Phillip Washburn is a third-year law student at the University of Michigan Law School. He is a Research Editor for the Journal of Law and Mobility. He can be reached at email@example.com or on Twitter: @PhilWashburn.
Micromobility usage was at an all-time high before March 2020. The culmination of decades of growth and industry involvement in the United States resulted in nearly 350 million rides taken on shared bikes and scooters since 2010. The National Association of City Transportation Officials (NACTO) reported this astounding statistic in their Shared Micromobility in the U.S.: 2019 report.
In 2019, more than 134 million shared trips were taken, 60% higher than trips taken in 2018. NACTO reported the average trip in 2019 was 11-12 minutes, covering a distance of 1-1.5 miles. These numbers are significant because they represent trips that may otherwise have been taken by car. 46% of all U.S. car trips are under 3 miles. Replacing short vehicle trips with micromobility trips helps decrease carbon consumption. It can also increase access to new forms of transportation for low socioeconomic status and minority communities in cities.
However, micromobility in cities can and should be doing better. The adoption rates for Capital Bikeshare, a cheap and widely available bike-sharing service in Washington, D.C., is significantly lower among the Black and African-American population than among the White population. This is surprising at first when you consider that micromobility enjoys a positive perception from diverse groups of people.
However, positive perception does not always translate into access. Micromobility needs to be made widely available to all populations in the cities in which they operate. Many bike and scooter sharing services are dockless, and thus can be left almost anywhere. Many scooter companies rely on contract workers to pick up scooters at night when the batteries are dead, charge them overnight at their residence, and redistribute the scooters in the morning. This method allows the scooter companies to rebalance their fleet, and direct where scooters are first released in the morning, and how many scooters are dropped off in each area.
Logically, companies have figured out where scooters are ridden the most. They have access to incredible real-time demand and use data. But this can lead to a feedback loop. Suppose early micromobility adopters are predominately white, male, and young. In that case, scooters will be placed where that demographic is likely to find them first in the morning. In cities where scooter numbers have a firm cap, access to scooters is a zero-sum game for things like early morning work commutes or grocery runs.
One solution to the access problem is having cities work with micromobility companies to ensure scooters’ placement is not only profitable but equitable. Scooters should be located in all communities, not merely in ones that have shown early to use micromobility most frequently. These goals can be accomplished by cities working directly with the providers to access the data and share public-private goals. It could also be done by working with unbiased third-parties to make recommendations for what policies will make micromobility systems most widely available.
Something the current pandemic has provided micromobility companies is a different picture. The NACTO report found that micromobility usage in cities was utilized at higher rates when made free to essential workers. The most-used Citi bike stations were at hospitals in April. Black workers are disproportionally found among essential workers, and essential workers’ utilizing micromobility systems revealed new commuter patterns. The pandemic may provide a picture of what access should look like while simultaneously exposing micromobility systems to underserved communities as cheap and viable transportation options. There is clearly work to be done, and the information is out there. It is time to put the information to use.
An IBM report released earlier this month revealed some significant changes in consumer sentiment and public willingness to use certain mobility methods as a result of COVID-19. The study polled more than 25,000 adults during the month of April. Of the respondents that regularly used buses, subways, or trains: 20 percent said they no longer would utilize those options; an additional 28 percent said they would use public transportation less often. 17 percent of people surveyed said they will use their personal vehicle more; 25 percent of that 17 percent said it will be their exclusive method of transportation going forward.
Consumer perception of public transportation and the ways we move has shifted dramatically in just three short months. These results indicate that a significant number of U.S. consumers intend to drastically change the ways they travel in the aftermath of COVID-19. If these sentiments remain in place in the coming years, the decrease in public transportation ridership would mean decreased fee collections, which can lead to several options for cities to fund public transportation, including (1) an increase in ridership fees, (2) an increase in general tax revenue devoted to public transportation, or (3) a decrease in service offerings. All of these options are undesirable, especially in cities where private vehicle ownership is low, and many workers may have no option other than public transportation. The cities with the largest annual ridership numbers for subway or metro are New York City, Washington D.C., Chicago, Boston, and the San Francisco Bay Area.
Removing 20 percent of public transportation riders completely and decreasing the usage of nearly 30 percent more would be financially catastrophic for any city transit authority. In 2019, the New York MTA brought in nearly $17 Billion. The current decrease in ridership (down 74 percent) has already required the MTA to seek billions in aid from the federal government and led to a first-ever decrease in working hours to sanitize trains overnight. A sustained decrease of more than 30 percent of rides per year would require a systemic overhaul of the metro system or some other drastic measures.
While some respondents indicated they will use their personal vehicles more, it is clear that in cities where public transportation is most utilized, many people do not have access to a personal vehicle. This will place a difficult decision on many underserved and minority communities: return to using public transportation and face an elevated risk of potential infection, struggle to find a job closer to home to avoid transportation, or save for a personal vehicle to avoid public transportation. Owning a vehicle in major cities can be prohibitively expensive for low-income households, and affordable parking can be nearly impossible to find. As transit authorities raise prices to compensate for lost riders, more riders may depart as the cost of ridership becomes too high for their budget. This could lead to a death spiral for public transportation. These systems simply cannot sustain 90 percent ridership decreases.
