Safety

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

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 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.

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 labelled 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.

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.

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.

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!

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.

A write-up of the afternoon sessions is now available here!

March 15, 2019 – 10:00 AM – 5:30 PM

Room 1225, Jeffries Hall, University of Michigan Law School 

In the case of automated driving, how and to whom should the rules of the road apply? This deep-dive conference brings together experts from government, industry, civil society, and academia to answer these questions through focused and robust discussion.

To ensure that discussions are accessible to all participants, the day will begin with an introduction to the legal and technical aspects of automated driving. It will then continue with a more general discussion of what it means to follow the law. After a lunch keynote by Rep. Debbie Dingell, expert panels will consider how traffic law should apply to automated driving and the legal person (if any) who should be responsible for traffic law violations. The day will conclude with audience discussion and a reception for all attendees.

(Re)Writing the Rules of the Road is presented by the University of Michigan Law School’s Law and Mobility Program, and co-sponsored by the University of South Carolina School of Law.

Schedule of Events

Morning Sessions 

  • 10:00 am – 10:45 am

Connected and Automated Vehicles – A Technical and Legal Primer

Prof. Bryant Walker Smith

Professor Bryant Walker Smith will provide a technical and legal introduction to automated driving and connected driving with an emphasis on the key concepts, terms, and laws that will be foundational to the afternoon sessions. This session is intended for all participants, including those with complementary expertise and those who are new to automated driving. Questions are welcome. 

  • 10:45 am – 11:15 am
Drivers Licenses for Robots? State DMV Approaches to CAV Regulation

Bernard Soriano, Deputy Director for the Califorina DMV and James Fackler, Assistant Administrator for the Customer Services Administration in the Michigan Secretary of State’s Office, discuss their respective state’s approaches to regulating connected and autonomous vehicles.

  • 11:15 am – 12:00 pm
Just What Is the Law? How Does Legal Theory Apply to Automated Vehicles and Other Autonomous Technologies?

Prof. Scott Hershovitz    

Human drivers regularly violate the rules of the road. What does this say about the meaning of law? Professor Scott Hershovitz introduces legal theory and relates it to automated driving and autonomy more generally.                  

Keynote & Lunch

  • 12:00 pm – 12:30 pm
Lunch

Free for all registered attendees!

  • 12:30 pm-1:30 pm

Keynote – Rep. Debbie Dingell

Rep. Dingell shares her insights from both national and local perspectives.  

Afternoon Sessions

(Chatham House Rule)

  • 1:30 pm – 3:00 pm
Crossing the Double Yellow Line: Should Automated Vehicles Always Follow the Rules of the Road as Written?

Should automated vehicles be designed to strictly follow the rules of the road? How should these vehicles reconcile conflicts between those rules? Are there meaningful differences among exceeding the posted speed limit to keep up with the flow of traffic, crossing a double yellow line to give more room to a bicyclist, and driving through a stop sign at the direction of a police officer? If flexibility and discretion are appropriate, how can they be achieved in law?

A panel of experts will each briefly present their views on these questions, followed by open discussion with other speakers and questions from the audience.

Featured Speakers:

Justice David F. Viviano, Michigan Supreme Court

Emily Frascaroli, Counsel, Ford Motor Company

Jessica Uguccioni, Lead Lawyer, Automated Vehicles Review, Law Commission of England and Wales

  • 3:15 pm – 4:45 pm
Who Gets the Ticket? Who or What is the Legal Driver, and How Should Law Be Enforced Against Them?

Who or what should decide whether an automated vehicle should violate a traffic law? And who or what should be responsible for that violation? Are there meaningful differences among laws about driving behavior, laws about vehicle maintenance, and laws and post-crash responsibilities? How should these laws be enforced? What are the respective roles for local, state, and national authorities?

A panel of experts will each briefly present their views on these questions, followed by open discussion with other speakers and questions from the audience.

Featured Speakers:

Thomas J. Buiteweg, Partner, Hudson Cook, LLP

Kelsey Brunette Fiedler, Ideation Analyst in Mobility Domain

Karlyn D. Stanley, Senior Policy Analyst, RAND Corporation

Daniel Hinkle, State Affairs Counsel, American Association for Justice

  • 4:45 pm – 5:30 pm 
 Summary and General Discussion                                     

Participants and attendees close out the day by taking part in wide discussion of all of the day’s panels.

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.

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.

Cite as: Raphael Beauregard-Lacroix, (Re)Writing the Rules of The Road: Reflections from the Journal of Law and Mobility’s 2019 Conference, 2019 J. L. & Mob. 97.

On March 15th, 2019, the Journal of Law and Mobility, part of the University of Michigan’s Law and Mobility Program, presented its inaugural conference, entitled “(Re)Writing the Rules of The Road.” The conference was focused on issues surrounding the relationship between automated vehicles (“AVs”) and the law. In the afternoon, two panels of experts from academia, government, industry, and civil society were brought together to discuss how traffic laws should apply to automated driving and the legal person (if any) who should be responsible for traffic law violations. The afternoon’s events occurred under a modified version of the Chatham House Rule, to allow the participants to speak more freely. In the interest of allowing those who did not attend to still benefit from the day’s discussion, the following document was prepared. This document is a summary of the two panels, and an effort has been made to de-identify the speaker while retaining the information conveyed. 

Panel I: Crossing the Double Yellow Line: Should Automated Vehicles Always Follow the Rules of the Road as Written?

The first panel focused on whether automated vehicles should be designed to strictly follow the rules of the road. Questions included – How should these vehicles reconcile conflicts between those rules? Are there meaningful differences between acts such as exceeding the posted speed limit to keep up with the flow of traffic, crossing a double yellow line to give more room to a bicyclist, or driving through a stop sign at the direction of a police officer? If flexibility and discretion are appropriate, how can this be reflected in law? 

Within the panel, there was an overall agreement that we need both flexibility in making the law, and flexibility in the law itself among the participants. It was agreed that rigidity, both on the side of the technology as well as on the side of norms, would not serve AVs well. The debate was focused over just how much flexibility there should be and how this flexibility can be formulated in the law.

One type of flexibility that already exists is legal standards. One participant emphasized that the law is not the monolith it may seem from the outside – following a single rule, like not crossing a double yellow line, is not the end of an individual’s interaction with the law. There are a host of different laws applying to different situations, and many of these laws are formulated as standards – for example, the standard that a person operating a vehicle drives with “due care and attention.” Such an approach to the law may change the reasoning of a judge when it would come to determining liability for an accident involving an AV. 

When we ask if AVs should always follow the law, our intuitive reaction is of course they should. Yet, some reflection may allow one to conclude that such strict programming might not be realistic. After all, human drivers routinely break the law. Moreover, most of the participants explicitly agreed that as humans, we get to choose to break the law, sometimes in a reasonable way, and we get to benefit from the discretion of law enforcement. 

That, however, does not necessarily translate to the world of AVs, where engineers make decisions about code and where enforcement can be automatized to a high degree, both ex ante and ex post. Moreover, such flexibilities in the law needs to be tailored to the specific social need; speeding is a “freedom” we enjoy with our own, personal legacy cars, and this type of law breaking does not fulfill the same social function as a driver being allowed to get on the sidewalk in order to avoid an accident. 

One participant suggested that in order to reduce frustrating interactions with AVs, and to overall foster greater safety, AVs need the flexibility not to follow the letter of the law in some situations. Looking to the specific example of the shuttles running on the University of Michigan’s North Campus – those vehicles are very strict in their compliance with the law. 1 1. Susan Carney, Mcity Driverless Shuttle launches on U-M’s North Campus, The Michigan Engineer (June 4, 2018), https://news.engin.umich.edu/2018/06/mcity-driverless-shuttle-launches-on-u-ms-north-campus/. × They travel slowly, to the extent that their behavior can annoy human drivers. When similar shuttles from the French company Navya were deployed in Las Vegas, 2 2. Paul Comfort, U.S. cities building on Las Vegas’ success with autonomous buses, Axios (Sept. 14, 2018), https://www.axios.com/us-cities-building-on-las-vegas-success-with-autonomous-buses-ce6b3d43-c5a3-4b39-a47b-2abde77eec4c.html. × there was an accident on the very first run. 3 3. Sean O’Kane, Self-driving shuttle crashed in Las Vegas because manual controls were locked away, The Verge (July 11, 2019, 5:32 PM), https://www.theverge.com/2019/7/11/20690793/self-driving-shuttle-crash-las-vegas-manual-controls-locked-away. × A car backed into the shuttle, and when a normal driver would have gotten out of the way, the shuttle did not.

One answer is that we will know it when we see it; or that solutions will emerge out of usage. However, many industry players do not favor such a risk-taking strategy. Indeed, it was argued that smaller players in the AV industry would not be able to keep up if those with deeper pockets decide to go the risky way. 

Another approach to the question is to ask what kind of goals should we be applying to AVs? A strict abidance to legal rules or mitigating harm? Maximizing safety? There are indications of some form of international consensus 4 4. UN resolution paves way for mass use of driverless cars, UN News (Oct. 10, 2018), https://news.un.org/en/story/2018/10/1022812. × (namely in the form of a UN Resolution) 5 5. UN Economic Commission for Europe, Revised draft resolution on the deployment of highly and fully automated vehicles in road traffic (July, 12, 2018), https://www.unece.org/fileadmin/DAM/trans/doc/2018/wp1/ECE-TRANS-WP.1-2018-4-Rev_2e.pdf × that the goal should not be strict abidance to the law, and that other road users may commit errors, which would then put the AV into a situation of deciding between strict legality and safety or harm. 

In Singapore, the government recently published “Technical Reference 68,” 6 6. Joint Media Release, Land Transport Authority, Enterprise Singapore, Standards Development Organization, & Singapore Standards Council, Singapore Develops Provisional National Standards to Guide Development of Fully Autonomous Vehicles (Jan. 31, 2019), https://www.lta.gov.sg/apps/news/page.aspx?c=2&id=8ea02b69-4505-45ff-8dca-7b094a7954f9. × which sets up a hierarchy of rules, such as safety, traffic flow, and with the general principle of minimizing rule breaking. This example shows that principles can act as a sense-check. That being said, the technical question of how to “code” the flexibility of a standard into AV software was not entirely answered. 

Some participants also reminded the audience that human drivers do not have to “declare their intentions” before breaking the law, while AV software developers would have to. Should they be punished for that in advance? Moreover, non-compliance with the law – such as municipal ordinances on parking – is the daily routine for certain business models such as those who rely on delivery. Yet, there is no widespread condemnation of that, and most of us enjoy having consumer goods delivered at home.

More generally, as one participant asked, if a person can reasonably decide to break the law as a driver, does that mean the developer or programmer of AV software can decide to break the law in a similar way and face liability later? Perhaps the answer is to turn the question around – change the law to better reflect the driving environment so AVs don’t have to be programmed to break it. 

Beyond flexibility, participants discussed how having multiple motor vehicle codes – in effect one per US State – makes toeing the line of the law difficult. One participant highlighted that having the software of an AV validated by one state is big enough a hurdle, and that more than a handful of such validations processes would be completely unreasonable for an AV developer. Having a single standard was identified as a positive step, while some conceded that states also serve the useful purpose of “incubating” various legal formulations and strategies, allowing in due time the federal government to “pick” the best one. 

Panel II: Who Gets the Ticket? Who or What is the Legal Driver, and How Should Law Be Enforced Against Them?

The second panel looked at who or what should decide whether an automated vehicle should violate a traffic law, and who or what should be responsible for that violation. Further questions included – Are there meaningful differences among laws about driving behavior, laws about vehicle maintenance, and laws and post-crash responsibilities? How should these laws be enforced? What are the respective roles for local, state, and national authorities?

The participants discussed several initiatives, both public and private, that aimed at defining, or helping define the notion of driver in the context of AVs. The Uniform Law Commission worked on the “ADP”, or “automated driving provider”, which would replace the human driver as the entity responsible in case of an accident. The latest report from the RAND Corporation highlighted that the ownership model of AVs will be different, as whole fleets will be owned and maintained by OEMs (“original equipment manufacturers”) or other types of businesses and that most likely these fleet operators would be the drivers. 7 7. James M. Anderson, et. al., Rethinking Insurance and Liability in the Transformative Age of Autonomous Vehicles (2018), https://www.rand.org/content/dam/rand/pubs/conf_proceedings/CF300/CF383/RAND_CF383.pdf. ×

Insurance was also identified as a matter to take into consideration in the shaping up of the notion of AV driver. As of the date of the conference, AVs are only insured outside of state-sponsored guarantee funds, which aim to cover policy holders in case of bankruptcy of the insurer. Such “non-admitted” insurance means that most insurers will simply refuse to insure AVs. Who gets to be the driver in the end may have repercussions on whether AVs become insurable or not. 

In addition, certain participants stressed the importance of having legally recognizable persons bear the responsibility – the idea that “software” may be held liable was largely rejected by the audience. There should also be only one such person, not several, if one wants to make it manageable from the perspective of the states’ motor vehicle codes. In addition, from a more purposive perspective, one would want the person liable for the “conduct” of the car to be able to effectuate required changes so to minimize the liability, through technical improvements for example. That being said, such persons will only accept to shoulder liability if costs can be reasonably estimated. It was recognized by participants that humans tend to trust other humans more than machines or software, and are more likely to “forgive” humans for their mistakes, or trust persons who, objectively speaking, should not be trusted.

Another way forward identified by participants is product liability law, whereby AVs would be understood as a consumer good like any other. The question then becomes one of apportionment of liability, which may be rather complex, as the experience of the Navya shuttle crash in Las Vegas has shown. 

Conclusion

The key takeaway from the two panels is that AV technology now stands at a crossroads, with key decisions being taken as we discuss by large industry players, national governments and industry bodies. As these decisions will have an impact down the road, all participants and panelists agreed that the “go fast and break things” approach will not lead to optimal outcomes. Specifically, one line of force that comes out from the two panels is the idea that it is humans who stand behind the technology, humans who take the key decisions, and also humans who will accept or reject commercially-deployed AVs, as passengers and road users. As humans, we live our daily lives, which for most of us include using roads under various capacities, in a densely codified environment. However, this code, unlike computer code, is in part unwritten, flexible and subject to contextualization. Moreover, we sometimes forgive each others’ mistakes. We often think of the technical challenges of AVs in terms of sensors, cameras and machine learning. Yet, the greatest technical challenge of all may be to express all the flexibility of our social and legal rules into unforgivably rigid programming language. 

“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.

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.

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.

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.

Cite as: Kyle D. Logue, The Deterrence Case for Comprehensive Automaker Enterprise Liability, 2019 J. L. & Mob. 1.

