Science & Technology Council released Automated Vehicles 4.0: Ensuring American Leadership in Automated Vehicles Technologies (“AV 4.0”). The report is intended to act as a set of unifying principles across 38 federal departments, agencies, commissions, and Executive offices. It offers guidance and an overarching vision to state and local government agencies, as well as technical experts and industry participants. AV 4.0 builds on AV 3.0, which was released in 2018, and AV 2.0, which was released in 2017.

Consistent across the three iterations of Automated Vehicle reports produced under the Trump administration has been the wholly restrained voluntary/guidance approach, without mandates or true regulation laid down. This “light touch” approach recognizes that much of the regulatory action is taking place at the state level, and voluntarily by industry and other AV stakeholders. The lack of federal enforceability removes the hope of any near-term consensus or consistency to the coordination of states and industry approach to automated vehicles.

As in AV 3.0, AV 4.0 begins with a discussion of guidelines and broad overarching principles that the federal government will recognize when developing AV technology. The three Principles and associated sub-areas are:

  1. Protect Users and Communities
    • (a) Prioritize Safety
    • (b) Emphasize Security and Cyber Security
    • (c) Ensure Privacy and Data Security
    • (d) Enhance Mobility and Accessibility
  2. Promote Efficient Markets
    • (a) Remain Technology Neutral
    • (b) Protect American Innovation and Creativity
    • (c) Modernize Regulations
  3. Facilitate Coordinated Efforts
    • (a) Promote Consistent Standards and Practices
    • (b) Ensure a Consistent Federal Approach
    • (c) Improve Transportation System-Level Effects

While these broader principles are new to AV 3.0, the sub-areas within each principle are a mixture of old principles from AV 3.0, combined with some new government focuses. (The new components are italicized  in the above list) These new components center mainly around the Trump administration’s desire to “Buy American, Hire American,” and bring in new focuses for security, cybersecurity, and privacy. The report does indicate that DOT will establish manufacturing, performance, and operational standards to increase safety in AV testing and integration. Still, the parameters of these standards remain unclear.

However, the majority of the report is devoted to Section III: U.S. Government Activities and Opportunities for Collaboration. The  driving purpose of the report is to provide general descriptions of the vast array of government agencies that are responsible (or will be responsible) for some level of AV-related policies or subjects. The report detail both the big and small ways that federal agencies, departments, offices, etc. will play a role in the development and commercialization of AVs. However, there is no real substantive or specific policy discussion.

The survey of government agency activity (and an appendix with links to government websites and contacts for agencies responsible for AV-related policies) are the real substance added. There is no description or plan of how interagency cooperation will occur, nor is there an overarching plan for the government’s approach to implementation. AV 4.0 is useful as a catalog for the various ways the federal government could interact with AV-policy but gives no further direction to how industry and states should regulate AVs. The DOT continues to kick the can down the road but has thankfully provided a clearinghouse of information on which agencies may be responsible for what activities, and the current efforts underway at the federal level, particularly on research and funding.

This restrained approach could be a good thing, given the rapid pace at which the AV industry is developing. However, there is a great deal more work that needs to be done at the federal level before any of the 10 core principles articulated can be realized. The Department of Transportation has requested public comment on AV 4.0.

Cars are getting smarter and safer. And yet this new breed of automobile remains inaccessible to large parts of the consumer base due to high costs. Some of these costs are a natural result of technological advancements in the automobile industry. Others however may be a product of inefficient market dynamics among car manufacturers, insurers and technology companies – which ultimately contribute to a reduced state of safety on our roads.

Automated Driver Assistance Systems (ADAS) that equip cars with services like autonomous braking systems, parking assistance, and blind spot detection are growing at an exponential rate. The global ADAS market size was estimated to be around $14.15 billion in 2016. Since then, it has witnessed a high rate of growth and is expected to reach $67 billion by 2025. Not only is this good news for ADAS developers, it can also significantly increase road safety. The Insurance Institute for Highway Safety estimates that the deployment of automatic emergency braking in most cars on the road, for instance, can prevent 28,000 crashes and 12,000 injuries by 2025.

The biggest roadblock to the easy adoption of ADAS-equipped cars remains its prohibitive cost. Lower rates of adoption not only reduce the overall safety of cars on the road, but also disproportionately affect poorer people. Unsurprisingly, a study in Maryland found that individuals at the upper end of the socioeconomic spectrum have greater access to vehicle safety features leaving those at the lower end at higher risk.

A significant contributing factor to the continued high cost of automated vehicles is the high rate of car insurance. This seems rather counter intuitive. The technological evolution of safety systems reduces the risk of car crashes and other incidents. Consequently, this was expected to cause a decline in insurance premiums. And yet, costs remain high. Insurance companies have resisted the demands for lowering the cost of premiums claiming that the data about ADAS systems and their efficacy in reducing risk is just not conclusive. Moreover, the industry claims, that even if ADAS systems can cause a reduction in the number of vehicular incidents, each incident involving an automated car costs more because of the sophisticated and often delicate hardware such as sensors and cameras installed in these cars. As the executive vice president of Hanover Insurance Group puts it, “There’s no such thing as a $300 bumper anymore. It’s closer to $1,500 in repair costs nowadays.”

There is no doubt that these are legitimate concerns. An industry whose entire business model involves pricing risk can hardly be blamed for seeking more accurate data for quantifying said risk. Unfortunately, none of the actors involved in the automated vehicle industry are particularly forthcoming with their data. At a relatively nascent stage, the AV industry is still highly competitive with large parts of operations shrouded in secrecy. Car manufacturers that operate fleets of automated vehicles and no doubt gather substantial data around crash reports are loathe to share it with insurers out of fears of giving away proprietary information and losing their competitive edge. The consequence of this lack of open exchange is that AVs continue to remain expensive and perhaps improperly priced from a risk standpoint.

There are some new attempts to work around this problem. Swiss Re, for example, is developing a global ADAS risk score that encourages car manufacturers to share data with them that they in turn would use to recommend discounts to insurers. Continental AG has similarly developed a Data Monetization Platform that seemingly allows fleet operators to sell data in a secure and transparent manner to city authorities, insurers and other interested parties. These are early days so whether these initiatives will be able to overcome the insecurities around trade secrets and proprietary data remains to be seen.

It is however clear that along with the evolution of cars and technologies the insurance industry too will need to change. As a recent Harvard Business Review article points out, automated vehicles will fundamentally alter the private car insurance market by shifting car ownership from an individual-centric model to a fleet-centric one, at least in the short to medium term. This shift itself could cost auto insurers nearly $25 billion (or 1/8th of the global market) in revenue from premiums. It is imperative therefore that the insurance industry devise new innovative approaches to price the risk associated with AVs. Hopefully they can do this without further driving up costs and while making safer technologies accessible to those that need it the most.

The delivery industry is evolving in order to keep up with the rise of home delivery. Arrival, a startup company in the process of building electric delivery vans, plans to add new vehicles to the roads in the next few years. The company plans to offer vehicles with different battery capacities, but the current model maxes out at 200 miles of range. Arrival’s vehicles are expected to carry 500 cubic feet of packages and up to two tons. In order to be competitive with the direction towards automation, Arrival is designing its vehicles to accommodate autonomous systems which will allow for a smooth transition once autonomous driving is more widely used. In the meantime, the vehicle’s Advanced Driver-Assistance Systems (ADAS) will increase safety and operating efficiencies.

Arrival has recently captured the interest of big corporations. Hyundai and Kia announced that they are investing around $110 million in Arrival and will jointly develop vehicles with them. UPS has been a partner of Arrival since 2016 and has both invested and ordered 10,000 of Arrival’s electric delivery vans. UPS was motivated to purchase these vehicles because of its efforts to cut emissions and delivery costs, both of which Arrival contends its vehicles will do. UPS plans to begin using some of these vehicles later this year.

The Arrival vans along with UPS’s Waymo project “will help us continue to push the envelope on technology and new delivery models that can complement the way our drivers work,” said Juan Perez, chief information and engineering officer at UPS.

Arrival sets itself apart from other electric delivery vehicle companies in a few ways. One is its plan to establish “microfactories” that take up 10,000 square meters and make around 10,000 vehicles a year for nearby customers. The use of microfactories instead of a large plant will significantly cut the costs of manufacturing. Another unique aspect of Arrival is its modular approach to production in which the vehicle’s weight, type, size, and shape can be customized according to the purchaser’s preference.

The environmental aspect of using electric vehicles over gas or diesel vehicles is a major component that will contribute to Arrival’s current and expected success. A report by the World Economic Forum revealed that deliveries will increase carbon emissions by 30% by 2030 unless there is effective intervention. One of the intervention options that will have the greatest impact on reducing CO2 emissions is switching to battery electric vehicles. According to the report, battery electric vehicles can reduce CO2 emissions by 16%. UPS currently has about 123,000 delivery vehicles in its fleet. If all goes well with the electrical vehicles it purchased then the vehicles currently in UPS’s use might be phased out which is the sort of intervention our environment needs.

“As mega-trends like population growth, urban migration, and e-commerce continue to accelerate, we recognize the need to work with partners around the world to solve both road congestion and pollution challenges for our customers and the communities we serve. Electric vehicles form a cornerstone to our sustainable urban delivery strategies. Taking an active investment role in Arrival enables UPS to collaborate on the design and production of the world’s most advanced electric delivery vehicles.”

Juan Perez of UPS

There is no doubt that unmanned aerial vehicles (UAVs), i.e. drone aircraft or drones, are an increasingly popular and strangely normal aspect of our everyday lives in 2020. And how could they not be? When there is a product that can appeal to pretty much any and every one – from farmers wanting to efficiently monitor their crops, to those of us just looking to take the perfect selfie – it’s going to be explosively popular. Even military forces around the world are getting in on the action. The innovative uses for drones seem borderline infinite, and there is no questioning their utility even when applied in ways that may come as a surprise. 

One use that many people are likely familiar with is that of commercial delivery. A number of companies within the United States have been eyeing the drone delivery market for some time now, particularly UPS and Alphabet’s Wing. Typically, the Federal Aviation Administration’s (FAA) rules governing drone flight in the United States require, among other things, that the drone remain in the operator’s line of sight for the entirety of the flight. This generally goes for both hobbyists and commercial operators. However, the FAA, in an effort to encourage and not stifle innovation, created the Unmanned Aircraft Systems (UAS) Integration Pilot Program (IPP).

To promote continued technological innovation and to ensure the global leadership of the United States in this emerging industry, the regulatory framework for UAS operations must be sufficiently flexible to keep pace with the advancement of UAS technology, while balancing the vital Federal roles in protecting privacy and civil liberties; mitigating risks to national security and homeland security; and protecting the safety of the American public, critical infrastructure, and the Nation’s airspace.

Presidential Memorandum for the Secretary of Transportation, Unmanned Aircraft Systems Integration Pilot Program

Additionally, the FAA has in place one particular process that allows operators to obtain exemption from specific rules governing drone flight: Part 135 certification process. All IPP participants go through the Part 135 certification process, including those companies looking to dive into the package delivery market. Currently, “Part 135 certification is the only path for small drones to carry the property of another for compensation beyond visual line of sight.” Both UPS and Alphabet’s Wing are IPP participants and have been granted Part 135 certificates, although not for the same type of operations – you can check out the four types operations for which operators can be granted a Part 135 certificate here.

It was announced on October 1, 2019 that UPS subsidiary UPS Flight Forward was awarded a Part 135 Standard certification, the first ever. Flight Forward, in partnership with drone manufacturer Matternet, started in and has continued to hone its operation model for drone delivery within the healthcare industry, with WakeMed Hospital in Raleigh, NC as the starting point. It has been reported that one goal of the program is to test delivery of healthcare necessities in area where roads may not be a viable option – think natural disasters. 

“This is history in the making, and we aren’t done yet. . . . We will soon announce other steps to build out our infrastructure, expand services for healthcare customers and put drones to new uses in the future.”

David Abney, UPS chief executive officer

Recently, the Flight Forward drone delivery service program has expanded its services to the University of California San Diego (USCD) Health system where the company’s drones will be used to transport things like blood samples and documents short distances between centers.

Interestingly enough, a proposed rule from the FAA was just recently (February 3, 2020) published in the Federal Register. The proposal, titled Type Certification of Unmanned Aircraft Systems, essentially wants to open the door to more companies who want to get involved in small-package delivery via drone fleets. This type of regulatory framework for delivery drones should work much in the same way that the type certification process operates for other aircraft, a model-by-model certification process that allows approved models to then operate throughout the US. If you feel particularly strongly about this, the FAA is accepting public comment on the proposed rule until March 4, 2020.

This seems to be just the tip of the iceberg of what needs to be and may soon be done to promote widespread use of and explosive growth within the commercial drone delivery world, but it is definitely a big step toward getting that goal off the ground – no pun intended. If nothing else, this change is a good example of how the law is attempting to keep up with innovations in technology and increases in demand for such services, and how policymakers are remaining flexible in their approaches.

The past few weeks have shown the intricate connection that access to transportation has with human health and the global economy. The outbreak of Coronavirus in Wuhan China, leading to mass international transportation restrictions, is a case study in the effects that transportation has on our daily lives and on the global economy.

Coronavirus Timeline

  • China first alerted the World Health Organization or several cases of pneumonia in Wuhan at the end of December 2019.
  • The first death in China, which occurred on January 9th,  wasn’t announced until January 11th.
  • The first WHO reported case outside of China, in Thailand, occurred on January 13th.
  • The United States announced it would start screening passengers arriving in airports from Wuhan, after a second death was announced on January 17th. Many European countries followed suit on January 22nd
  • On January 23rd, China quarantined Wuhan, suspending air and rail departures
  • On January 24th, China shut down 13 more cities, affecting 41 million people. Several entertainment venues, including Shanghai Disneyland and sections of the Great Wall, were also shut down.
  • On January 25th, five more cities were placed under travel restrictions, increasing the total number of persons affected to 56 million. Hong Kong canceled Lunar New Year celebrations and restricted travel to mainland China.

In less than 4 weeks, China went from reporting pneumonia-like symptoms to restricting the travel of over 50 million people. Wuhan, a city of more than 11 million people, was shut down right before the beginning of the Chinese New Year, one of the busiest travel weeks in the world. The travel restrictions are meant to prevent the spread of the Coronavirus, a necessary tactic with more than 100 people dead, and more than 6,000 cases of infection.

The U.S., Europe, and Asia began enforcing new regulations to block visitors from China. At the same time, major airlines suspended flights to the country for the foreseeable future. The Chinese authorities shut down commercial flights and prohibited people from leaving Wuhan using buses, subways, or ferries. The restrictions also included blocking expressways. The reason for the shutdown: evidence suggests that the virus passes from person to person through close contact. One unintended consequence of the travel restrictions: stock market crashes.

The primary difficulty in shutting down Wuhan is that it is a central hub for industry and commerce in Central China. It is home to the region’s biggest airport and a deep-water port. Tens of thousands of travelers enter and depart Wuhan every day.

Access to hospitals is one of the most significant concerns about the outbreak. The power of the Chinese government to shut down transportation is perhaps most starkly seen in their goal to build a hospital in Wuhan in less than two weeks.

Restricting travel on the world’s second-largest economy on the eve of the busiest travel week in China caused the single largest day drop in U.S. stocks since September 2019. Millions of Chinese residents would typically make hundreds of millions of trips during the Chinese New Year to visit loved ones, celebrate the beginning of a new year, and enjoy time away from work. Last year, consumers in China spent $148 billion on retail and catering and generated $74 billion in domestic tourism on 415 million trips. China’s movie sector also brought in 10% of its annual revenue during the Chinese New Year. In response to the travel restrictions on January 25th, stocks like Disney, AMEX, and American Airlines all plummeted when markets opened Monday the 27th.

Limits on mobility and transportation affect things much more important than the U.S. stock market. The Chinese New Year is the most important celebration in the Chinese Calendar. It is a time to celebrate family, ancestors, and togetherness. Those affected by travel restrictions decided to forgo trips to see loved ones and visits to important cultural sites, as well as museums, galleries, and other sources of entertainment. The need to protect human health and prevent the spread of Coronavirus is paramount. But other than the Coronavirus affecting people’s physical health, the restrictions on mobility will prevent spiritual and familial connections that underpin Chinese society.

The impact transportation and mobility have on economics, and human health is clearly demonstrated in the Chinese travel restrictions. With 50 million citizens under “city-arrest” and the rest of the country reticent to travel, shockwaves have been felt across the globe. I hope the Coronavirus crisis can be solved quickly and efficiently, and that the Chinese can return to a sense of normalcy and free mobility.

As I wrote about last time, the Uniform Law Commission recently passed the Uniform Automated Operation of Vehicles Act. Today, I want to focus on Sections 5, 6, and 7 of that Act, which are titled, respectively, “Vehicle Registration,” “Automated-Driving Provider,” and “Associated Automated Vehicle.” The three sections are meant to complement each other and the generally applicable rules regarding motor vehicle registration in a state. The Comments to Section 7 give a nice synopsis of the way these three sections interact:

Existing state law generally requires the registration of a motor vehicle that is operated on a public road. If an automated vehicle qualifies as such a motor vehicle, it too must be registered. The person seeking that registration—typically the vehicle owner—must comply with all conditions of registration under existing law. Section 5 of this act adds a further condition: For the owner of an automated vehicle to register the vehicle, an automated driving provider must have designated that vehicle as an associated automated vehicle. Section 6 specifies how an entity declares that it is an automated driving provider, and Section 7 specifies how that entity then designates its associated automated vehicles. These three sections work together with existing law to ensure that a properly registered automated vehicle has a legal driver when it is under automated operation. In general, only if an automated vehicle is associated with an automated driving provider may it be registered and operated on public roads.

The Act’s comments are fairly dense, but we can work through them section by section. Under current state law, the owner of a motor vehicle must generally register that vehicle with the state according to state registration rules. The Act retains that requirement for the owner of an automated vehicles, but also adds a new condition of registration. Under Section 5, an automated vehicle may be registered only if an entity has:

(1) declared itself to be an automated driving provider (ADP) (explained in Section 6) and

(2) designated that particular automated vehicles as one of its associated automated vehicles (explained in Section 7).

The vehicle owner and the ADP do not necessarily have to be the same legal person. The vehicle owner could be an individual, and the ADP could be an original equipment manufacturer (OEM) like Ford, Honda, or Tesla. The manufacturer, or some other entity like an insurer or fleet operator, would declare themselves to be the ADP to the state, and declare the automated vehicles to be one of its associated vehicles, but the individual would own and register the car. This has the effect of “compelling” vehicle manufacturers, or some other entity, to declare themselves to be the entity legally defined as the driver for any consequences that arise from the vehicles actions on public roads. The comments to Section 6 clarify:

To become an automated driving provider, an entity must make an affirmative declaration that includes specific representations. This means that, first, an entity does not become an automated driving provider against its will and, second, not every entity can become an automated driving provider. Subsection (a) identifies three basic qualifications, at least one of which a provider must satisfy, and subsection (c) identifies four key requirements, all of which the provider must satisfy.

To qualify as an ADP, an entity must have either participated substantially in the development of the system, submitted safety self-assessments with NHTSA, or be a registered manufacturer with NHTSA. The purpose of these sections is to require registration with the state, ensuring that every automated vehicle on a state’s roads has an entity associated with it, against whom the state can credibly enforce relevant provisions of the state vehicle code.

Manufacturers are not required to register as an ADP. But they will be incentivized to declare themselves as ADP’s for the simple reason that if they do not, their customers will be unable to register or use their vehicles in a state that has adopted the Act. If customers in one state were unable to register Ford vehicles but could register Honda vehicles, then everyone in that state would buy Honda automated vehicles and nobody would buy Ford. Under Section 7, once an ADP has designated an associated automated vehicle, the association remains until the ADP is not recognized by the state agency, ceases to exist under principles of corporate law, or affirmatively withdraws the designation.

This approach is a great way to allow manufacturers of automated vehicles to select the states in which they wish to be responsible for their vehicles. If they register as an ADP in Arizona, but not New Mexico, then their customers will be able to register and drive their vehicles on the public roads in Arizona, but not New Mexico. This can allow manufacturers to choose where they accept liability for the automated features of their vehicles.

However, this could cause problems. Assuming uniform adoption of the Act (which is unlikely), if manufacturers are selective with the states where they register as ADP’s then there could be adjacent states where a manufacturer is an ADP in state X, and not in state Y. If customers in state X drive their automated vehicle across the border into state Y, there could be legal questions if the manufacturer is liable for accidents that occur in state Y, especially if they specifically chose not to register there. This could lead to geofencing at state borders, requirements that shift control back to the human driver as they cross state borders, or a whole host of other potential solutions. These solutions could also cause problems. What if a driver is asleep as the vehicle crosses into a state where that manufacturer has not registered? What if the driver overrides and continues allowing the vehicle to drive? Has liability shifted from the manufacturer to the owner given the owner’s conscious choice?