The same IBM survey also found that the decision to buy a personal vehicle after COVID-19 was “greatly” influenced by a constraint on their personal finances for more than 33 percent of respondents. 25 percent said they would hold off on buying a vehicle for more than 6 months. So for many people who wish to stop using public transportation, there is no safe and affordable option immediately available. Some may point to rideshare services as a safer alternative to the cramped quarters of public transportation. But according to the survey, of the respondents who used rideshare apps and services already, more than 50 percent said they would use the services less, or stop entirely. Uber and Lyft are going to see an incredible drop off in ridership; Uber and Lyft both halted their carpooling services in March. Uber trips were already down 70 percent in some cities in March. These numbers are sure to increase, and the companies will recover financially due to the increase in demand for UberEats during this crisis. However, the surge in ridership seen in recent years will take many years to reach 2019 peaks.
Finally, the IBM survey also asked about working from home, a topic I wrote about at the end of March. Around 40 percent of respondents indicated they feel strongly that their employer should provide employees the option to opt-in to remote working from home going forward. 75 percent indicated they would like to continue working from home at least occasionally, and more than 50 percent indicated they would like working from home to be their primary work method. Perhaps companies will heed the desires of their employees. It is unlikely that many companies will offer the “work from home, forever” option that Twitter and Facebook have provided. But almost certainly we will see an increase in the ability of employees to work from home, now that their ability to do so has been demonstrated. Especially in cities like New York and San Francisco where the annual cost of office space is more than $13,000 per employee. If more tech companies follow Facebook’s lead and allow many employees to work remotely forever, we may even see housing prices start to decrease in some select areas and a further decrease in public transportation ridership in cities like San Francisco.
Mobility is going to change immensely once this crisis is over, whenever that may be. Public transportation must be overhauled in its current processes and operations if it hopes to regain public confidence and achieve ridership numbers anywhere near 2019 levels during the next decade.
It feels like much longer than two months ago that I first
wrote about the coronavirus, Covid-19. At the time of my first blog post on
the subject, the world had just witnessed China quarantine more than 50 million
people in four weeks. The United States is now under conditions that
significantly exceed that number. As of March 26th, more
than 20 U.S. states have imposed either statewide orders, or partial
orders, for residents to stay at home and shelter in place. Currently, more
million citizens are being urged to stay at home. Social Distancing, Zoom,
and Flatten the Curve have become household names and phrases overnight. As I
write this, millions of citizens are entering their second or third week of
working from home.
As the United States reckons with this outbreak’s severity and we learn to live at a distance, it is crucial to reflect on the unintended secondary effects that have become apparent from en masse “work from home” (“WFH”). Perhaps we can learn something. Perhaps it is just refreshing to note them. Perhaps it could provide inspiration for solutions to many problems we are already facing or will one day face.
Traffic in various cities across the world has decreased
dramatically. With millions of people working from home for the foreseeable
future, there are fewer cars on the road during traditional rush hour peaks.
Traffic in Chicago
is moving as much as 60% faster; traffic in Los Angeles is moving 35% more
quickly than usual. 8am LA rush hour
traffic was flowing around 60 miles per hour, while it typically dips down to
Roughly the same increase in speed was measured during the evening commute
A decrease in rush hour traffic was an easily predicted effect of mass-quarantining. One unintended side effect is the sharp decrease in pollution over major cities. There has been a severe downturn in Nitrogen Dioxide (“NO2“) — a significant pollutant released from the burning of fossil fuels — over Los Angeles, Seattle, and New York. The same significant drop in NO2 has been seen over China around Wuhan, Shanghai, and Beijing.
This decrease in pollution and an increase in traffic speeds
reflect the anticipated benefits of autonomous vehicles. One of the benefits of
AVs is the decrease in emissions that come from daily commutes. Most autonomous
vehicle manufacturers and testers use electric vehicles because the electrical
power the advanced computer systems draw exceeds the capacity of most car
batteries. An increase in electric vehicles on the roads will decrease fossil
fuels being burned while driving, which would likely lead to a reduction in
pollutants (like NO2) over concentrated areas over roadways.
Another benefit of AVs is the decrease in traffic time. Vehicles the communicate with other vehicles (“V2V”) or that communicate with infrastructure (“V2I”) will, over time, allow for fewer slowdowns and higher average driving speeds. Because vehicles can communicate when they are slowing down, speeding up, turning, exiting, etc. the flow of highway traffic will become smoother as fewer interruptions cause human drivers to hit the breaks or come to a standstill. AVs that platoon in synchronization can also increase traffic speeds.