I.         Introduction

Automobiles are much safer today than they used to be. Perhaps the best illustration of this fact is the decades’ long decline in the number of auto-related deaths per-mile-driven. 8 8. General Statistics: Fatality Facts, INS. INST. FOR HIGHWAY SAFETY: HIGHWAY LOSS DATA INST., https://www.iihs.org/iihs/topics/t/general-statistics/fatalityfacts/over view-of-fatality-facts (last visited Nov. 13, 2018) (showing motor vehicle crash deaths per 100 million miles driven has declined from 3.35 in 1976 to 1.18 in 2016). × And yet motor vehicles—including cars, trucks, and SUVs— continue to be among the most dangerous products sold anywhere. Automobiles pose a larger risk of accidental death than any other product, except perhaps for opioids. 9 9. In 2016, which is the most recent year for which the Centers for Disease Control has final data as of the time of this writing, there were 58,335 deaths attributable to accidental poisoning, which includes accidental deaths from drug overdose (which, of course, includes accidental opioid overdose). JIAQUAN XU ET AL., CTRS. FOR DISEASE CONTROL & PREVENTION, NATIONAL VITAL STATISTICS REPORTS 34 (vol. 67, no. 5 July 26, 2018) [henceforth, CDC, 2016 Final Death data]. The CDC estimates that roughly 42,000 deaths in 2016 were attributable to opioids, the vast majority of which would presumably be considered accidental deaths. Drug Overdose Death Data, CTRS. FOR DISEASE CONTROL & PREVENTION, https://www.cdc.gov/drugoverdose/data/statedeaths .html (last visited Nov. 13, 2018). Note also that firearms are involved in more deaths per year than motor vehicles, but the vast majority of those deaths are caused intentionally, either suicide (22,938 deaths in 2016) or homicide (14,415). The other leading causes of accidental deaths that year included the following: falls (34,673), firearms (495), and drowning (3,786). CDC, 2016 Final Death data, at 50. × Annual auto-crash deaths in the United States have never fallen below 30,000, reaching a recent peak of roughly 40,000 in 2016. 10 10. For 2016, there were 40,327 motor-vehicle-related accidental deaths. CDC, 2016 Final Death data, at 52. × In addition to these tens of thousands (internationally, millions 11 11. Internationally, the number of annual fatalities attributable to motor vehicle accidents is in the millions. Number of Road Traffic Deaths, WORLD HEALTH ORG., http://www.who.int/gho/road_safety/mortality/number_text/en/ (last visited Nov. 13, 2018) (estimating worldwide auto accident deaths in 2013 to be roughly 1.25 million). × ) of deaths attributable to motor-vehicle crashes, there are many other social costs. Victims of serious auto accidents, for example, often incur extraordinary medical expenses both to provide treatment immediately after the accident and, sometimes, to provide treatment for the rest of their lives. 12 12. LAWRENCE BLINCOE ET AL., NAT’L HIGHWAY TRAFFIC SAFETY ADMIN., THE ECONOMIC AND SOCIETAL IMPACT OF MOTOR VEHICLE CRASHES, 2010 (REVISED) 5 (May 2015) (finding medical costs responsible for $23.4 billion of the total economic cost of motor vehicle crashes in 2010). × Those crash victims whose injuries render them unable to work can experience weeks, months, even years of lost income, which, from their employers’ perspective, is lost productivity. 13 13. Id. (finding $77.4 billion in lost productivity as a result of motor vehicle crashes in 2010). × Auto accidents also cause non-trivial amounts of property damage, mostly to the automobiles themselves though also occasionally to highways, bridges, or other elements of transportation infrastructure. Finally, serious motor vehicle accidents often cause severe noneconomic injuries—that is, severe “pain and suffering”—as a result of accident victims’ painful and debilitating physical injuries. According to some estimates, such noneconomic harms, in the aggregate, amount to more than twice the magnitude of the aggregate economic damages caused by auto accidents. 14 14. DANIEL SMITH, NAT’L HIGHWAY TRAFFIC SAFETY ADMIN., OVERVIEW OF NHTSA PRIORITY PLAN FOR VEHICLE SAFETY AND FUEL ECONOMY, 2015 TO 2017 at 2 (June 2015) (“In addition to the terrible personal toll, these crashes have a huge economic impact on our society with an estimated annual cost of $242 billion, which is an average of $784 for every person in the United States. These crashes also result in $594 billion in societal harm from loss of life and the pain and decreased quality of life due to injuries.”). ×

All of this may be about to change. According to many auto-industry experts, the eventual transition to driverless vehicles will drastically lower the economic and noneconomic costs of auto accidents. 15 15. See, e.g., Adrienne LaFrance, Self-Driving Cars Could Save 300,000 Lives Per Decade in America, THE ATLANTIC (Sept. 29, 2015), https://www.theatlantic.com/ technology/archive/2015/09/self-driving-cars-could-save-300000-lives-per-decade-in-america/407956/ (“Researchers estimate that driverless cars could, by midcentury, reduce traffic fatalities by up to 90 percent.”). × Why might this be so? Because humans are so bad at driving. When it comes to operating motor vehicles, people have bad judgment, slow reflexes, inadequate skills, and short attention spans. They drive too fast. They drive while intoxicated. They drive while sleepy. They drive while distracted. In fact, according to the National Highway Traffic Safety Administration, roughly 94 percent of auto accidents today are attributable to “driver error.” 16 16. NAT’L HIGHWAY TRAFFIC SAFETY ADMIN., CRITICAL REASONS FOR CRASHES INVESTIGATED IN THE NATIONAL MOTOR VEHICLE CRASH CAUSATION SURVEY 2 (Mar. 2018), https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812506. Another 2 percent of accidents are attributable to vehicle component failure, 2 percent to environmental conditions (such as slick roads), and 2 percent to “unknown.” Id. What precisely these statistics mean, however, is not entirely clear. Specifically, it is not obvious how NHTSA’s statistical categories (such as “vehicle component failure”) would relate to analogous legal concepts (such as “defective product”). × Computers can do better. At least that is the hope: that machine-learning computer algorithms, in combination with state-of-the-art sensors and advanced robotics, will be better—much better—drivers than humans are. 17 17. For an extended argument for why driverless cars are better drivers than humans, see, e.g., HOD LIPSON & MELBA KURMAN, DRIVERLESS: INTELLIGENT CARS AND THE ROAD AHEAD (MIT Press 2016). × Whether this will in fact be true is still unproven, but is most likely to be true with respect to so-called fully driverless “Level 5” vehicles, 18 18. See infra note 12. Level 5 vehicles are also sometimes called autonomous vehicles, though that use of the term ignores the distinction between connected vehicles and truly autonomous vehicles. This Article will larger ignore that distinction as well. × which are those autonomous or connected vehicles that are capable of operating on any road and under any conditions that a human driver can handle but with no input from a human passenger other than the choice of destination. 19 19. It is these Level 5 vehicles that hold the real promise for substantial accident-risk reduction. SAE INTERNATIONAL, TAXONOMY AND DEFINITIONS FOR TERMS RELATED TO DRIVING AUTOMATION SYSTEMS FOR ON-ROAD MOTOR VEHICLES J3016 (2018), https://saemobilus.sae.org/content/j3016_201806 (explaining levels 0, no autonomous features, through level 5, where a computer is “operating the vehicle on-road anywhere that a typically skilled human driver can reasonably operate a conventional vehicle”). This is in large part because Level 5 vehicles do not have the “handoff problem,” which occurs at that moment (with levels 1 through 4) when control of the vehicle must be transferred from the algorithm to the human driver. Alex Davies, The Very Human Problem Blocking the Path to Self-Driving Cars, WIRED (Jan. 1, 2017), https://www.wired.com/2017/01/human-problem-blocking-path-self-driving-cars/ (discussing how existence of handoff problem led Google, in 2012, and other companies more recently, to commit to developing level 5 autonomy). × Level 5 vehicles, because they would not suffer from the problems that plague human decision making in the driving context, do hold the promise to be substantially safer than the fully or even partially human-driven alternative. 20 20. One can certainly imagine the possibility of driving algorithms going haywire or sensors failing in ways that cause terrible accidents. But presumably, regulators will not permit Level 5s to be sold until they prove themselves in large numbers of test miles to be substantially safer than human drivers. Some commentators have suggested that regulators not approve Level 5s unless and until they are shown to be twice as safe as human drivers. Mark A. Geistfeld, A Roadmap for Autonomous Vehicles: State Tort Liability, Automobile Insurance, and Federal Safety Regulation, 105 CALIF. L. REV. 1611, 1653 (2017). ×

As promising as a world of highways filled with computer-driven vehicles might be, from an accident-reduction perspective, 21 21. If the advent of autonomous and connected vehicles means more vehicles on the road, it could be bad news for efforts to combat climate change and improve air quality. × such a high-tech world is still only a possibility. And even if it happens, it will not be for a number of years. There continue to be major technological hurdles, as well as potential consumer resistance to actually riding in a driverless vehicle. 22 22. American Drivers Grow More Afraid of Driverless Vehicles, INS. J. (May 22, 2018), https://www.insurancejournal.com/news/national/2018/05/22/490014.htm (noting that 73% of American drivers report being too afraid to ride in a fully automated vehicle). × Therefore, the introduction, spread, and eventual dominance of Level 5s will take some time. 23 23. Many experts think consumers will not even be able to purchase fully autonomous vehicles for another decade. Justin Gerdes, Not So Fast. Fully Autonomous Vehicles are More than a Decade Away, Experts Say, GREEN TECH MEDIA (Feb. 6, 2018), https://www.greentechmedia.com/articles/read/fully-autonomous-vehicles-decade-away-experts (reporting results of informal poll of 300 industry experts). × During that transition, most automobiles will continue to be driven mostly by humans. Indeed, even in the long run, when Level 5 vehicles have been perfected and are available to the general public either through individual purchases and leases or through some ride-sharing arrangement (via Uber or Lyft or some similar web-based platform), we should still expect to see a substantial number of fully or partially human-driven vehicles traveling alongside them. 24 24. See, e.g., Background On: Self-Driving Cars and Insurance, INS. INFO. INST. (July 30, 2018), https://www.iii.org/article/background-on-self-driving-cars-and-insurance (“According to the Insurance Institute for Highway Safety, it is anticipated that there will be 3.5 million self-driving vehicles on U.S. roads by 2025, and 4.5 million by 2030. However, the institute cautioned that these vehicles would not be fully autonomous, but would operate autonomously under certain conditions.”). ×

If I am right about this picture of the automotive future, what should the role of auto tort law be, now and going forward? More specifically, if we conceive of auto tort law—including both automaker product liability and driver negligence liability (and the insurance that covers both types of liability)—as a system of ex post auto-crash deterrence, what would the optimal or efficient auto tort/insurance regime look like? 25 25. For this Article, I assume that the primary role of auto tort law is efficient deterrence. That means, creating incentives that induce all relevant parties—drivers, automakers, even pedestrians—to take efficient or cost-justified steps to minimize the probability and severity of accidents. On this view, the goal is not necessarily zero accidents, because the cost of accident avoidance eventually renders additional investments in accident prevention inefficient and socially undesirable. This is a standard type of normative analysis of accident law. It is, of course, not the only way to evaluate an accident law regime. For example, if the primary function of auto tort law were instead merely compensation for the harms caused by auto accidents, or were to achieve corrective justice (in the sense of reversing wrongfully caused harms), some system other than the one proposed in this Article might make more sense. × Further, how should such an optimally designed auto tort/insurance regime take into account the emergence of Level 5 vehicles?

These questions are the subject of this Article. Specifically, this Article lays out the potential (at this point purely theoretical) deterrence benefits of replacing our current auto tort regime (including auto products liability law, driver-based negligence claims, and auto no-fault regimes) with a single, comprehensive automaker enterprise liability system. 26 26. The term “enterprise liability” has long been used to stand for the idea that “business enterprises ought to be responsible for losses resulting from products they introduce into society.” George L. Priest, The Invention of Enterprise Liability: A Political History of The Intellectual Foundations of Modern Tort Law, 14 J. LEGAL STUD. 461, 463 (1985) (describing intellectual history of enterprise liability idea). See also Gregory C. Keating, The Theory of Enterprise Liability and Common Law Strict Liability, 54 VAND. L. REV. 1285, 1287 (2001) (“[E]nterprise liability expresses the maxim that those who profit from the imposition of risk should bear the costs of the accidents that are a price of their profits.”). The concept of enterprise liability was much discussed in the 1980s and 1990s among tort scholars. See, e.g., Priest, supra; James A. Henderson Jr. The Boundary Problems of Enterprise Liability, 41 MD L. REV. 659 (1982) (discussing line-drawing issues that arise in connection with adopting enterprise liability regimes); and Kenneth S. Abraham & Paul C. Weiler, Enterprise Medical Liability and the Evolution of the American Health Care System, 108 HARV. L. REV. 381 (1994) (applying enterprise liability concepts to medical system). I, together with my colleagues and friends Jon Hanson and Steve Croley, started writing about enterprise liability around this time. See, e.g., Jon D. Hanson & Kyle D. Logue, The First-Party Insurance Externality: An Economic Justification for Enterprise Liability, 76 CORNELL L. REV. 129 (1990); and Steven P. Croley & Jon D. Hanson, Rescuing the Revolution: The Revived Case for Enterprise Liability, 91 MICH. L. REV. 683 (1993). × This new regime would apply not only to Level 5 vehicles, but to all automobiles made and sold to be driven on public roads. 27 27. For a more recent proposal to create a special auto-manufacturer responsibility regime, which has similarities to the one I am describing here, but that—critically—would be limited to accidents involving fully automated vehicles, see 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. (forthcoming 2019). × Because such a system would make automakers unconditionally responsible for the economic losses resulting from any crashes of their vehicles, it would in effect make automakers into auto insurers as well, although such a change will likely lead to some restructuring in how automobiles are insured and sold. Or so I will argue.

My basic argument is that a comprehensive automaker enterprise liability regime may have previously unexplored, or at least forgotten, deterrence benefits. 28 28. In an article published in 1985, Professor Howard Latin outlined an automaker enterprise liability proposal similar to the one I am describing in this Article. Howard A. Latin, Problem-Solving Behavior and Theories of Tort Liability, 73 CAL. L. REV. 677 (1985). That article, brought to my attention by Professor Stephen Sugarman, also makes a deterrence case for adopting an automaker enterprise liability regime, emphasizing some (though not all) of the same arguments I make here. See also Bryant Walker Smith, Regulation and the Risk of Inaction, in AUTONOMOUS DRIVING 584 (Markus Maurer, et al. eds., 2016), https://link.springer.com/chapter/10.1007/978-3-662-48847-8_27 (exploring (very briefly) the idea of using auto enterprise liability as a means of encouraging automotive safety innovation). × First, it could greatly simplify our existing auto tort regime by replacing all of automaker liability law (including product design defect claims) and driver liability law (as well as existing no-fault regime) with a single enterprise liability regime under which all auto-accident victims could seek recovery. Second, it could encourage automakers to design and manufacturer safer vehicles, whether that means safer human-driven vehicles (with automated features) or Level 5 vehicles. Third, it could incentivize automakers to provide better warnings and instructions with their vehicles, including better ways to deal with the “hand off” problem that occurs when vehicles switch from semi-self-driving mode to human-driven mode. 29 29. Steven Ashley, Level 3 “Hand Off” is Challenging AI Researchers, SAE INT’L (Jan. 17, 2017), https://www.sae.org/news/2017/01/sae-level-3-hand-off-is-challenging-ai-researchers. × Fourth, enterprise liability could result in automobile prices that better reflect the actual costs of driving, leading to more optimal levels of auto sales and miles driven. Fifth, enterprise liability could induce auto companies to coordinate (in a way they are not presently coordinating) with the one industry that has more information than the auto companies have about how the specific driving patterns of individual human drivers affect the risk of auto accidents: namely, the auto insurance industry. Finally, a comprehensive automaker enterprise liability regime would provide an implicit subsidy for the development and deployment of driverless technology, but only to the extent that automakers actually expect such technology to reduce accident costs. All of these points will be developed below.

The argument will proceed as follows. Part II evaluates existing auto tort law—including automaker liability law and driver liability law—from the perspective of optimal deterrence. Part III outlines one plausible version of a comprehensive automaker enterprise liability regime and summarizes the primary deterrence advantages of such a regime. Part IV briefly concludes with a discussion of caveats, concerns, and a list of questions for future research.

II.         Evaluating the Deterrence Implications of Current Auto Tort Law

Automaker Liability Law

To understand the deterrence benefits of an auto enterprise liability regime, it is necessary first to understand the deterrence consequences of the current auto tort regime. To that end, this Part describes the current auto tort system—both automaker liability law and driver liability law—and, drawing on well-known insights from deterrence theory and economic analysis of liability rules, explores what the general deterrence consequences of that regime might be. This is an entirely theoretical discussion. The ultimate question—which auto tort regime comes closes to minimizing the costs of auto accidents—can of course only be answered with empirical research that is beyond the scope of this short paper.