Questions of tort liability, jurisdiction over manufacturers, and technological work-arounds could abound if OEM’s are selective with their registration as ADPs. But they should be allowed to select where they want to sell their automated vehicles if they will be required to legally be identified as the responsible entity. Sections 5, 6, and 7 of the Automated Vehicle Act will likely cause much debate in states that consider adopting the Act.

On Thursday, January 16, 2020, the Official Report of the Special Committee to review the Federal Aviation Administration’s Aircraft Certification Process was released, and it seems like quite a few people – i.e. very vocal critics of Boeing and the FAA – are not likely to be pleased by the lack of lambasting language in the report. This is only the most recent development in the still-unfolding story of the Boeing 737 MAX passenger airliner, the aircraft at the center of the two fatal crashes in October 2018 and March 2019 that killed 346 people in total. The committee’s report has been released amid outcry over recently disclosed internal documents diplomatically labeled as “troubling” and reports of impending job cuts and layoffs from companies within the Boeing 737 MAX supply chain. “Troubling” may be putting it mildly.

“The Committee applauds the remarkable gains in safety achieved by U.S. aviation and recognizes the safety benefits provided to the worldwide aviation system. However, each member of the Committee fully acknowledges the two foundational premises that risk will always exist in aviation and that no fatality in commercial aviation is acceptable.”

Official Report of the Special Committee to review the FAA’s Aircraft Certification Process, Executive Summary, page 6

With all of this currently happening, now is a good time for a bit of background to get up to speed. On October 29, 2018, Indonesian Lion Air Flight 610 departed from Jakarta and crashed into the Java Sea twelve minutes later, killing all 189 passengers and crew on board. Less than five months later on March 10, 2019, Ethiopian Airlines Flight 302 departed from Addis Ababa and flew for only six minutes before plummeting directly into a field at almost 700 miles per hour. Once again, all passengers and crew on board, totaling 157 people, were killed in the crash.

In the interim between the two crashes, partial fault was tentatively attributed to malfunctions in one of the aircraft’s Angle of Attack (AOA) sensors (check out these sources for a relatively clear and more in-depth explanation of the technical side of this).The MAX was equipped with the Maneuvering Characteristics Augmentation System (MCAS), an automated system designed to activate and correct the problem when the AOA began to reach unsafe levels. Unfortunately, it didn’t quite work out that way. Erroneous AOA readings during both flights led to MCAS automatically activating, pitching the nose of the aircraft down while pilot and co-pilot fought to right the aircraft. This happened repeatedly until the planes ultimately crashed.

Today, in the aftermath of the two planes crashing, it’s understood that the single faulty AOA sensor and MCAS are among a number of factors that caused the accidents. Since then, Boeing and the FAA have had no shortage of critics. Going into the entire timeline of events would take quite a while, so here are some highlights: the MAX was grounded around the world and the grounding remains in effect today; Boeing reportedly misled FAA regulators as to the full extent of MCAS’s abilities and failed to mention the system in pilots’ manuals; and the international aviation community has come down hard on the FAA’s certification process, with some countries demanding changes before it will allow the MAX to return to service. (A timeline of pretty much everything can be found here.)

“The FAA’s certification system is a process sanctioned by Congress, driven by regulation, directed by the FAA, and implemented by certified organizations and individuals. It is an iterative, comprehensive process grounded in the cumulative expertise of the FAA gained through over a half century of process management and oversight.”

Official Report of the Special Committee to review the FAA’s Aircraft Certification Process, Executive Summary, page 6

Clearly, Boeing and the FAA are ready for the plot twists to come to an end and the Special Committee’s report must seem like a small point of light in an incredibly long, bleak, and dark night. My personal flair for dramatics aside, the report does seem to come to different conclusions than most. The Committee, made up of five aviation safety experts chosen by Secretary of Transportation Elaine Chao, was formed to review: 1) “the FAA’s product certification process, the use of delegated authority, and the approval and oversight of designees”, and 2) “the certification process applied to the Boeing 737 MAX 8, which occurred from 2012 to 2017.” While the report does provide a number of recommendations, the Committee ultimately came to the conclusions that the FAA’s current certification process based on delegated authority is good one and that the FAA and Boeing followed the required process in certifying the MAX.

“As reflected by the safety statistics cited above, the Committee found that the FAA’s certification system is effective and a significant contributor to the world’s safest aviation system.”

Official Report of the Special Committee to review the FAA’s Aircraft Certification Process, Executive Summary, page 6

The report also cautions against a complete overhaul of the FAA’s delegation of authority framework for the certification process. However, members of Congress couldn’t seem to disagree more, especially after a slew of internal communications showing Boeing employees saying some pretty damning things were released earlier this month – calling regulators ‘clowns’ is never a good call. One particularly vocal FAA critic and crusader for legislative action is Peter DeFazio (D-Ore.), Chair of the House Committee on Transportation and Infrastructure. Pulling no punches, DeFazio has stated that “the FAA rolled the dice on the safety of the traveling public” in allowing the MAX to fly despite knowing the risks.

“Any radical changes to this system could undermine the collaboration and expertise that undergird the current certification system, jeopardizing the remarkable level of safety that has been attained in recent decades.”

Official Report of the Special Committee to review the FAA’s Aircraft Certification Process, Executive Summary, page 8

The question now is how, or even if, this report will impact the calls for change. Recent plot twists caution that there’s no telling what will happen next.

The Uniform Law Commission (“ULC”) is a non-governmental body composed of state-selected lawyers who oversee the preparation of “Uniform Laws” to be proposed to the states for adoption. The group’s most well-known body of law will be familiar to any lawyer or law student who paid attention in first-year contracts: the Uniform Commercial Code (UCC). Not all projects of the ULC are as successful as the UCC. In fact, many are never adopted by any state.

The ULC appointed a Drafting Committee on Highly Automated Vehicles in 2017.  The Committee recently completed an Automated Vehicles Act, titled “The Uniform Automated Operation of Vehicles Act,” which is a “uniform law covering the deployment of automated driving systems (SAE levels 3 through 5).” The Act is intended to cover a vast array of issues likely to be faced by states in the coming decades as autonomous vehicles become more ubiquitous. The ULC description of the Automated Vehicles Act states:

The Uniform Automated Operation of Vehicles Act regulates important aspects of the operation of automated vehicles.  This act covers the deployment of automated vehicles on roads held open to the public by reconciling automated driving with a typical state motor vehicle code.  Many of the act’s sections – including definitions, driver licensing, vehicle registration, equipment, and rules of the road – correspond to, refer to, and can be incorporated into existing sections of a typical vehicle code.  This act also introduces the concept of automated driving providers (ADPs) as a legal entity that must declare itself to the state and designate the automated vehicles for which it will act as the legal driver when the vehicle is in automated operation.  The ADP might be an automated driving system developer, a vehicle manufacturer, a fleet operator, an insurer, or another kind of market participant that has yet to emerge.  Only an automated vehicle that is associated with an ADP may be registered.  In this way, the Automated Operation of Vehicles Act uses the motor vehicle registration framework that already exists in states – and that applies to both conventional and automated vehicles – to incentivize self-identification by ADPs.  By harnessing an existing framework, the act also seeks to respect and empower state motor vehicle agencies.

The final version of the act can be downloaded here.

This Act is a step in the right direction. It does much of the leg-work for state legislatures to exempt autonomous vehicles from a variety of state laws by providing language which can be easily inserted into various state vehicle codes. States can choose to enact certain parts of the Uniform Act, picking and choosing the sections or phrases they want and discarding the rest. This is beneficial because it will likely mean more states will enact some form of AV exemption. However, it also means there could be substantial variation between states that adopt some but not all of the Act. The passage of a Uniform Act by the ULC does not ensure there will be uniform adoption.

The act is not very long, only 28 pages including all the comments and legislative notes. There are many sections that deserve a more extensive dive, but I want to begin with a subsection that relates to a topic I’ve written about before: Platooning. The Act does not include a provision that would legalize platooning, but it does contain a single provision that addresses state laws regarding minimum following distance: Section 9 (h). Section 9 covers “Rules of the Road.” Subsection (h) states:

A provision of [this state’s vehicle code] imposing a minimum following distance other than a reasonable and prudent distance does not apply to the automated operation of an automated vehicle.

The comment to the section clarifies subsection h:

[T]his section provides that a numerical minimal following-distance requirement does not apply to the automated operation of automated vehicles. These numerical minimums may be unnecessarily large for automated vehicles that react faster than human drivers. However, the common “reasonable and prudent” following-distance requirement continues to apply. This bracketed subsection (h) differs in scope from following-distance legislation enacted in some states to facilitate the platooning of vehicles, particularly commercial trucks, that use advanced technologies but may not necessarily qualify as automated vehicles.

As I’ve written about before, platooning vehicles that follow at incredibly close distances could be considered “reasonable and prudent” given the connected nature and quick response times of the technology. If the Uniform Act were adopted in some states, it could present the opportunity to argue that there is, or should be, a reasonable car standard applied to autonomous vehicles. The act also solves the problems of states with 300-500-foot following distance requirements for trucks.

The passage of the Act is exciting for many reasons. It shows that the legal world is taking autonomous vehicles seriously, and is taking fundamental steps to create a legal framework within which these vehicles can operate. It also provides a baseline for states to modify their existing laws to allow autonomous vehicles to be exempted from many requirements that need not apply to autonomous vehicles. For example, there is no need for a steering wheel or gas pedals in an AV. There may be a need for a large touchscreen like in the various Tesla models, which would be distracting in traditional vehicles. The Act will hopefully spark discussions about the proper way to regulate autonomous vehicles at the state level, and may even spark debate over the merits of varied state or uniform federal regulation.

Imagine that you and your friends go out for a night on the town. By the time you are well and tired, it seems as though everyone else simultaneously had the same idea. With everyone around you clamoring to call an Uber or Lyft, you and your friends take one look at the gridlocked streets and agree that the roads are just not the way to go tonight. However, the skies look clear and traffic-free, so why not take a helicopter across town? While this may seem like the start of a very odd joke, it’s a future that Los Angeles-based startup up Skyryse is looking to bring to the present and a reality that is closer than you might think.

“Skyryse is on a mission to get people where they want to be quickly, affordably and safely.”

Skyryse, Our Vision

While this may be enough to start stirring up the questions in your mind, here’s another twist to Skyrise’s plans for urban travel: fully automated flight. In mid-December Skyrise held a demonstration highlighting a helicopter that took off, flew for fifteen minutes, and then landed, all fully automated.

The demonstration showed a lot of what Skyryse has in mind for making urban air mobility a widely adopted norm for traveling short distances. For one, Skyryse unveiled its Skyryse Flight Stack, which “comprises of technology that automates flight in [Federal Aviation Administration]-approved helicopters, safety and communication systems, and a network of smart helipads to ultimately create a new transportation system.”

“Unlike other companies building autonomous vertical takeoff and landing (VTOL) aircraft from scratch or only for the military, Skyryse refits existing consumer-grade, dependable and certified aircraft and technologies with software and hardware innovations.”

PRNewswire.com

Simply put, Skyryse isn’t building new aircraft, it’s taking what already works and adding a little bit of spice. The company’s goal is to develop a fully autonomous VTOL flight system that can be installed in both legacy and future helicopter models, as well as helipads capable of communicating with the outfitted aircraft information such as changing weather conditions or low-flying objects. Skyryse aims to become the first fully operational air taxi service available to the public that doesn’t break the bank.

Now, you may be thinking that a self-flying helicopter is a ride on which you would rather not be a passenger but have no fear. Passengers on aircraft in Skyryse’s fleet are accompanied by a trained and certified pilot who oversees the flight system and can take over the controls in the event of an emergency or potential malfunction. While this does leave open the potential for awkward conversation, it does add an extra layer of safety and checks on the autonomous system.

I personally think this sounds incredible, if it can–no pun intended–get off the ground. Why not take to the skies to avoid the mad rush of cars and congestion of city streets? And why not use already available aircraft to do it? It all makes sense and seems pretty logical. However, we all know that logic does not always guarantee success.

My main concerns surround public perceptions and pricing. For perception, I am curious about the projected amount of time it will take before there is enough demand to justify a supply. How long will air taxi companies have to advertise and ultimately wait before enough people know about and trust their autonomous aircraft? As for pricing, the concerns and questions are probably pretty clear. How is this going to be affordable for everyone, and when? It has been reported that Skyryse plans to release the details of how it will achieve affordable pricing at some point this year. I for one am looking forward to the day when I can hop in line at a helipad and quickly fly across town, all without breaking the bank.

Tesla and the State of Michigan have settled Tesla’s constitutional challenge to Michigan’s refusal to grant Tesla’s request for a Class A license, which would have allowed Tesla to open a company-owned dealership in the state. The lawsuit, which was filed in federal court in the Western District of Michigan in 2016 and was scheduled to go to trial this year, grew out of a 2014 legislative amendment to Michigan’s automobile dealer law that made it unlawful for an automobile manufacturer to open its own retail store in the state, essentially forcing automobile manufacturers to distribute cars through franchised dealers. I detailed the nefarious circumstances and effects of the 2014 legislation in Tesla, Dealer Franchise Laws, and the Politics of Crony Capitalism, 101 Iowa L. Rev. 573 (2016).

There are two important terms to the settlement: (1) the state will not contest Tesla’s right to operate service centers in Michigan through a subsidiary; and (2) the state will not contest Tesla’s right to market cars to consumers in Michigan through a “gallery” model. This settlement  allows Tesla to sell and service cars in Michigan as it wants, and thus represents a total victory for Tesla in Michigan. It could also be a tipping point in Tesla’s ongoing battle for the right to engage in direct distribution in other states.

In my view, the service component is the more important aspect of the settlement. Tesla was already able to sell cars to customers in Michigan by marketing them over the Internet and delivering them out of state, so the agreement on the gallery marketing model is helpful but not essential. On the other hand, until today Tesla was prohibited from opening a service center in Michigan, which required Michigan Tesla owners to drive to Ohio for service. It will now be able to open service centers in Michigan through a subsidiary. (The subsidiary requirement will not impose any greater burden than a few hours of corporate lawyer time). Having access to service centers in Michigan will significantly increase the appeal of owning a Tesla in the Wolverine State.

The settlement also allows Tesla to open galleries in the state, although it still may not transact “sales” of its cars in the state. In effect, this means that Tesla can have sales people show its cars to potential customers in retail spaces (i.e., malls), arrange for test drives, help customers figure out what options they want on their car, and facilitate the paperwork. The customer will then have to complete the actual sales transaction over the Internet or telephone with Tesla in California (or wherever Tesla houses its sales function). The car will then be delivered to the customer in Michigan, which will increase the convenience of the buyer experience. The only remaining limit is that the sales contract needs to say that title will transfer out of state; otherwise, the customer can configure and order the car from within the state. 

There is no good reason to deny Tesla the right to open whatever sort of sales operation it wants in Michigan, but this remaining limitation will have relatively little effect on Tesla’s business model. Even in states where Tesla has complete freedom to sell cars as it wants, it doesn’t generally open traditional dealerships with lots of inventory sitting on a lot. The company operates on a custom order basis and usually uses the sort of galleries it will now be able to open in Michigan. So, while still arbitrary and annoying, the Michigan settlement gives Tesla everything it needs to compete in Michigan.

Tesla is clearly a big winner in this settlement. Who are the other winners? And who are the losers? 

Other new electric vehicle manufacturers, like Ford and Amazon-backed Rivian Motors (which will begin selling cars in 2020) and Faraday Future (which hopefully will be able to get to market eventually) will benefit from the trail Tesla has blazed. Having settled on these terms with Tesla, it would seem legally very difficult for the state to deny a similar arrangement to any other company situated like Tesla. 

The car dealer’s lobby, which has fought tooth-and-nail to stop Tesla from distributing directing on a state-by-state basis, is clearly a big loser. Michigan, the state with the most pro-dealer law on direct distribution, has now opened the doors for new EV companies to bypass the traditional dealer model entirely.

In the short run, traditional car companies like General Motors and Ford are also losers. GM, in particular, has backed the dealers politically in opposing the right to engage in direct distribution, apparently because forcing Tesla to distribute through the dated and increasingly inefficient dealer model will slow Tesla’s market penetration. Not only does the Michigan settlement allow Tesla to avoid the cumbersome dealer model and to start gaining significant market share in America’s car capital, but it’s far from clear that traditional car companies that do franchise independent dealerships would be eligible to operate their own direct distribution system on a similar model. In other words, the Michigan settlement may permit Tesla and other EV manufacturers to leapfrog traditional car companies on distribution.

Just as there is no good basis in public policy to limit Tesla’s right to engage in direct distribution, there is also no reasonable basis to prohibit it to traditional car manufacturers either. As I have previously detailed at length, there is simply no consumer protection reason that any car company shouldn’t be able to choose how it sells cars to consumers. As companies like Tesla and Rivian accustom car buyers to the benefits of dealing directly with the manufacturer, there will be increasing competitive pressure on GM, Ford, Chrysler, and foreign auto makers to seek legislative changes in hold-out states like Michigan that still prohibit direct distribution.

Finally, although the immediate consequences of the settlement will be felt only in Michigan, the settlement will put increasing pressure on other hold-out states that still block Tesla from selling to consumers. The more states that allow direct distribution and the more customers that experience it, the less credible the dealers’ lobby will be in arguing that direct distribution harms consumers. With new entry by other companies like Rivian on a direct distribution model, the political and legal battles over car distribution are at a tipping point. Although there will still be a place for franchised dealers to play a role in car distribution for some time, the inflexible and mandatory system created by the dealer laws of the mid-twentieth century is on its last legs.

If there are any ideas that the internet believes to be the truth in this modern day in age, I think that the following would at least make the list: the government is likely watching you through the camera in your laptop, and Facebook’s algorithm may know you better than anyone else. While the internet normalizes being surveilled – and George Orwell can be heard continuously rolling over in his grave – the collection, analysis, and sale of information and user data is something to, at the very least, keep in mind.

Target can predict when a shopper is due to give birth based on subtle changes in shopping habits (going from scented to unscented soap, for example); your phone tracks where you are and how often you go to the point that it recognizes your patterns and routines, suggesting certain destinations you visit regularly; and health insurance companies believe they can infer that you will be too expensive to cover simply from looking at your magazine subscriptions, whether you have any relatives living nearby, and how much time you spend watching television. It is both fascinating and startling in equal measure.

When we narrow our focus to transportation and mobility, there is still an entire world of information that is being collected, sold, and turned into, for example, new marketing strategies for companies purchasing that data from brokers. Other times, the actor using that data-turned-actionable intelligence is a government entity. Either way, it’s good know and understand some of what is being collected and how it may be used, even if it’s only the tip of the iceberg. Car insurance companies track and collect data on how often drivers slam on brakes or suddenly accelerate and offer rewards for not doing those things. People have been subjected to police suspicion or even been arrested based on incorrect geolocation data collected from their cell phones.

Despite the potentially grim picture I may have painted, user data isn’t always wielded for evil or surveillance. Recently, popular navigation app Waze added a feature that allows its users to report unplowed roads plaguing drivers during the winter months. The feature was developed through collaboration with the Virginia Department of Transportation (VDOT). Users in areas with inclement winter weather are now notified when they are coming upon a roadway that is reportedly in need of a snowplow. In addition to providing users with information and warnings, Waze also partners with transportation agencies across the U.S. and provides these agencies or local governments with this winter transportation information through the Waze for Cities Data program. The point is to make responsible parties aware of the areas that are still in need of a snowplow and assist them in prioritizing and deploying resources.

This sort of data collection is innocent enough and helpful in a person’s everyday life. According to Waze, the data is anonymized and contains no personally identifiable information (PII) when it becomes accessible to government agencies. However, as cars and cities become smarter the risk of an individual user’s data being used for more concerning purposes is likely to increase. This danger is in addition to the privacy risks that come from carrying around and depending upon personal devices such as cell phones.

“[Cars are] data-collecting machines that patrol the streets through various levels of autonomy. That means that our mobility infrastructure is no longer static either, that infrastructure is now a data source and a data interpreter.”