One of the much-touted benefits of autonomous vehicles is
productivity that a driver can experience by freeing up their attention and
hands from needing to drive and monitor their vehicle. Although not to the same
scale, faster traffic speeds from increased WFH translates into less time
wasted on a commute and more time with family and at work. The same is true of
WFH; my daily commute has changed from a 15-minute walk to the law school to a
15-second walk from the kitchen up to my desk.
One metric I am interested in seeing after the Covid-19 social
distancing and en masse WFH is worker productivity while working from home. If
workers are similarly (or more) productive when working from home, we could see
an uptick in companies allowing employees to WFH weekly, or even on an
unlimited basis (subject to approval of some sort). Similarly, if some of the
benefits that AVs seek to bring — decreased traffic, reduced pollution,
increased productivity — can be achieved through en masse WFH, should AV
proponents, and others interested in these benefits, be advocating for more WFH
in other contexts? Companies could even use WFH to advertise their “green”
efforts, by touting the number of driven miles and pollutants they eliminate
annually by requiring employees to WFH periodically.
If we anticipate future events like Covid-19, where social
distancing becomes crucial, keeping WFH skills sharp may become a necessity.
Allowing or requiring workers to stay home one or more days per week could be a
method to keep those skills sharp: being productive at home, efficient communication
online, and keeping in contact with employees and supervisors. As this crisis
continues to unfold, it is essential to remember that this round of social
distancing will not last forever. As a country, we will emerge from this crisis
changed. How we change is interesting to project, but it is similarly essential
to aid in preventing future problems and adapting future solutions.
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.
Vehicles Active in CA
Miles Driven in 2019
Engagements per 1,000 miles
Average Miles Between Engagements
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
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.
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,”
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.
would like to thank Fiona Mulroe for the inspiration to take this approach to
the disengagement report
In January of this year, the
United States Department of Transportation and the National Science &
Technology Council released Automated
Vehicles 4.0: Ensuring American Leadership in Automated Vehicles Technologies
(“AV 4.0”). The report is intended to act as a set of unifying principles
across 38 federal departments, agencies, commissions, and Executive offices. It
offers guidance and an overarching vision to state and local government
agencies, as well as technical experts and industry participants. AV 4.0 builds
on AV 3.0, which was released in 2018, and AV 2.0, which was released in 2017.
Consistent across the three
iterations of Automated Vehicle reports produced under the Trump administration
has been the wholly restrained voluntary/guidance approach, without mandates or
true regulation laid down. This “light
touch” approach recognizes that much of the regulatory action is taking
place at the state level, and voluntarily by industry and other AV
stakeholders. The lack of federal enforceability removes the hope of any
near-term consensus or consistency to the coordination of states and industry
approach to automated vehicles.
As in AV
3.0, AV 4.0 begins with a discussion of guidelines and broad overarching
principles that the federal government will recognize when developing AV
technology. The three Principles and associated sub-areas are:
Protect Users and Communities
(a) Prioritize Safety
(b) Emphasize Security and Cyber Security
(c) Ensure Privacy and Data Security
(d) Enhance Mobility and Accessibility
Promote Efficient Markets
(a) Remain Technology Neutral
(b) Protect American Innovation and Creativity
(c) Modernize Regulations
Facilitate Coordinated Efforts
(a) Promote Consistent Standards and Practices
(b) Ensure a Consistent Federal Approach
(c) Improve Transportation System-Level Effects
While these broader principles
are new to AV 3.0, the sub-areas within each principle are a mixture of old
principles from AV 3.0, combined with some new government focuses. (The new
components are italicized in the above
list) These new components center mainly around the Trump administration’s
desire to “Buy American, Hire American,” and bring in new focuses for
security, cybersecurity, and privacy. The report does indicate that DOT will establish
manufacturing, performance, and operational standards to increase safety in AV
testing and integration. Still, the parameters of these standards remain
However, the majority of the
report is devoted to Section III: U.S.
Government Activities and Opportunities for Collaboration. The driving purpose of the report is to provide
general descriptions of the vast array of government agencies that are
responsible (or will be responsible) for some level of AV-related policies or
subjects. The report detail both the big and small ways that federal agencies,
departments, offices, etc. will play a role in the development and commercialization
of AVs. However, there is no real substantive or specific policy discussion.
The survey of government agency activity (and an appendix
with links to government websites and contacts for agencies responsible for
AV-related policies) are the real substance added. There is no description or
plan of how interagency cooperation will occur, nor is there an overarching
plan for the government’s approach to implementation. AV 4.0 is useful as a
catalog for the various ways the federal government could interact with
AV-policy but gives no further direction to how industry and states should
regulate AVs. The DOT continues to kick the can down the road but has
thankfully provided a clearinghouse of information on which agencies may be
responsible for what activities, and the current efforts underway at the
federal level, particularly on research and funding.
This restrained approach could be a good thing, given the
rapid pace at which the AV industry is developing. However, there is a great
deal more work that needs to be done at the federal level before any of the 10
core principles articulated can be realized. The Department of Transportation
has requested public comment on AV 4.0.
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.
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
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
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,
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
The impact transportation and mobility have on economics,
and human health is clearly demonstrated in the Chinese travel restrictions.