Current automaker liability law, like manufacturer liability law generally, is primarily a negligence-based regime, by which I mean the following: Under current law in most U.S. jurisdictions, individuals who suffer harm caused in an automobile crash can recover from the automaker in tort if they can prove that the harm resulted from negligence (or a lack of reasonable care) on the part of the automaker in designing or constructing the vehicle. 30 30. See, e.g., Larsen v. GM, 391 F.2d 495, 504 (1968) (holding, among other things, that auto manufacturers have a duty to use reasonable care in design and construction of vehicles). × Alternatively, auto accident victims can invoke modern products liability doctrine and argue that a “defect” in the vehicle’s design, manufacturing process, or warnings caused the harm. 31 31. RESTATEMENT (THIRD) TORTS: PROD. LIAB. §§1 & 2 (AM. LAW INST. 1998) (setting forth general rules for liability resulting from product defects). × This latter approach also typically requires some showing of automaker negligence. This is because, in the bulk of U.S. jurisdictions, important aspects of the product defect law are equivalent to negligence law. 32 32. A majority of jurisdictions apply a risk-utility version of the design defect test, which is similar to the common cost-benefit formulations of negligence. RESTATEMENT (THIRD) TORTS: PROD. LIAB., §2, cmt. D (AM. LAW. INST. 1998). Moreover, the adequacy of product warnings is often evaluated according to a negligence-based reasonableness test. RESTATEMENT (THIRD) TORTS: LIABILITY FOR PHYSICAL AND EMOTIONAL HARM, § 3 (AM. LAW. INST. 1998). Also, in the jurisdictions that define design defect according to “reasonable consumer expectations,” there is an obvious reliance on negligence-based principles as well, such as the concept of reasonableness. Current products liability law with respect to warnings is also essentially a negligence-based regime. RESTATEMENT (THIRD) TORTS: PROD. LIAB., §2, cmt. I (AM. LAW. INST. 1998). (“Commercial product sellers must provide reasonable instructions and warnings about risks of injury posed by products.”). × For this reason, auto products-liability, despite sometimes being labeled a form of “strict liability,” 33 33. For an example of lawyers characterizing auto products liability generally, including design defect and warning defect claims, as a form of “strict liability,” see, e.g., DEREK H. SWANSON & LIN WEI, MCGUIREWOODS, UNITED STATES AUTOMOTIVE PRODUCTS LIABILITY LAW 7 (2009), https://www.mcguirewoods.com/news-resources/publications/us-automotive-products-liability.pdf. × is in fact largely a form of negligence liability. 34 34. I am of course not the first person to observe that modern “strict” products liability operates in practice largely as a negligence regime. See, e.g., DAVID G. OWEN, PRODUCTS LIABILITY LAW 38 (3rd ed. 2015) (“These two propositions—that manufacturers must guard against risks only if they are foreseeable, and that manufacturers must guard against those risks only with precautions that are reasonable—are the two major pillars of modern products liability law in America.”). This is not to say that there are no aspects of strict liability in the current auto products liability system. For example, manufacturing defect cases approximate true strict liability. That is, when the product’s design satisfies the risk-utility standard (or is, in a sense, reasonable or non-negligent) but the particular product that caused the harm in the case did so as a result of some sort of malfunction in the vehicle that is not a result of negligent maintenance on the part of the vehicle owner (e.g., the brakes or the steering mechanism simply fails), the automaker is strictly liable. With respect to Level 5 vehicles, presumably a much higher percentage of the accidents would be a result of vehicular malfunction than is the case with human-drive vehicles; thus, there would be a much larger domain of true strict liability if existing product liability doctrine were applied to Level 5 accidents than is currently the case with automaker liability cases. Further, in design defect jurisdictions that apply a consumer expectations test, strict liability also seems likely, assuming courts conclude that consumers reasonably expect Level 5s not to crash. Still, there would be some negligence-based liability with respect to the design of the vehicles and the algorithm that drives them. See, e.g., Bryant Walker Smith, Automated Driving and Product Liability, 2017 MICH. ST. L. REV. 1 (2017) (noting that, applying existing law, automaker liability for Level 5 accidents will likely turn on some version of “unreasonable performance” by the vehicle, which sometimes will approximate strict liability and sometimes negligence); and Mark A. Geistfeld, A Roadmap for Autonomous Vehicles: State Tort Liability, Automobile Insurance, and Federal Safety Regulation, 105 CAL. L. REV. (forthcoming 2018) (observing that applying existing products liability law to Level 5s will sometimes result in strict liability and sometimes negligence-based liability). ×

A negligence-based automaker liability regime can in theory have certain deterrence advantages, if one makes particular assumptions. Those assumptions, however, are keys to the analysis—and do not always apply. For starters, a negligence-based automaker liability regime can create efficient incentives with respect to automaker care levels. Automaker “care levels” are the precautions taken by automakers—in the design, production, and warnings with respect to their vehicles—that reduce the probability or severity of auto accidents. 35 35. See generally STEVEN SHAVELL, ECONOMIC ANALYSIS OF ACCIDENT LAW 73–85 (1987) (comparing theoretical deterrence benefits of negligence liability rule and strict liability rule, in terms of care levels and activity levels); WILLIAM M. LANDES & RICHARD A. POSNER, THE ECONOMIC STRUCTURE OF TORT LAW 54–84 (1987) (same); and A. MITCHELL POLINSKY, AN INTRODUCTION TO LAW AND ECONOMICS 113–123 (3rd ed. 2003) (discussing choice of optimal products liability rules in particular). × Efficient automaker care levels occur when the automaker has made all available investments in care—in crash-risk reduction—that reduce expected auto-accident costs by more than the marginal costs of the additional care. 36 36. Put differently, when an automaker is investing efficiently in care, there are no additional investments in accident reduction that could be made that would reduce expected accident costs by more than the costs of accident avoidance. × Thus, an efficient negligence-based tort liability rule would hold an automaker liable for the harms resulting from a given auto accident only if that automaker failed to take efficient care. For example, if there was an alternative automotive design or alternative warning that the automaker could have used that would have reduced expected accident costs by more than the marginal costs of that design or warning change, failing to deploy that alternative design or warning in their vehicles would constitute negligence on the part of the automaker, and would therefore be potential grounds for tort liability. 37 37. The plaintiff must also demonstrate causation. ×

This sort of efficient negligence-based liability rule would induce automakers to take efficient care if we assume the following to be true: (a) that automakers are aware of the law and respond rationally to it, and (b) that courts applying a negligence-based automaker liability rules perform a thorough and accurate cost-benefit analysis (for example, judges and juries do not tend to make systematic errors in their determinations regarding what constitutes automaker negligence or what counts as a design defect). Under those assumptions, the negligence-based regime would incentivize efficient automaker care levels. Why? Because automakers would under those assumptions realize that they can avoid negligence-based liability entirely if they merely make all cost-justified investments in auto safety (e.g., all cost-justified design and warning changes). Knowing this, they would have a strong legal and financial incentives to do just that. 38 38. This insight is simply an application of a standard conclusion regarding the effects on injurer care levels of a perfectly applied negligence rule. See generally supra sources cited in note 28. ×

In addition, a negligence-based automaker liability regime can also create incentives for efficient driver care-levels—incentives for drivers to drive reasonably carefully—even in the absence of a defense of contributory negligence or comparative fault. 39 39. See generally supra sources cited in note 28. × This is because a negligence-based regime, by its nature, leaves accident costs on victims and their insurers when the automaker is not negligent. That fact will induce drivers to drive carefully, so as to minimize their own risk of uncompensated accident losses. Again, however, this conclusion holds only if certain key assumptions are also true. Specifically, we must assume the following: a) that drivers, like automakers, are knowledgeable about tort law and respond rationally to the potential of tort rules to apply to their future conduct; and b) that drivers actually bear these costs and do not externalize them to someone else.

To put all of this together, according to standard deterrence theory, an efficiently and accurately applied negligence-based automaker liability rule can produce efficient incentives for both automakers and drivers to take care to avoid auto accidents. 40 40. See generally supra sources cited in note 28. This conclusion also assumes that automakers are well informed about and respond rationally to tort liability rules. ×

But there are obvious problems with this rosy picture. First, consider the effects on automaker care levels if we relax the assumption that courts accurately apply negligence-based standards. If judges and juries are not very good at doing the complex and information-intensive analysis necessary to determine what particular automotive designs, warnings, or instructions are cost-justified or reasonable (or not defective), the outcomes of courts’ negligence determinations become highly uncertain. This can in turn produce incentives for automakers both to over-invest and to under-invest in auto safety. 41 41. See generally Mark Grady, A New Positive Economic Theory of Negligence, 92 Yale L.J. 799 (1983); and John Calfee & Richard Craswell, Some Effects of Uncertainty on Compliance with Legal Standards, 70 Va. L. Rev. 965, 982 (1984). ×

The incentive to over-invest in auto safety can arise when manufacturers expect courts to set the standard of reasonable care (or a non-defective design) inefficiently high—that is, when manufacturers expect that courts may find a design defect notwithstanding the fact that the automaker’s design decisions were consistent with an accurate, objective, comprehensive risk-utility test. If that is the expectation, then automakers would have an incentive to satisfy the inefficiently high court- or jury-imposed design standard (or warning standard) in order to avoid liability. The incentive to under-invest in safety can arise if courts rely too much on custom within the industry as their source for what constitutes reasonable care, or a non-defective design or warning. This is because industry custom can (famously) lag behind what is truly efficient levels of safety. 42 42. The T.J. Hooper, 60 F.2d 737 (2d Cir. 1937) (“a whole calling may have unduly lagged in the adoption of new and available devices”). In product liability design defect cases, of course, courts do not generally permit compliance with industry custom to be totally exculpatory; however, it can be considered relevant to the risk-utility negligence-based balancing test. See, e.g., Carter v. Massey-Ferguson, Inc., 716 F.2d 344 (5th Cir. 1983). However, if a defendant in a negligence-based product liability regime has adopted a design that is the safest in use at the time of manufacturing, it may be difficult for the plaintiff to prevail. See RESTATEMENT (THIRD) TORTS: PROD. LIAB., §2, cmt. D (AM. LAW. INST. 1998). × It is not a surprise, then, that commentators have argued that custom-based standards of care, like those that currently apply to automaker liability, can inhibit innovation. 43 43. See, e.g., Gideon Parchomovsky & Alex Stein, Tort and Innovation, 107 Mich. L. Rev. 285 (2008). ×

A second problem with a negligence-based auto products liability regime has to do with driver care levels. For a negligence-based regime to efficiently incentivize drivers to drive carefully (by imposing on drivers the risk of accidents that are not cost-justifiably preventable by the manufacturer), recall that we assumed that drivers are well informed of both accident risks and how those risks are allocated according to the specific rules of auto tort law. Those assumptions are obviously unrealistic. Drivers simply are not aware of the tort law rules that apply to them or the product liability rules that apply to automakers. Moreover, even when drivers do know about accident risks and legal rules, there are reasons to believe (discussed below) 44 44. See infra, discussion at notes 44–48 and 51. × either that drivers will not respond rationally to that information or that they will externalize those risks to insurance companies. If I am right about that—about drivers’ lack of information about driving risk and auto tort law, and about their cognitive biases and cost-externalization—then the ability of a negligence-based auto products liability regime to optimize driver care levels is substantially undermined. Legally imposing costs on drivers would not, or at least may not, have the desired deterrence effect on driver care levels. 45 45. By contrast, the assumption that automobile manufacturers—with their teams of expert engineers, lawyers, and accountants—are fully informed of the torts liability regime in which they operate and how those rules are likely to affect them. This claim—that auto manufacturers are likely to be better informed (both about the risks of auto accidents and about the relevant liability rules) and more classically rational in their decision-making than drivers—is not new. See, e.g., Latin, supra note 21, at 692–93 (arguing that, because drivers are much less likely to know about and respond rationally to having auto-accident losses imposed on them than auto manufacturers are, a regime of auto-manufacturer enterprise liability could produce an overall improvement in social welfare, through a reduction in overall auto accidents). ×

The final deterrence problem with a negligence-based auto products liability regime would exist even if judges and juries were good (accurate and unbiased) at applying risk-utility or cost-benefit standards. In fact, this problem results because automakers would expect accurate application of the negligence-based rules. The problem involves the effect of a negligence-based automaker liability rule on the number of vehicles sold, or, in the language of deterrence, the effect on automaker “activity levels.” 46 46. See supra sources cited in note 28. × Even an efficiently safe car (one with no defects whatsoever) that is driven carefully by its human or algorithmic driver poses some residual or irreducible risk of crashing. This residual risk will have a tendency to be ignored or externalized by automakers under a negligence-based product liability regime because automakers can virtually insulate themselves against liability by merely complying with the liability standard. 47 47. See supra sources cited in note 28. Of course, this automaker activity level effect is mitigated to some extent when automakers except to be held liable by courts despite having taken reasonable care. These effects are unlikely, however, to be perfectly offsetting. × The result of this externality is that the scale of operation in the auto industry—the number of cars sold—may be higher than the social-welfare maximizing level, even ignoring the effect of automobile emissions on the environment, because the price of vehicles does not include this cost of unpreventable auto accidents.

To summarize, given how our current negligence-based automaker liability regime is applied in practice, there are reasons to be concerned that automaker and driver care levels may be too low and activity levels too high. What’s more, this concern would apply not only to human-driven vehicles, but to Level 5 vehicles as well. That is, there is nothing about the nature of Level 5 vehicles that would suggest these problems are less likely to be present than would be the case for human-driven vehicles. 48 48. With Level 5 vehicles, if there were a problem with “driver care levels,” it would be a problem automaker care levels. That is, with Level 5s, driver care levels are, by definition, included as a part of manufacturer care level. × This activity-level inefficiency associated with current automaker liability law has been totally ignored by those who have argued in favor of applying existing product liability standards, or revised but still negligence-based versions of existing product liability standards, to Level 5 vehicles.

Driver Liability Law

In a majority of states in the U.S., if someone is injured or suffers property damage as a result of a driver’s negligent operation of an automobile, rather than as a result of automaker negligence, the victim may recover from the negligent driver under standard common-law principles of tort. 49 49. For a summary of emergence of fault-based and no-fault auto liability/insurance systems, see JAMES M. ANDERSON, PAUL HEATON, SEPHEN J. CARROLL, THE U.S. EXPERIENCE WITH NO-FAULT AUTOMOBILE INSURANCE: A RETROSPECTIVE 19–61 (2010), https://www.rand.org/content/dam/rand/pubs/monographs/2010/RAND_MG8 60.pdf. × The victim must demonstrate that the harm to her was a result of the driver’s failure to do something that a reasonable driver would have done under the circumstances, or the drivers’ doing something that a reasonable driver under the circumstances would not have done. 50 50. RESTATEMENT (SECOND) OF TORTS § 284 (defining negligent conduct in terms of what reasonably prudent person would do or not do); see also RESTATEMENT (THIRD) OF TORTS: LIABILITY FOR PHYSICAL AND EMOTIONAL HARM, § 3 cmt. h (Am. Law. Inst. 1998) (“Many cases say that negligence consists of “the failure to do something which a reasonably careful person would do, [or] the doing of something which a reasonably careful person would not do.”“) (citations omitted). × Accident victims who can recover include pedestrians, cyclists, passengers, or other drivers—anyone who is harmed as a result of driver negligence.

Because driver liability is also a negligence-based regime, it has similar potential to provide efficient deterrence as does a negligence-based automaker liability regime. Specifically, negligence-based driver liability law can have beneficial deterrence effects on driver care levels, if we make the following assumptions:

  • Drivers are well informed about accident risks (and how their behavioral changes affect those accident risks),
  • Drivers are well-informed about the rules of tort law,
  • Drivers internalize those risks (do not externalize them to insurers, for example), and
  • Drivers process the information about those risks rationally (without any systematic cognitive biases), and we assume again that
  • Courts are good at applying cost-benefit-type negligence-based liability rules.

If all of those assumptions are true, then, for the same reason that automakers would be incentivized by a negligence-based automaker liability regime, drivers too would be incentivized to drive with efficient care—in terms of driving speed, safe braking and passing practices, smart-phone usage (or non-usage), and the like. This is so because, by taking efficient care in driving, drivers would avoid liability for the accidents that nevertheless occur. Again, under a negligence-based regime, driving with efficient care can be seen as a type of insurance for drivers, a fact that—if all of the above-listed assumptions are true—would incentivize safe driving.