Trevor English, InterestingEngineering.com

Uber went through a phase of tracking users even while not using the app; a number of smart city technologies are capable of capturing and combining  PII and household level data about individuals; and the City of Los Angeles wants to collect real-time data on your individual e-scooter and bikeshare trips – California’s legislature doesn’t exactly agree. As these capabilities are advancing, so is the law, but that doesn’t necessarily mean that the race is a close one. So, while our cars and scooters and rideshare apps may not yet be the modern iteration of Big Brother, there’s always tomorrow.

Several major OEMs have recently announced scaling back of their shared or automated mobility ventures. Ford and Volkswagen are giving up investments in “robotaxis” – the CEO of their software partner, Argo, was quoted saying he “hates the word” anyway – and similar services operated by German automakers are withdrawing from various markets or shutting down altogether, after overextending themselves during the last 18 months.

Two separate trends seem to contribute to that movement. The first one, car ownership is still growing worldwide, albeit modestly – roughly 1% per year over the last ten years in Germany, for example – while sales of new cars is slumping. It is important to differentiate these two: while new car sales affect the revenues of OEMs, and may indicate changes in consumption patterns, car ownership rates indicate people’s attitude vis-à-vis car ownership better. In that sense, we see a continued attachment to personal car ownership, a cultural phenomenon that is much more difficult to displace or even disrupt than what some may have thought previously. Hence, the dreaded “peak car” that will relegate the iconic 20th century consumer good to museums may not materialize for a while.

The second trend has to do with an observation made time and again: OEMs are not naturally good at running mobility services: their business is making cars. As one bank analyst put it, no one expects Airbus or Boeing to run an airline. Why should it be any different with car OEMs? Thinking about the prospects of automation, it became commonplace for large industrial players to partner with specialized software developers to develop the automated driving system. That may result in a great product, but it does not give create a market and a business plan when it comes to the AVs themselves. As it turned out, the main business plan, which was to use these cars as part of large car-sharing services or sell them to existing mobility operators, ran into a some roadblocks: OEMs found themselves competing with already existing mobility operators in a difficult market; and putting an AV safely on the road is a much more daunting task than once thought. As 2019 comes to a close, we have yet to see an actual commercial “robotaxi” deployment outside of test runs.

This second trend puts a large question mark on the short and medium term financial viability of investments in “robotaxis” and automated mobility operations, generally. OEMs and their partners, looking for ways to put all those vehicle automation efforts to profitable use, look at other markets, such as heavy, non-passenger road and industrial vehicles. Nevertheless, no one seems poised to completely exit the automated passenger mobility market; they all keep a foot in the door, continuing their tests and “gathering more data,” in order to allegedly understand the mobility needs of road users. Beyond these noble intentions, however, there is an exit plan: if all else fails, they can monetize their data sets to data hungry software developers.

In the end, this comes back to a point frequently addressed on this blog, that of safety. Technological advances in automation (broadly speaking) are bringing increased safety to existing cars, and they will continue to do so. We might have become overly fixated by the golden goose of the “Level 5” robotaxi (or even Level 3), which may or may not come in the next ten years, neglecting the low-hanging fruit. While laugh at our ancestors dreaming about flying cars for the year 2000, our future selves scoff at us for chasing robotaxis by 2020.

Cargo Bikes in NYC

These past few weeks millions of people went online, added various items to their cart, and hit “submit order.” From Thanksgiving until the end of December, the volume of packages hitting the road will be substantial. With Black Friday, Cyber Monday, and holiday shopping all taking place in a short time span, the resulting packages will cause delivery trucks in heavily populated cities to disrupt road traffic more than ever.

New York City (NYC) has the highest population density of any city in the United States with over 27,000 people per square mile. Not only is NYC the most populated, it also has more packages delivered than anywhere else in the country. There are nearly 1.5 million packages delivered a day in NYC and during the holiday season that number climbs even higher. When making deliveries, trucks park in bus lanes and bike lanes, double-park, cause a significant number of cyclist accidents, and contribute to congestion. Additionally, delivery trucks pollute the air by sitting in traffic and idling its engines throughout the day.

Delivery companies and the Department of Transportation (DOT) are recognizing the rate people are ordering online and have begun to realize that large trucks may not be the most feasible option to navigate the busy streets. Recently, the city approved a new program in which cargo bikes operated by Amazon, UPS, and DHL will be allowed to make deliveries for the next six months. The Commercial Cargo Bike Program consists of around 100 pedal-assisted, electronic cargo bikes that are ready to replace some of the delivery trucks on the road.

“There’s no doubt the rise in deliveries has caused chaos on our streets–but there are plenty of thoughtful solutions out there to make our streets safer and more sustainable. I’m excited to see DOT exploring this new technology which will help bring NYC’s freight and delivery systems into the 21st Century. I look forward to seeing these cargo bikes on the road and working with DOT in the near future to take a comprehensive look at how we manage these deliveries.”

City Council Speaker Corey Johnson

The goal of the program is to monitor and collect data on how the cargo bikes handle the streets by looking at the cargo bike’s speed, size, parking, use of bike lanes, and effect on overall traffic in Manhattan. The data will be assessed by the DOT to determine whether a more permanent implementation of cargo bikes is appropriate for NYC. In the meantime, cargo bikes are permitted to travel on the street and in bike lanes at a maximum speed of 12mph as well as park in existing commercial loading areas without paying the meters. According to DHL, their cargo bikes can hold 300 pounds, which depending on the size of the packages, could be around 100 to 150 shipments per day. For each cargo bike put on the road, there is meant to be one delivery truck taken off.

Other large cities such as Paris, London, Dublin, and Seattle, have found success in using cargo bikes. UPS has cargo bikes in over 30 cities all over the world. In NYC, however, Amazon is at the forefront of the cargo bike movement. Amazon’s cargo bikes comprise 90 of the initial 100 bikes deployed for the program and they hope to add more soon. Amazon began putting their cargo bikes on the streets before the Commercial Cargo Bike Program was officially approved. Their cargo bikes were first put to use ten months ago for Prime Now grocery deliveries.

The convenience, flexibility, and efficiency of cargo bikes make them just one of many possible solutions for package delivery in densely populated cities. Now that cargo bikes have the support of NYC and the DOT, residents might begin to see some much needed relief to the vehicle congestion caused by too many trucks on the road.

Over the last few years, emerging mobility technologies from CAVs to e-scooters have become the targets of malicious hackers. CAVs, for example, are complicated machines with many different components, which opens up many avenues for attack. Hackers can reprogram key fobs and keyless ignition systems. Fleet management software used worldwide can be used to kill vehicle engines. CAV systems can be confused with things as simple a sticker on a stop sign. Even the diagnostic systems within a vehicle, which are required to be accessible, can be weaponized against a vehicle by way of a $10 piece of tech.

For mobility-as-a-service (“MaaS”) companies, the security of their networks and user accounts is also at threat. In 2015 a number of Uber accounts were found for sale on the “dark web,” and this year a similar market for Lime scooter accounts popped up. Hacking is not even required in some cases. Car2Go paused service in Chicago after 100 vehicles were stolen by people exploiting the company’s app (the company is now ending service in the city, though they say it’s for business reasons).

The wireless systems used for vehicle connectivity are also a target. On faction in the current battle over radio spectrum is pushing cellular technology, especially 5G tech as the future of vehicle-to-vehicle communication. While 5G is more secure than older wireless networks, it is not widespread in the U.S., leaving vulnerabilities. As some companies push for “over-the-air” updates, where vehicle software is wirelessly updated, unsecure wireless networks could lead to serious vehicle safety issues.

So what can be done to deal with these cybersecurity threats? For a start, there are standard-setting discussions underway, and there have been proposals for the government to step up cybersecurity regulation for vehicles. A California bill on the security of the “internet-of-things” could also influence vehicle security. Auto suppliers are putting cybersecurity into their development process. Government researchers, like those Argonne National Labs outside Chicago, are looking for vulnerabilities up and down the supply chain, including threats involving public car chargers. Given the ever-changing nature of cybersecurity threats, the real solution is “all of the above.” Laws and regulations can spark efforts, but they’ll likely never be able to keep up with evolving threats, meaning companies and researchers will always have to be watchful.

P.S. – Here is a good example of how cybersecurity threats are always changing. In 2018, security researchers were able to hack into a smartphone’s microphone and use it to steal user’s passwords, using the acoustic signature of the password. In other words, they could figure out your password by listening to you type it in.

Last month FCC Chairman Ajit Pai announced a plan to allow unlicensed use of a 45-megahertz (MHz) chunk of the mid-band spectrum. How is this even close to related to mobility or transportation? In 1999, the FCC dedicated 75 MHz of the 5.9GHz band to vehicle-related communications and transportation safety, specifically to dedicated short-range communications (DSRC). Guess where that 45MHz portion is right now; you only get one try.

That’s right. Aiming for a 40-60 split in favor of unlicensed use, the FCC is cutting into the dedicated DSRC MHz to make room for what Chairman Pai likened to a “teenage phenom”. This reduction of the so-called “safety band” has garnered a healthy mix of responses, with the two opposing ends of the spectrum being vigorous support and scathing disbelief. For example:

“There’s always going to be something new just around the corner. If we’re going to be afraid to take advantage of the technology that’s available today to save lives, then we’re not doing our jobs.”

Carlos Braceras, Executive Director of Utah Department of Transportation

“The FCC is prepared to trade safer roads for more connectivity by giving away much of the 5.9GHz safety spectrum, and it proposes to make such an inexplicable decision in the absence of data. The Commission is prepared to put not just drivers but pedestrians and other vulnerable users, particularly first responders and those in work zones, at grave risk, and for what?”

Shailen Bhatt, President and CEO of ITS America

Let’s take a quick step back. What is actually is the DSRC spectrum? The DSRC spectrum addresses transportation safety via on-board and roadside wireless safety systems allowing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Essentially, it wants cars to talk to other cars and to traffic lights. However, the FCC has its sights set on a much larger goal: vehicle-to-everything communications (V2X).

Specifically, the plan proposes going beyond the practice of using short-wave technology, such as radios, in favor of prioritizing V2X using cellular technology (C-V2X), which is incompatible with DSRC.

“If it were a medicine, V2X might be considered a miracle drug capable of slowing down a public-health epidemic of U.S. traffic fatalities that last year numbered more than 36,000.”

Jeff Plungis, ConsumerReports.org

So you might assume that C-V2X tech would be getting a shot in the arm in the form of a 45MHz dedication. However, you’d be wrong. Chairman Pai’s remarks in November announced that the lower 45MHz are for unlicensed use. In particular, this would work toward addressing the ever-increasing demand for WiFi bandwidth. It was also proposed that the remaining 30MHz of the spectrum be dedicated to Intelligent Transportation Systems (ITS), with 20MHz to C-V2X and the remaining 10MHz potentially left to DSRC. Faster internet and lower chances of being hit by a car while crossing the road? It seems like finally being able to have our cake and eat it, too.

“So moving forward, let’s resist the notion that we have to choose between automotive safety and Wi-Fi. My proposal would do far more for both automotive safety and Wi-Fi than the status quo.”

Ajit Pai, FCC Chairman

But, of course, there are some drawbacks. Critics have pointed to a number of issues that they claim will come from splitting the safety band. For one, what about DSCR? Cities and municipalities may be sent back to square one in terms of smart transportation infrastructure developments and advancements is they focused their efforts on DSRC systems. Additionally, some auto-manufacturers may prefer C-V2X, but a number have already been installing DSCR systems, a potentially unworkable endeavor should this plan be put into action. The proposed plan doesn’t go as far as to kill DSCR, but some argue that it may as well.

The FCC’s concerns and proposed answers are admirable, but I can’t help but wonder how much of it is simply shiny paint covering tired wallpaper. For one, is the FCC’s true motivation actually addressing the lack of movement within the safety band for V2V, V2I, and V2X? Or, is it convenient? Chairman Pai indicated that this proposal came into being when the FCC was looking for contiguous swathes of the spectrum that it could open up for different types of unlicensed operations. While there is no doubt that jump starting transportation-related communications is important, the FCC’s dedication to transportation safety comes across as secondary.

I clearly don’t have answers, but these questions and others will hopefully be addressed as the FCC concludes the notice and comment period for the proposal and the next steps are taken.

As audiences worldwide await the release of Star Wars: The Rise of Skywalker, a few recent developments in transportation technology are taking cues (directly or indirectly) from the technology of a galaxy far, far away.

Last week, the opening ceremony of a new ride at Star Wars: Galaxy’s Edge, the Star Wars themed land at Walt Disney World, included actual flying X-Wing starfighters, built from Boeing-made drones. There are two important things to take from this development: (1) Boeing is apparently now a supplier for General Leia Organa’s Resistance, and; (2) Boeing is confident enough in their “Cargo Air Vehicle” drone to allow a highly-publicized public display. The all-electric Cargo Air Vehicle flew for the first time earlier this year, and is designed to carry up to 500 lbs. of cargo at a time. I’ve written about aerial delivery drones before, in October and September, but this new Boeing vehicle has a much higher carrying capacity than the smaller drones those articles focused on. Of course, a highly controlled environment like a major theme park is perhaps not as challenging an environment as the vehicles would face elsewhere, the visibility of this deployment raises interesting questions about Boeing’s future plans for the testing and deployment of the vehicles.

Another emerging technology that is attempting to recreate the Star Wars universe here on Earth is flying taxis. A number of prototype flying taxis have been revealed over the past few years, though none have the smooth lines of those seen in Star Wars, or the retro-styling of another sci-fi mainstay, the Jetson’s car. In June, Uber showed off the design of their proposed air taxi, an electric vehicle they will be testing in LA and Dallas in 2020. Industry boosters see a future with many such vehicles crisscrossing major metro areas (hmmm…where have I seen that before…). However, there are a number of challenges:

  • How do you make them cost-effective? Aircraft are expensive, and the proposed air taxis are no different. So how do you make them efficient enough to justify their cost? Will making them electric do the trick, or will the cost of batteries and other equipment sink the concept?
  • What is the economy of scale for this type of transportation? Right now, Uber offers helicopter flights from Manhattan to JFK Airport for $200-225 a person. If an air taxi ride has similar costs, how many people will really take advantage of them?
  • What infrastructure will they need? Where are they going to land? Uber has mocked-up glossy “skyport” designs, which they say will combine street-level mobility with their aerial offerings, but how many of these will be necessary if more than one company operates in a given metro area? Will skyports proliferate? In some cities, like London, there is already a scramble for roof space to transform into landing pads for air taxis and drones.
  • How do we regulate these vehicles? Between the aerial taxis and delivery drones, the skies would seem to be primed for traffic jams. Does the FAA retain full control over everything flying, or will states and even municipalities have to step in to help regulate a proliferation of flying vehicles?

Just like connected and automate vehicles, air taxes mix promising new technology with a sci-fi edge. It remains to be seen if air taxis will actually prove cost-effective enough to function for anyone other than the wealthy, but if Disney World’s use of drone X-Wings is any indication, a new hope for aerial vehicles may be just around the corner.

P.S. – Those who are skeptical of self-driving vehicles may have found a new patron saint in The Mandalorian, who turns down a droid-piloted speeder in favor of one driven by a person (also, apparently Uber service in the Outer Rim involves flutes?). To be fair, Mando later has some issues with his adorable companion playing with the controls of his ship, proving that humanoid controlled vehicles are still prone to problems (Han could have told him that).

When Elon Musk unveiled the Cybertruck late last month, it sent shockwaves throughout the electric vehicle world, the stock market, and the internet. The sleek bodied, sharp-edged vehicle is reminiscent of the classic Back to the Future DeLorean. It has already been pre-ordered by over 200K customers, according to a tweet by Elon Musk. (It is important to note that a pre-order involves only a $100 deposit, which is refundable). Despite the large volume of pre-orders, Tesla’s stock price dropped by 5% in the days following the announcement — decreasing Musk’s net worth by over $750 million due to his significant holdings in Tesla. Notwithstanding the market reaction to the unveiling, the Cybertruck will likely be a success in the pick-up truck consumer market.

One of the entertainment factors of the reveal was the on-stage demonstration that the vehicle is built for abuse. Unlike other Tesla vehicles that are made of stamped alumni or steel, the Cybertruck is built using 30X cold-rolled steel. The body of the vehicle took a blow from a sledgehammer without leaving a scratch. However, one window did unexpectedly shatter when a steel ball was thrown into it. The truck is meant to withstand anything a user can throw at it, which will likely appeal to current pick-up truck owners who use their trucks for towing, camping, off-roading, or any other number of activities.

The Cybertruck appears to be slightly larger than the Ford F150 (the best-selling vehicle for over three decades), and was shown capable of beating the Ford F150 in a Tug of War. Tesla’s press release indicated that there are three versions of the truck that will ultimately be available.

Cybertruck is designed to have the utility of a truck and the performance of a sports car. The vehicle is built to be durable, versatile and capable, with exceptional performance both on-road and off-road. Cybertruck will come in three variants: Single Motor Rear-Wheel Drive, Dual Motor All-Wheel Drive, and Tri Motor All-Wheel Drive.

Base Model

  • Price:               $39,000
  • Range:             250 miles
  • Tow Rating:    7,500 lbs
  • 0-60 mph:        6.5 seconds

Dual Motor

  • Price:               $49,000
  • Range:             300 miles
  • Tow Rating:    10,000 lbs
  • 0-60 mph:        4.5 seconds

Tri-Motor*

  • Price:               $69,900
  • Range:             500 miles
  • Tow Rating:    14,000 lbs
  • 0-60 mph:        <3 seconds
    * Tri-Motor Production won’t begin until 2022

The Truck Market

It makes perfect sense that Tesla has finally entered the pick-up truck arena. Trucks account for roughly 15 percent of U.S. vehicle sales each year, a slice of the pie that has been growing since 2009. Americans buy nearly a million Ford F150’s every year. Not only is there market demand, but pick-up trucks are the perfect build for an electric vehicle; they are large and typically more expensive than sedans, and can better carry the large and (currently) costly batteries. 

Towing will also be easier with an electric truck, given the toque an electric vehicle can exert. Torque generally describes how quickly a vehicle will accelerate and its ability to pull a load. In an electric vehicle, high torque is available at low speeds and is relatively constant over a wide range of speeds. High torque enables an EV to move faster from a dead stop. This phenomenon can be described as “instant torque.”

However, perhaps consistent with the incredible increase in truck ownership over the past decade, truck owners frequently use their trucks much like other car owners: for commuting to work. So perhaps increased towing ability is not quite the selling point for Tesla.

A 500-mile range is incredibly impressive, considering many EVs have a range right at or below 300 miles per charge, with many below 200 miles. However, it is not likely to be seen as an improvement for truck drivers, who pleasure drive more than twice as often as other vehicle owners. Even at the top of the line, a 500-mile range is lower than an F150, which can get nearly 700 miles per tank (assuming 19 mpg and a 36-gallon tank).

If the Cybertruck can take control of a sizable segment of the truck market and begin chipping away at the market share of their low-fuel economy competitors, Tesla may begin making tangible progress towards decreasing domestic oil consumption and quicken the transition to an electrified transportation sector.

Ultimately, the sleek new design and popular appeal of the Tesla brand will likely make the Cybertruck a successful product. But it is doubtful that many purchasers will utilize the benefits an electric truck has over a traditional pick-up. They will instead likely use the vehicle as they would any other car, or as a status symbol. There are plenty of SUV and light-duty truck owners who will be glad to switch to an environmentally friendly alternative that still allows them to ride high above traffic. Others will be more than happy to end their reliance on highly-fluctuating fuel prices.

Earlier this month, Connecticut’s Governor Ned Lamont announced and released the details of his plan to upgrade and “transform” the state’s transportation system. The plan, Connecticut 2030 (CT2030), allocates $21 billion primarily to improving Connecticut’s highways, airports, mass transit, and ports and is pitched as “what Connecticut families and employers deserve.” While that is a wonderful goal, as usual, I have questions. However, I want to go over the basics of CT2030 before getting into those questions.

“CT2030 will result in nothing short of a transformation of the economy and quality of life in Connecticut. When residents are able to travel to and from at drastically quicker rates, families can thrive, employees are more productive, and businesses are able to grow and provide more opportunities.”

Impact of CT2030

Overall, the main point of CT2030 seems to be enabling people and business to move more quickly and more efficiently. Gov. Lamont aims to achieve CT2030’s goals by addressing four main focus areas mentioned above: highways, airports, mass transit, and ports.

Highways. The main thrust of CT2030’s highway plans appear to center significantly on I-84, I-91, and I-95. This makes sense, seeing as to it that multiple spots along each of these highways rank within the top 100 worst traffic bottlenecks in the United States. These three highways will be the focus of projects such as lane additions, exit enhancements, bridge improvements, and “user fee” installations (i.e. tolls).