With 50 million citizens under “city-arrest” and the rest of the country
reticent to travel, shockwaves have been felt across the globe. I hope the
Coronavirus crisis can be solved quickly and efficiently, and that the Chinese
can return to a sense of normalcy and free mobility.
As I wrote about last time, the Uniform Law Commission recently passed the Uniform Automated Operation of Vehicles Act. Today, I want to focus on Sections 5, 6, and 7 of that Act, which are titled, respectively, “Vehicle Registration,” “Automated-Driving Provider,” and “Associated Automated Vehicle.” The three sections are meant to complement each other and the generally applicable rules regarding motor vehicle registration in a state. The Comments to Section 7 give a nice synopsis of the way these three sections interact:
Existing state law generally requires the registration of a motor vehicle that is operated on a public road. If an automated vehicle qualifies as such a motor vehicle, it too must be registered. The person seeking that registration—typically the vehicle owner—must comply with all conditions of registration under existing law. Section 5 of this act adds a further condition: For the owner of an automated vehicle to register the vehicle, an automated driving provider must have designated that vehicle as an associated automated vehicle. Section 6 specifies how an entity declares that it is an automated driving provider, and Section 7 specifies how that entity then designates its associated automated vehicles. These three sections work together with existing law to ensure that a properly registered automated vehicle has a legal driver when it is under automated operation. In general, only if an automated vehicle is associated with an automated driving provider may it be registered and operated on public roads.
The Act’s comments are fairly dense, but we can work through them section by section. Under current state law, the owner of a motor vehicle must generally register that vehicle with the state according to state registration rules. The Act retains that requirement for the owner of an automated vehicles, but also adds a new condition of registration. Under Section 5, an automated vehicle may be registered only if an entity has:
(1) declared itself to be an automated driving provider (ADP) (explained in Section 6) and
(2) designated that particular automated vehicles as one of its associated automated vehicles (explained in Section 7).
The vehicle owner and the ADP do
not necessarily have to be the same legal person. The vehicle owner could be an
individual, and the ADP could be an original equipment manufacturer (OEM) like
Ford, Honda, or Tesla. The manufacturer, or some other entity like an insurer
or fleet operator, would declare themselves to be the ADP to the state, and
declare the automated vehicles to be one of its associated vehicles, but the
individual would own and register the car. This has the effect of “compelling”
vehicle manufacturers, or some other entity, to declare themselves to be the
entity legally defined as the driver for any consequences that arise from the
vehicles actions on public roads. The comments to Section 6 clarify:
To become an automated driving provider, an entity must make an affirmative declaration that includes specific representations. This means that, first, an entity does not become an automated driving provider against its will and, second, not every entity can become an automated driving provider. Subsection (a) identifies three basic qualifications, at least one of which a provider must satisfy, and subsection (c) identifies four key requirements, all of which the provider must satisfy.
To qualify as an ADP, an entity must have either participated substantially in the development of the system, submitted safety self-assessments with NHTSA, or be a registered manufacturer with NHTSA. The purpose of these sections is to require registration with the state, ensuring that every automated vehicle on a state’s roads has an entity associated with it, against whom the state can credibly enforce relevant provisions of the state vehicle code.
Manufacturers are not required to register as an ADP. But
they will be incentivized to declare themselves as ADP’s for the simple reason
that if they do not, their customers will be unable to register or use their
vehicles in a state that has adopted the Act. If customers in one state were
unable to register Ford vehicles but could register Honda vehicles, then
everyone in that state would buy Honda automated vehicles and nobody would buy
Ford. Under Section 7, once an ADP has designated an associated automated
vehicle, the association remains until the ADP is not recognized by the state
agency, ceases to exist under principles of corporate law, or affirmatively
withdraws the designation.
This approach is a great way to allow manufacturers of
automated vehicles to select the states in which they wish to be responsible
for their vehicles. If they register as an ADP in Arizona, but not New Mexico,
then their customers will be able to register and drive their vehicles on the
public roads in Arizona, but not New Mexico. This can allow manufacturers to
choose where they accept liability for the automated features of their
However, this could cause problems. Assuming uniform adoption of the Act (which is unlikely), if manufacturers are selective with the states where they register as ADP’s then there could be adjacent states where a manufacturer is an ADP in state X, and not in state Y. If customers in state X drive their automated vehicle across the border into state Y, there could be legal questions if the manufacturer is liable for accidents that occur in state Y, especially if they specifically chose not to register there. This could lead to geofencing at state borders, requirements that shift control back to the human driver as they cross state borders, or a whole host of other potential solutions. These solutions could also cause problems. What if a driver is asleep as the vehicle crosses into a state where that manufacturer has not registered? What if the driver overrides and continues allowing the vehicle to drive? Has liability shifted from the manufacturer to the owner given the owner’s conscious choice?