The reasons that this vision of negligence-based driver liability law do not describe reality should be clear at this point. The assumptions listed above on which the analysis depends almost certainly do not hold in the real world. While drivers may be generally aware of the broad outlines of the driver liability regime in their state (whether it is fault-based or no-fault), they likely do not understand what the precise implications of that fact are on their chances of being found liable in court for unsafe driving. What’s more, the average driver, while generally and vaguely cognizant of the risks of driving, is almost certainly uneducated about the precise levels of risk associated with various aspects of driving—for example, precisely how much the chance of a crash is increased by texting while driving or changing lanes abruptly with no signal. In fact, there is a good chance that most drivers underestimate those risks.

Why would drivers tend to underestimate such risks? First, there is the long list of well-documented cognitive biases that affect how individuals process information generally. 51 51. The sources here are many. A decent place to start would be the classic essay by Amos Tversky & Daniel Kahneman, Judgment Under Uncertainty: Heuristics and Biases, in JUDGMENT UNDER UNCERTAINTY. HEURISTICS AND BIASES 3 (Daniel Kahneman, Paul Slovic, & Amos Tversky eds., 1982). More recent summaries of the literature include DANIEL KAHNEMAN, THINKING, FAST AND SLOW (2011); and RICHARD H. THALER, MISBEHAVING: THE MAKING OF BEHAVIORIAL ECONOMICS (2015). A classic article summarizing the application of behavioral insights to law and economics is Christine Jolls, Cass R. Sunstein & Richard H. Thaler, A Behavioral Approach to Law and Economics, 50 STAN. L. REV. 1471 (1998). × One famous example is the tendency of individuals to ignore the risk of very low probability events and underestimate the likelihood of some high probability events. 52 52. For a summary of the relative behavioral literature as it relates to products liability, see Jon D. Hanson & Douglas A. Kysar, Taking Behavioralism Seriously: the Problem of Market Manipulation, 74 N.Y.U. L. REV. 630, 643–87 (1999). For early applications of behavioral insights to products liability law, see Latin, supra note 21; and Howard A. Latin, “Good” Warnings, Bad Products, and Cognitive Limitations, 41 UCLA L. REV. 1193, 1194–95 (1994). For a discussion of the findings on very low probability and high probability events, see Hanson & Kysar, supra note 45, at 716–20. Note that there is also research showing that consumers sometimes overestimate the risks of merely “low probability” events—those that fall between very low probability and high probability. Id. (discussing research summarized in Enterprise Responsibility for Personal Injury, 1 A.L.I. 230 (1991)). × Auto-crash risks may similarly be ignored or underestimated. 53 53. Whether auto risks are more likely to be very low, merely low, or high probability events is not entirely clear. However, the most important insight of the Hanson & Kysar article is that, because product manufacturers—including automakers–have considerable influence over how consumers perceive the risk of their products (and because product manufacturers—including automakers–have a strong market incentive to ensure that consumers underestimate the risks of their products), there is every likelihood that consumers on balance underestimate the risks of auto accidents. Id. Moreover, Hanson & Kysar, in a follow up article, provide considerable anecdotal evidence of actual market manipulation of consumer risk perceptions by manufacturers. Jon D. Hanson & Douglas A. Kysar, Taking Behavioralism Seriously: Some Evidence of Market Manipulation, 112 HARV. L. REV. 1420, 1466 (1999). × Also, drivers are especially prone to overestimating their own driving ability and thus their own ability to avoid crashes. 54 54. This finding has proven robust over many years. See, e.g., Ola Svenson, Are We All Less Risky and More Skillful Than Our Fellow Drivers?, 47 ACTA PSYCHOLOGICA 143 (1981); Timo Lajunen & Heikki Summala, Driving experience, personality, and skill and safety-motive dimensions in drivers’ self-assessments 19 PERSONALITY AND INDIVIDUAL DIFFERENCES. 307 (1995); A.F. Williams, Views of US drivers about driving safety 34 J. SAFETY RES. 491 (2003). See also Jolls et al., supra, at 1537–38 (discussing problem of “overoptimisim” among drivers); Hanson & Kysar, Taking Behavioralism Seriously: A Response to Market Manipulation, 6 ROGER WILLIAMS L. REV. 259, 354–55 (1999) (same). × Moreover, drivers not only underestimate their own likelihood of a crash relative to the average driver (which they do), they also overestimate their own likelihood of a crash relative to the actual probability. 55 55. Christine Jolls, Behavioral Economics Analysis of Redistributive Legal Rules, 51 VAND. L. REV. 1653, 1660 (citing Richard J. Arnould & Henry Grabowski, Auto Safety Regulation: An Analysis of Market Failure, 12 BELL J. ECON. 27, 34–35 (1981) and Colin F. Camerer & Howard Kunreuther, Decision Processes for Low Probability Events: Policy Implications, 8 J. POLY. ANALYSIS & MGMT. 565, 566 (1989)). × For all of these reasons, a negligence-based driver liability regime, which relies on assumptions of informed and rational drivers to produce optimal driver care levels, may not produce the deterrence benefits that are predicted by deterrence theory. 56 56. The evidence on whether negligence-based driver liability law reduces auto accidents, or the harms resulting from auto accidents, is probably best characterized as inconclusive. See generally Nora Freeman Engstrom, An Alternative Explanation of No-Fault’s Demise, 61 DEPAUL L. REV. 303, 332–333 (2012) (“[R]oughly half of the studies published thus far claim that no-fault coverage increases fatal accidents, while the other half find no effect, and the notion that no-fault reduces fatalities has been seemingly put to rest.”) (footnotes omitted). The hope that a shift away from a negligence-based driver-liability regime would not substantially reduce auto accidents, along with the overall desire to lower auto insurance rates, was one of the original justifications for the movement towards auto no-fault regimes in the 1970s and 1980s. Id. × In addition, it is commonly argued that drivers have many powerful incentives to drive carefully even in the absence of a negligence-based regime that left on them the uninsured costs of auto accidents, incentives such as the desire to avoid a traffic fines or, more importantly, a crash that could be painful or even fatal to them or their loved ones. 57 57. Latin, supra note 21, at 690–91; Engstrom, supra note 49, at 330. ×

How does this pessimistic picture of driver liability law as a system of incentivizing good driving change if we introduce auto insurance? The answer to that question turns out to be complicated. On one hand, automobile insurance has the potential to correct some of these deterrence-related problems. 58 58. See generally Omri Ben-Shahar & Kyle D. Logue, Outsourcing Regulation: How Insurance Reduces Moral Hazard, 111 MICH. L. REV. 197 (2012) (discussing ways that insurance companies help insureds reduce risk). × Here’s why. Auto insurers are, unlike most drivers, extremely well informed about the intricacies of accident law. They employ teams of lawyers whose job is to understand how driver liability laws in each state affect the liability risks of their customers. Indeed, their profitability and their survival as going concerns depend on this expert understanding of the auto liability laws of all sorts. In addition, auto insurers have unparalleled access to enormous amounts of detailed information regarding the crash-risk characteristics of millions of drivers and automobiles. This is the result of decades of experience providing auto insurance coverage to hundreds of millions of drivers and vehicles, which in turn means pricing millions of auto insurance policies and adjusting millions of auto-crash claims over the years. No other institution or organization would have the same amount of driver-specific, automobile-specific data, as would the auto insurance industry.

In addition, recent innovations in “telematics” (which combines telecommunications, data science, and automotive technology) have increased auto insurers’ ability to gather and analyze risk-relevant driver and vehicle data. 59 59. Background On: Pay-As-You-Drive Auto Insurance (Telematics), INS. INFO. INST., https://www.iii.org/article/background-on-pay-as-you-drive-auto-insurance-tele matics (last visited Nov. 21, 2018). × With this new and emerging technology, not only do insurers have access to information regarding how drivers’ past auto-claims and traffic-ticket histories affect their riskiness as drivers; they also have the ability to gather information on the effects of a range of specific driving behaviors on auto-crash risks. 60 60. Id. See also Ben-Shahar & Logue, supra note 51. × For example, a number of insurers currently gather information about drivers’ braking, acceleration, speeding, turning, and cornering behaviors and then send that information back to the insurers for analysis. 61 61. Yuanjing Yao, Evolution of Insurance: A Telematics-Based Personal Auto Insurance Study, U. CONN. HONORS SCHOLAR THESES, 590, 598 (2018), https://opencommons.uconn.edu/srhonors_theses/590/. × Once this driver-specific data is combined with data gather by insurers and others (including NHTSA) about what factors cause auto accidents generally, it becomes possible for auto insurers to link specific driving behaviors of particular drivers with premium discounts. 62 62. Id. ×

All of this information is to varying degrees already being taken into account by many auto insurance companies in the pricing of their insurance policies. For example, policy discounts are offered to drivers with good safety records 63 63. Most auto insurers give discounts for being accident free for a given period of time. Car Insurance Discounts, VALUEPENGUIN, https://www.valuepenguin.com/car-insurance-discounts (last visited Nov. 21, 2018). See also Yao, supra note 54 (discussing use of behavioral driving discounts among insurers). × as well as for vehicles with particular safety features. 64 64. One survey of the leading car insurers, found the following additional vehicle-safety-related discounts: passive restraint (25% to 30%), new car (10%), daytime running lights (around 3%). Id. Some insurers are starting to offer discounts for semi-autonomous features such as adaptive cruise control, collision avoidance systems, and lane departure warnings. Cherise Threewitt, What Car Insurance Discounts Can I Get?, U.S. NEWS & WORLD REP. (June 29, 2018), https://cars.usnews.com/cars-trucks/car-insurance/car-insurance-discounts. × In addition, insurers are now offering discounts if drivers will improve their driving ability—for example, if they will take defensive driving classes. 65 65. Car Insurance Discounts, supra note 56 (reporting insurers giving discounts of 10% to 15% for completion of defensive driving courses). × Because of telematics revolution, auto insurers are even able to adjust premiums on the basis of the specific driving behavior of individual drivers. For example, some insurers give discounts for a range of driver-care-level factors such as wearing seatbelts, driving at moderate speeds, limiting late night trips, and avoiding aggressive braking. 66 66. Id. See also Barbara Marquand, Comparing Drivewise, Snapshot and Other Usage-Based Insurance Plans, NERDWALLET (Feb. 8, 2016), https://www. nerdwallet.com/blog/insurance/comparing-drivewise-snapshot-usage-based-insurance/. × Also, the advances in telematics have made “pay as you go” auto insurance, under which premiums are a function of the number of miles driven, more accurate—and thus more prevalent—than ever before. 67 67. Usage-Based Insurance and Telematics, NAT’L ASS’N OF INS. COMMISSIONERS (July 26, 2018), https://www.naic.org/cipr_topics/topic_usage_based_insurance.htm. × Driving-behavior-sensitive auto insurance premiums—which could take into account both good and bad driving choices (i.e., driver care levels) and, critically, the number of miles driven (i.e., driver activity levels)—hold the promise of incentivizing risk-reducing driving behavior in a way that even the most sophisticated government regulator could not hope to do. 68 68. See generally Ben-Shahar & Logue, supra note 51 (discussing potential risk reducing benefits of high-tech auto-insurance pricing); Hanson & Logue, supra note 19, at 192–93 (suggesting reasons why auto insurance is better at risk-segregating than other types of first-party insurance). What little empirical research has been done on the subject tends to confirm that incentive-based insurance pricing tends to alter driving behavior in a risk-reducing direction. See Mark Stevenson et al., The effects of feedback and incentive-based insurance on driving behaviours: study approach and protocols, 24 INJ. PREVENTION, 89, 93 n. 27–30 (2018), https://injuryprevention.bmj.com/content/24/1/89; see also Telematics Helps Reduce collisions and Claims, AUTOMOTIVE FLEET (Nov. 10, 2017), https://www.automotive-fleet.com/157806/telematics-helps-reduce-collisions-and-claims. ×

But here is the problem: Under current law and given existing market conditions, auto insurers do not have strong incentives to make full use of their comparative advantage at gathering risk-relevant information and pricing their insurance on the basis of that information, or at least there is reason to be concerned about their incentives to do so. The reason for concern is that the amount of coverage currently being provided by auto insurers presently represents only a fraction (in many cases a small fraction) of the total risks of auto crashes. This is true of first-party auto insurance coverage, which tends to cover only a fraction of the accident risks that any driver faces. 69 69. This assertion requires some explanation. There are no good studies on this particular question. So my claim is derived from circumstantial evidence of a sort. First, note that, whereas all states require some amount of liability insurance coverage for anyone who drives on public roadways, only a small minority of states require drivers to purchase auto insurance that provides any sort of first-party medical or disability benefits. See, e.g., Background on: Compulsory Auto/Uninsured Motorists, INS. INFO. INST. (April 16, 2018), https://www.iii.org/article/background-on-compulsory-auto-uninsured-motorists. What’s more, even when there is mandated medical or disability coverage, the amount of required coverage is almost always far less than would potentially be recoverable under an auto tort claim, whether it be an automaker liability claim or a driver liability claim, and far less than the potentially enormous total costs (in the millions) of any given auto accident. Id. (for example, noting mandatory amounts of bodily injury liability coverage ranging from $15,000 to $50,000 per person). Karl Eisenhower, Personal Injury Protection: How PIP Insurance Works in Your State, WALLET HUB (Jan. 9, 2015), https://wallethub.com/edu/pip-insurance/9248/ (noting PIP mandates ranging from $2000 per person in Utah to $50,000 in New York.) The only state that requires unlimited PIP coverage is Michigan. Id. Further, even when drivers do purchase first-party medical or disability coverage through their auto-insurance policy, that coverage is often secondary to the victims’ other forms of first-party health or disability insurance. For example, in some states requiring PIP coverage in auto policies, the insured can elect to make auto PIP coverage secondary to other first-party health and disability insurance. This is sometimes called the “coordination” option. MICH. DEPART. INS. & FIN. SERV., YOUR GUIDE TO AUTOMOBILE INSURANCE: FOR MICHIGAN CONSUMERS 10 (Sept. 2017), https://www.michigan.gov/documents/ difs/Auto_Insurance_Guide_448003_7.pdf. Because making auto health insurance secondary lowers the insured’s auto insurance premiums, and has little or no effect on her first-party health and disability insurance premiums, most insureds choose the coordination option, which means most insureds choose to make their non-auto first-party insurers primary. In sum, most auto health and disability risks end up being borne by non-auto first-party insurers—such as health insurers and disability insurers. × It is also true of auto liability coverage, owing in part to the fact that the mandatory minimum amounts in most states are far less than the maximum harm threatened by an auto accident that results in even one serious injury or death. 70 70. State mandated minimums for liability coverage for personal injuries to a single person range from a low of $10,000 (Florida) to a high of $50,000 (Alaska and Maine), and by for the most common minimum is $25,000. Car Insurance Laws by State, FINDLAW, https://injury.findlaw.com/car-accidents/car-insurance-laws-by-state.html (last visited Nov. 19, 2018) (gathering links to state laws). A single accident resulting in serious bodily injury or death could easily produce economic losses alone in excess of $1 million. × As a result, many of the costs of auto accidents are currently being externalized to non-auto first-party health and disability insurers who—unlike auto insurers in the telematics age—do not tailor premiums at all based on their insureds’ driving decisions. 71 71. Most first-party health and disability insurers make no effort to price their coverage in a way that reflects the riskiness of insureds’ driving choices—such as how they drive, how much they drive, or even what type of vehicle they drive. See generally Hanson & Logue, supra note 19 (using fact that most non-auto first-party insurers do not price-differentiate on basis of consumer product use to argue for enterprise liability for product accident risks). There is a perfectly sensible reason for this fact: the risks of auto-related health or disability claims are only a small fraction of the overall health and disability risks covered by any given first-party health or disability insurer. It is not worth the insurers’ while to tailor their insurance premiums on the basis of any particular behavioral choice of their insureds, other than perhaps the choice to smoke or not. The result of all this: that portion of auto crash risks that are ultimately born by non-auto first-party insurers get externalized (or largely ignored) by drivers, with obvious deterrence consequences. × Moreover, to the extent auto insurers do attempt to charge individualized, behaviorally- and risk-adjusted auto insurance rates (which, as I noted above, they are increasingly trying to do), this incentive is undermined by the fact that auto insurers cover only a fraction of the risks of auto accidents. 72 72. Because auto insurers do not bear all of the risks of auto accidents, the premium discounts they are willing to offer to induce safer driving habits may not be adequate. The point can be illustrated with a simple example. Suppose there was some investment in driver care that cost $50 but would reduce expected accident costs by $80. Say it would reduce a chance of a $200,000 loss from .001 to .0006. If the auto insurer bore the full $200,000 risk, it would have an incentive to offer a premium discount to cover the cost of driver care, with an additional discount perhaps up to a total just short of the $80 saved by the additional investment in driver care. But what if the auto-insurer bore only, say, $40,000 of the $200,000 potential loss? Then the largest discount it could offer without losing money would be $16, which would be the amount of the savings in going from a .001 to a .0006 risk of, now, $40,000 in covered losses. But that discount would not be enough to induce the consumer to make the investment in care, assuming the other $160,000 in expected accident cost is externalized either because of drivers’ under-estimation of risk or because of non-adjusting non-auto first-party insurance coverage. ×