Mass Transit. This portion of CT2030 focuses on public transportation in the forms of railways and buses. Again, the plans here are “all about less time commuting and more time with your family.” Railways would look forward to projects for straightening and upgrading tracks, replacing aging bridges, installing new signaling systems, and adding new cars and locomotives. Buses, in a much smaller endeavor, would receive upgrades providing consistency for users across the state’s bus system. These upgrades include fitting all bus stops with shelters for protection against bad weather and signs with information on operating routes, as well as providing real-time information updates via text message or phone app.

Airports. This seems to be one of the most underdeveloped aspects of CT2030. The two enhancements to Connecticut’s aviation sector are (1) connecting the Bradley International Airport to surrounding areas via direct railway lines, and (2) the development of a “fully functioning regional airport in South-Central CT.”

Ports. Connecticut’s four major ports and the associated maritime industry annually generate an estimated $11.2 billion. The projects for these ports are unique to each location. They include dredging to allow for larger ships and freighters to pass through more frequently and the implementation of a high-speed ferry system to provide services for commuters as well as tourists.

Now for some questions:

What about induced demand? Congestion can’t always be solved by simply adding more lanes, no matter how logical that solution would seem. And it does make sense: remove the congestion by removing the bottleneck. However, this reasonable answer runs full speed into the issue of induced demand. The phenomenon of induced demand can be stated simply: “When you provide more of something, or provide it for a cheaper price, people are more likely to use it.” This means that increasing capacity does little to relieve busy roadways when traffic acts as a “gas” and the “volume expands to fill the capacity.”

“Widening a highway is no more a solution to traffic than buying bigger pants is a solution to overeating.”

David Andrew, Hartford Courant

While some experts argue that induced capacity doesn’t cause as much strife as people claim, the potential is still something that should be taken into account. If CT2030 centers on reducing highway commute time through widening projects, there needs to be at least some discussion addressing the possible negative impacts, such as an increase in urban sprawl, carbon emissions, and more.

What about pedestrian infrastructure? While CT2030 allocates approximately $21 billion to its various projects, only an estimated $52 million would be dedicated to the Community Connectivity Program (CCP), a “grant program for municipalities to make improvements to sidewalks” that “helps local communities make necessary improvements for pedestrians.” If my math is even close to correct – honestly, no promises – this amounts to less than half of a percent.

Admittedly, I’m using the term “pedestrian infrastructure” broadly to include traffic calming and bicycle infrastructure in addition to traditional pedestrian infrastructure while CT2030 narrows the scope of CCP down to sidewalk projects. However, this doesn’t defeat the question of why so little focus is dedicated to pedestrian infrastructure.

There are plenty of unanswered questions and unaddressed concerns still surrounding CT2030. One major question mark is whether it will actually be implemented. This is thanks to Gov. Lamont and state legislators starring in leading roles opposite one another in a multi-season drama. With this in mind, it will be interesting to see how and if Connecticut moves forward with CT2030 or any rival transportation plans.

Regardless of the mixed reactions to Tesla’s new Cybertruck, the electric vehicle revolution is here. Some analysts have predicted that within twenty years, half of new vehicles sold will be electric. For the future of the planet, we may need them to be. One core tenet of climate change mitigation is fairly simple in concept, even if difficult in practice: electrify everything. Quickly phasing out polluting technologies—such as the internal combustion engine—and replacing them with electric batteries that are charged by renewable energy sources is our best shot to reduce emissions fast enough to limit some of the worst effects of climate change.

One thing standing in the way of our electrified future is—or as will be discussed below, may be—the lack of charging infrastructure. Electric vehicles today travel about 200 miles per charge. This is a shorter distance than most gasoline-fueled cars. And gasoline-powered cars need a five minute fill-up after traveling a few hundred miles, which is much less onerous than the hour or two that it would take to restore the 200 mile range on your electric vehicle even with the best available chargers.

But how much of a problem is the lack of infrastructure, really? The average driver only rarely takes road trips of several hundred miles. Indeed, the average car only drives forty miles per day. Level 2 EVSE charging infrastructure is relatively inexpensive to install in most homes, and powerful enough to charge a vehicle overnight. Given how cheap it already is to charge a vehicle at home, it’s no surprise that most existing public charging stations are rarely used.

This ease of charging at home is likely to be a key long-term difference in infrastructure needs between the incoming era of electric vehicles and the past era of gas-powered vehicles. It would be implausible to install a gas pump in your home garage, making publicly available filling stations placed throughout cities and towns a necessity. When it comes to electric vehicles however, far fewer stations should be needed on the surface streets because the vast majority of people driving on them will be able to get more than enough charge by simply plugging into a wall outlet each day.

Of course, EV charging infrastructure will still need to be built out in order to maximize the uptake and utility of the next generation of cars. While the vast majority of people drive no more than a few dozen miles on a daily basis, most will also expect to take the occasional long road trip during the useful life of their car. Even as modern EVs push towards a 300 mile battery range, having to stop for an hour or more to recharge every few hours will continue to be seen as impractical.

This means there will continue to be a need for superfast chargers. The good news is, speedy chargers are already on the horizon. Late last year, Porsche and BMW unveiled a prototype charging station that will supply roughly sixty miles of battery life in just three minutes, about the length of time it takes to fill up a gas tank today. Venture capital investments in EV charging infrastructure totaled $1.7 billion from 2010 through the first quarter of 2019, and the total amount rose every year from 2015 through 2018.

Such investment, and the continued technological improvement it brings, will be necessary for the EV takeover of the vehicle market to reach its full potential. But thanks to increasing battery ranges and the ease of charging at home, the need for buildout with day-to-day use in mind may not be so great as previously thought.

On November 19, the NTSB held a public board meeting on the 2018 Uber accident in Tempe, Arizona, involving an “automated” (actually level 3) Uber-operated Volvo SUV. One woman, Elaine Herzberg, a pedestrian, died in the accident. In the wake of the report, it is now a good time to come back to level 3 cars and the question of “safety drivers.”

Given that the purpose of the meeting was to put the blame on someone, media outlets were quick to pick up a culprit for their headlines: the “safety driver” who kept looking at her phone? The sensors who detected all kinds of stuff but never a person? Uber, who deactivated the OEM’s emergency braking? Or maybe, Uber’s “safety culture”? A whole industry’s?

The Board actually blames all of them, steering clear of singling out one event or actor. It is probably the safest and most reasonable course of action for a regulator, and it has relevant implications for how law enforcement will handle accidents involving AVs in the future. But because we are humans, we may stick more strongly with the human part of the story, that of the safety driver.

She was allegedly looking at her phone, “watching TV” as one article put it; following the latest episode of The Voice. The Board determined that she looked at the road one second before the impact. That is short, but under more normal circumstances, enough to smash the brakes. Maybe her foot was far from the pedal; maybe she just did not react because she was not in an “aware” state of mind (“automation complacency,” the report calls it). In any case, it was her job to look on the road, and she was violating Uber’s policy by using her phone while working as a safety driver.

At the time of the accident, the Tempe police released footage from the dash cam, a few seconds up to the impact, showing a poorly-lit street. The relevance of this footage was then disputed in an Ars Technica article which aims to demonstrate how actually well lit the street is, and how just the front lights of the car should have made the victim visible on time. Yet, I think it is too easy to put the blame on the safety driver. She was not doing her job, but what kind of job was it? Humans drive reasonably well, but that’s when we’re actually driving, not sitting in the driver seat with nothing else to do but to wait for something to jump out of the roadside. Even if she had been paying attention, injury was reasonably foreseeable. And even if she would have been driving in broad daylight, there remains a more fundamental problem besides safety driver distraction.

The [NTSB] also found that Uber’s autonomous vehicles were not properly programmed to react to pedestrians crossing the street outside of designated crosswalksone article writes. I find that finding somewhat more appalling than that of a safety driver being distracted. Call that human bias; still I do not expect machines to be perfect. But what this tells us is that stricter monitoring of cellphone usage of safety drivers will not cut it either, if the sensors keep failing. The sensors need to be able to handle this kind of situation. A car whose sensors cannot recognize a slowly crossing pedestrian (anywhere, even in the middle of the highway) does not have its place on a 45-mph road, period.

If there is one thing this accident has shown, it is that “safety drivers” add little to the safety of AVs. It’s a coin flip: the reactivity and skill of the driver makes up for the sensor failure; in other cases, a distracted, “complacent” driver (for any reason, phone or other) does not make up for the sensor failure. It is safe to say that the overall effect on safety is at best neutral. And even worse: it may provide a false sense of safety to the operator, as it apparently did here. This, in turn, prompts us to think about level 3 altogether.

While Uber has stated that it has “significantly improved its safety culture” since the accident, the question of the overall safety of these level 3 cars remains. And beyond everything Uber can do, one may wonder if such accidents are not bound to repeat themselves should level 3 cars see mass commercial deployments. Humans are not reliable “safety drivers.” And in a scenario that involves such drivers, it takes much less than the deadly laundry list of failures we had here to have such an accident happen. Being complacent may also mean that your foot is not close to the pedals, or that your hands are not “hovering above the steering wheel” as they should (apparently) be. That half second extra it takes to smash the brakes or grip the wheel is time enough to transform serious injury into death.

The paramount error here was to integrate a human, a person Uber should have known would be distracted or less responsive than an average driver, as a final safety for sensor failure. Not a long time ago, many industry players were concerned about early standardization. Now that some companies are out there, going fast and literally breaking people (not even things, mind you!), time has come to seriously discuss safety and testing standards, at the US federal and, why not, international level.

A University of Michigan Law School Problem Solving Initiative class on AV standardization will take place during the Winter semester of 2020, with deliverables in April. Stay tuned!

An important development in artificial intelligence space occurred last month with the Pentagon’s Defense Innovation Board releasing draft recommendations [PDF] on the ethical use of AI by the Department of Defense. The recommendations if adopted are expected to “help guide, inform, and inculcate the ethical and responsible use of AI – in both combat and non-combat environments.”

For better or for worse, a predominant debate around the development of autonomous systems today revolves around ethics. By definition, autonomous systems are predicated on self-learning and reduced human involvement. As Andrew Moore, head of Google Cloud AI and former dean of computer science at Carnegie Mellon University defines it, artificial intelligence is just “the science and engineering of making computers behave in ways that, until recently, we thought required human intelligence.”

How then do makers of these systems ensure that the human values that guide everyday interactions are replicated in decisions that machines make? The answer, the argument goes, lies in coding ethical principles that have been tested for centuries into otherwise “ethically blind” machines.

Critics of this argument posit that this recent trend of researching and codifying ethical guidelines is just one way for tech companies to avoid government regulation. Major companies like Google, Facebook and Amazon have all either adopted AI charters or established committees to define ethical principles. Whether these approaches are useful is still open to debate. One research for example found that priming software developers with ethical codes of conduct had “no observed effect” [PDF] on their decision making. Does this then mean that the whole conversation around AI and ethics is moot? Perhaps not.

In the study and development of autonomous systems, the content of ethical guidelines is only as important as the institution adopting them. The primary reason ethical principles adopted by tech companies are met with cynicism is that they are voluntary and do not in and of themselves ensure implementation in practice. On the other hand, when similar principles are adopted by institutions that consider the prescribed codes as a red lines and have the legal authority to implement them, these ethical guidelines become massively important documents.

The Pentagon’s recommendations – essentially five high level principles – must be lauded for moving the conversation in the right direction. The draft document establishes that AI systems developed and deployed by the DoD must be responsible, equitable, traceable, reliable, and governable. Of special note among these are the calls to make AI traceable and governable. Traceability in this context refers to the ability of a technician to reverse engineer the decision making process of an autonomous system and glean how it arrived at the conclusion that it did. The report calls this “auditable methodologies, data sources, and design procedure and documentation.” Governable AI similarly requires systems to be developed with the ability to “disengage or deactivate deployed systems that demonstrate escalatory or other behavior.”

Both of these aspects are frequently the most overlooked in conversations around autonomous systems and yet are critical for ensuring reliability. They are also likely to be the most contested as questions of accountability arise when machines malfunction as they are bound to. They are also likely to make ‘decision made by algorithm’ a less viable defense when creators of AI are confronted with questions of bias and discrimination – as Apple and Goldman Sachs’ credit limit-assigning algorithm recently was.

While the most direct applications of the DoD’s principles is in the context of lethal autonomous weapon systems, their relevance will likely be felt far and wide. The various private technology companies that are currently soliciting and building various autonomous systems for military use – such as Microsoft’s $10 billion JEDI contract to overhaul the military’s cloud computing infrastructure and Amazon’s facial recognition system used by law enforcement – will likely have to invest in building new fail safes into their systems to comply with the DoD’s recommendations. It is likely that these efforts will have a bleed through effect into systems being developed for civilian use as well. The DoD is certainly not the first institution to adopt these principles. Non-governmental agencies such as the Institute of Electricals and Electronic Engineers (IEEE) – the largest technical professional organization in the world – have also called [PDF] for adoption of standards around transparency and accountability in AI to provide “an unambiguous rationale” for all decisions taken. While the specific questions around which ethical principles can be applied to machine learning continue for the foreseeable future, the Pentagon’s draft could play a key role in moving the needle forward.

Developments in technology have led to an increased reliance on artificial intelligence and autonomy in various vehicles such as cars, planes, helicopters and trains. The latest vehicles to implement autonomous technology into their operations are shipping vessels. Autonomous ships will transform the industry and current regulations are being reassessed to determine the best way to include this futuristic way of shipping.

he shipping industry is regulated on a global level and it remains one of the most heavily regulated industries today. International shipping is principally regulated by the International Maritime Organization, a United Nations agency responsible for the safety of life at sea and the protection of the marine environment. The International Maritime Organization (IMO) developed a comprehensive framework of global maritime safety regulations that was adopted from international conventions. In order to be proactive, IMO initiated a regulatory scoping exercise on Maritime Autonomous Surface Ships (MASS). The scoping exercise is led by IMO’s Maritime Safety Committee and is expected to be completed by 2020. The goal of the exercise is to determine how autonomous ships may be implemented into regulations and will touch on issues such as safety, security, liability, the marine environment and the human element.

In order to assess the scope of differing levels of autonomous ships, IMO defined four degrees of autonomy. The lowest degree of autonomy involves automated processes that can control the ship at times. Seafarers will remain in charge of operating and controlling the ship when the automated system is not activated. The second degree is a remotely controlled ship with seafarers still on board. The ship will be controlled from another location but the seafarers on board will be able to take control if necessary. The next degree is a remotely controlled ship without any seafarers on board. Lastly, the highest degree of autonomy is a fully autonomous, unmanned ship that is equipped with the ability to make decisions and take action by itself.

Several companies have already begun implementing autonomous capabilities into their ships and the technology is rapidly developing. While the scoping exercise is underway, the Maritime Safety Committee approved interim guidelines for trials to be completed on existing and emerging autonomous ships. The trials should be generic and goal-based and take a precautionary approach to ensure the operations are safe, secure, and environmentally sound. In 2018, Rolls-Royce conducted its first test of an autonomous ferry named Falco. To demonstrate two degrees of autonomy, the ferry was fully autonomous on its outward voyage and then switched to a remotely controlled operation on its return to port. The controller was in a command center 30 miles away and he successfully took over operations of the ship and guided it to the dock.

Autonomous ships are expected to improve safety, reduce operating costs, increase efficiency and minimize the effects of shipping on the environment. An increased reliance on autonomy will reduce the chance for human error thereby improving safety. Human error accounts for 75-96% of marine accidents and accounted for $1.6 billion in losses between 2011 and 2016. Operational costs are also expected to decrease as there will be little to no crew on board. Crew costs can constitute up to 42% of a ship’s operating costs. If there is no crew then accommodations such as living quarters, air conditioning and cooking facilities can be eliminated. Further, a ship free from crew accommodations and seafarers will make voyages more efficient because the ship will have an alternate design and an increased carrying capacity. Lastly, autonomous ships may prove to be better for the environment than current vessels. The ships are expected to operate with alternative fuel sources, zero-emissions technologies and no ballast. 

As we have seen in other transportation industries, regulation for autonomous vehicles falls far behind the technological innovation. By taking a proactive approach in the case of autonomous shipping, IMO may be ready to create regulations that better reflect the future of shipping within the next decade. 

Last time I wrote about platooning, and the potential economic savings that could benefit the commercial trucking sector if heavy duty trucks were to implement the technology. This week, I’m writing about one of the current barriers to implementing platooning both as a commercial method, and in the larger scheme of highway driving.

One of the most readily identifiable barriers to the widespread implementation of truck platooning is the ‘Following Too Close’ (“FTC”) laws enforced by almost every state. There is currently a patchwork of state legislation which prevents vehicles from following too closely behind another vehicle. Violating these laws is negligence per se.

For those who don’t quite remember 1L torts, negligence per se essentially means “if you violate this statute, that proves an element of negligence.” Therefore, if one vehicle is following too closely behind another vehicle in violation of an FTC statute, that satisfies the breach element of negligence and is likely enough to be fined for negligent driving.

These laws are typically meant to prevent vehicles from following dangerously close or tailgating other vehicles. The state laws that regulate this conduct can be divided into roughly four categories. Some states prescribe the distance or time a driver must remain behind the vehicle in front of them; others impose a more subjective standard. The subjective standards are far more common than the objective standards.

Subjective Categories

  • Reasonable and Prudent” requires enough space between vehicles for a safe stop in case of an emergency. This FTC rule is the most common for cars and seems to be a mere codification of common-law rules of ordinary care.
  • “Sufficient space to enter and occupy without danger” requires trucks and vehicles with trailers to leave enough space that another vehicle may “enter and occupy such space without danger.” This is the most common rule for trucks.

Objective Categories

  • Distance-Based: Some states prescribe the distance at which a vehicle may follow another vehicle; others identify a proportionate interval based on distance and speed. These are the most common rules for heavy trucks and frequently set the minimum distance between 300 and 500 feet.
  • Time: Timing is the least common FTC, but the two jurisdictions that impose this rule require drivers to travel “at least two seconds behind the vehicle being followed.”

It is easy to see how, given the close distance at which vehicles need to follow to benefit from platooning, any of these laws would on their face prohibit platooning within their borders. However, several states have already enacted legislation which exempts the trailing truck in a platoon from their “Following Too Close” laws. As of April 2019, 15 states had enacted legislation to that effect. Additional states have passed legislation to allow platoon testing or pilot programs within their states.

However, despite some states enacting this legislation, a non-uniform regulatory scheme does not provide  the level of certainty that will incentivize investment in platooning technology. Uncertain state regulation can disincentivize interstate carriers from investing in platooning, and could lead to a system where platooning trucks only operate within single state boundaries.

Although the exemptions are a step in the right direction, non-uniformity will likely result in an overall lower platooning usage rate, limiting the wide-spread fuel efficiency and safety benefits that are derived when platooning is implemented on a large, interstate scale. Without uniform legislation that allows platooning to be operated consistently across all the states, the need for different systems will hinder the technology’s development, and the rate at which trucking companies begin to adopt it.

However, even if not all states pass legislation exempting platooning vehicles from their FTC laws, there could be a way around the subjective elements. The most common subjective law, “Reasonable and Prudent” requires only enough space that the vehicles can safely stop in case of an emergency. When considering a human driver this distance is likely dozens of feet, given the speed at which cars travel on the interstate. However, recall from last week that platooning vehicles are synchronized in their acceleration, deceleration, and braking.

If the vehicles travel in tandem, and brake at the same time and speed, any distance of greater than several feet would be considered “reasonable and prudent.” Perhaps what needs to be developed is a “reasonable platooning vehicle” standard, rather than a “reasonable driver” standard, when it comes to autonomous vehicle technology. Then again, considering the ever-looming potential for technological failure, it could be argued that following that close behind another heavy vehicle is never reasonable and prudent, once again requiring an exemption rather than an interpretive legal argument for a new “reasonableness” standard.

Either way, to ensure certainty for businesses, more states should exempt platooning vehicles from their “Following Too Close” laws. Otherwise, the technology may never achieve a scale that makes it worth the early investment.

On April 8, 2019, it was announced at the 35th Space Symposium in Colorado Springs, Colorado that the space industry was getting an Information Sharing and Analysis Center (ISAC). Kratos Defense & Security Solutions, “as a service to the industry and with the support of the U.S. Government,” was the first founding member of the Space-ISAC (S-ISAC).

“[ISACs] helps critical infrastructure owners and operators protect their facilities, personnel and customers from cyber and physical security threats and other hazards. ISACs collect, analyze and disseminate actionable threat information to their members and provide members with tools to mitigate risks and enhance resiliency.”