Questions of tort liability, jurisdiction over manufacturers, and technological work-arounds could abound if OEM’s are selective with their registration as ADPs. But they should be allowed to select where they want to sell their automated vehicles if they will be required to legally be identified as the responsible entity. Sections 5, 6, and 7 of the Automated Vehicle Act will likely cause much debate in states that consider adopting the Act.
The Uniform Law Commission (“ULC”) is a non-governmental body composed of state-selected lawyers who oversee the preparation of “Uniform Laws” to be proposed to the states for adoption. The group’s most well-known body of law will be familiar to any lawyer or law student who paid attention in first-year contracts: the Uniform Commercial Code (UCC). Not all projects of the ULC are as successful as the UCC. In fact, many are never adopted by any state.
The ULC appointed a Drafting Committee on Highly Automated Vehicles in 2017. The Committee recently completed an Automated Vehicles Act, titled “The Uniform Automated Operation of Vehicles Act,” which is a “uniform law covering the deployment of automated driving systems (SAE levels 3 through 5).” The Act is intended to cover a vast array of issues likely to be faced by states in the coming decades as autonomous vehicles become more ubiquitous. The ULC description of the Automated Vehicles Act states:
The Uniform Automated Operation of Vehicles Act regulates important aspects of the operation of automated vehicles. This act covers the deployment of automated vehicles on roads held open to the public by reconciling automated driving with a typical state motor vehicle code. Many of the act’s sections – including definitions, driver licensing, vehicle registration, equipment, and rules of the road – correspond to, refer to, and can be incorporated into existing sections of a typical vehicle code. This act also introduces the concept of automated driving providers (ADPs) as a legal entity that must declare itself to the state and designate the automated vehicles for which it will act as the legal driver when the vehicle is in automated operation. The ADP might be an automated driving system developer, a vehicle manufacturer, a fleet operator, an insurer, or another kind of market participant that has yet to emerge. Only an automated vehicle that is associated with an ADP may be registered. In this way, the Automated Operation of Vehicles Act uses the motor vehicle registration framework that already exists in states – and that applies to both conventional and automated vehicles – to incentivize self-identification by ADPs. By harnessing an existing framework, the act also seeks to respect and empower state motor vehicle agencies.
The final version of the act can be downloaded here.
This Act is a step in the
right direction. It does much of the leg-work for state legislatures to exempt
autonomous vehicles from a variety of state laws by providing language which
can be easily inserted into various state vehicle codes. States can choose to
enact certain parts of the Uniform Act, picking and choosing the sections or
phrases they want and discarding the rest. This is beneficial because it will
likely mean more states will enact some form of AV exemption. However, it also
means there could be substantial variation between states that adopt some but
not all of the Act. The passage of a Uniform Act by the ULC does not ensure
there will be uniform adoption.
The act is not very long,
only 28 pages including all the comments and legislative notes. There are many
sections that deserve a more extensive dive, but I want to begin with a
subsection that relates to a topic I’ve written about before: Platooning. The Act does not include a provision that would legalize
platooning, but it does contain a single provision that addresses state laws
following distance: Section 9 (h). Section 9 covers “Rules of the Road.” Subsection
A provision of [this state’s vehicle code] imposing a minimum following distance other than a reasonable and prudent distance does not apply to the automated operation of an automated vehicle.
The comment to the section
clarifies subsection h:
[T]his section provides that a numerical minimal following-distance requirement does not apply to the automated operation of automated vehicles. These numerical minimums may be unnecessarily large for automated vehicles that react faster than human drivers. However, the common “reasonable and prudent” following-distance requirement continues to apply. This bracketed subsection (h) differs in scope from following-distance legislation enacted in some states to facilitate the platooning of vehicles, particularly commercial trucks, that use advanced technologies but may not necessarily qualify as automated vehicles.
As I’ve written about before,
platooning vehicles that follow at incredibly close distances could be
considered “reasonable and prudent” given the connected nature and quick
response times of the technology. If the Uniform Act were adopted in some
states, it could present the opportunity to argue that there is, or should be,
a reasonable car standard applied to autonomous vehicles. The act also solves
the problems of states with 300-500-foot following distance requirements for
The passage of the Act is
exciting for many reasons. It shows that the legal world is taking autonomous
vehicles seriously, and is taking fundamental steps to create a legal framework
within which these vehicles can operate. It also provides a baseline for states
to modify their existing laws to allow autonomous vehicles to be exempted from
many requirements that need not apply to autonomous vehicles. For example,
there is no need for a steering wheel or gas pedals in an AV. There may be a
need for a large
touchscreen like in the various Tesla models, which would be distracting in
traditional vehicles. The Act will hopefully spark discussions about the proper
way to regulate autonomous vehicles at the state level, and may even spark debate
over the merits of varied state or uniform federal regulation.