It should also be noted, however, that there are important ways in which the allocation of auto-accident risks to non-auto first-party insurers has cost-reducing advantages. This may seem incongruous with the argument in the previous paragraph, but it is not: While auto insurers are in a good position, through premium discounts, to help optimize driver care and activity levels, auto insurers are not necessarily in a good position to minimize some other costs associated with providing insurance benefits. For example, primary health care coverage provided through auto insurance companies is almost certainly much more expensive than primary health care provided through regular non-auto first-party health insurers. This would be because, although auto insurers, in a sense, specialize increasingly in reducing driver ex ante moral hazard, it is non-auto health insurance companies who specialize in reducing ex post medical moral hazard—that is, excessive or wasteful use of the healthcare system. 73 73. The claim that first-party health insurers specialize in trying to hold down health care costs may seem controversial, at least for fee-for-service policies. My claim is only that health insurers—especially ones that use managed care tools—are probably better at holding down ex post health care costs than are auto insurers. This is one of the reasons that auto no-fault regimes which make auto PIP coverage primary over non-auto first-party health coverage are so expensive, and why auto-no-fault regimes have not led to the cost savings that were expected. See Engstrom supra note 49. Professor Engstrom notes that “[m]edical insurers . . . reduce costs via discounts and fee schedules, and the limit patient treatment using any number of mechanism, including deductibles, co-payments, utilization controls, and medical protocols . . . , [a]uto insurers . . . tend to pay almost any bills that a victim incurs . . . dramatically increasing . . . the cost of care. Id. at 341 (citations omitted). × My point here is only that the current division of auto-accident costs, allocating so little to auto insurers, may be non-optimal, given auto insurers potential ability to incentivize better (and less) driving. 74 74. In Part III below, I suggest that, by adopting an automaker enterprise liability regime, automakers will have an incentive to strike the efficient balance between amount of auto-crash costs allocated to auto insurers and amount allocated to non-auto insurers. ×

To summarize, because of drivers’ lack of accident-risk information and understanding of auto tort law and their susceptibility to cognitive biases, and because of the presence of cost-externalizing insurance coverage, there is reason to be doubtful that the current negligence-based auto tort laws—automaker liability laws as well as driver liability laws—work to optimize driver care and activity levels. As discussed in the next Part, the adoption of an auto enterprise liability regime could in theory create incentives for automakers, together with auto insurers, to provide better driver-side incentives, as well as better automaker safety incentives.

III.         The Automaker Enterprise Liability Alternative 75 75. The arguments in this section draw on prior work done by me and a number of other scholars on the deterrence benefits of enterprise liability in various contexts. See, e.g., Hanson & Logue, supra note 19; Steve P. Croley & Jon D. Hanson, Rescuing the Revolution: The Revived Case for Enterprise Liability, 91 MICH. L. REV. 683 (1993); Kyle D. Logue & Jon D. Hanson, The Costs of Cigarettes: The Economic Case for Ex Post Incentive-Based Regulation, 107 YALE L.J. 1163 (1998); and Jon D. Hanson & Douglas A. Kysar, Taking Behavioralism Seriously: Some Evidence of Market Manipulation, 112 YALE L.J. 1420, 1553 (1999). In addition, as mentioned in an earlier footnote, the argument here has some overlap with a proposal made by Howard Latin. See generally Latin, supra note 21 (making a deterrence case of automaker enterprise liability). ×

The Basic Proposal

As an alternative to our current negligence-based auto tort regime, consider the possibility of a comprehensive automaker enterprise liability regime. Under such a regime, anyone who suffers a physical injury or property damage in an automobile accident—whether driver, passenger, or pedestrian—would be legally entitled to recover, from the manufacturer of the vehicle involved, compensation for the losses sustained as result of the accident. 76 76. This could be done through the existing court system or through specialized courts or agencies set up to handle auto-crash disputes. × Thus, to recover under this enterprise liability regime, accident victims would not be required to show negligence on the part of manufacturer or anyone else. Nor would accident victims have to prove that the automobiles, or any of the warnings or instructions accompanying the automobiles, are in anyway defective or unreasonably dangerous. Rather, crash victims would need only to prove that the harms for which they seek compensation “arose out of the use of” a vehicle that was designed and built by the manufacturer from whom compensation is sought. Each automaker, therefore, would be financially responsible for the losses resulting from any crash arising out of the use of that automaker’s vehicles. 77 77. The “arising out of the use of” analysis would replace a causation determination. This phrase is used now in standard auto insurance policies. Thus, an automaker enterprise liability regime would be a particular type of cause-based no-fault compensation regime, modeled after similar programs that have been adopted outside of the auto context, such as workers’ compensation laws at the state level or the vaccine compensation program at the federal level. See generally Jon D. Hanson, Kyle D. Logue & Michael S. Zamore, Smokers’ Compensation: Toward a Blueprint for Federal Regulation of Cigarette Manufacturers, 22 S. ILL. L.J. 519 (1998) (discussing deterrence benefits of cause-based no-fault compensation regimes). In the Workers’ Compensation context, claims against employers are limited to injuries or illness that “arise out of the course of employment.” Professors Abraham and Rabin have proposed a similar regime—that would also use the “arising out of” standard—but that would apply exclusively to accidents involving Level 5 automated vehicles. Rabin & Abraham, supra note 20. My idea is to make such a regime comprehensive, to apply to all motor vehicles, subject to transition rules discussed below. Some scholars have expressed concern about the use of enterprise liability regimes that rely on boundary-maintaining doctrines such as the “arising out of” concept used in workers’ compensation regimes, among other places. See, e.g., Henderson, supra note 19. This is of course a reasonable concern, although the evidence suggests that programs such as workers’ compensation have found relatively effective ways to police the borders of their programs. DON DEWEES, DAVID DUFF & MICHAEL TREBILCOCK, EXPLORING THE DOMAIN OF ACCIDENT LAW: TAKING THE FACTS SERIOUSLY 393-394 (1996) (reporting administrative costs for workers’ compensation regimes that are low relative to those of the tort system). ×

That is the most basic picture of the proposal. Now consider a few possible details of such a program. One important initial question is who exactly would fall within the class of “automakers” to whom the enterprise liability regime would apply. The most obvious class of defendants/payers would be the original equipment manufacturers (OEMs) of the vehicles involved in the crash. They are the ones who generally make the key automotive design choices, have control over the manufacturing processes, and decide on the terms of any warning or instruction manual; and they are also the ones with the greatest expertise on such questions. Auto manufacturers also determine the pricing of their vehicles and the number of them to produce, subject of course to the constraints of supply and demand. Given that manufacturer care levels and activity levels are key auto-accident deterrence variables, making OEMs responsible for the auto-crash costs associated with their vehicles has obvious deterrence benefits, discussed further below.

Liability under an enterprise liability regime, however, would not necessarily be limited to auto manufacturers. Liability could also be extended, on a joint and several basis (or on a several basis), to a range of other enterprises that fall within the design, production, sale, and distribution chain of any given vehicle. 78 78. Thus the concept of “automaker” in an automaker enterprise liability regime could be similar to the concept of a “seller” in existing products liability law. × In most cases, it is likely that the crash victim would bring the claim against the manufacturer, and then the manufacturer would either implead the other parties in the chain of production into that suit or would sue them separately in a contribution action. Precisely how the responsibility for the costs of any accident would be allocated among the various parties on the automaker side of the ledger is beyond the scope of this Article. That allocation of responsibility, however, would presumably be determined mostly by contracts among the counter-parties, which contracts should be enforced so long as the cost of auto accidents is not allocated to parties who are insolvent or judgment proof, which if permitted would undermine the deterrence benefits of the regime. 79 79. See Steven Shavell, The Judgment Proof Problem, 6 INT’L REV. OF L. & ECON. 45 (1986) (explaining how presence of insolvent defendants undermines incentive effects of liability law). ×

The types and amount of compensation recoverable under an automaker enterprise liability regime would probably be limited to economic losses—medical expenses, lost income, and property damage. There is of course a deterrence argument for including noneconomic or pain-and-suffering damages as well, since failing to include noneconomic damages could produce a serious externality. 80 80. Noneconomic damages are generally not covered by first-party insurance policies, which means, insofar as drivers (and consumers generally), because of the cognitive biases already discussed, ignore or underestimate the risks of auto accidents, they will externalize noneconomic damages as well. Including noneconomic damages, therefore, has the potential to improve care levels and activity levels. See Hanson & Logue, supra note 19, at 186–89 (describing the “unambiguous deterrence benefits of nonpecuniary-loss damages”). × However, some have argued that individuals do not desire to purchase insurance against non-economic losses (as evidenced by the dearth of pain-and-suffering insurance observed in the marketplace), and therefore should not be forced to purchase such coverage through a mandatory compensation regime. 81 81. Examples of this sort of argument can be found in George L. Priest, The Current Insurance Crisis and Modern Tort Law, 96 YALE L.J. 1521, 1546–47; and Alan Schwartz, Proposals for Products Liability Reform: A Theoretical Synthesis, 97 YALE L.J. 353, 362–67 (1988). For a powerful set of counter arguments, providing arguments why consumers might—and evidence that they in fact do—demand insurance for noneconomic losses, see Steven P. Croley & Jon D. Hanson, The Nonpecuniary Costs of Accidents: Pain-and-Suffering Damages in Tort Law, 108 HARV. L. REV. 1785 (1995). × In any event, limiting compensation to economic losses, and thus not providing compensation for noneconomic harms, is a common and reasonable political compromise that is often made when no-fault cause-based compensation regimes are adopted. 82 82. See generally Hanson, Logue & Zamore, supra note 66, at 556–62 (reviewing arguments for limiting damages in no-fault cause based compensation regimes to economic damages). ×

It is worth emphasizing again that the compensation regime I am imagining is a comprehensive automaker enterprise liability regime. In other words, it would apply to all automobiles (sold after the effective date of the enacting legislation), whether driven by humans, computer algorithms, or any combination of the two. Thus, unlike some other proposals for manufacturer-funded vehicle compensation regimes, my proposal would not apply exclusively to Level 5 vehicles. 83 83. For an interesting proposal to create a special enterprise liability-type regime, similar to the one I am describing, but that would be limited to accidents involving automated vehicles, see Abraham & Rabin, supra note 20. × Which is not to say that the regime would not have special rules for autonomous and connected vehicles. For example, whereas Level 5s may be in fewer accidents, or fewer accidents involving serious physical injuries or deaths (that’s the hope anyway), Level 5 vehicle accidents may involve much higher auto-repair costs than accidents involving human-driven vehicles, because of the expense of repairing high-tech sensors as well as computer hardware and software. 84 84. Because of the higher repair costs, some in the auto insurance industry have proposed mandatory minimum auto repair coverage for self-driving vehicles. TRAVELERS INSTITUTE, INSURING AUTONOMY: HOW AUTO INSURANCE CAN ADAPT TO CHANGING RISKS 11 (2018), https://www.travelers.com/iw-documents/travelers-institute/Final-Digital-2018-0710-AV-White-Paper-No-SAE.pdf. Under enterprise liability, of course, there would indeed be mandatory minimum auto repair coverage, as well as mandatory minimum personal injury coverage, but the coverage mandate would be imposed on automakers instead of auto purchasers. ×

If an automaker enterprise liability regime were adopted, there would be no need for either the existing automaker liability laws (i.e., products liability as applied to automobiles), driver liability laws, or state auto no-fault laws. All of those auto tort regimes would be replaced by a single comprehensive automaker enterprise liability regime. 85 85. Tort liability for non-economic and potentially punitive damages could be retained for especially egregious behavior, such as recklessness or intentionally harmful actions, on the part of defendants. × Further, if a motor-vehicle crash were to involve two or more vehicles made by different auto manufacturers, the enterprise liability regime would handle the accident as follows: First, the victims would simply file claims for their covered economic losses, naming the automakers of all of the vehicles involved in the accident. After a factual determination was made of whether in fact all of the named vehicles contributed in some way to the accident, the victims’ crash costs would be split between or among the automakers (or the auto insurers covering the losses for each automaker). The split among the automakers could either be equal (each vehicle manufacturer bearing its pro rata share of the crash costs) or according to any other reasonable allocation formula that the industry agrees upon. 86 86. The deterrence benefit for automaker and driver care and activity levels would largely remain, without the need for individualized fault determinations in multi-vehicle crashes. The crash data gathered from all the payouts under the program would provide information as to which types of vehicles and which drivers tended to be in accidents, how much damage resulted from those accidents, and under what circumstances. This information would be combined with the data gathered by automakers and auto insurers regarding individual vehicle and driver behavior in contexts not involving accidents. There would be little additional deterrence benefit to investing in the costly judicial determination of which driver, if any, was at fault or which vehicle, if any, was defective. ×

One result of the adoption of a comprehensive automaker enterprise liability regime would be an increase in the apparent (and the experienced or internalized) price of most newly purchased automobiles, relative to vehicles purchased before the effective date of the enacting legislation. 87 87. This assumes that the new law would have a grandfather provision exempting vehicles built and sold before new law’s effective date. As discussed in the conclusion, such complete grandfathering is not the only conceivable approach to handling the transition to the new regime. × This would happen because the cost of auto accidents that had been hidden in non-auto first-party insurance coverage prior to the enterprise liability regime would, with the adoption of the new system, be brought into the open through increases in automobile and auto-insurance prices. Because such a shift would be a significant change in the automotive marketplace, it would probably be prudent (and politically necessary) to institute a delayed effective date and/or an extended phase-in period over which the law would take effect. 88 88. If there is indeed deterrence value to shifting these costs from non-auto first-party insurers to automakers, as argued in the next section, then the overall price of vehicles (including the costs covered by various forms of first-party non-auto-specific insurance) should eventually go down, especially if the pace of the transition to driverless technology is hastened. Indeed, a significant result of adopting a comprehensive automaker enterprise liability regime is that Level 5 vehicles, if they provide as big an advance in safety as many are expecting, would be substantially less expensive overall than conventional human-driven vehicles. Cf. Bryant Walker Smith, Automated Driving and Product Liability, 2017 MICH. ST. L. REV. 1 (2017) (discussing the potentially massive reduction in overall vehicle prices resulting from the shift to automated vehicles under existing product liability law). A bigger concern with the price increase is the effect on low-income drivers. I address this concern briefly in Part IV below, though the cost of mobility generally is a topic worthy of special consideration. ×

The Theoretical Deterrence Benefits

Under a comprehensive automaker enterprise liability regime, because automakers would be responsible for all of the economic costs of auto accidents associated with their vehicles, they would be forced to internalize those costs. As a result, there would be beneficial deterrence consequences for automaker, and potentially driver, care and activity levels. This section explores those consequences.