National Council of ISACs

ISACs, first introduced in Presidential Decision Directive-63 (PDD-63) in 1998, were intended to be the one aspect of the United States’ development of “measures to swiftly eliminate any significant vulnerability to both physical and cyber attacks on our critical infrastructures, including especially our cyber systems.” PDD-63 requested “each critical infrastructure sector to establish sector-specific organizations to share information about threats and vulnerabilities.” In 2003, Homeland Security Presidential Directive 7 (HSPD-7) reaffirmed the relationship between the public and private sectors of critical infrastructure in the development of ISACs.

Today, there are ISACs in place for a number of subsectors within the sixteen critical infrastructure sectors, for specific geographic regions, and for different levels of government.

However, the S-ISAC, while undoubtedly a good call, has left me with a few questions.

Why so much government involvement?

From what I’ve read, the Federal government’s role is to “collaborate with appropriate private sector entities and continue to encourage the development of information sharing and analysis mechanisms.” For example, the Aviation-ISAC (A-ISAC) was formed when “[t]here was consensus that the community needed an Aviation ISAC”; the Automotive-ISAC (Auto-ISAC) came into being when “[fourteen] light-duty vehicle [Original Equipment Manufacturers] decided to come together to charter the formation of Auto-ISAC”; and the Information Technology-ISAC (IT-ISAC) “was established by leading Information Technology Companies in 2000.”

Reportedly, it was not the private actors within the space industry that recognized or felt the need for the S-ISAC, but an interagency body designed to keep an eye on and occasionally guide or direct efforts across space agencies. The Science and Technology Partnership Forum has three principle partner agencies: U.S. Air Force (USAF) Space Command, the National Aeronautics and Space Administration (NASA), and the National Reconnaissance Office (NRO).

Additionally, it appears as though Kratos, a contractor for the Department of Defense and other agencies, was the only private actor involved in the development and formation of the S-ISAC.

These are just something to keep in mind. The S-ISAC’s perhaps unique characteristics must be considered in light of the clear national security and defense interests that these agencies and others have in the information sharing mechanism. Also, since the announcement of the S-ISAC, Kratos has been joined by Booz Allen Hamilton, Mitre Corporation, Lockheed Martin, and SES as founding members.

Why an ISAC?

Again, ISACs are typically the domain of the private owners, operators, and actors within an industry or sector. As new vulnerabilities and threats related to the United States’ space activities have rapidly manifested in recent years and are quickly emerging today, it would seem to make sense for the Federal government to push for the development of an Information Sharing and Analysis Organization (ISAO). ISAOs, formed in response to Executive Order 13691 (EO 13691) in 2015, are designed to enable private companies and federal agencies “to share information related to cybersecurity risks and incidents and collaborate to respond in as close to real time as possible.”

While ISAOs and ISACs share the same goals, there appear to be a number of differences between the two information-sharing mechanisms. ISACs can have high membership fees that individual members are responsible for, potentially blocking smaller organizations or new actors from joining, and that often work to fund the sector’s ISAC; however, grants from the Department of Homeland Security (DHS) are available to provide additional funding for the establishment and continued operation of ISAOs.  ISACs – for example, the A-ISAC – seem to monitor and control the flow of member-provided information available to the Federal government more closely than ISAOs.

Also, ISACs – such as those recognized by the National Council of ISACs (NCI) – are typically limited to sectors that have been designated as Critical Infrastructure and the associated sub-sectors. Despite obvious reasons why it should, space has not been recognized as a critical infrastructure sector.

For now, this seems like a good place to end. This introductory look into ISACs generally and the S-ISAC has left me with many questions about the organization itself and its developing relationship with the private space industry as a whole. Hopefully, these questions and more will be answered in the coming days as the S-ISAC and the private space industry continue to develop and grow. 

Here are some of my unaddressed questions to consider while exploring and considering the new S-ISAC: Why develop the S-ISAC now? What types of companies are welcome to become members, only defense contractors or, for example, commercial satellite constellation companies and small rocket launchers? As the commercial space industry continues to grow in areas such as space tourism, will the S-ISAC welcome these actors as well or will we see the establishment of a nearly-identical organization with a different name?

Nowadays it seems like everyone wants to get in on the rapidly-growing commercial space industry, reportedly worth approximately $340 billion per year. From Stratolaunch Systems’ “world’s largest plane, which acts as a launch pad in the sky,” to NASA’s Space Act Agreements (SAA) with Boeing and SpaceX for taxi services to and from the International Space Station (ISS), this is certainly not your parents’ space race.

While the private space industry of today may not have bloomed until after we entered the 21st century, the United States’ love affair with space activities in the private sector can be traced back to the 1960’s, although it was the passage of the Commercial Space Launch Act in 1984 that really lit a fire under private industry. It goes without saying that a lot has changed in the years between then and now.

As a matter of fact, the private space sector as we know it today has a term all its own: NewSpace.

“Alt.space, NewSpace, entrepreneurial space, and other labels have been used to describe approaches to space development that different significantly from that taken by NASA and the mainstream aerospace industry.”

HobbySpace.com

NewSpace is a move away from the traditional understanding of space being the domain of government agencies alone and a step toward more affordable access to space. This transition has allowed for the incredible growth and expansion of the economic endeavors within the private space sector, and it’s only expected to get bigger and more profitable as time and developments continue to advance.

However, beyond the incredible news stories about “the world’s first commercial Spaceline” and Elon Musk sending his car into space – which you can track here, by the way – there is an entire universe of issues and concerns that do and/or will cause hiccups and delays to entering the first space tourists into orbit.

One of the first concerns that comes to mind is often that of safety. Saying that there are a few safety concerns relating to commercial space transportation would be putting it very, very lightly. Risks and dangers plague every step of the process, from launchpad to landing. I am all for scientific inquiry and experimentation, but unfortunately this is one area where trial and error has a good chance of ending in both the loss of equipment and the loss of life.

Commercial space transportation is still a fairly high-risk industry in terms of safety, and the responsibility to develop safety regulations for the U.S. commercial space transportation industry rests with the Federal Aviation Administration (FAA) Office of Commercial Space Transportation (AST). The AST issues licenses and experimental permits for launch or reentry vehicles and spaceports after the issuance of a safety approval.

According to the AST website, the FAA “has the authority to issue a safety approval for one or more of the following safety elements: a launch vehicle, a reentry vehicle, a safety system, process, service, or any identified component thereof, and qualified and trained personnel performing a process or function related to licensed launch activities.”

I will stop myself here (for now), but this is just a drop in the bucket. There are plenty of topics surrounding commercial space flight that this post didn’t discuss, such as issues with funding, the minefield that is space debris, and the question of whose law governs in space. While this may seem like a lot, be reassured by the fact that this means we all may have the chance to live out that childhood (adulthood) dream of being an astronaut.

One of the most exciting and economically advantageous aspects of autonomous vehicle technology is the ability for cars and heavy trucks to “platoon.” Platooning is a driver-assist technology that allows vehicles to travel in tandem, maintaining a close, constant distance. Imagine trucks are racers in a bicycle or foot race. By drafting closely behind one another, the vehicles reduce their energy (fuel) consumption.

I personally find that large-scale platooning should be the ultimate goal of autonomous vehicle technology; the potential time and fuel savings would be enormous if the highways were filled with vehicles drafting behind one another. Imagine a highway system without rubberneckers, the guy on the highway that floors it, and then slams on the breaks during rush hour, or the “Phantom Traffic Jam.” Imagine an organized “train” of cars and trucks instead, following at a close, but technologically safe distance (between 25 and 75-feet) and at a uniform speed.

This future is more likely to begin on a smaller scale, and in the commercial shipping sector, rather than in the consumer vehicle market. The work has already started with some platooning pilot programs involving heavy trucks.

These programs employ short-range communications technology and advanced driver assistance systems in their testing. The technology creates a seamless interface supporting synchronized actions; however, drivers are still needed to steer and monitor the system. When done with heavy commercial trucks — tractor-trailers, 18-wheelers, or semi-trucks (depending on what area of the country you live in) — the trucks are “coupled” through vehicle-to-vehicle (V2V) communication. The V2V technology allows the vehicles to synchronize acceleration, deceleration, and braking to increase efficiency and safety.

The economic incentives for platooning in the freight industry derive from the potential fuel savings, which come from reductions to aerodynamic drag. While both vehicles in a pair of platooning trucks save fuel, the rear vehicle typically saves significantly more. Tests conducted by the National Renewable Energy Laboratory demonstrated average fuel savings up to 6.4 percent for a pair of platooning trucks: a lower amount (up to 5.3 percent) for the lead truck and a higher amount (up to 9.7 percent) for the trailing truck. These numbers varied based on the size of the gap between the two trucks, and the driving speed. The ability to decrease fuel consumption in heavy freight vehicles represents an enormous area to reduce the cost of shipping.

Fuel costs account for roughly one-third of the trucking industries’ cost per mile; a typical heavy-duty freight vehicle incurs between $70,000 and $125,000 in fuel costs each year. Vehicles that reduce their fuel consumption by 6.4 percent would save $4,500 to $8,000 per year. These savings are potentially enormous when extrapolated across the more than 2-million tractor-trailers on the road. The ability to decrease shipping and transportation costs should be a substantial incentive for large shipping companies like Fed Ex, UPS, and Amazon. 

While getting the significant players in the transportation industry is crucial, an estimated 90% of the trucking companies in the U.S. are made up of fleets with six trucks or less, and 97% have fewer than 20. Converting existing truck cabs with the necessary technology could pose a substantial hardship for these small businesses. However, it is projected that owner-operators would recoup their investment in 10-months, and fleet operators would recoup theirs in 18-months. This relatively short period could incentivize even small-scale operators to invest in the technology.

Platooning technology could also help offset the recent spike in the average cost of truck operations. Most of these costs came from increases in driver wages and benefits, likely due to a shortage of long-haul truck drivers. The shortage of drivers is only expected to grow; the combination of long hours, inconsistent schedules, long stretches of solitude, and low pay have increased the turnover rate and disincentivized new drivers from entering the labor market. While the technology is not yet poised to run without drivers, a single truck driver would one day lead a platoon train of autonomous trucks, decreasing the need for drivers in every cab.

My vision of a highway filled with platooning vehicles may not be feasible yet, but with proper investment by businesses, platooning technology could become viable, and cost-effective, within a few years.

2018 was the year of the electric scooter. They appeared unexpectedly, lined up on sidewalks, often without enough time for city regulators and officials to prepare for their arrival. Their spontaneous presence and practically unregulated use provoked outrage from consumers, city councils, and sidewalk users everywhere.

If 2018 was the year of the electric scooter, 2020 might be the year of the electric moped. Revel, the New York-based electric moped start-up, has placed more than 1,400 mopeds across Washington, D.C., and Brooklyn and Queens, New York, with plans to expand to 10 cities by mid-2020.

Revel’s mopeds operate in much the same manner as the many electric scooters offered by companies like Spin, Lime, and Bird. Riders sign up, pay for, and lock/unlock the vehicles through an app. But where scooters are suitable for last-mile travel, mopeds may fill a medium-trip sized gap in micro-mobility. Mopeds are better for longer trips where being able to sit down and travel at faster speeds is desirable. They are a good compliment, not a rival, to other micro mobility services. The more mobility services available to the public, the more comfortable people will be using them. Overcoming the threshold is important to increasing the use of alternative transportation services.

However, in stark contrast to the drop and run business method initially employed by many electric scooter companies, Revel differentiates itself by emphasizing safety and garnering regulatory approval before deploying. When Washington D.C. announced in August that the city was launching a demonstration pilot for “motor-driven cycles” (“mopeds”), Revel CEO Frank Reig expressed immediate interest in participation:

“We share their goals of providing new, reliable transportation options that work seamlessly in the city’s current regulatory, transportation, and parking systems and help the District meet its aggressive carbon emissions goals.”

Revel’s policy is not just to work with regulators when required; they seek to foster a cooperative environment that sets the company up for long term success and partnership with the cities where the mopeds eventually deploy. Whereas many cities have banned scooters, temporarily or permanently, working upfront with city officials may benefit Revel in the long-term — potentially protecting them from being required to pull their vehicles from city streets.

The cooperative method should provide an example of conduct to other micro-mobility companies seeking to expand their operations; sometimes, it is better to ask permission rather than forgiveness. The goodwill from the city may pay off in the long run if local governments decide to limit how many companies may operate in the city. They also avoid the potential regulatory gap that electric scooter fall into; mopeds are definitely a motor vehicle, CEO Reig has made sure to emphasize:

These mopeds are motor vehicles. This means there is no regulatory gray area: you have to have a license plate. To get that license plate, you have to register each vehicle with the Department of Motor Vehicles in each state and show third-party auto liability insurance. And then because it’s a motor vehicle, it’s clear that it rides in the street, so we’re completely off sidewalks.

Another area of differentiation is safety and employment. Revel’s mopeds are limited to riders aged 21 and older, capped at speeds of 30 miles-per-hour, provide riders with two helmets, and require riders to submit their driver’s license for a safe history driving check. Moreover, unlike electric scooter companies that rely on people working in the so-called “gig-economy” to charge their scooters, Revel relies on full-time employees to swap out batteries on the vehicles. This employment structure is another selling point for cities: full-time jobs and payroll taxes. The company is making an investment that other mobility companies that operate on an independent contractor model do not make. The relationship provides benefits for the cities and Revel, according to CEO Reig:

Our biggest lesson from New York and Washington is that Revel works for cities as they exist today. They work for our riders. They work for our regulators who are seeking ways to enhance their transportation networks, not disrupt them.

After receiving nearly $27 million in Series A funding, including an investment by Toyota AI Ventures, Revel could potentially increase its vehicle fleet 10-fold, aiding them in meeting their ambitious expansion plans by the middle of next year.

Earlier this week, Raphaël wrote about the role for no-fault insurance in an age of automated vehicles. The post raised several important questions about the future of the auto insurance industry as technology advances:

Who do we want to protect? Passengers, for sure. But drivers? There is no driver! Or rather, there are many drivers. To some extent, at least under a layman’s understanding of the term “driver,” all the actors along the supply chain are driving the AV. Or, to be more precise, it is difficult to pinpoint a single driver: the “operator”? The software designer? And that is already assuming that there is a single entity who designed the software or operates what may be a fleet of AVs. And there may be others, as the AV industry continues to evolve

While Raphaël’s questions will be extremely important for the industry going forward, I want to pose a slightly different question here: Should drivers of Level 4 or Level 5 automated vehicles be required to purchase insurance at all?

Today, every US state except New Hampshire and Virginia require vehicle owners to purchase auto insurance. In a world where human drivers are in control of the vehicle, this makes sense. While flawed product designs or other manufacturer errors may contribute to car accidents today, many if not most accidents also involve some element of operator error.

In a world of fully autonomous vehicles however, this will no longer be the case. The human sitting in what is today the driver’s seat will not be in control of the vehicle in any meaningful way. Every movement such a vehicle makes will have been designed and programmed by the manufacturer or some company along its supply chain.

Given the extent of manufacturer control, would it be reasonable to have accident payouts determined by the law of products liability? Or perhaps, as Michigan Law professor Kyle Logue argued in a recent article, liability should be apportioned through a scheme of strict enterprise liability, in which automakers would be “unconditionally responsible for the economic losses resulting from any crashes of their vehicles.”

Even with the heightened manufacturer liability that may accompany highly autonomous vehicles, some room may be left for owner error, and thus for traditional insurance. Owners may be held responsible for routine maintenance of their vehicles, for ensuring software is upgraded in a timely fashion, or for actions taken if the vehicle is ever taken out of autonomous mode. But even if some minimal level of owner responsibility leads lawmakers to reject Professor Logue’s theory of enterprise liability in favor of maintenance of insurance requirements for owner/operators, insurance’s role will surely be different than it is today.

Which brings me back to a version of Raphaël’s questions that I started with. Who is the true operator of an AV, and what are they responsible for? Answering these background questions will go a long way towards determining the future of auto insurance in the era of automated vehicles.

In a recent article published on Reuters Regulatory Intelligence, a DC-area lawyer said the following regarding the potential of implementing no-fault insurance “to” automated vehicles:

“Drivers have an inherent incentive to drive safely, so as not to be injured or killed on the roadways. That inherent incentive is what mitigates the “moral hazard” of a no-fault system. But in a no-fault model for autonomous vehicles, the incentives toward safety would be degraded given that manufacturers do not suffer the physical consequences of unsafe operation, as do drivers.”

Intuitively, this seems right. Yet, I thought: is there more to it? What does a world with an AV no-fault insurance scheme would look like?

This might be puzzling at first: what does one mean with no-fault AV insurance? In a more standard setting, a no-fault insurance system means that one gets the benefits of their own insurance without regard to the actual “fault” (such as negligence) and that civil suits on the basis of one’s fault are banned or severely restricted. No-fault systems are straightforward and predictable, although potentially less “just,” to the extent that a negligent driver may get away with nothing more than a deductible to pay or eventually a higher premium.

There was, and there still is, a good policy ground behind no-fault systems around car accidents: avoiding the social cost of civil litigation, and shifting the financial cost of such litigation towards the insurers, between whom things are more often than not settled out of court. Those we want to protect with no-fault insurance schemes are drivers (and passengers), and that is a majority of the population.

Now let’s consider AVs. Who do we want to protect? Passengers, for sure. But drivers? There is no driver! Or rather, there are many drivers. To some extent, at least under a layman’s understanding of the term “driver,” all the actors along the supply chain are driving the AV. Or, to be more precise, it is difficult to pinpoint a single driver: the “operator”? The software designer? And that is already assuming that there is a single entity who designed the software or operates what may be a fleet of AVs. And there may be others, as the AV industry continues to evolve; we can already see that various paths are taken by industry players, some acting for a form of vertical integration, others relying on a variety of suppliers, in a less streamlined way.

Do these all these industry players deserve extra protection? They are all corporate entities after all, and as the lawyer mentions in the above article, none of them are subject to physical injury in case of an accident. While expensive litigation can drive corporations to the ground, the case for shifting costs to insurers, when it comes to AV drivers, appears less clear. What is clear, though, is that human victims of an accident involving an AV ought to be as protected as if the accident did not involve an AV, and maybe even more.

The final answer will come from lawmakers. Moreover, one should not forget that no-fault insurance is mandatory only in a minority of US states, despite being prevalent in the rest of the world. Yet I believe there might be a case here to adopt a legal scheme which would both guarantee a litigation-free recourse to human accident victims, potentially in the form of an industry-funded guarantee fund, while giving the opportunity to the various players along the supply chain to fight it out, in court if need be, on the basis of the reality of their involvement in the cause of the accident; they are all sophisticated players after all and all share in the benefits of the risk they create. The stories of human victims, though, are what may “kill” the industry, if not enough care is taken to ensure a high level of legal protection.

October 2019 Mobility Grab Bag

Every month brings new developments in mobility, so let’s take a minute to breakdown a few recent developments that touch on issues we’ve previously discussed in the blog:

New AV Deployments

This month saw a test deployment of Level 4 vehicles in London, which even allowed members of the public to be passengers (with a safety driver). Meanwhile, in Arizona, Waymo announced it will be deploying vehicles without safety drivers, though it appears only members of their early-access test group will be riding in them for now. We’ve written a lot about Waymo, from some early problems with pedestrians and other drivers, to the regulations placed on them by Arizona’s government, to their potential ability to navigate human controlled intersections.

Georgia Supreme Court Requires a Warrant for Vehicle Data

This Monday, the Georgia Supreme Court, in the case of Mobley v. State, ruled that recovering data from a vehicle without a warrant “implicates the Fourth Amendment, regardless of any reasonable expectations of privacy.” The court found that an investigator entering the vehicle to download data from the vehicle’s airbag control unit constituted “physical intrusion of a personal motor vehicle,” an action which “generally is a search for purposes of the Fourth Amendment under the traditional common law trespass standard.” Given the amount of data that is collected currently by vehicles and the ever-increasing amount of data that CAVs can and will collect, rulings like this are very important in dictating how and when law enforcement can obtain vehicle data. We’ve previously written about CAVs and the 4th Amendment, as well as other privacy implications of CAVs, both in regards to government access to data and the use of CAV data by private parties.  

Personal Cargo Bots Could Bring Even More Traffic to Your Sidewalk

In May, as part of a series on drones, I wrote about a number of test programs deploying small delivery bots for last-mile deliveries via the sidewalk. A recent Washington Post article highlights another potential contender for sidewalk space – personal cargo bots. Called “gita” the bot can travel at up to 6 mph as it uses it’s onboard cameras to track and follow its’ owner, via the owner’s gait. The bot’s developers see it as helping enhance mobility, as it would allow people to go shopping on foot without being concerned about carrying their goods home. For city-dwellers that may improve grocery trips, if they can shell out the $3,000+ price tag!