When Elon Musk unveiled the Cybertruck late
last month, it sent shockwaves throughout the electric vehicle world, the stock
market, and the internet. The sleek bodied, sharp-edged vehicle is reminiscent of the classic Back to the Future DeLorean. It has already been
pre-ordered by over 200K customers, according to a tweet by Elon Musk. (It is important to note that a pre-order involves only a
$100 deposit, which is refundable). Despite the large volume of pre-orders, Tesla’s stock price
dropped by 5% in the days following the announcement — decreasing Musk’s net
worth by over $750 million due to his significant holdings in
Tesla. Notwithstanding the market reaction to the unveiling, the Cybertruck
will likely be a success in the pick-up truck consumer market.
One of the entertainment factors of the reveal was the on-stage demonstration that the vehicle is built for abuse. Unlike other Tesla vehicles that are made of stamped alumni or steel, the Cybertruck is built using 30X cold-rolled steel. The body of the vehicle took a blow from a sledgehammer without leaving a scratch. However, one window did unexpectedly shatter when a steel ball was thrown into it. The truck is meant to withstand anything a user can throw at it, which will likely appeal to current pick-up truck owners who use their trucks for towing, camping, off-roading, or any other number of activities.
The Cybertruck appears to be slightly larger than the Ford F150 (the best-selling vehicle for over three decades), and was shown capable of beating the Ford F150 in a Tug of War. Tesla’s press releaseindicated that there are three versions of the truck that will ultimately be available.
Cybertruck is designed to have the utility of a truck and the performance of a sports car. The vehicle is built to be durable, versatile and capable, with exceptional performance both on-road and off-road. Cybertruck will come in three variants: Single Motor Rear-Wheel Drive, Dual Motor All-Wheel Drive, and Tri Motor All-Wheel Drive.
Range: 250 miles
Tow Rating: 7,500 lbs
0-60 mph: 6.5 seconds
Range: 300 miles
Tow Rating: 10,000 lbs
0-60 mph: 4.5 seconds
Range: 500 miles
Tow Rating: 14,000 lbs
0-60 mph: <3 seconds * Tri-Motor Production won’t begin until 2022
It makes perfect sense that Tesla has finally
entered the pick-up truck arena. Trucks account for roughly 15 percent of U.S. vehicle sales each year, a slice
of the pie that has been growing since 2009. Americans buy nearly a million
Ford F150’s every year. Not only is there market demand, but pick-up trucks are
the perfect build for an electric vehicle; they are large and
typically more expensive than sedans, and can better carry the large and
(currently) costly batteries.
Towing will also be easier with an electric
truck, given the toque an electric vehicle can exert. Torque generally
describes how quickly a vehicle will accelerate and its ability to pull a load.
In an electric vehicle, high torque is available at low speeds and is
relatively constant over a wide range of speeds. High torque enables an EV to
move faster from a dead stop. This phenomenon can be described as “instant torque.”
However, perhaps consistent with the
incredible increase in truck ownership over the past decade, truck owners frequently
use their trucks much like other car owners: for commuting to
work. So perhaps increased towing ability is not quite the selling point for
A 500-mile range is incredibly impressive,
considering many EVs have a range right at or below 300 miles per charge, with many below 200 miles. However,
it is not likely to be seen as an improvement for truck drivers, who pleasure
drive more than twice as often as other vehicle owners. Even at the top of the
line, a 500-mile range is lower than an F150, which can get nearly 700 miles
per tank (assuming 19 mpg and a 36-gallon tank).
If the Cybertruck can take control of a
sizable segment of the truck market and begin chipping away at the market share
of their low-fuel economy competitors, Tesla may begin making tangible progress
towards decreasing domestic oil consumption and quicken the transition to an
electrified transportation sector.
Ultimately, the sleek new design and popular
appeal of the Tesla brand will likely make the Cybertruck a successful product.
But it is doubtful that many purchasers will utilize the benefits an electric
truck has over a traditional pick-up. They will instead likely use the vehicle
as they would any other car, or as a status symbol. There are plenty of SUV and
light-duty truck owners who will be glad to switch to an environmentally
friendly alternative that still allows them to ride high above traffic. Others
will be more than happy to end their reliance on highly-fluctuating fuel
time I wrote about platooning, and the potential economic savings that
could benefit the commercial trucking sector if heavy duty trucks were to
implement the technology. This week, I’m writing about one of the current
barriers to implementing platooning both as a commercial method, and in the
larger scheme of highway driving.
One of the most readily identifiable barriers to the
widespread implementation of truck platooning is the ‘Following Too Close’
(“FTC”) laws enforced by almost every state. There is currently a patchwork of
state legislation which prevents vehicles from following too closely behind
another vehicle. Violating these laws is negligence
For those who don’t quite remember 1L torts, negligence per se essentially means
“if you violate this statute, that proves an element of negligence.” Therefore,
if one vehicle is following too closely behind another vehicle in violation of
an FTC statute, that satisfies the breach element of negligence and is likely
enough to be fined for negligent driving.
These laws are typically meant to prevent vehicles from
following dangerously close or tailgating other vehicles. The state laws that
regulate this conduct can be divided into roughly four categories. Some states
prescribe the distance or time a driver must remain behind the vehicle in front
of them; others impose a more subjective standard. The subjective standards are
far more common than the objective standards.