First, automakers would have a strong legal and financial incentive to develop and implement cost-justified auto-safety innovations, whatever those might be. That is, if an automaker determined that there was some new brake design (such as a new computer-assisted automatic braking system) or some new guided cruise control mechanism that would reduce overall accident costs relative to its costs of development and implementation, then enterprise liability would reward them implementing those innovations, and punish them for not doing so. What’s more, there would be no inefficient incentive to stick with existing industry customs or consumer expectations if such customs or expectations were lagging behind proven safety innovations. Likewise, there would be no incentive to over-invest in safety features that are likely to impress a court or jury in a negligence-based lawsuit (such as a design defect lawsuit) but that, in actuality, provide less additional accident-risk reduction than they cost to produce. 89 89. Obviously, automakers already have some incentives to develop such safety technology, in part because of consumer tastes for safer vehicles and perhaps because of the threat of potential liability under existing tort law. See, e.g., Press Release, NHTSA, NHTSA-IIHS Announcement on AEB, (Dec. 21, 2017), https://www.nhtsa.gov/press-releases/nhtsa-iihs-announcement-aeb (“Twenty automakers pledged to voluntarily equip virtually all new passenger vehicles by September 1, 2022, with a low-speed AEB system that includes forward collision warning technology proven to help prevent and mitigate front-to-rear crashes.”). Consistent with this fact, it is common knowledge that safety innovation has been happening for decades without the presence of an automaker enterprise liability regime. My argument is that, according to a nuanced application of standard deterrence theory, safety-enhancing automotive innovations would be more likely to be adopted and would be adopted more quickly under an automaker enterprise liability regime. See, e.g., Latin, supra note 21, at 691 (making similar argument with respect to airbags, suggesting that adoption of automaker enterprise liability would have hastened the industry’s move to include airbags). ×

Second, enterprise liability would force the price of automobiles to reflect the full-expected costs of auto accidents. That cost-internalization, in turn, could result in a scale of automotive manufacturing and sales that would be closer to the social optimum than is currently the case, as drivers would—in deciding whether to purchase a vehicle—be more likely to take into account something closer to the full social costs of that decision. In other words, auto enterprise liability could push us in the direction of optimal manufacturer activity levels: the optimal number of vehicles being sold. If that were to happen, it would be a clear improvement—in terms of overall efficiency—over the existing negligence-based automaker liability regime.

It is worth pausing here to emphasize the potential effects of a comprehensive automaker enterprise liability regime on the development of and transition to Level 5 vehicles. Because it to would be a comprehensive regime, it would apply to both driverless and human-driven vehicles. Assuming automakers expect Level 5s to bring a dramatic reduction in expected accident costs relative to human-driven vehicles, then Level 5s, when they eventually are available for sale to consumers, would have a substantially lower enterprise liability “tax” relative to human-driven vehicles made and produced after the new regime is adopted, since the human-drive vehicles would have much higher expected accident costs. 90 90. For now, I am assuming that “old” vehicles, produced before the enactment of the new regime, would be totally grandfathered and thus exempt from the new law. I return to this assumption in the conclusion. × As a result, there would be a natural enterprise liability subsidy in favor of the production of Level 5 vehicles; and this subsidy, in effect, would be funded by a relatively high enterprise liability tax on human-driven vehicles, again, assuming such vehicles are not nearly as safe as Level 5s. Thus, the adoption of a comprehensive automaker liability regime would, under present assumptions, strongly incentivize and reward auto manufacturers to proceed, as quickly as is feasible, with the development and distribution of Level 5 vehicles. By contrast, if a special liability regime were adopted just for Level 5s, that increased their potential accident liability relative to human-driven vehicles, there would be a disincentive to move to Level 5s in the absence of a separate subsidy regime, perhaps funded by federal income taxes. 91 91. Abraham and Rabin make such a proposal, including the need for a subsidy for Level 5 vehicles. Abraham & Rabin, supra note 20, at 45. ×

There are efficiency reasons to prefer a Level 5 vehicle subsidy that is funded through an enterprise liability tax on auto sales, with the amount of the cross-subsidy depending on the relative risk of vehicles (and drivers), over a subsidy funded by federal income taxes. The main advantage has to do with information. Under the direct subsidy, the regulator—or whatever government body would be asked to determine the amount and structure of the subsidy—would have to determine which particular safety technologies to subsidize and which not to subsidize and how much the subsidy should be. This would require an enormous amount of information and expertise that is not within the government’s comparative advantage relative to the auto industry. By contrast, under the subsidy structure inherent in a comprehensive enterprise liability regime, it is the auto industry who would calculate the appropriate amount of the subsidy ex ante, based on their educated guesses about (a) the amount of costs to be imposed on them under the regime for accidents involving human-driven vehicles, (b) the amount of costs that would be imposed on them if they make the investment necessary to develop and implement Level 5 vehicles, and (c) the R&D, design, manufacturing, marketing, training, and other costs that would be necessary to get Level 5s fully up and running. 92 92. It is at least possible that the expected accident costs associated with Level 5 vehicles will not be, overall, a lot less than that of human-driven vehicles, once the cost of repairing the vehicles is taken into account. That is, while Level 5s are expected to reduce frequency collisions and the number of auto-related deaths and serious bodily injuries, they may result in increased repair costs, due to the expense of repairing or replacing the damaged technology in a Level 5 vehicle. In that sense, we might be trading one sort of cost for another, which of course can be socially desirable. This fact, however, might counsel in favor of including at least some noneconomic (or pain-and-suffering) damages in the enterprise liability regime, to make sure that such costs get included in the enterprise liability subsidy for Level 5 vehicles. ×

If an enterprise liability regime is likely to have deterrence benefits on the automaker side, what about its deterrence effects on driver behavior? How an auto-enterprise liability regime would affect the driving behavior of human drivers is of course an especially important question, given that, with non-Level 5 vehicles, human drivers make most of the important operational decisions. In fact, enterprise liability could actually help with driver care and activity levels in a number of ways. First, enterprise liability would create strong legal and financial incentives for automakers to develop and adopt the most cost-effective ways of warning drivers about crash risks and of instructing drivers about how best to avoid certain types of accidents. 93 93. It is a standard conclusion of deterrence theory that enterprise liability would provide strong incentives for manufacturers to develop effective warnings. Croley & Hanson, supra note 68, at 786–792. × This effect flows from the fact that enterprise liability makes automakers’ responsible for all the economic costs of their vehicles’ accidents: If an automaker could actually reduce the frequency or severity of accidents in its vehicles by altering the wording, design, or placement of warnings or instructions, it would have an incentive to do so. On the other hand, if some new or revised warning would be more likely to confuse or annoy drivers than to educate them, the automaker would be incentivized under enterprise liability not to add that sort of unhelpful warning—even if it would have gotten the automaker “off the hook” under a more traditional negligence-based warning-defect standard. Automakers would do whatever works best to reduce accident costs, which would redound to their benefit as reduced auto-accident claim payouts over time.

In addition, enterprise liability could incentivize automakers to restructure the ways that automobiles are insured and sold in order to improve driver care and activity levels. First, consider how an enterprise liability regime might affect how auto insurance is provided. Note that under an enterprise liability regime automakers would have an incentive to shift contractually much of the expected costs of auto accidents to auto insurers. This somewhat counterintuitive result flows from the fact that auto insurers’ have a comparative advantage with respect to monitoring and regulating driver care- and activity-levels. If automakers could get auto insurers to take on somewhat more of the risk of auto accidents, the insurers would have a strong incentive to help drivers reduce expected accident costs. That is, because of competition for customers in the insurance industry, auto insurers would be incentivized to use the tools at their disposal—including individualized, driving-behaviorally-sensitive, risk-adjusted insurance premiums—in ways that would tend to encourage better driving habits and perhaps less driving, especially by high risk drivers. 94 94. Ben-Shahar & Logue, supra note 51, at 220–223. ×

What does this mean for how auto insurance would be sold? Auto insurance under an enterprise liability regime might be sold in the same way that it is today. An individual auto purchaser, in other words, might pay the automaker one price for the vehicle itself and then purchase a separate auto insurance policy at the same time from a separate auto insurance company. However, given that automakers would be ultimately responsible legally (through the doctrine of subrogation) for the auto-accident losses paid by the auto insurers, there would be strong incentives for contractual coordination between automakers and auto insurers. Individual auto manufacturers might even be induced to partner with particular auto insurers in an effort to offer the best, most competitively priced, combined product of vehicle and vehicle-insurance coverage. 95 95. Why are automakers and auto insurers not incentivized now, without the adoption of enterprise liability, to coordinate in the way described in the text? This is a fair question, one that I have put to representatives of both industries and to which I have yet to get a good answer. I suspect that under current legal rules and market conditions, those incentives are dampened. Automakers can largely avoid liability by complying with the largely negligence-based product liability rules, and auto insurers make profits from insuring the residual accident risk. Neither industry—car makers or car insurers—are being forced to bear the full losses of auto accidents. In addition, because much of the risk of auto accidents are externalized by drivers to their non-auto first-party insurers, as discussed above, there is little demand-side incentive for either industry to coordinate with the other. ×

Another way that enterprise liability could improve driver care and activity levels is through its effect on how automobiles are sold. For example, the introduction of an enterprise liability regime might push the automotive industry in the direction of lease transactions rather than outright sales. This is because leasing would make it easier for automakers to enforce the terms of the auto insurance policies, which again might be sold by an insurer who was contractually partnered with the automaker. Under a lease arrangement, for example, if a driver became uninsurable (because of bad driving behavior and/or increased claim payouts), or if the driver simply stopped paying her premiums, there might be a provision in the lease empowering the automaker to reclaim the vehicle.

In addition to favoring leasehold arrangements, the introduction of enterprise liability might create market pressure on auto manufacturers to sell vehicles to commercial purchasers rather than individual consumers. That is, automakers under enterprise liability might be incentivized to sell to commercial entities—fleet operators—who would agree contractually to indemnify the manufacturer for any enterprise liability payments made to victims harmed by vehicles in their fleets. These commercial purchasers, in turn, would either lease the vehicles to individual drivers or perhaps make them available through ride-share arrangements. Automakers in turn could be incentivized to choose commercial purchasers who are financially responsible and would be incentivized to purchase efficient auto insurance contracts to cover the enterprise liability payouts. Such a trend toward commercial fleets would be consistent with already existing market trends towards ride-sharing companies, which trends are expected to accelerate with the advent of Level 5 vehicles. 96 96. Andrew G. Simpson, If They Try It, They’ll Like It: How Ridesharing, Autonomous Cars Will Win Over the Public, INSURANCE JOURNAL (Jan. 23, 2018), https://www.insurancejournal.com/news/national/2018/01/23/478073.htm. ×

I am not suggesting that comprehensive automaker enterprise liability would necessarily result in auto lease arrangements replacing individual sales, or ride sharing replacing driving. Rather, the point is that, once automakers are made legally responsible for the cost of auto accidents (or for most of those costs), they will have an incentive (and the ability) to structure automobile distribution markets in ways that are closer the social optimal.

IV.         Caveats, Concerns, and Conclusions

The description I have given here of an automaker enterprise liability regime is necessarily only a rough outline of an idea, a jumping off point for further discussion. The actual design of such a program would require empirical research into a range of topics, including whether shifting to enterprise liability would actually, and not just theoretically, produce substantial deterrence benefits. Among the other questions that would need to be answered include the following:

Under any real-world version of an automaker enterprise liability regime, there is the question of how long the automakers’ responsibility for insuring their vehicles would remain in effect. Would it be for the useful life of the vehicle or for some set period of time, say, ten years? If for some set period of time, who then would be responsible for covering the accidents arising out of the use of the vehicle? Also, what would the precise relationship be between an automaker enterprise liability regime and state mandatory insurance/financial responsibility laws? Presumably, rescission of coverage by the insurer due to excessive accident experience or failure to pay premiums would result in a suspension of driving privileges, but how would that be enforced? All good questions.

Similarly, if an auto enterprise liability regime were adopted, would it in fact have a grandfather provision perhaps exempting all vehicles manufactured and sold before a given date, as suggested above? Or would older vehicles made before the new law goes into effect be transitioned into the new regime over time? If older vehicles were fully exempted from (or grandfathered out of) the new regime, how would we deal with the resulting, potentially large, price differential between new vehicles (which would be priced with full accident costs internalized into the purchase price) and used vehicles (which would not be)? What role could increased mandatory minimum levels of auto insurance play in assisting with that transition? 97 97. An alternative to a comprehensive automaker enterprise liability regime would be simply to increase auto insurance mandates to provide coverage closer to what would be provided under an enterprise liability regime. Such a regime could be made comprehensive, in the sense that it would apply both to human-driven and computer-driven vehicles, with perhaps higher repair cost minimum coverage for Level 5 vehicles. A comprehensive mandatory auto insurance regime could also replace all of existing automaker liability and driver liability law in much the same way as I propose for auto enterprise liability and would also likely result in contractual coordination between the automakers and the auto insurers to provide the best combination of auto safety and auto-crash risk coverage. A full discussion of this auto-insurance-mandate alternative to automaker enterprise liability is of course beyond the scope of this Article. ×

There is also a whole range of question regarding how an automaker enterprise liability regime would deal with the threat of auto crashes (or stolen or destroyed data) resulting from criminal hacking of a connected system. Existing and growing markets in cyber insurance coverage might be able to handle the risks of posed to data stored in the vehicles, but the market may have more difficulty covering cyber risks to life, limb, and property. 98 98. Most cyber polices include exclusions for physical damages to persons or property. John Buchanan, Dustin Cho, and Patrick Rawsthorne, When Things Get Hacked: Coverage for Cyber Physical Risks, 2018 A.B.A. LITIG. SEC., INS. COVERAGE LITIG. COMM. HOT TOPICS FOR ICLC’S 40TH—THE COVERAGE BATTLES OF 2028 TUCSON, ARIZONA—MARCH 3, 2018, 2. × Solutions range from expanding the role of the federal government as a reinsurer of last resort to limiting liability for cyber-related physical risks to the amount of mandatory liability insurance coverage. All of these details, and many others, would need to be addressed before any comprehensive automaker enterprise liability regime could seriously be considered.

The final concern raised by the idea of an automaker enterprise liability regime involves the cost. The concern is not that the “experienced” price of autos would rise, although that would certainly be true in the short run. As already noted, such a price increase would be the source of much of the deterrence benefit of an enterprise liability regime, the mechanism through which deterrence would work, incentives for accident-avoidance optimized. Rather, the concern has to do with the problem of affordability. For some households, owning an automobile is already unaffordable, which is a source of hardship and an obstacle to social mobility. For those households, a program that raised the price of autos, even in an effort to make them safer, may not be a welcome change without some form of compensating subsidy. My own view is that some type of taxpayer funded transportation subsidies for the low-income drivers may indeed be desirable (from a social justice perspective), whether or not an automaker enterprise liability regime were adopted. But that topic too must await another day.


   Douglas A. Kahn Collegiate Professor of Law, University of Michigan Law School. Professor Logue received helpful suggestions on the ideas in this Article from numerous participants at a conference on Traffic Accident Liability and the Future of Autonomous Vehicles held at Wake Forest University School of Law and from his Michigan Law colleagues at a Fawley Lunch Workshop in Ann Arbor. Thanks also to Bryant Walker Smith for his comments and notes.

 

Recently, I wrote about the prospects for federal legislation addressing connected and autonomous vehicles. While the subject will be taken up in the new Congress, the failed push for a bill at the end of 2018 is an indication of the steep hill any CAV legislation will have to overcome. Despite the lack of federal legislation, the Department of Transportation (DOT) has been active in this space. In October 2018, the Department issued Preparing for the Future of Transportation: Automated Vehicles 3.0, DOT’s most comprehensive guide to date outlining their plan for the roll-out of CAVs. The document indicates that the department expects to prioritize working with industry to create a set of voluntary safety standards over the development of mandatory regulations.

Given the Trump administration’s broad emphasis on deregulation as a driver of economic growth, this emphasis on voluntary standards is unsurprising. A handful of consumer groups focused on auto safety have raised the alarm over this strategy, arguing that mandatory regulations are the only way to both ensure safety and make the general public confident in automated driving technology.

The remainder of this post will discuss the effectiveness of voluntary safety standards relative to mandatory regulation for the CAV industry, and consider the prospects of each going forward. While little information is available about the response to either option in the CAV field, I will seek to draw lessons from experience with regulation of the traditional automobile industry.