Even More Aerial Drones to Bring Goods to Your Door

Last month, as part two the drone series, I looked at aerial delivery drones. In that piece I mentioned that Google-owned Wing would be making drone deliveries in Virginia, and Wing recently announced a partnership with Walgreens that will be part of that test. Yesterday Wired pointed out that UPS has made a similar deal with CVS – though it remains to be seen if the drones will have to deliver the infamously long CVS receipts as well. As Wired pointed out, drugstores, since they carry goods that could lead to an emergency when a home runs out of them (like medication and diapers), speedy air delivery could fill a useful niche. So next time you’re home with a cold, you may be able to order decongestant to be flown to your bedside, or at least to the yard outside your bedroom window.

P.S. – While not related to any past writings, this article  is pretty interesting – Purdue scientists took inspiration from the small hairs on the legs of spiders to invent a new sensor that can ignore minor forces acting on a vehicle while detecting major forces, making it easier for CAVs and drones to focus computing power on important things in their environment without getting distracted.

While AVs have a lot of technological leaps to make before widespread deployment, developers and governments alike also need to also consider the human factors involved, including good old fashioned human fear. Earlier this year, a AAA study showed that almost three out of four (71%) Americans are afraid to ride in an AV. This is a 10% rise in apprehension from earlier studies, a trend that could be connected to the publicity around the 2018 Uber crash in Tempe, Ariz., where a test vehicle struck and killed a pedestrian. This lack of trust in AVs alone should be concerning to developers, but in some places that lack of trust has turned into outright enmity.

Test deployments, like the one undertaken by Waymo in Arizona, have become the targets of anger from drivers and pedestrians, including an incident where man pointed a gun at a passing Waymo test vehicle, in full view of the AV’s safety driver. In that case, the man with the weapon (who was arrested) claimed he hated the vehicles, specifically citing the Uber crash as a reason for his anger. Waymo test vehicles have been also been pelted with rocks, had their tires slashed, and motorists have even tried to run them off the road. The incidents have led to caution on the part of Waymo, who has trained their drivers on how to respond to harassment (including how to spot vehicles that are following them, as witnessed by a group of Arizona Republic reporters last December). Arizona is not the only place where this has happened – in California, during a 3 month period of 2018, 2 of the 6 accidents involving AVs were caused by other drivers intentionally colliding with the AV.

So where is this anger coming from? For some in Arizona, it was from feeling that their community was being used as a laboratory, with them as guinea pigs, by AV developers. Ironically, that line of thought has been cited by a number of people who currently oppose the deployment of test AVs in and around Silicon Valley. It’s rather telling that the employees of many of the companies pushing for AV testing don’t want it to occur in their own towns (some going as far as to threaten to “storm city hall” if testing came to Palo Alto…). Other objections may stem from people seeing AVs as a proxy for all automation, and the potential loss of jobs that entails.

So what can be done to make people trust AVs, or at least accept them enough to not run them off the road? On the jobs front, in June a group of Senators introduced a bill to have the Labor Department track jobs being displaced by automation. Responding to the changes brought on by automation is a center point of Democratic Presidential Candidate Andrew Yang’s campaign, and the issue has been raised by other candidates as well. The potential of automation to take away jobs is a long-standing issue made more visible by AVs on the road, and one that won’t be solved by AV proponents alone. What AV supporters have done and can continue to do is attempt to educate the public on now only potential befits of AV deployment (which PAVE, an industry coalition has done), but also better explain just how AV technology works. At least part of the AV fear stems from not understanding how the tech actually operates, and transparency in that vein could go a long way. Future test projects also need to be sure to get input from communities before they start testing, to ease the feeling of AVs being imposed upon an unwilling neighborhood. A recent debate over AV testing in Pittsburgh, where the city obtained funds for community outreach only after approving testing, leading to push back from community members, is a good example of how a proper pre-testing order-of-operations is vital.

For now, there is clearly a lot of room for public engagement and education. Developers should take advantage of this period where AVs are in the public eye without being widely deployed to build trust and understanding, so that once the vehicles start appearing everywhere they are met with open arms, or at least tolerated, rather than ran off the road. After all, while AVs themselves may not feel road rage, it’s already clear they can be victims of it.

P.S. – If you’re interested in learning more about negative reactions to robots, a good starting point is this NY Times article from January 2018.

In 2015, Google’s parent, Alphabet, decided the time was ripe for establishing a subsidiary in charge of investing in “smart infrastructure” projects – from waste to transport and energy. Its aim was specifically to implement such projects, transforming our urban landscape into a realm of dynamic and connected infrastructure pieces. Fast forward two years, and Sidewalk Labs had become embroiled in a smart city project covering a somewhat derelict (but highly valuable) area of the Toronto along the shores of Lake Ontario. 

Already in 2001, the Canadian metropolis set up the aptly named Waterfront Toronto (WT), a publicly-controlled corporation in charge of revitalizing the whole Lake Ontario waterfront along the city. WT then published early in 2017 a “Request for Proposals,” looking for an “investment and funding partner” for what would become known as the Quayside project. By the end of the year, the Alphabet subsidiary was chosen by WT.

It is important to note that this project was initially thought as a real estate one, and the desired innovation was to be found in building materials and carbon neutrality, while achieving certain goals in terms of social housing. There was no express desire for a model “smart city” of any sort, although the document does mention the usage of “smart technologies,” but always in the context of reducing building costs and improving the carbon footprint. 

Critics were quick to point out the puzzling choice; as innovative as it may be, Alphabet has no experience in real estate development. Rather, its core business is data processing and analytics, sometimes for research and often for advertisement purposes. What was meant to be a carbon-positive real-estate project seemed to be morphing into a hyper-connected (expensive) urban hub. 

And then came Sidewalk Labs’ detailed proposal. The visuals are neat; tellingly, there is not a single electronic device to be found in those pictures (is that one man on his cellphone?!) The words, however, tell another story. Carbon footprint and costs of building take a second seat to (personal) data processing: “Sidewalk expects Quayside to become the most measurable community in the world,” as stated in their winning proposal. One wonders whether the drafters of the proposal sincerely thought that, in this day an age, such a statement would fly with the public opinion. 

Critics of the project (who have since coalesced in the #BlockSidewalk movement) used the opportunity to dig deeper into WT itself, highlighting governance issues and the top-down character of the original Request for Proposals, beyond the plethora of data privacy questions (if not problems) the Sidewalk Labs proposal raised. In response, Sidewalk Labs deployed a vast campaign of public relations, whose success is far from guaranteed: they have “upgraded” their project, aiming for a bigger plot of land and even a new light rail plan (funded mostly on public money). At the time of this writing, WT has yet to make its final decision whether to retain the project of the Alphabet’s subsidiary. 

What lessons can we draw from this Toronto experience? “Smart city” projects are bound to become more commonplace, and while this one was not meant as such, some will be more straightforward in their aims. First, we should question the necessity of connecting every single thing and person. It matters to have in mind the social objectives of a given project, such as carbon footprint or building costs reduction. Collection of personal data can thus be articulated around and in function of those objectives, rather than as an end in itself. Connecting the park bench may be fancy, but for what purpose? More down to earth, the same question can be asked of street lights. 

As Christof Spieler reminds us in a recent tweet thread, certain municipal governments may be approached with “free” turnkey projects of connected infrastructure, in exchange (oh wait, it’s not free?) of both data and integration of the developer’s pre-existing systems into that infrastructure. Think of advertisements, and all the other possible monetization avenues… As Spieler points out, monetized smart infrastructure may come at a heavy social cost. 

Beyond that, one may wonder – who do we want as developers of such projects? Do we need the Sidewalk Labs of this world to realize the post-industrial heaven shown in the visuals of the Proposal? How will multinational data crunchers with an ominous track record make our cities smarter? The burden of proof is on them.

I recently wrote about a renewed federal push to regulate automated vehicles. I’ve previously highlighted a range of state regulatory schemes, including California’s relatively strict set of regulations. Meanwhile, the advent of truly automated vehicles, which seemed imminent when Waymo announced its driverless shuttle service in Phoenix, now may be farther away than we expected. Waymo’s shuttle’s still have human safety drivers, and the technology has not advanced as quickly as expected to handle all the vagaries of the road.

But as Congress and the states struggle to get a regulatory handle on this new technology, a recent Tesla update raises an important question. Is the regulatory state agile enough to adapt when the automated vehicle market evolves in unexpected ways?

Last week, Tesla unveiled “Smart Summon,” a feature in some vehicles that allows the user to summon the car to their location. With a range of 200 feet, Smart Summon is primarily designed for use in parking lots. At least one video shows its successful use in a Costco parking lot, avoiding pedestrians and other vehicles to meet its owner at the storefront. However, the feature is not limited to use in parking lots, and videos have emerged of users trying out Smart Summon on public roads, and even running in front of their vehicle to try and make the car chase them. Despite the potential dangers this technology presents, no one has yet been injured or hit by a driverless Tesla being summoned.

Despite the seriousness with which California takes automated vehicle regulation, state authorities have determined that Teslas equipped with Smart Summon are not autonomous, and thus do not need to meet California’s AV standards. Based on regulatory definitions, this is probably the correct. A state DMV spokesperson said the state defines AVs as vehicles able to drive without active physical control or monitoring by a human. Smart Summon requires a user to be attentive to their smartphone. Furthermore, its inability to operate more than 200 feet from a human controller means that it would not satisfy SAE autonomous driving level four or five.

Despite not being a true AV though, it’s clear that Smart Summon presents many of the same dangers as one. It operates in unpredictable parking lots, filled with pedestrians and vehicles and shopping carts all moving around each other in unpredictable ways. It is the sort of environment that can get dicey for a human driver, with our experience and understanding of the subtle signals humans give off to make an otherwise unexpected move a little bit more predictable. And despite a small-print company warning that Smart Summon requires “active driver supervision,” the amount of supervision anyone can truly give a moving vehicle from 200 feet away is certainly questionable.

And yet, these vehicle are not AVs. Instead, they seem to fall within an increasingly muddled gray area of transportation that is something short of fully automated, but requires much less than full and active driver attention. In California’s current regulatory environment, this technology fits neatly into a gap.

A year ago, many people assumed we were rapidly approaching the rise of Level 4 automated vehicles that could operate smoothly on city streets. Regulations developed at the time are written with that sort of technology in mind. Even one year out, legislators were not thinking of how to assure the safety of something like Smart Summon.

So how should something like Smart Summon be regulated? What will autonomous—or semi-autonomous—technology look like a year from now, and how can government agencies prepare for it? Given the unpredictable nature of an early stage technology, regulators will continue struggling to answer these questions.

The European Union recently adopted new rules to help consumers repair household appliances like refrigerators and televisions. The rules require manufacturers to provide spare parts for years after sale – the number of years depending on the device. The “Ecodesign Directive” is intended to help protect the environment by extending the life of consumer appliances. The regulation also applies to servers, requiring firmware updates for 7 years post-production. These regulations are part of a larger battle over consumers’ right to repair their belongings, including vehicles. Vehicles are already part of the right to repair discussion, and the deployment of technically complicated CAVs will ramp up that conversation, as some manufacturers seek to limit the ability of individuals to repair their vehicles.

One current battle over the right to repair is taking place in California. In September of last year, the California Farm Bureau, the agricultural lobbying group that represents farmers, gave up the right to purchase repair parts for farm equipment without going through a dealer. Rather than allowing farmers to buy parts from whomever they’d like, California farmers have to turn to equipment dealers, who previously were unwilling to even allow farmer’s access to repair manuals for vehicles they already owned. A big part of the dispute stems from companies like John Deere placing digital locks on their equipment that prevent “unauthorized” repairs – i.e. repairs done by anyone other than a John Deere employee. The company even made farmers sign license agreements forbidding nearly all repairs or modifications, and shielding John Deere from liability for any losses farmers may suffer from software failures. Some farmers resorted to using Ukrainian sourced firmware to update their vehicle’s software, rather than pay to hire a John Deere technician. The California case is especially ironic, as the state has solid right to repair laws for other consumer goods, requiring companies to offer repairs for electronics for 7 years after production (though companies like Apple have been fighting against the state passing even more open right to repair laws).

In 2018, supporters of the right to repair were boosted by a copyright decision from the Librarian of Congress, which granted an exception to existing copyright law to allow owners and repair professionals to hack into a device to repair it. The exception is limited, however, and doesn’t include things like video game consoles, though its’ language did include “motorized land vehicles.”

So how could battles over the right to repair influence the deployment of CAVs? First off, given the amount of complicated equipment and software that goes into CAVs, regulations like those recently adopted in the EU could help extend the lifespan of a vehicle. Cars last a long time, with the average American vehicle being 11.8 years old. Right to repair laws could require manufactures to supply the parts and software updates needed to keep CAVs on the road. New legislation could protect consumer access to the data within their vehicle, so they don’t have to rely on proprietary manufacturer systems to know what’s going on inside their vehicle. A 2011 study of auto repair shops showed a 24% savings for consumers who used a third-party repair shop over a dealership, so independent access to data and spare parts is vital to keeping consumer maintenance costs down. People are very used to taking their cars to independent repair shops or even fixing them at home, and many consumers are likely to want to keep their ability to do so as CAVs spread into service.

P.S. – Two updates to my drone post from last week:

Update 1 – University of Michigan (Go Blue!) researchers have demonstrated a drone that can be used to place shingles on a roof, using an interesting system of static cameras surrounding the work-site, rather than on-board cameras, though it remains to be seen how many people want a nail gun equipped drone flying over their head…

Update 2 – UPS has been granted approval to fly an unlimited number of delivery drones beyond line-of-sight, though they still can’t fly over urban areas. They have been testing the drones by delivery medical supplies on a North Carolina hospital campus.

Last week I covered the various companies who are seeking to use aerial drones to deliver goods to your door. Today, in the third part to my series on delivery (you’ll find Part 1 here, and an even earlier post on delivery, from December of 2018, here), I’m going to look at recent proposals to use automated vehicles to deliver consumer goods.

As an introduction, I’m going to include a paragraph from that December 2018 post as an introduction to some of the ways automated vehicles are being used to make deliveries :

The potential for CAVs as delivery vehicles is already being tested by companies like Domino’s and Kroger, among others. Earlier this year Toyota announced delivery partnerships with Amazon and Pizza Hut, and Waymo’s CEO recently highlighted it as an area of opportunity.  This week the New York Times profiled Nuro, the start-up working with Kroger to test robotic delivery cars in Scottsdale, Ariz. Nuro’s vehicles are designed in-house, and look like “toasters-on-wheels,” and are currently followed everywhere they go by human safety drivers in conventionally driven “shadow car.” When the vehicle stops for a delivery, customers enter a PIN code into a small touch pad to open the compartment containing their order. The current charge for same-day delivery using the system is around $6. Ford has also flagged the delivery market as an area they’d like to explore, citing projections that by 2026 the last-mile delivery market for CAVs will hit $130 billion.

Don’t Forget to Tip Your (Robotic) Delivery Driver – Dec. 21, 2018

Since that post, Domino’s has announced a partnership with Nuro as well, with plans to test in Houston at some point this year. Walmart has also jumped in on the action – partnering with another AV developer, Gatik. For now Walmart’s test is limited to a 2-mile route between two of their stores in the company’s hometown of Bentonville, Arkansas. Why the interest? In part because of the potential cost savings – a recent Ford estimate calculates AVs could reduce the cost per mile for deliveries from $2.50 to $1. No doubt the combination of lower costs and ever-greater demand for delivery is a powerful motivator, pushing companies to explore not only AVs, but also drones and delivery bots, as discussed in Parts I and II of this series.

Beyond last-mile deliveries, there is a great deal of interest in automating semi-trucks and other large delivery vehicles. One company, TuSimple, is working with both the U.S. Postal Service (USPS) and UPS to move packages between cities. Interestingly, in UPS’ case, the company only announced the partnership after TuSimple had already been delivering goods for months – which seems to indicate the program is not just a grab for positive PR. The USPS’ test was more limited, running for two-weeks and five round trips. All of the trips included a safety driver and an engineer, and both tests were carried out in the Southwest. Meanwhile, in Sweden, a completely driverless electric truck was deployed in May, a global first. Given a nation-wide shortage of truck drivers (a recent estimate puts the U.S. deficit at roughly 60,000 drivers), automated trucks present a solution that doesn’t overly disrupt a truck-heavy commercial delivery system.

But what would the wide-spread adoption of AVs as part of the delivery ecosystem mean? We can already see that the demand for faster and faster delivery is taking its toll. Recently, the NY Times and Buzzfeed News both published articles detailing the human cost of Amazon’s push for same or next-day delivery. Under-trained drivers pushed to the limit have killed people in seemingly avoidable accidents that don’t often happen with more highly-trained delivery drivers (like those used by the USPS, UPS, and FedEx). Amazon has avoided liability by using a number of third-party companies as contractors, making those companies, and not Amazon, responsible for accidents. AVs would certainly be safer for the public, as they wouldn’t fall prey to the pressures of human drivers, though that does nothing to alleviate the pressures on the human delivery people, who would still be needed to move goods from the vehicle to a door. At the same time, Amazon may continue to escape liability, if the AVs remain owned by third parties. There is also the greater question of the environmental impact of the growing number of delivery vehicles on the road (not to mention the waste created by packing materials and shipping boxes). I’ll leave a greater discussion about those issues to future posts and other forums, but those questions, among so many others (privacy, cybersecurity, and traffic management among them) are important to consider as automated delivery vehicles of all kinds begin to fill our streets and skies.

P.S. – In a follow up to last week’s blog, the USPS has stated to investigate the use of aerial drones, and is now seeking information from drone operators and developers.

This is the much-delayed second part in a series of posts I started earlier this year. In that first post I discussed how companies are experimenting with small delivery robots that crawl along sidewalks to deliver goods right to your door. However, the sidewalk is not the only place where delivery drones may soon be found, as many companies are interested in using aerial drones to bring their products right to consumers.

In April, Wing, a division of Google parent company Alphabet, was given approval to start delivering goods via drone in Canberra, Australia. At launch, the drones were delivering food, medicine, and other products from 12 local businesses. This formal launch came after a trial period that ran for 18 months and 3,000 deliveries. Also in April, Wing received an FAA certification typically used for small airlines, as they begin to plan U.S. based tests, again with the intent to partner with local businesses. Not to be left behind, in June Amazon revealed it’s own delivery drone, which is indented to bring good directly from their warehouses to nearby customers within 30 minutes. Also in June, Uber announced a plan to partner with McDonalds to test delivery drones in San Diego. In Ohio, a partnership between the Air Force and the state government will allow drones to test outside of line-of-sight (a range that most civilian drones are currently limited to by the FAA). One company that intends to take part in the Ohio testing is VyrtX, which is looking to use drones to deliver human organs for transplant. 

But just what would wider use of such delivery drones mean for society? What would it mean to live in a world with robots buzzing around above our heads? In the Australian tests there were complaints about noise, with some residents claiming the sound of the machines caused them significant distress. In January of this year an unidentified drone shut down London’s Heathrow Airport, showing what can happen when drones wander into places they’re not welcome. In February of this year NASA announced two tests of “urban drone traffic management,” one in Texas, and the other in Nevada. Such a system would no doubt be necessary before widespread deployment of any of the systems so far proposed – to prevent incidents like the one in London.   

There is also a major privacy concern with drones collecting data as they fly above homes and businesses. This concern extends beyond just what privately owned drones may find, but also what law enforcement could collect. In Florida v. Riley, a 1988 case, the Supreme Court found that there is not reasonable expectation of privacy from aircraft (in that case, a police helicopter) flying in navigable airspace above a person’s home, when the air craft is flying within FAA regulations. So drones would provide a useful tool for investigations, and one that is limited only by FAA rules.

There are a lot of unanswered questions about delivery drones – and given the highly-regulated nature of all forms of air travel, the federal government, via the FAA, currently has a lot of power over just what can go on in U.S. airspace. What remains to be seen is if this regulatory structure will stifle drone development or instead insure that any market for delivery drones is developed deliberately, rather than ad hoc, with an emphasis on safety.

P.S. – A brief follow-up to my last article – Ford recently partnered with Agility Robotics on a new form of last mile delivery bot, a bipedal unit designed to carry up to 40 pounds. Could it become the C-3PO to the R2-D2-like bots already in testing?

Anyone currently living in a large city or an American college town has had some experiences with scooters – would that be the mere annoyance of having them zip around on sidewalks. Or, as a friend of mine did, attempt to use one without checking first where the throttle is…

Montréal, the economic and cultural capital of Québec province in Canada, has recently given temporary “test” licenses to micromobility scooters and bikes operators Bird, Lime and Jump, the latter two being owned by Google and Uber, respectively. 