“Reasonable and Prudent” requires enough space between vehicles for a safe stop in case of an emergency. This FTC rule is the most common for cars and seems to be a mere codification of common-law rules of ordinary care.
“Sufficient space to enter and occupy without danger” requires trucks and vehicles with trailers to leave enough space that another vehicle may “enter and occupy such space without danger.” This is the most common rule for trucks.
Distance-Based: Some states prescribe the distance at which a vehicle may follow another vehicle; others identify a proportionate interval based on distance and speed. These are the most common rules for heavy trucks and frequently set the minimum distance between 300 and 500 feet.
Time: Timing is the least common FTC, but the two jurisdictions that impose this rule require drivers to travel “at least two seconds behind the vehicle being followed.”
It is easy to see how, given the close distance at which vehicles need to follow to benefit from platooning, any of these laws would on their face prohibit platooning within their borders. However, several states have already enacted legislation which exempts the trailing truck in a platoon from their “Following Too Close” laws. As of April 2019, 15 states had enacted legislation to that effect. Additional states have passed legislation to allow platoon testing or pilot programs within their states.
However, despite some states enacting this
legislation, a non-uniform regulatory scheme does not provide the level of certainty that will incentivize
investment in platooning technology. Uncertain state regulation can disincentivize
interstate carriers from investing in platooning, and could lead to a system
where platooning trucks only operate within single state boundaries.
Although the exemptions are a step in the
right direction, non-uniformity will likely result in an overall lower platooning
usage rate, limiting the wide-spread fuel efficiency and safety benefits that
are derived when platooning is implemented on a large, interstate scale.
Without uniform legislation that allows platooning to be operated consistently
across all the states, the need for different systems will hinder the technology’s
development, and the rate at which trucking companies begin to adopt it.
However, even if not all states pass legislation exempting
platooning vehicles from their FTC laws, there could be a way around the
subjective elements. The most common subjective law, “Reasonable and Prudent”
requires only enough space that the vehicles can safely stop in case of an
emergency. When considering a human driver this distance is likely dozens of
feet, given the speed at which cars travel on the interstate. However, recall
from last week that platooning vehicles are synchronized in their acceleration,
deceleration, and braking.
If the vehicles travel in tandem, and brake at the same time
and speed, any distance of greater than several feet would be considered
“reasonable and prudent.” Perhaps what needs to be developed is a “reasonable
platooning vehicle” standard, rather than a “reasonable driver” standard, when
it comes to autonomous vehicle technology. Then again, considering the ever-looming
potential for technological failure, it could be argued that following that
close behind another heavy vehicle is never
reasonable and prudent, once again requiring an exemption rather than an
interpretive legal argument for a new “reasonableness” standard.
Either way, to ensure certainty for businesses, more states
should exempt platooning vehicles from their “Following Too Close” laws.
Otherwise, the technology may never achieve a scale that makes it worth the early
One of the most exciting and economically advantageous aspects of autonomous vehicle technology is the ability for cars and heavy trucks to “platoon.” Platooning is a driver-assist technology that allows vehicles to travel in tandem, maintaining a close, constant distance. Imagine trucks are racers in a bicycle or foot race. By drafting closely behind one another, the vehicles reduce their energy (fuel) consumption.
I personally find that large-scale platooning should be the ultimate goal of autonomous vehicle technology; the potential time and fuel savings would be enormous if the highways were filled with vehicles drafting behind one another. Imagine a highway system without rubberneckers, the guy on the highway that floors it, and then slams on the breaks during rush hour, or the “Phantom Traffic Jam.” Imagine an organized “train” of cars and trucks instead, following at a close, but technologically safe distance (between 25 and 75-feet) and at a uniform speed.
This future is more likely to begin on a smaller scale, and in the commercial shipping sector, rather than in the consumer vehicle market. The work has already started with some platooning pilot programs involving heavy trucks.
These programs employ short-range communications technology and advanced driver assistance systems in their testing. The technology creates a seamless interface supporting synchronized actions; however, drivers are still needed to steer and monitor the system. When done with heavy commercial trucks — tractor-trailers, 18-wheelers, or semi-trucks (depending on what area of the country you live in) — the trucks are “coupled” through vehicle-to-vehicle (V2V) communication. The V2V technology allows the vehicles to synchronize acceleration, deceleration, and braking to increase efficiency and safety.
The economic incentives for platooning in the freight industry derive from the potential fuel savings, which come from reductions to aerodynamic drag. While both vehicles in a pair of platooning trucks save fuel, the rear vehicle typically saves significantly more. Tests conducted by the National Renewable Energy Laboratory demonstrated average fuel savings up to 6.4 percent for a pair of platooning trucks: a lower amount (up to 5.3 percent) for the lead truck and a higher amount (up to 9.7 percent) for the trailing truck. These numbers varied based on the size of the gap between the two trucks, and the driving speed. The ability to decrease fuel consumption in heavy freight vehicles represents an enormous area to reduce the cost of shipping.