The National Highway Transportation Safety Administration (NHTSA) has undergone a dramatic strategic shift over its half-century existence. In its early days, NHTSA was primarily devoted to promulgating technology-forcing regulations that sought to drive innovation across the industry. Jerry Mashaw and David Harfst have documented the agency’s shift away from adopting regulations in favor of an aggressive recall policy for defective products in the 1980s. As they write, the agency then returned to a regulatory policy in the 21st century. However, rather than attempt to force technology, they chose to mandate technologies that were already in use across most of the auto industry. While these new standards still took the form of mandatory regulation, they operated as virtually voluntary standards because they mandated technologies the industry had largely already adopted on its own. Mashaw and Harfst found that this shift was essentially a trade-off of slower adoption of new safety technology, and potentially lost lives, in favor of greater legitimacy in the eyes of the courts and industry. Particularly given the rise of pre-enforcement judicial review of regulations, this shift may be seen as a defensive mechanism to allow more regulations to survive court challenges.

Even as NHTSA has pulled back from technology forcing regulations, there has been no sustained public push for more aggressive auto safety regulation. This may be because the number of traffic fatalities has been fallen slightly in recent decades. This shift is likely due more to a reduction in drunk driving than improved technology. With studies showing that the public is particularly wary of CAV adoption, it remains to be seen whether NHTSA will seek to return to its technology-forcing origins. While the auto industry has traditionally preferred voluntary adoption of new technologies, it may be the case that government mandates would help ease public concern about CAV safety, speed the adoption of this new technology, and ultimately save lives.

Guest Blog by Jesse Halfon

Last month, two California Highway Patrol (CHP) officers made news following an arrest for drunk driving. What made the arrest unusual was that the officers initially observed the driver asleep behind the wheel while the car, a Tesla Model S, drove 70 mph on Autopilot, the vehicle’s semi-automated driving system.

Much of the media coverage about the incident revolved around the CHP maneuver to safely bring the vehicle to a stop. The officers were able to manipulate Tesla Autopilot to slow down and ultimately stop mid-highway using two patrol vehicles, one in front and one behind the ‘driverless’ car.

But USC Law Professor Orin Kerr mused online about a constitutional quandary relating to the stop, asking, “At what point is a driver asleep in an electric car that is on autopilot “seized” by the police slowing down and stopping the car by getting in front of it?” This question centered around when a person asleep was seized,a reasonable 4th Amendment inquiry given the U.S. Supreme Court standard that a seizure occurs when a reasonable person would not have felt ‘free to leave’ or otherwise terminate the encounter with law enforcement.[1] 

Kerr’s issue was largely hypothetical given that the police in this situation unquestionably had the legal right to stop the vehicle (and thereby seize the driver) based on public safety concerns alone.

However, a larger 4th Amendment question regarding semi-automated vehicles looms. Namely, what constitutes’reasonable suspicion’ to stop the driver of a vehicle on Autopilot for a traditional traffic violation like ‘reckless driving’ or ‘careless driving’?[2] Though there are no current laws that prescribe the safe operation of a semi-autonomous vehicle, many common traffic offenses are implicated by the use of automated driving features.

Some ‘automated’ traffic violations will be unchanged from the perspective of law enforcement. For example, if a vehicle on Autopilot[3] fails to properly stay inits lane, the officer can assess the vehicle’s behavior objectively and ticket the driver who is ultimately responsible for safe operation of the automobile.Other specific traffic violations will also be clear-cut. New York, for example still requires by statute that a driver keep at least one hand on the wheel.[4] Many states ban texting while driving, which though often ambiguous, allows for more obvious visual cues for an officer to assess.

However, other traffic violations like reckless driving[5] will be more difficult to assess in the context of semi-automated driving.

YouTube is filled with videos of people playing cards, dancing, and doing various other non-driving activities in their Teslas while Autopilot is activated. While most of these videos are performative, real-world scenarios are commonplace. Indeed, for many consumers, the entire point of having a semi-autonomous driving system is to enable safe multi-tasking while behind the wheel.

Take for example, the Tesla driver who is seen biting into a cheeseburger with both hands on the sandwich (and no hands on the wheel). Is this sufficient for an officer to stop a driver for careless driving?Or what about a driver writing a note on a piece of paper in the center console while talking on the phone. If during this activity, the driver’s eyes are off the road for 3-4 seconds, is there reasonable suspicion of ‘reckless driving’that would justify a stop? 5-6 seconds? 10? 20?

In these types of cases, the driver may argue that they were safely monitoring their semi-automated vehicle within the appropriate technological parameters. If a vehicle is maintaining a safe speed and lane-keeping on a low traffic highway, drivers will protest – how can they be judged as ‘careless’ or ‘reckless’ for light multi-tasking or brief recreation while the car drives itself?

The 4th Amendment calculus will be especially complicated for officers given that they will be unable to determine from their vantage point whether a semi-autonomous system is even activated. Autopilot is an optional upgrade for Tesla vehicles and vehicles that are equipped with L2/L3 systems will often be driven inattentively without the ‘driverless’ feature enabled. Moreover, most vehicles driven today don’t even have advanced automated driving features.

A Tesla driver whose hands are off the steering wheel could be safely multi-tasking using Autopilot. But they could also be steering with their legs or not at all. This leaves the officer, tasked with monitoring safe driving for public protection, in a difficult situation. It also leaves drivers, who take advantage of semi-automated systems, vulnerable to traffic stops that are arguably unnecessary and burdensome.

Of course, a driver may succeed in convincing a patrol office not to issue a ticket by explaining their carefully considered use of the semi-automated vehicle. Or the driver could have a ‘careless driving’ ticket dismissed in court using the rational of safely using the technology. But once a police-citizen interaction is initiated, the stakes are high.

Designing a semi-automated vehicle that defines the parameters of safe driving is complex. Crafting constitutional jurisprudence that defines the parameters police behavior may be even more complex. Hopefully the Courts are up to the task of navigating this challenging legal terrain.

Jesse Halfon is an attorney in Dykema’s Automotive and Products Liability practice group and a member of its Mobility and Advanced Transportation Team.


[1] United States v. Mendenhall, 446 U.S. 544, 554 (1980); United States v. Drayton, 536 U.S. 194, 202 (2002);Florida v. Bostick, 501 U.S. 429, 435-36 (1991).

[2] Some traffic violations are misdemeanors or felonies. To make an arrest in public for a misdemeanor, an officer needs probable cause and the crime must have occurred in the officer’s presence.  For a Terry stop involving a traffic misdemeanor, only reasonable suspicion is required.

[3] Tesla Autopilot is one of several semi-automated systems currently on the market. Others,including Cadillac Super Cruise Mercedes-Benz Drive Pilot and Volvo’s Pilot Assist offer comparable capabilities.

[4] New York Vehicle and Traffic Law § 1226.

[5] Most states have a criminal offense for reckless driving. Michigan’s statute is representative and defines reckless driving as the operation of a vehicle “in willful or wanton disregard for the safety of persons or property”.  See Michigan Motor Vehicle Code § 257.626. Michigan also has a civil infraction for careless driving that is violated when a vehicle is operated in a ‘careless or negligent manner’. See Michigan Motor Vehicle Code § 257.626b

California has become the second state in the nation to permit connected and automated vehicles (CAVs) to operate on public roads without a safety driver. With the recent announcement that Waymo has obtained approval to test driverless CAVs in a handful of Northern California communities, the state joins Arizona on the leading edge of the driverless vehicle revolution. Similar to the Arizona experiment, which I wrote about recently, California has positioned itself to play a key role in shaping the speed and direction of growth in the CAV industry.

California’s regulatory apparatus, while not without its critics, will provide an interesting contrast to the relatively lax system enacted by Arizona. The remainder of this post will explore the key differences between these two approaches to governance of CAVs.

Arizona requires merely that CAV operators submit written confirmation to the State that each vehicle complies with all relevant federal law, that it is capable of reaching a “minimal risk condition” when necessary, and that it be capable of complying with traffic and safety laws. California, by contrast, has a handful of more specific requirements. In addition to the need to comply with federal law, California requires that driverless CAV operators:

  • Notify local authorities in communities where testing will take place
  • Submit a law enforcement interaction plan
  • Certify that the vehicles meet the autonomous vehicle Level 4 or 5 definition of the Society for Automotive Engineers
  • Maintain a communication link between the vehicle and a remote operator
  • Inform the DMV of the intended operational design domain
  • Submit an annual disengagement report to the DMV
  • Submit collision reports to the DMV within 10 days of a crash

In addition to these requirements for driverless vehicle testing, California has a further set of requirements before driverless CAVs can be certified for public use. This supplemental set of requirements generally revolves around data recording and security against cyber-attacks.

Critics have argued that even California’s approach to CAVs is not safety conscious enough. Consumer Watchdog, a California public interest group, has raised an alarm that the state is merely taking Waymo’s word that it has met requirements “without any real verification.” The organization has also suggested that California’s regulations are not substantively strict enough, arguing that they are turning people “into human guinea pigs for testing [Waymo’s] robot cars.” Proponents though, argue that the safety concerns are overblown in light of the potential for vast improvements relative to error-prone human drivers.

While the debate over how much regulation is proper persists, it is notable how quickly California seems to be following in the footsteps of Arizona in the rollout of CAVs. One key argument in favor of Arizona’s light touch regulation is that it has positioned the state to take the lead in development of this new technology. California’s oversight, while not enough for some, is undoubtedly more rigorous than that of its neighbor to the east. Arizona’s approach does appear to have given the state a short head start in the CAV race. California’s progress, though, indicates that modest increases in state oversight may not present a substantial barrier to the adoption of this new technology.

Tesla’s enthusiastic marketing of its Autopilot feature may be landing the company in legal hot water. Last week, a Florida man sued the car manufacturer after his Model S crashed into a stalled vehicle at high speed. The driver, who allegedly suffered spinal and brain injuries, claims that Tesla’s “purposefully manipulative sales pitch” had duped him and other Tesla owners into the mistaken belief that their vehicles can travel on the highway almost without supervision. The outcome of the case may carry key lessons not only for Tesla, but for all automakers as they develop more autonomous features.

This isn’t the first time Tesla has faced legal challenges related to the Autopilot feature. In May, the company paid $5 million to settle a class action suit claiming its Autopilot 2.0 upgrade was unusable and dangerous. This case, while currently only involving one plaintiff, could have even broader ramifications. The plaintiff’s products liability suit claims that the company has systematically duped consumers through a “pervasive national marketing campaign.” If successful, this suit could open the door to recovery for others who crash while using Autopilot.

While Tesla has typically been more grandiose in their advertising techniques than more traditional automakers, their legal challenges do serve to highlight the struggles that auto manufacturers will face in the coming years. This year alone, Ford has packaged its driver assist features into a system called Co-Pilot 360 and GM has called its Super Cruise system “the world’s first true hands-free driver assistance feature for the freeway.” In the near future, other car manufacturers are expected to join these companies in developing ever more autonomous features.

As the auto industry collectively drives toward the creation of truly autonomous vehicles, there will be an understandable temptation to hype up every new technological feature. Arguably, many of these features will increase auto safety when used properly. Certainly, road testing such features is a key step on the path towards fully driverless cars. The challenges facing Tesla should serve as a warning though. Companies need to be cautious in describing their driver-assist technologies, and ensuring that customers understand the limits of such new features. Doing so will have the dual benefit of reminding drivers that they should still be in control of the vehicle, and shielding themselves from the type of liability Tesla faces today.

 

By the end of this year, Alphabet subsidiary Waymo plans to launch one of the nation’s first commercial driverless taxi services in Phoenix, Arizona. As preparations move forward, there has been increasing attention focused on Arizona’s regulatory scheme regarding connected and automated vehicles (CAVs), and the ongoing debate over whether and how their deployment should be more tightly controlled.

In 2015, Arizona Governor Doug Ducey issued an executive order directing state agencies to “undertake any steps necessary to support the testing and operation of self-driving vehicles” on public roads in the state. The order helped facilitate the Phoenix metro area’s development as a key testing ground for CAV technology and laid the groundwork for Waymo’s pioneering move to roll out its driverless service commercially in the state. It has also been the target of criticism for not focusing enough on auto safety, particularly in the aftermath of a deadly crash involving an Uber-operated CAV in March.

As the technology advances and the date of Waymo’s commercial rollout approaches, Governor Ducey has issued a new executive order laying out a few more requirements that CAVs must comply with in order to operate on Arizona’s streets. While the new order is still designed to facilitate the proliferation of CAVs, it includes new requirements that CAV owners affirm that the vehicles meet all relevant federal standards, and that they are capable of reaching a “minimal risk condition” if the autonomous system fails.

Along with these basic safety precautions, the order also directs the Arizona Departments of Public Safety and Transportation to issue a protocol for law enforcement interaction with CAVs. This protocol is a public document intended both to guide officers in interactions with CAVs and to facilitate owners in designing their cars to handle those interactions. The protocol, issued by the state Department of Transportation in May, requires CAV operators to file an interaction protocol with the Department explaining how the vehicle will operate during emergencies and in interactions with law enforcement. As CAVs proliferate, a uniform standard for police interactions across the industry may become necessary for purposes of administrative efficiency. If and when that occurs, the initial standard set by Waymo in Arizona is likely to bear an outsized influence on the nationwide industry.

Critics have called the new executive order’s modest increase in safety requirements too little for such an unknown and potentially dangerous technology. Even among critics however, there is no agreement as to how exactly CAVs should be regulated. Many have argued for, at minimum, more transparency from the CAV companies regarding their own safety and testing procedures. On the other hand, advocates of Arizona’s relaxed regulatory strategy suggest that public unease with CAVs, along with the national news coverage of each accident, will be enough to push companies to adopt their own stringent testing and safety procedures.

This more hands-off regulatory approach will get its first close-up over the next few months in Arizona. The results are likely to shape the speed and direction of growth in the industry for years to come.

 

As per my last post, our law school problem solving class is looking at problems created by the interaction between connected and automated vehicles and other roadway users. This article from The Information offers some interesting insights on the difficulties Waymo is facing as it deploys its robo-taxi service in Phoenix.  Basically, the problem comes down to . . . people.  A blurb from the article:

The biggest issue for Waymo’s vans and other companies’ prototypes is human drivers or pedestrians who fail to observe traffic laws. They do so by speeding, by not coming to complete stops, by turning illegally, texting while driving, or with an endless array of other moving violations that have become an accepted part of driving. Waymo’s prototypes sometimes respond to these maneuvers by stopping abruptly in ways that human drivers don’t anticipate. As a result, human drivers from time to time have rear-ended the Waymo vans.

Cite as: Daniel A. Crane, The Future of Law and Mobility, 2018 J. L. & Mob. 1.

Introduction

With the launch of the new Journal of Law and Mobility, the University of Michigan is recognizing the transformative impact of new transportation and mobility technologies, from cars, to trucks, to pedestrians, to drones. The coming transition towards intelligent, automated, and connected mobility systems will transform not only the way people and goods move about, but also the way human safety, privacy, and security are protected, cities are organized, machines and people are connected, and the public and private spheres are defined.

Law will be at the center of these transformations, as it always is. There has already been a good deal of thinking about the ways that law must adapt to make connected and automated mobility feasible in areas like tort liability, insurance, federal preemption, and data privacy. 99 99. See, e.g., Daniel A. Crane, Kyle D. Logue & Bryce Pilz, A Survey of Legal Issues Arising from the Deployment of Autonomous and Connected Vehicles, 23 Mich. Tel. & Tech. L. Rev. 191 (2017). × But it is also not too early to begin pondering the many implications for law and regulation arising from the technology’s spillover effects as it begins to permeate society. For better or worse, connected and automated mobility will disrupt legal practices and concepts in a variety of ways additional to the obvious “regulation of the car.” Policing practices and Fourth Amendment law, now so heavily centered on routine automobile stops, will of necessity require reconsideration. Notions of ownership of physical property (i.e., an automobile) and data (i.e., accident records) will be challenged by the automated sharing economy. And the economic and regulatory structure of the transportation network will have to be reconsidered as mobility transitions from a largely individualistic model of drivers in their own cars pursuing their own ends within the confines of general rules of the road to a model in which shared and interconnected vehicles make collective decisions to optimize the system’s performance. In these and many other ways, the coming mobility revolution will challenge existing legal concepts and practices with implications far beyond the “cool new gadget of driverless cars.”