Operations started late spring, among some skepticism from Montrealers. Not only in face of the strict regulations imposed by the city’s bylaw, but also the steep price of the services. As one article from the leading French language daily La Presse compares, a ride that takes slightly more than 20 minutes by foot would cost more than 4 Canadian dollars (about $3) with either Lime (scooters) or Jump (bikes), for a total ride time of 12 minutes. The subway and the existing dock-based bike-share service (BIXI) are cheaper, if not both cheaper and quicker. 

While Montréal’s young and active population segment can be understood as the perfect customer base for micromobility, its local government, like many others across the world who face a similar scooter invasion, really mean it with tough regulation. Closer to home, Ann Arbor banned Bird, Lyft and Lime earlier this spring for failure to cooperate; Nashville mayor attempted a blanket ban; Boulder is considering lifting its ban; several Californian cities are enforcing a strict geofencing policy; further away from the US, Amsterdam is also going to put cameras in place in order to better enforce its bikes-first regulation after having already handed out 3500 (!) individual fines over the course of a few months. As NPR reports, the trend is toward further tightening of scooter regulations across the board.

So is Montréal’s story any different? Not really. It faces the same chaotic parking situation as everywhere else, with misplaced scooters, found outside of their geofence or simply where they should not be. In its bylaw providing for the current test licenses, the city council came up with a new acronym: the unpronounceable VNILSSA, or DSUV in English. The English version stands for “dockless self-serve unimmatriculated vehicles”. The bylaw sets a high standard for operators: they are responsible for the proper parking of their scooters at all times. Not only can scooters only be parked in designated (and physically marked) parking areas, but the operator has two hours to deal with a misplaced scooter after receiving a complaint from the municipal government, with up to ten hours when such a complaint is made by a customer outside of business hours. In addition, customers must be 18 to ride and must wear a helmet. 

Tough regulations are nice, but are they even enforced? The wear-a-helmet part of the bylaw is the police’s task to enforce and there has not been much going on that front so far. As for the other parts, the city had been playing it cool, so far, giving a chance to the operators to adjust themselves. But that did not suffice: the mayor’s team recently announced the start of fining season, targeting both customers who misplace their scooter or bike if caught red-handed and the operators in other situations. The mayor’s thinly veiled expression of dissatisfaction earlier prompted Lime to send an email to all its customers, asking them in turn to email the mayor’s office with a pre-formatted letter praising the micromobility service. The test run was meant to last until mid-November, but it looks like may end early… The mobility director of the mayor’s team pledged that most of the data regarding complaints and their handling – data which operators must keep – would be published on the city’s open data portal at the end of the test run. 

If Chris Schafer, an executive at Lime Canada, believes that customers still need to be “educated” to innovative micro-mobility, Montréal’s story may prove once more that micromobility operators also need to be educated, when it comes to respecting the rules and consumers’ taste for responsible corporate behavior.

Back in January, I wrote about the auto industry’s growing sense that a set of nationwide regulatory standards was needed to govern automated vehicles (AVs). To date, twenty-nine states and Washington, DC have enacted AV-related legislation. A handful more have adopted Executive Orders or developed some other form of AV regulation. As the number of states with varying regulatory regimes continues to rise, the industry and some experts have grown concerned that the need to comply with a patchwork of disparate laws could hinder development of the industry.

Despite these concerns, and bipartisan support, the federal AV START Act died in the Senate at the close of 2018. After passing the House, a group of Senate Democrats became concerned that the bill focused too much on encouraging AV adoption at the expense of meaningful safety regulation. After the bill went down at the end of the year, the industry significantly reduced its lobbying efforts. This led some observers to conclude that the effort to pass AV START would not be renewed any time soon.

Never ones to let a good acronym go to waste, several members of Congress have begun work to revive the American Vision for Safer Transportation Through Advancement of Revolutionary Technologies (AV START) Act. Over the summer, a bipartisan group of lawmakers in both chambers held a series of meetings to discuss a new deal. Their hope is that, with Democrats now in control of the House, the safety concerns that stalled the bill in the upper chamber last winter will be assuaged earlier in the process.

Congress’ efforts, spearheaded by Senator Gary Peters (D-MI) appear to be making at least some headway. Both the House Committee on Energy and Commerce, and the Senate Committee on Commerce, Science and Transportation, sent letters to a variety of stakeholders requesting comments on a potential bill.

The legislature appears to be moving forward deliberately however, and to date no hearings on the subject have been scheduled in either the House or Senate. As Congress once again builds an effort to pass comprehensive AV legislation, this blog will be following and providing updates.

I previously blogged on automated emergency braking (AEB) standardization taking place at the World Forum for Harmonization of Vehicle Regulations (also known as WP.29), a UN working group tasked with managing a few international conventions on the topic, including the 1958 Agreement on wheeled vehicles standards.

It turns out the World Forum recently published the result of a joint effort undertaken by the EU, US, China, and Japan regarding AV safety. Titled Revised Framework document on automated/autonomous vehicles, its purpose is to “provide guidance” regarding “key principles” of AV safety, in addition to setting the agenda for the various subcommittees of the Forum.

One may first wonder what China and the US are doing there, as they are not members to the 1958 Agreement. It turns out that participation in the World Forum is open to everyone (at the UN), regardless of membership in the Agreement. China and the US are thus given the opportunity to influence the adoption of one standard over the other through participation in the Forum and its sub-working groups, without being bound if the outcome is not to their liking in the end. Peachy!

International lawyers know that every word counts, and every word can be assumed to have been negotiated down to the comma, or so it is safe to assume. Using that kind of close textual analysis, what stands out in this otherwise terse UN prose? First, the only sentence couched in mandatory terms. Setting out the drafters’ “safety vision,” it goes as follows: AVs “shall not cause any non-tolerable risk, meaning . . . shall not cause any traffic accidents resulting in injury or death that are reasonably foreseeable and preventable.”

This sets the bar very high in terms of AV behavioral standard, markedly higher than for human drivers. We cause plenty of accidents which would be “reasonably foreseeable and preventable.” A large part of accidents are probably the result of human error, distraction, or recklessness, all things “foreseeable” and “preventable.” Nevertheless, we are allowed to drive and are insurable (except in the most egregious cases…) Whether this is a good standard for AVs can be discussed, but what is certain is that it reflects the general idea that we as humans hold machines to a much higher “standard of behavior” than other humans; we forgive other humans for their mistakes, but machines ought to be perfect – or almost so.

In second position: AVs “should ensure compliance with road traffic regulations.” This is striking by its simplicity, and I suppose that the whole discussion on how the law and its enforcement are actually rather flexible (such as the kind of discussion this very journal hosted last year in Ann Arbor) has not reached Geneva yet. As it can be seen in the report on this conference, one cannot just ask AVs to “comply” with the law; there is much more to it.

In third position: AV’s “should allow interaction with the other road users (e.g. by means of external human machine interface on operational status of the vehicle, etc.)” Hold on! Turns out this was a topic at last year’s Problem-Solving Initiative hosted by University of Michigan Law School, and we concluded that this was actually a bad idea. Why? First, people need to understand whatever “message” is sent by such an interface. Language may come in the way. Then, the word interaction suggests some form of control by the other road user. Think of a hand signal to get the right of way from an AV; living in a college town, it is not difficult to imagine how would such “responsive” AVs could wreak havoc in areas with plenty of “other road users,” on their feet or zipping around on scooters… Our conclusion was that the AV could send simple light signals to indicate its systems have “noticed” a crossing pedestrian for example, without any additional control mechanisms begin given to the pedestrian. Obviously, jaywalking in front on an AV would still result in the AV breaking… and maybe sending angry light signals or honking just like a human driver would do.

Finally: cybersecurity and system updates. Oof! Cybersecurity issues of IoT devices is an evergreen source of memes and mockery, windows to a quirky dystopian future where software updates (or lack thereof) would prevent one from turning the lights on, flushing the toilet, or getting out of the house… or where a botnet of connected wine bottles sends DDoS attacks across the web’s vast expanse. What about a software update while getting on a crowded highway from an entry ramp? In that regard, the language of those sections seems rather meek, simply quoting the need for respecting “established” cybersecurity “best practices” and ensuring system updates “in a safe and secured way…” I don’t know what cybersecurity best practices are, but looking at the constant stream of IT industry leaders caught in various cybersecurity scandals, I have some doubts. If there is one area where actual standards are badly needed, it is in consumer-facing connected objects.

All in all, is this just yet another useless piece of paper produced by an equally useless international organization? If one is looking for raw power, probably. But there is more to it: the interest of such a document is that it reflects the lowest common denominator among countries with diverging interests. The fact that they agree on something, (or maybe nothing) can be a vital piece of information. If I were an OEM or policy maker, it is certainly something I would be monitoring with due care.

“Safety.” A single word that goes hand-in-hand (and rhymes!) with CAV. If much has been said and written about CAV safety already (including on this very blog, here and there,) two things are certain: while human drivers seem relatively safe – when considering the number of fatalities per mile driven – there are still too many accidents, and increasingly more of them. 

The traditional approach to safely deploying CAVs has been to make them drive, drive so many miles, and with so few accidents and “disengagements,” that the regulator (and the public) would consider them safe enough. Or even safer than us!  

Is that the right way? One can question where CAVs are being driven. If all animals were once equal, not every mile can be equally driven. All drivers know that a mile on a straight, well-maintained road by a fine sunny day is not the same as a mile drive on the proverbially mediocre Michigan roads during a bout of freezing rain. The economics are clear; the investments in AV technology will only turn a profit through mass deployment. Running a few demos and prototypes in Las Vegas won’t cut it; CAVs need to be ready to tackle the diversity of weather patterns we find throughout the world beyond the confines of the US South-West.

Beyond the location, there is the additional question of whether such “testing” method is the right one in the first place. Many are challenging what appears to be the dominant approach, most recently during this summer’s Automated Vehicle Symposium. Their suggestion: proper comparison and concrete test scenarios. For example, rather than simply aiming for the least amount of accidents per 1000’s of miles driven, one can measure break speed at 35mph, in low-visibility and wet conditions, when a pedestrian appears 10 yards in front of the vehicle. In such a scenario, human drivers can meaningfully be compared to software ones. Furthermore, on that basis, all industry players could come together to develop a safety checklist which any CAV must be able to pass before hitting the road. 

Developing a coherent (and standardized?) approach to safety testing should be at the top of the agenda, with a looming push in Congress to get the AV bill rolling. While there are indications that the industry might not be expecting much from the federal government, this bill still has the possibility of allowing CAVs on the road without standardized safety tests, which could result in dire consequences for the industry and its risk-seeking members. Not to mention that a high-risk business environment squeezes out players with shallower pockets (and possibly innovation) and puts all road users, especially those without the benefit of a metal rig around them, at physical and financial risk were an accident to materialize. Signs of moderation, such as Cruise postponing the launch of its flagship product, allows one to be cautiously hopeful that “go fast and break things” mentality will not take hold in the automated driving industry.

*Correction 9/9/19 – A correction was made regarding the membership to 1958 Agreement and participation at the World Forum.

A European Commission plan to implement the connected car-specific 802.11p “Wi-Fi” standard for vehicle-to-vehicle (V2V) communication was scrapped early July after a committee of the Council of the European Union (which formally represents individual member states’ during the legislative process) rejected it. The standard, also known as ITS-G5 in the EU, operates in the same frequency range as domestic Wi-Fi, now most often deployed under the 802.11n specification.

The reason for this rejection were made clear by the opponents of “Wi-Fi V2V”: telecommunication operators, and consortia of IT equipment and car manufacturers (such as BMW and Qualcomm) would never allow locking out 5G and its ultra-low latency, “vehicle-to-everything” (V2X) solutions. In turn, countries with substantial industrial interest in those sectors (Germany and Finland, to name only two,) opposed the Commission plan.

Yet it appears that Commissioner Bulc had convincing arguments in favor of 802.11p. In her letter to the European Parliament’s members, she stresses that the technology is available now, and can be successfully and quickly implemented, for immediate improvements in road safety. In her view, failure to standardize now means that widespread V2V communication will not happen until the “5G solutions” come around.

5G is a polarizing issue, and information about it is often tainted with various industries’ talking points. It first matters to differentiate 5G as the follow-up on 4G, and 5G as the whole-new-thing-everyone-keeps-talking-about. As the follow up on 4G, 5G is the technology that underpins data delivery to individual cellphones. It operates mostly in higher frequencies than current 4G, higher frequencies which have a lower range and thus require more antennas. That in turn explains why most current cellphone 5G deployments are concentrated in large cities.

The “other” 5G is based on a promise: the higher the frequency, the higher the bandwidth and the lower the latency. Going into the hundreds of GHz, 5G theoretically delivers large bandwidth (in the range of 10 Gbps) in less than 1ms, with the major downside of a proportionally reduced range and ability to penetrate dense materials.

The logical conclusions of these technical limitations is that the high-bandwidth, low-latency 5G, set to revolutionize the “smart”-everything and that managed to gather some excitement will become a reality the day our cities are literally covered with antennas at every street corner, on every lamppost and stop sign. Feasible over decades in cities (with whose money, though?), a V2X world based on a dense mesh of antennas looks wholly unrealistic in lower density areas.

Why does it make sense, then, to kick out a simple, cheap and patent-free solution to V2V communication in favor of a costly and hypothetical V2X?

Follow the money, one would have said: what is key in this debate is understanding the basic economics of 5G. As the deployment goes on, it is those who hold the “Standard Essential Patents” (SEPs) who stand to profit the most. As reported by Nikkei in May 2019, China leads the march with more than a third of SEPs, followed by South Korea, the US, Finland, Sweden and Japan.

If the seat of the V2V standard is already taken by Wi-Fi, that is one less market to recoup the costs of 5G development. It thus does not come as a surprise that Finland was one of the most vocal opponents to the adoption of 802.11p, despite having no car industry – its telecom and IT sector have invested heavily in 5G and are visibly poised to reap the rewards.

Reasonable engineers may disagree on the merits of 802.11p – as the United States’ own experience with DSRC, based on that same standard, shows. Yet, the V2X 5G solutions are nowhere to be seen now, and investing in such solutions was and remains to this day a risky enterprise. Investments required are huge, and one can predict there will be some public money involved at some point to deploy all that infrastructure.

“The automotive industry is now free to choose the best technology to protect road users and drivers” said Lise Fuhr, director general of the European Telecommunications Network Operators’ Association (ETNO) after their win at the EU Council. I would rather say: free to choose the technology that will preserve telcos’ and some automakers’ risky business model. In the meantime, European citizens and taxpayers subsidize that “freedom” with more car accidents and fatalities, not to speak of other monetary costs 5G brings about. The seat will have been kept warm until the day their 5G arrives – if it does – at some point between 2020 and 2025. In the meantime, users will have to satisfy ourselves of with collision radars, parking cameras, cruise control and our good ol’ human senses.

One of the most persistent issues in public transportation is the so-called “last mile” problem. The essence of the problem is that, if the distance between the nearest transit stop and a rider’s home or office is too far to comfortably walk, potential riders will be more likely to drive than use public transit. The rise of smartphone enabled mobility options like ridesharing, bike-share, and e-scooters have been pitched as potential solutions to this problem. However, some cities have found that these technologies may create as many problems as they solve.

This post will focus in particular on the rise of e-scooters. Over roughly the last two years, e-scooters from companies like Bird and Lime have proliferated across American cities. Often appearing seemingly out of nowhere as companies frequently launch the product by dropping off a batch of scooters overnight without warning, they have been a source of angst for many city officials.

As the scooters spread, ridership has proliferated. Thanks to ease of use, the proliferation of smartphones, and increasing comfort with new forms of mobility, ridership has accelerated at a faster pace than ride-hailing apps, bikeshare programs, or other mobility platforms that have developed in recent years.

With this growth though has come challenges. In June, Nashville chose to ban e-scooters in the aftermath of the city’s first rider death. Last year, in response to concerns about safety and obstruction of sidewalks, Cleveland banned e-scooters. In the initial rollout period Cleveland was far from alone, as cities from St. Louis to San Francisco to Santa Monica also moved to ban or significantly reduce the number of scooters allowed.

Some of these bans, or at least use restrictions, may have been justified. Because they have no defined ports at which to be put away, scooters are often left blockading the sidewalk. At least 8 scooter riders have died in crashes, and users often remain confused about what laws apply to them and where they can ride. Hospitals across the country have seen a spike in emergency room visits related to scooter crashes, and the Centers for Disease Control has found that head trauma is the most common injury resulting from a scooter crash.

Slowly though, cities have begun experimenting with ways to let scooters in without letting them run wild. Last month Cleveland allowed scooters back in, with new limitations on where they are allowed to go and who is allowed to ride. Norfolk, VA recently contracted with e-scooter company Lime to allow them to have a local monopoly over scooter service in the city. The move may allow Norfolk greater control over how Lime operates within its borders, which could ultimately increase safety.

Given the obvious potential for e-scooters to increase mobility to parts of a city that aren’t within easy walking distance of transit stations, cities should continue working to find ways to allow them in while mitigating safety concerns. The results in cities like Norfolk and Cleveland that are working to introduce regulation to this new industry will be important to watch in the coming months.

In my previous posts, I have written a lot about city design and integrating emerging forms of transit, primarily automated vehicles, into the transportation landscape of a city. I am spending this summer in Washington, DC, and am getting an up-close look at this city’s transit options. I left my car behind for the summer, so for the first time in years, I am entirely reliant on public transportation, ridesharing apps, and my own feet to navigate the city. In the process, I have learned a few things that I plan to explore in more depth over the course of the summer. For now, here are the highlights:

1. Scooters do provide important transit for at least some people:

My house is about 0.6 miles from the bus line I take to work. So far, I have walked to that stop every morning. Along the way though, I see people riding by on scooters between the metro or bus station and their homes. It may yet be the case that scooters are a passing fad, and for now they appear – at least anecdotally – to have been adopted primarily by younger people. And to be sure, regulating them has been controversial in cities across the nation, which I plan to address in a coming post. For now though, they do show promise as a “last-mile” transit option for people who prefer not to drive.

2. A wide range of transit options improves access and reliability:

I ride the bus to and from work every day. When I want to explore the city on weekends, I take the metro downtown. I was running late to meet a friend the other day, and got an Uber. Others use scooters or the city’s bike-share program to get where they need to go. All of these options will work better or worse for different people, and for different purposes. All of them operating together can create a more functional, accessible transit system that serves the entire city.

3. Walkable neighborhoods ease the burden on a city’s transit system:

I live in a neighborhood with a grocery store, a Target, and a handful of bars and restaurants within a few blocks radius. As a consequence, I can walk just about everywhere I have to go except my office. Later this summer, I plan to explore ways in which cities can encourage development of walkable neighborhoods, thus easing the burden on overtaxed public transit systems and reducing the use of personal cars in the long run.

4. Affordable housing is directly linked to transit equity:

Perhaps this goes without saying, but a good, comprehensive transit network within a city does little good for the people who cannot afford to live in that city. This week, I’ve spoken with a couple people in my office who live an hour outside the city because it’s more affordable than living here. They drive to the farthest out metro stations, park there then ride into the city. To be sure, this still reduces congestion within the city. But good, reliable public transit is primarily important for the quality of life, cost savings, and environmental benefits that come with reduced use of personal automobiles and shorter commutes. People who have to commute a long way to even get to the public transit system in the city where they work are largely left out of those benefits.

As we move towards a future of fully automated vehicles, the types of crime – and attendant need for criminal enforcement – committed with cars is likely to evolve. As our transit system becomes more automated, the danger of a hack, and the difficulty of discovering the crime through ordinary policing tactics, is likely to increase. Some experts have expressed concerns that automated vehicles would be just as easy to use for delivery of drugs or guns as for more innocuous packages. Others, such as Duke University professor Mary Cummings, say that vehicles are too easy to hack and steer off course.

Going beyond relatively ordinary crimes such as theft, an unclassified FBI report obtained by The Guardian revealed the agency’s concern that autonomous vehicles could be commandeered and utilized as a “potential lethal weapon” or even self-driving bomb.

The likelihood that automated vehicles will generally obey the traffic laws complicates the ability of police to find crimes being committed with these vehicles using traditional methods. As I have written previously, traffic stops prompted by minor violations are a point of contact at which cops often look for evidence of more serious crime. While there is some hope that a reduction in such stops may reduce racial bias in policing, it also highlights the need for law enforcement to reduce dependence on this method of tracking serious crime.