Fuel costs account for roughly one-third of the trucking industries’ cost per mile; a typical heavy-duty freight vehicle incurs between $70,000 and $125,000 in fuel costs each year. Vehicles that reduce their fuel consumption by 6.4 percent would save $4,500 to $8,000 per year. These savings are potentially enormous when extrapolated across the more than 2-million tractor-trailers on the road. The ability to decrease shipping and transportation costs should be a substantial incentive for large shipping companies like Fed Ex, UPS, and Amazon.
While getting the significant players in the transportation industry is crucial, an estimated 90% of the trucking companies in the U.S. are made up of fleets with six trucks or less, and 97% have fewer than 20. Converting existing truck cabs with the necessary technology could pose a substantial hardship for these small businesses. However, it is projected that owner-operators would recoup their investment in 10-months, and fleet operators would recoup theirs in 18-months. This relatively short period could incentivize even small-scale operators to invest in the technology.
Platooning technology could also help offset the recent spike in the average cost of truck operations. Most of these costs came from increases in driver wages and benefits, likely due to a shortage of long-haul truck drivers. The shortage of drivers is only expected to grow; the combination of long hours, inconsistent schedules, long stretches of solitude, and low pay have increased the turnover rate and disincentivized new drivers from entering the labor market. While the technology is not yet poised to run without drivers, a single truck driver would one day lead a platoon train of autonomous trucks, decreasing the need for drivers in every cab.
My vision of a highway filled with platooning vehicles may not be feasible yet, but with proper investment by businesses, platooning technology could become viable, and cost-effective, within a few years.
If 2018 was the year of the electric scooter, 2020 might be the year of the electric moped. Revel, the New York-based electric moped start-up, has placed more than 1,400 mopeds across Washington, D.C., and Brooklyn and Queens, New York, with plans to expand to 10 cities by mid-2020.
Revel’s mopeds operate in much the same manner as the many
electric scooters offered by companies like Spin, Lime, and Bird. Riders sign
up, pay for, and lock/unlock the vehicles through an app. But where scooters
are suitable for last-mile travel, mopeds may fill a medium-trip sized gap in
micro-mobility. Mopeds are better for longer trips where being able to sit down
and travel at faster speeds is desirable. They are a good compliment, not a
rival, to other micro mobility services. The more mobility services available
to the public, the more comfortable people will be using them. Overcoming the
threshold is important to increasing the use of alternative transportation
However, in stark contrast to the drop and run business method initially employed by many electric scooter companies, Revel differentiates itself by emphasizing safety and garnering regulatory approval before deploying. When Washington D.C. announced in August that the city was launching a demonstration pilot for “motor-driven cycles” (“mopeds”), Revel CEO Frank Reig expressed immediate interest in participation:
“We share their goals of providing new, reliable transportation options that work seamlessly in the city’s current regulatory, transportation, and parking systems and help the District meet its aggressive carbon emissions goals.”
Revel’s policy is not just to work with regulators when
required; they seek to foster a cooperative environment that sets the company
up for long term success and partnership with the cities where the mopeds
eventually deploy. Whereas many cities have banned
scooters, temporarily or permanently, working upfront with city officials may
benefit Revel in the long-term — potentially protecting them from being
required to pull
their vehicles from city streets.
The cooperative method should provide an example of conduct to other micro-mobility companies seeking to expand their operations; sometimes, it is better to ask permission rather than forgiveness. The goodwill from the city may pay off in the long run if local governments decide to limit how many companies may operate in the city. They also avoid the potential regulatory gap that electric scooter fall into; mopeds are definitely a motor vehicle, CEO Reig has made sure to emphasize:
These mopeds are motor vehicles. This means there is no regulatory gray area: you have to have a license plate. To get that license plate, you have to register each vehicle with the Department of Motor Vehicles in each state and show third-party auto liability insurance. And then because it’s a motor vehicle, it’s clear that it rides in the street, so we’re completely off sidewalks.
Another area of differentiation is safety and employment.
Revel’s mopeds are limited to riders aged 21 and older, capped at speeds of 30
miles-per-hour, provide riders with two helmets, and require riders to submit their
driver’s license for a safe history driving check. Moreover, unlike electric
scooter companies that rely on people working in the so-called “gig-economy” to charge their
scooters, Revel relies on full-time employees to swap out batteries on the
vehicles. This employment structure is another selling point for cities:
full-time jobs and payrolltaxes. The company is making an investment
that other mobility companies that operate on an independent contractor model
do not make. The relationship provides benefits for the cities and Revel, according
to CEO Reig:
Our biggest lesson from New York and Washington is that Revel works for cities as they exist today. They work for our riders. They work for our regulators who are seeking ways to enhance their transportation networks, not disrupt them.
After receiving nearly $27 million in Series A funding,
including an investment by Toyota AI Ventures, Revel could potentially increase
its vehicle fleet 10-fold,
aiding them in meeting their ambitious expansion plans by the middle of next