Despite the great importance of the coming mobility revolution, the case for a field of study in “law and mobility” is not obvious. In this inaugural essay for the Journal of Law and Mobility, I shall endeavor briefly to make that case.

I. Driverless Cars and the Law of the Horse

A technological phenomenon can be tremendously important to society without necessarily meriting its own field of legal study because of what Judge Frank Easterbrook has described as “the law of the horse” problem. 100 100. Frank H.Easterbrook,Cyberspace and the Law of the Horse, 1996 U. Chi. Legal F. 207, 207-16. × Writing against the burgeoning field of “Internet law” in the early 1990s, Easterbrook argued against organizing legal analysis around particular technologies:

The best way to learn the law applicable to specialized endeavors is to study general rules. Lots of cases deal with sales of horses; others deal with people kicked by horses; still more deal with the licensing and racing of horses, or with the care veterinarians give to horses, or with prizes at horse shows. Any effort to collect these strands into a course on “The Law of the Horse” is doomed to be shallow and to miss unifying principles. 101 101. Id. ×

Prominent advocates of “Internet law” as a field rebutted Easterbrook’s concern, arguing that focusing on cyberlaw as a field could be productive to understanding aspects of this important human endeavor in ways that merely studying general principles might miss. 102 102. Lawrence Lessig, The Law of the Horse: What Cyberlaw Might Teach, 113 Harv. L. Rev. 501 (1999). × Despite Easterbrook’s protestation, a distinct field of cyberlaw has grown up in recent decades.

“The law of the horse” debate seems particularly apt to the question of law and mobility since the automobile is the lineal successor of the horse as society’s key transportation technology. Without attempting to offer a general solution to the “law of the horse” question, it is worth drawing a distinction between two different kinds of disruptive technologies—those in which the technological change produces social changes indirectly and without significant possibilities for legal intervention, and those in which law is central to the formation of the technology itself.

An example of the first species of technological change is air conditioning. The rise of air conditioning in the mid-twentieth century had tremendous effects on society, including dramatic increases in business productivity, changes in living patterns as people shifted indoors, and the extension of retail store hours and hence the growing commercialization of American culture. 103 103. Stan Cox, Losing Our Cool: Uncomfortable Truths About Our Air-Conditioned World (and Finding New Ways to Get Through the Summer) (2012). × The South’s share of U.S. population was in steady decline until the 1960s when, in lockstep with the growth of air conditioning and people’s willingness to settle in hot places, the trend abruptly reversed and the South’s share grew dramatically. 104 104. Paul Krugman, Air Conditioning and the Rise of the South, New York Times March 28, 2015. × The political consequences were enormous—from Richard Nixon through George W. Bush, every elected President hailed from warm climates.

One could say, without exaggeration, that the Willis Carrier’s frigid contraption exerted a greater effect on American business, culture, and politics than almost any other invention in the twentieth century. And, yet, it would seem silly to launch a field of study in “law and air conditioning.” Air conditioning’s social, economic, and political effects were largely indirect—the result of human decisions in response to the new circumstances created by the new technology rather than an immediate consequence of the technology itself. Even if regulators had foreseen the dramatic demographic effects of air conditioning’s spread, there is little they could have done (short of killing or limiting the technology) to mediate the process of change by regulating the technology.

Contrast the Internet. Like air conditioning, the Internet has had tremendous implications for culture, business, and politics, but unlike air conditioning, many of these effects were artifacts of design decisions regarding the legal architecture of cyberspace. From questions of taxation of online commercial transactions, 105 105. See, e.g., John E. Sununu, The Taxation of Internet Commerce, 39 Harv. J. Leg. 325 (2002). × to circumvention of digital rights management technologies, 106 106. See, e.g., David Nimmer, A Rif on Fair Use in the Digital Millenium Copyright Act, 148 U. Pa. L. Rev. 673 (2000). × to personal jurisdiction over geographically remote online interlocutors, 107 107. Note, No Bad Puns: A Different Approach to the Problem of Personal Jurisdiction and the Internet, 116 Harv. L. Rev. 1821 (2003). × and in countless other ways, a complex of legal and regulatory decisions created the modern Internet. From the beginning, law was hovering over the face of cyberspace. Al Gore may not have created the Internet, but lawyers had as much to do with it as did engineers.

The Internet’s legal architecture was not established at a single point in time, by a single set of actors, or with a single set of ideological commitments or policy considerations. Copyright structures were born of the contestation among one set of stakeholders, which was distinct from the sets of stakeholders contesting over tax policy, net neutrality, or revenge porn. And yet, the decisions made in separate regulatory spheres often interact in underappreciated ways to lend the Internet its social and economic character. Tax policy made Amazon dominant in retail, copyright policy made Google dominant in search, and data protection law (or its absence) made Facebook dominant in social media—with the result that all three have become antitrust problems.

Whether or not law students should be encouraged to study “Internet law” in a discrete course, it seems evident with the benefit of thirty years of hindsight that the role of law in mediating cyberspace cannot be adequately comprehended without a systemic inquiry. Mobility, I would argue, will be much the same. While the individual components of the coming shift toward connectivity and automation—i.e., insurance, tort liability, indemnification, intellectual property, federal preemption, municipal traffic law, etc.—will have analogues in known circumstances and hence will benefit from consideration as general questions of insurance, torts, and so forth, the interaction of the many moving parts will produce a novel, complex ecosystem. Given the potential of that ecosystem to transform human life in many significant ways, it is well worth investing some effort in studying “law and mobility” as a comprehensive field.

II. An Illustration from Three Connected Topics

It would be foolish to attempt a description of mobility’s future legal architecture at this early stage in the mobility revolution. However, in an effort to provide some further motivation for the field of “law and mobility,” let me offer an illustration from three areas in which legal practices and doctrines may be affected in complex ways by the shift toward connected and automated vehicles. Although these three topics entail consideration of separate fields of law, the technological and legal decisions made with respect to them could well have system-wide implications, which shows the value of keeping the entire system in perspective as discrete problems are addressed.

A. Policing and Public Security

For better or for worse, the advent of automated vehicles will redefine the way that policing and law enforcement are conducted. Routine traffic stops are fraught, but potentially strategically significant, moments for police-citizen interactions. Half of all citizen-police interactions, 108 108. Samuel Walker, Science and Politics in Police Research: Reflections on their Tangled Relationship, 593 Annals Am. Acad. Pol. & Soc. Sci. 137, 142 (2004); ATTHEW R. DUROSE ET. AL., U.S. DEP’T OF JUSTICE, OFFICE OF JUSTICE PROGRAMS, BUREAU OF JUSTICE STATISTICS, CONTACTS BETWEEN POLICE AND THE PUBLIC, 2005, 1 (2007). × more than forty percent of all drug arrests, 109 109. David A. Sklansky,Traffic Stops, Minority Motorists, and the Future of the Fourth Amendment, 1997SUP. CT. REV. 271, 299. × and over 30% of police shootings 110 110. Adams v. Williams, 407 U.S. 143, 148 n.3 (1972). × occur in the context of traffic stops. Much of the social tension over racial profiling and enforcement inequality has arisen in the context of police practices with respect to minority motorists. 111 111. Ronnie A. Dunn, Racial Profiling: A Persistent Civil Rights Challenge Even in the Twenty-First Century, 66 Case W. Res. L. Rev. 957, 979 (2016) (reporting statistics on disproportionate effects on racial minorities of routine traffic stops). × The traffic stop is central to modern policing, including both its successes and pathologies.

Will there continue to be routine police stops in a world of automated vehicles? Surely traffic stops will not disappear altogether, since driverless cars may still have broken taillights or lapsed registrations. 112 112. See John Frank Weaver, Robot, Do You Know Why I Stopped You?. × But with the advent of cars programmed to follow the rules of the road, the number of occasions for the police to stop cars will decline significantly. As a general matter, the police need probable cause to stop a vehicle on a roadway. 113 113. Whren v. U.S., 517 U.S. 806 (1996). × A world of predominantly automated vehicles will mean many fewer traffic violations and hence many fewer police stops and many fewer police-citizen interactions and arrests for evidence of crime discovered during those stops.

On the positive side, that could mean a significant reduction in some of the abuses and racial tensions around policing. But it could also deprive the police of a crime detection dragnet, with the consequence either that the crime rate will increase due to the lower detection rate or that the police will deploy new crime detection strategies that could create new problems of their own.

Addressing these potentially sweeping changes to the practices of policing brought about by automated vehicle technologies requires considering both the structure of the relevant technology and the law itself. On the technological side, connected and automated vehicles could be designed for easy monitoring and controlling by the police. That could entail a decline in privacy for vehicle occupants, but also potentially reduce the need for physical stops by the police (cars that can be remotely monitored can be remotely ticketed) and hence some of the police-citizen roadside friction that has dominated recent troubles.

On the legal side, the advent of connected and automated vehicles will require rethinking the structure of Fourth Amendment law as required to automobiles. At present, individual rights as against searches and seizures often rely on distinctions between drivers and passengers, or owners and occupants. For example, a passenger in a car may challenge the legality of the police stop of a car, 114 114. Brendlin v. California, 551 U.S. 249 (2007). × but have diminished expectations of privacy in the search of the vehicle’s interior if they are not the vehicle’s owners or bailees. 115 115. U.S. v. Jones, 565 U.S. 400 (2012). × In a mobility fleet without drivers and (as discussed momentarily) perhaps without many individual owners, these conceptions of the relationship of people to cars will require reconsideration.

B. Ownership, Sharing, and the Public/Private Divide

In American culture, the individually owned automobile has historically been far more than a transportation device—it has been an icon of freedom, mobility, and personal identity. As Ted McAllister has written concerning the growth of automobile culture in the early twentieth century:

The automobile squared perfectly with a distinctive American ideal of freedom—freedom of mobility. Always a restless nation, with complex migratory patterns throughout the 17th, 18th, and 19thcenturies, the car came just as a certain kind of mobility had reached an end with the closing of the frontier. But the restlessness had not ended, and the car allowed control of space like no other form of transportation. 116 116. Ted v. McAllister, Cars, Individualism, and the Paradox of Freedom in a Mass Society. ×

Individual car ownership has long been central to conceptions of property and economic status. The average American adult currently spends about ten percent of his or her income on an automobile, 117 117. Máté Petrány, This Is How Much Americans Spend on their Cars. × making it by far his or her most expensive item of personal property. The social costs of individual automobile ownership are far higher. 118 118. Edward Humes, The Absurd Primacy of the Automobile in American Life; Robert Moor, What Happens to the American Myth When You Take the Driver Out of It?. ×

The automobile’s run as an icon of social status through ownership may be ending. Futurists expect that the availability of on-demand automated vehicle service will complete the transition from mobility as personal property to mobility as a service, as more and more households stop buying cars and rely instead on ride sharing services. 119 119. Smart Cities and the Vehicle Ownership Shift. × Ride sharing companies like Uber and Lyft have long been on this case, and now automobile manufacturers are scrambling to market their vehicles as shared services. 120 120. Ryan Felton, GM Aims to Get Ahead of Everyone with Autonomous Ride-Sharing Service in Multiple Cities by 2019. × With the decline of individual ownership, what will happen to conceptions of property in the physical space of the automobile, in the contractual right to use a particular car or fleet of automobiles, and in the data generated about occupants and vehicles?

The coming transition from individual ownership to shared service will also raise important questions about the line between the public and private domains. At present, the “public sphere” is defined by mass transit whereas the individually owned automobile constitutes the “private sphere.” The public sphere operates according to ancient common carrier rules of universal access and non-discrimination, whereas a car is not quite “a man’s castle on wheels” for constitutional purposes, 121 121. See Illinois v. Lidster, 540 U.S. 419, 424 (2004) (“The Fourth Amendment does not treat a motorist’scaras hiscastle.”). × but still a non-public space dominated by individual rights as against the state rather than public obligations. 122 122. E.g., Byrne v. Rutledge, 623 F.3d 46 (2d Cir. 2010) (holding the motor vehicle license plates were nonpublic fora and that state’s ban on vanity plates referencing religious topic violated First Amendment). × As more and more vehicles are held and used in shared fleets rather than individual hands, the traditional line between publicly minded “mass transit” and individually minded vehicle ownership will come under pressure, with significant consequences for both efficiency and equality.

C. Platform Mobility, Competition, and Regulation

The coming transition toward ride sharing fleets rather than individual vehicle ownership described in the previous section will have additional important implications for the economic structure of mobility—which of course will raise important regulatory questions as well. At present, the private transportation system is highly atomistic. In the United States alone, there are 264 million individually owned motor vehicles in operation. 123 123. U.S. Dep’t of Energy, Transportation Energy Data Book, Chapter 8, Household Vehicles and Characteristics, Table 8.1, Population and Vehicle Profile, https://cta.ornl.gov/data/chapter8.shtml (last visited May 29, 2018). × For the reasons previously identified, expect many of these vehicles to shift toward corporate-owned fleets in coming years. The question then will be how many such fleets will operate—whether we will see robust fleet-to-fleet competition or instead the convergence toward a few dominant providers as we are seeing in other important areas of the “platform economy.”

There is every reason to believe that, before too long, mobility will tend in the direction of other monopoly or oligopoly platforms because it will share their economic structure. The key economic facts behind the rise of dominant platforms like Amazon, Twitter, Google, Facebook, Microsoft, and Apple are the presence of scale economies and network effects—system attributes that make the system more desirable for others users as new users join. 124 124. See generally DavidS.Evans& Richard Schmalensee, A Guide to the Antitrust Economics of Networks, Antitrust, Spring 1996, at 36; Michael L. Katz & Carl Shapiro, Systems Competition andNetworkEffects, 8 J. Econ. Persp. 93 (1994). × In the case of the mobility revolution, a number of features are suggestive of future scale economies and network effects. The more cars in a fleet, the more likely it is that one will be available when summoned by a user. The more cars connected to other cars in a fleet, the higher the quality of the information (on such topics as road and weather conditions and vehicle performance) available within the fleet and the steeper the machine learning curve.

As is true with other platforms, the mere presence of scale economic and network effects does not have to lead inexorably to market concentration or monopoly. Law and regulation may intervene to mitigate these effects, for example by requiring information sharing or interconnection among rival platforms. But such mandatory information sharing or interconnection obligations are not always advisable, as they can diminish a platform’s incentives to invest in its own infrastructure or otherwise impair incentives to compete.

Circling back to the “law of the horse” point raised at the outset, these issues are not, of course, unique to law and mobility. But this brief examination of these three topics—policing, ownership, and competition—shows the value of considering law and mobility as a distinct topic. Technological, legal, and regulatory decisions we make with respect to one particular set of problems will have implications for distinct problems perhaps not under consideration at that moment. For example, law and technology will operate conjunctively to define the bounds of privacy expectations in connected and automated vehicles, with implications for search and seizure law, property and data privacy norms, and sharing obligations to promote competition. Pulling a “privacy lever” in one context—say to safeguard against excessive police searches—could have spillover effects in another context, for example by bolstering a dominant mobility platform’s arguments against mandatory data sharing. Although the interactions between the different technological decisions and related legal norms are surely impossible to predict or manage with exactitude, consideration of law and mobility as a system will permit a holistic view of this complex, evolving ecosystem.

Conclusion

Law and regulation will be at the center of the coming mobility revolution. Many of the patterns we will observe at the intersection of law and the new technologies will be familiar—at least if we spend the time to study past technological revolutions—and general principles will be sufficient to answer many of the rising questions. At the same time, there is a benefit to considering the field of law and mobility comprehensively with an eye to understanding the often subtle interactions between discrete technological and legal decisions. The Journal of Law and Mobility aims to play an important role in this fast-moving space.


Frederick Paul Furth, Sr. Professor of Law, University of Michigan. I am grateful for helpful comments from Ellen Partridge and Bryant Walker Smith. All errors are my own.