While the potential for criminal activity or even terrorism using automated vehicles is a real possibility, some experts are less concerned. Arthur Rizer, from the conservative think tank R Street Institute, argued that the lives saved by adoption of driverless technology will far outweigh any risk of criminal or terror threat from a hacking. Rizer calls the risk “minute compared to the lives that we will save just from reducing traffic accidents.”

If a significant portion of the roughly 40,000 traffic fatalities per year can be prevented by the adoption of automated vehicles, Rizer is likely correct that the benefits will outweigh any risk that vehicles will be hacked by bad actors. Nevertheless, there is a possibility that, as CalTech professor Patrick Lin warns, automated vehicles “may enable new crimes that we can’t even imagine today.” Going forward, it will be important for law enforcement to develop new techniques of tracking crime facilitated by automated vehicles.

All the way back in December, I wrote about how various companies, including Amazon (in partnership with Toyota), Postmates, Domino’s and Kroger were all working on using CAVs and drones to deliver goods to consumers. Since then there have been a number of news stories on similar projects across the globe, which deserve some attention, as you’ll see in this, the first of three posts:

On the Ground

In my December post I talked about Postmates’ testing of delivery robots that could bring products directly to your door. This winter similar ‘bots were deployed on the campuses of the University of the Pacific (sponsored by PepsiCo), and George Mason University (via start-up Starship Technologies and food-services giant Sodexo). College campuses, which tend to feature greater walkability and an always snack-craving populace, seem to be the perfect testing ground for such systems. And the robots seem to have made a difference in the eating habits, at least at George Mason – with an additional 1,500 breakfast orders being delivered via robot. This may be due to the fact the robots were integrated into the campus meal plan, meaning students weren’t just able to order snacks, but could order full meals and pay for them via their meal plan.  

While these delivery services may be seen as saviors to hung-over college students in need of a bacon, egg, and cheese sandwich, the expansion of such programs does raise issues. Just as ridesharing has changed the way cities have to manage curb space, delivery ‘bots raise questions of sidewalk management. Just how much of public space should we cede to commercial use? How will the ‘bots be programmed to “share the road” with pedestrians. Of course, that may not be as big of an issue in more sprawling American cites that don’t have the same density of foot traffic. They’ll also have to content with being messed with by humans, as was the case in this video, where a ‘bot’s cameras were intentionally covered in snow (there is a happy ending, as seen in the footage – after a good Samaritan cleaned off  the camera the ‘bot continues on its way, after saying “thank you!” to its’ human helper). In an attempt to get ahead of these issues San Francisco banned sidewalk delivery ‘bots in 2017, and has only slowly opened up room for testing. Will other cities follow suit? Or will they open the floodgates? Currently, the California DMV is considering new rules on delivery ‘bots and car-sized autonomous delivery vehicles, so look for a follow-up blog once those are out.

Given my continued interest in data collection and privacy, (an interest echoed in more recent blog posts by Kevin – available here, here, and here) I’d be remiss to not flag those issues here. (those issues also come up in the context of aerial deliveries, discussed in our next post). Not only would sidewalk based delivery ‘bots collect data on the items you order and when, they could potentially collect data about your home or its surrounding environment (think back to when Google was caught collecting wi-fi data with its’ Street View cars).

In our next post – aerial delivery drones!

Many have claimed that EU’s General Data Protection Regulation (GDPR) would “kill AI”. Shortly after its entry into force at the end of May 2018, the New York Times was already carrying industry concerns: “the new European data privacy legislation is so stringent that it could kill off data-driven online services and chill innovations like driverless cars, tech industry groups warn.” Following that train of thought, news outlets, general and specialized alike, have since then piled up on how such regulations on “data” would generally be harmful to innovation.

To be sure, other voices make themselves heard too. When trust in a technology is at stake, heralds of that technology understand that appearing to embrace regulation is a good PR move. Yet, beyond what could be seen as a cynical attitude, there are the pragmatists too. For them, regulation is a given, and with the right mindset, it can be transformed into an advantage.

This is such a mindset one could expect for European Union institutions. Speaking at a tech conference in Slovenia last April, EU Commissioner for Transport Violeta Bulc painted a rosy future for European transportation. Not only is Europe ready for automation, but it is embracing it. Already, car manufacturers must integrate certain automation components to all their new cars, such as lane assistance, distraction sensors and a black box used to “determine the cause of accidents.” And then not only cars, but ships, planes, trains, even drones are part of the EU’s vision for an integrated transportation system, as part of the “mobility as a service,” or MaaS vision. To support that MaaS (all-electric and paperless,) a “European GPS,” Galileo, and widespread 5G deployment, with even a priority on rural areas!

Is this all fluff? Far from seeking refuge from overbearing European red tape, most European AI and automation leaders see themselves in a “tortoise and the hare” paradigm: let the US innovators go fast and break things; we’ll take steady measured steps forward, but we’ll get there, and maybe even before the US. This is what a recent Bloomberg feature article on the booming European automation scene. Concretely, what are these steps? As far as AVs go, the first and main one is shared data sharing. Intense AV testing might be Arizona’s and California’s go-to model. But what is the use case for Waymo’s car beyond the dry, wide, and dunny streets of Phoenix? What about dense urban environments with narrow streets, like in Europe? Or snowy, low-density countryside roads, of which there are plenty in the US during the winter months? Safety in mass deployment will come from the capacity to aggregate everyone’s data, not just your own.

The most surprising part is that this push to open the “walled gardens” of the large OEMs does not even come from the government, but from tech firms. One of them, Austrian, is working an open AV operating system, with the intention to keep safety at the core of its business philosophy. As its founder told Bloomberg, “open to information sharing” is a requirement for safety. With such an angle, one is not surprised to read that the main challenge the company faces is the standardization of data flows; a tough challenge. But isn’t what innovation is about?

While the clever scientists won’t give the press all their tricks, many appear confident, stating simply that working with such regulations simply requires a “different approach.”

A couple weeks ago, I wrote a post outlining the fledgling legal efforts to address the increasingly urgent privacy concerns related to automated vehicles. While Europe’s General Data Privacy Regulation and California’s Consumer Privacy Act set a few standards to limit data sharing, the US as a whole has yet to seriously step into the field of data privacy. In the absence of national regulation in the United States, this post will look at an industry created standard. The auto industry standard is important not only for its present-day impact on how auto companies use our personal information, but also for the role it is likely to play in influencing any eventual Congressional legislation on the subject.

In 2014, two major industry trade associations – the Alliance of Automobile Manufacturers and the Association of Global Automakers collaborated to create a set of guiding principles for collection and management of consumer data. These twenty automakers, including the “Big Three” in the US and virtually every major auto company around the globe, created a list of seven privacy protection principles to abide by in the coming years.

In the list, two of the principles are somewhat well fleshed out: transparency and choice. On transparency, the automakers have pledged to provide “clear, meaningful information” about things like the types of information collected, why that information is collected, and who it is shared with. For certain types of information, primarily the collection of geolocation, biometric, or driver behavior information, the principles go one step further, requiring “clear, meaningful, and prominent notices.”  When it comes to choice, the industry says that simply choosing to use a vehicle constitutes consent for most types of data collection. Affirmative consent is sometimes required when geolocation, biometric or driver behavior data is shared, but that requirement contains several important exceptions that allow the automaker to share such data with their corporate partners.

The remaining five: respect for context; data minimization, de-identification and retention; data security; integrity and access, and; accountability may serve as important benchmarks going forward. For now, each of these five points contains no more than a handful of sentences pledging things like “reasonable measures.”

These industry-developed privacy protection principles are, for the most part, still pretty vague. The document describing all seven of them in-depth runs a mere 12 pages. In order for the standards to be truly meaningful, much more needs to be known about what constitutes reasonable measures, and in what sorts of situations geolocation, biometric, or driver behavior data can be shared. Furthermore, consumers should know whether the automaker’s corporate partners are bound by the same limits on data sharing to which the manufacturers have held themselves.

Without more detail, it is unclear whether these principles afford consumers any more protections than they would have otherwise had. They are important nonetheless for two reasons. They show that the industry at least recognizes some potential problems with unclear data-sharing rules, and they will likely play a key role in the development of any future legislation or federal regulation on the topic.

For the past several months, this blog has primarily focused on new legal questions that will be raised by connected and automated vehicles. This new transportation technology will undoubtedly raise novel concerns around tort liability, traffic stops, and city design. Along with raising novel problems, CAVs will also add new urgency to longstanding legal challenges. In some ways, this is best encapsulated in the field of privacy and data management.

In recent decades, the need to understand where our data goes has increased exponentially. The smartphones that most of us carry around every day are already capable of tracking our location, and recording a lot of our personal information. In addition to this computer/data generation machine in our pockets, the CAV will be a supercomputer on wheels, predicted to generate 4,000 gigabytes of data per day. Human driven vehicles with some automated features, such as Tesla’s with the company’s “Autopilot” functionality, already collect vast amounts of user data. Tesla’s website notes that the company may access a user’s browsing history, navigation history, and radio listening history, for example.

In response to this growing concern, California recently passed a sweeping new digital privacy law, set to take effect in 2020. Nicknamed “GDPR-Lite” after the European Union’s General Data Protection Regulation, California’s law “grants consumers the right to know what information companies are collecting about them, why they are collecting that data and with whom they are sharing it.” It also requires companies to delete data about a customer upon request, and mandates that companies provide the same quality and cost of service to users who opt out of data collection as those who opt in.

In comparison to the GDPR, California’s law is relatively limited in scope. The California Consumer Privacy Act (CCPA) is tailored to apply only to businesses that are relatively large or that are primarily engaged in the business of collecting and selling personal data. Furthermore, CCPA contains few limitations on what a business can do internally with data it collects. Instead, it focuses on the sale of that data to third parties.

In many ways, it remains too early to evaluate the effectiveness of California’s approach. This is in part because the law does not take effect until the beginning of next year. The bill also enables the California Attorney General to issue guidance and regulations fleshing out the requirements of the bill. These as-yet-unknown regulations will play a major role in how CCPA operates in practice.

Regardless of its uncertainties and potential shortcomings though, CCPA is likely to play a significant role in the future of American data privacy law and policy. It is the first significant privacy legislation in the US to respond to the recent tech boom, and it comes out of a state that is the world’s fifth largest economy. CCPA’s implementation will undoubtedly provide important lessons for both other states and the federal government as they consider the future of data privacy.

With roughly a clip a month – most of these being corporate fluff – Waymo’s YouTube channel is not the most exciting nor informative one. At least, those (like me) who keep looking for clues about Waymo’s whereabouts should not expect anything to come out of there.

That was until February 20th, when Waymo low-key published a 15 second clip of their car in action – the main screen showing a rendering of what the car “sees” and the corner thumbnail showing the view from the dash cam. The key point: Waymo’s car apparently crosses a broken-lights, police-controlled intersection without any hurdle. Amazing! Should we conclude that level 5 is at our very doorsteps?

The car and tech press was quick to spot this one, and reports were mostly praise. Yet Brad Templeton, in his piece for Forbes pinpoints at a few things that the clip does not say. First, we have the fact that Waymo operates in a geographically-enclosed area, where the streets, sidewalk and other hard infrastructure (lights, signs, and probably lines) are pre-mapped and already loaded in the algorithm. In other words, Waymo’s car does not discover stuff as it cruises along the streets of Northern California. Moreover, the street lights here do not work and so technically, this is just another four-way stop-signed intersection, with the difference that it is rather busy and there is a traffic police directing traffic in the middle. Finally, the car just goes straight, which is by far the easiest option (no left turn, for example…)

Beyond that, what Waymo alleges and wants us to see, is that car “recognizes” the policeman, or at the very least, recognizes that there is something person-shaped standing in the middle of the intersection and making certain gestures at the car, and that the car’s sensors and Waymo’s algorithms are now at the level of being able to understand hand signals of law enforcement officers.

Now I heard, less than a year ago, the CEO of a major player in the industry assert that such a thing was impossible – in reference to CAVs being able to detect and correctly interpret hand signals cyclists sometime use. It seems that a few months later, we’re there. Or are we? One issue which flew more or less under the radar, is how exactly does the car recognize the LEO here? Would a random passerby playing traffic cop have the same effect? If so, is that what we want?

As a member of the “Connected and Automated Vehicles: Preparing for a Mixed Fleet Future” Problem Solving Initiative class held at the University of Michigan Law School last semester, my team and I have had the opportunity to think about just that – how to make sure that road interactions stay as close as possible as they are today – and conversely how to foreclose awkward interactions or possible abuses that “new ways to communicate” would add. Should a simple hand motion be able to “command” a CAV? While such a question cuts across many domains, our perspective was a mostly legal one and our conclusion was that any new signal that CAV technology enables (from the perspective of pedestrians and other road users) should be non-mandatory and limited to enabling mutual understanding of intentions without affecting the behavior of the CAV. Now what we see in this video is the opposite; seemingly, the traffic police person is not equipped with special beacons that broadcast some form of “law enforcement” signal, and it is implied – although, unconfirmed – that there is no human intervention. We are left awed, maybe, but reassured? Maybe not.

The takeaway may be just this: the issues raised by this video are real ones, and are issues Waymo, and others, will at some point have to address publicly. Secrecy may be good for business, but only so much. Engagement by key industry players is of the highest importance, if we want to foster trust and avoid having the CAV technology crash land in our societies.

Earlier this month, the Journal of Law and Mobility hosted our first annual conference at the University of Michigan Law School. The event provided a great opportunity to convene some of the top minds working at the intersection of law and automated vehicles. What struck me most about the conference, put on by an organization dedicated to Law and mobility, was how few of the big questions related to automated vehicles are actually legal questions at this point in their development.

The afternoon panel on whether AVs should always follow the rules of the road as written was emblematic of this juxtaposition. The panel nominally focused on whether AVs should follow traffic laws. Should an automated vehicle be capable of running a red light, or swerving across a double yellow line while driving down the street? Should it always obey the posted speed limit?

The knee-jerk reaction of most people would probably be something along the lines of, “of course you shouldn’t program a car that can break the law.” After all, human drivers are supposed to follow the law. So why should an automated vehicle, which is programmed in advance by a human making a sober, conscious choice, be allowed to do any differently?

Once you scratch the surface though, the question becomes much more nuanced. Human drivers break the law in all kinds of minor ways in order to maintain safety, or in response to the circumstances of the moment. A human driver will run a red light if there is no cross-traffic and the car bearing down from behind is showing no signs of slowing down. A human will drive into the wrong lane or onto the shoulder to avoid a downed tree branch, or a child rushing out into the street. A human driver may speed away if they notice a car near them acting erratically. All of these actions, although they violate the law, may be taken in the interest of safety in the right circumstances. Even knowing they violated the law, a human driver who was ticketed in such a circumstance would feel their legal consequence was unjustified.

If automated vehicles should be able to break the law in at least some circumstances, the question shifts – which circumstances? Answering that question is beyond the scope of this post. At the moment, I don’t think anyone has the right answer. Instead, the point of this post is to highlight the type of moment-to-moment decisions every driver makes every day to keep themselves and those around them safe. The rules of the road provide a rough cut, codifying what will be best for most people most of the time. They could not possibly anticipate every situation and create a special legal rule for that situation. If they tried, the traffic laws would quickly grow to fill several libraries.

In my view, the question of whether an AV should be able to break the law is only tangentially a legal question. After arriving at an answer of, “probably sometimes,” the question quickly shifts to when, and in what circumstances, and whether the law needs to adapt to make different maneuvers legal. These questions have legal aspects to them, but they are also moral and ethical questions weighted with a full range of human driving experience.  Answering them will be among the most important and difficult challenges for the AV industry in the coming years.

The “Trolley Problem” has been buzzing around for a while now, so much that it became the subject of large empirical studies which aimed at finding a solution to it that be as close to “our values” as possible, as more casually the subject of an episode of The Good Place.

Could it be, however, that the trolley problem isn’t one? In a recent article, the EU Observer, an investigative not-for-profit outlet based in Brussels, slashed at the European Commission for its “tunnel vision” with regards to CAVs and how it seems to embrace the benefits of this technological and social change without an ounce of doubt or skepticism. While there are certainly things to be worried about when it comes to CAV deployment (see previous posts from this very blog by fellow bloggers here and here) the famed trolley might not be one of those.

The trolley problem seeks to illustrate one of the choices that a self-driving algorithm must – allegedly – make. Faced with a situation where the only alternative to kill is to kill, the trolley problem asks the question of who is to be killed: the young? The old? The pedestrian? The foreigner? Those who put forward the trolley problem usually do so in order to show that as humans, we are forced with morally untenable alternative when coding algorithms, like deciding who is to be saved in an unavoidable crash.

The trolley problem is not a problem, however, because it makes a number of assumptions – too many. The result is a hypothetical scenario which is simple, almost elegant, but mostly blatantly wrong. One such assumption is the rails. Not necessarily the physical ones, like those of actual trolleys, but the ones on which the whole problem is cast. CAVs are not on rails, in any sense of the word, and their algorithms will include the opportunity to go “off-rails” when needed – like get on the shoulder or on the sidewalk. The rules of the road incorporate a certain amount of flexibility already, and such flexibilities will be built in the algorithm.

Moreover, the very purpose of the constant sensor input processed by the driving algorithm is precisely to avoid putting the CAV in such a situation where the only options that remain are collision or collision.

But what if? What if a collision is truly unavoidable? Even then, it is highly misleading to portray CAV algorithm design as a job where one has to incorporate a piece of code specific to every single decision to be made in the course of driving. The CAV will never be faced with an input of the type we all-too-often present the trolley problem: go left and kill this old woman, go right and kill this baby. The driving algorithm will certainly not understand the situation as one where it would kill someone; it may understand that a collision is imminent and that multiple paths are closed. What would it do, then? Break, I guess, and steer to try to avoid a collision, like the rest of us would do.

Maybe what the trolley problem truly reveals is the idea that we are uneasy with automated cars causing accidents – that is, they being machines, we are much more comfortable with the idea that they will be perfect and will be coded so that no accident may ever happen. If, as a first milestone, CAVs are as safe as human drivers, that would certainly be a great scientific achievement. I do recognize however that it might not be enough for the public perception, but that speaks more of our relationship to machines than to any truth behind the murderous trolley. All in all, it is unfortunate that such a problem continues to keep brains busy while there are more tangible problems (such as what to do with all those batteries) which deserve research, media attention and political action.

The common story of automated vehicle safety is that by eliminating human error from the driving equation, cars will act more predictably, fewer crashes will occur, and lives will be saved. That future is still uncertain though. Questions still remain about whether CAVs will truly be safer drivers than humans in practice, and for whom they will be safer. In the remainder of this post, I will address this “for whom” question.

A recent study from Benjamin Wilson, Judy Hoffman, and Jamie Morgenstern at Georgia Tech found that state-of-the-art object detection systems – the type used in autonomous vehicles – demonstrate higher error rates in detection of darker-skinned pedestrians as compared to lighter-skinned pedestrians. Controlling for things like time-of-day or obstructed views, the technology was five percentage points less accurate at detecting people with darker skin-tones.

The Georgia Tech study is far from the first report of algorithmic bias. In 2015, Google found itself at the center of controversy when its algorithm for Google Photos incorrectly classified some black people as gorillas. More than two years later, Google’s temporary fix of removing the label “gorilla” from the program entirely was still in place. The company says they are working on a long-term fix to their facial recognition software. However, the continued presence of the temporary solution several years after the initial firestorm is some indication either of the difficulty of achieving a real solution or the lack of any serious coordinated response across the tech industry.

Algorithmic bias is a serious problem that must be tackled with a serious investment of resources across the industry. In the case of autonomous vehicles, the problem could be literally life and death. The potential for bias in automated systems begs for an answer to serious moral and legal questions. If a car is safer overall, but more likely to run over a black or brown pedestrian than a white one, should that car be allowed on the road? What is the safety baseline against which such a vehicle should be judged? Is the standard, “The AV should be just as likely (hopefully not very likely) to hit any given pedestrian?” Or is it “The AV should hit any given pedestrian less often than a human driven vehicle would?” Given our knowledge of algorithmic bias, should an automaker be opened up to more damages if their vehicle hits a black or brown pedestrian than when it hits a white pedestrian? Do tort law claims, like design defect or negligence, provide adequate incentive for automakers to address algorithmic bias in their systems? Or should the government set up a uniform system of regulation and testing around the detection of algorithmic bias in autonomous vehicles and other advanced, potentially dangerous technologies?

These are questions that I cannot answer today. But as the Georgia Tech study and the Google Photos scandal demonstrate, they are questions that the AV industry, government, and society as a whole will need to address in the coming years.