November 2018

In the U.S., Thanksgiving represents the busiest travel period of the year, with AAA predicting that this year 54 million people will travel 50 miles or more before sitting down for turkey and stuffing. So how will CAVs and other mobility innovations change how we travel, not just at Thanksgiving, but yearlong? Lets take a look at a few recent stories that could point the way:

Waymo’s Self-Driving Service Hits the Bigtime

Back in August, Dan mentioned some issues Waymo’s automated vans had run into in Phoenix. Those issues don’t seem to have slowed the Alphabet (Google) owned company, as they have announced (as noted by Kevin) the launch of commercial service in December. The company is planning a slow roll out, and some cars will still have backup drivers, but by the Christmas travel season, some people in Arizona will be able to hail a driverless taxi to shuttle them to the airport.

Multimodality – Instead of a Taxi to the Airport, How About an E-Scooter and a Bus?

Uber has recently started to personalize suggestions on how to complete a trip. Depending on the distance to be traveled, the app will suggest you use a JUMP bike instead. Travelers in select cities can use Citymapper to plan trips across rideshares and public transit. In Chicago, for example, the app coordinates city buses, Divy bike shares, the ‘L’ system, and commuter rail. In London, Citymapper users can even hail a rideshare via the app’s own fleet. Meanwhile, bike and scooter startup Lime is expanding their services to include cars on their platform, and plans to deploy up to 500 cars in Seattle by the end of the year.

These companies are far from the only parties trying to synchronize how we use various mobility services. While the promise of a single app for all our mobility needs is yet to be fulfilled, the momentum is clearly there. Such an app would further enhance the congestion (and environmental) benefits that are projected to come with wider adoption of CAVs. While CAVs can better coordinate the cars that are on the road, multimodal programs can take even more cars off the road by pointing users to more efficient public transit or bikes/scooters.

Leaving Car Ownership Behind (Eventually…)

While some drivers may use self-driving cars and multimodality services to supplement their personal vehicles, there is an increasing push to replace vehicle ownership altogether. Lyft has launched a “ditch your car” challenge in a number of cities, encouraging users to try to live without their vehicles for a month. They’ve also launched a subscription service, offering 30 rides (up to $15 each) a month for $299.

Not interested in completely ditching your car? GM’s Maven platform lets you rent out your own vehicle, and is expanding in 2019 to include non-GM vehicles. Or you can opt for a more old-fashioned carpool, facilitated by Waze, which is slowly expanding a service to connect potential carpool members. So by next Thanksgiving, you may be able to snag a Waze carpool while leaving your personal vehicle behind to earn a little extra cash on Maven.

The point of this round up is not to provide a commercial for these platforms, but to highlight the ongoing disruption of the way people move through the world, a disruption that will only continue as CAVs reach greater deployment.

CAVs and the Traffic Stop

The traffic stop has long been a primary point of interaction between police and the community. As consent Department of Justice (DOJ) investigations into local police departments in Ferguson, Baltimore, and Chicago made clear in recent years, they are also a moment that is open to large-scale abuse. The rise of connected and autonomous vehicles (CAVs) will fundamentally alter, and perhaps dramatically reduce the occurrence of, this common police tactic. In order to avoid replicating the problematic aspects of traffic stops, communities need to grapple with the ways in which their current system has failed, and how policing should look in the future.

Local police departments in at least some parts of the country have been found to use routine traffic stops as a fundraising tool for the city. Due to either implicit or explicit bias, such policies frequently have an outsized impact on minority members of the community. DOJs investigation of the Ferguson Police Department unearthed a city government primarily concerned with the use of traffic stops to “fill the revenue pipeline.” Particularly in light of decreased sales tax revenue, city officials saw the need to increase traffic citations as “not an insignificant issue.” This attitude filtered down from the City Council and Financial Director to line officers, who were regularly reminded of the need to increase “traffic productivity.” In Ferguson, demand that the police department be a revenue generation machine contributed to racial bias in the city’s criminal justice system. African American drivers were the subjects of 85% of the traffic stops, despite constituting only 67% of the population. Among those stopped, 11% of black drivers were searched, compared to only 5% of white drivers. While the Ferguson report throws the twin problems of racialized policing and use of the police for revenue generation into stark relief, the city is far from alone. The investigations in Baltimore and Chicago found similar abuses. A review of academic literature by researchers at Princeton found that “Blacks and Hispanics are more likely to be stopped by the police, convicted of a crime, and . . . issued a lengthy prison sentence” than similarly situated whites.

These findings highlight the centrality of the traffic stop to modern policing. Traffic stops not only lead directly to citations – for speeding, missing stop signs, and the like – but also to searches of individuals and vehicles that may lead to more serious crimes for things like possession of drugs or weapons. The importance of traffic stops has been spurred on by a Supreme Court that has given its blessing to pretextual stops, in which an officer can stop a car as long as there is a valid reason, regardless of their actual reason. Widespread use of CAVs, however, could seriously cut down on pretextual stops. If a CAV is programmed to travel no faster than the speed limit, to always signal turns, and to never run a red light after all, the number of available pretexts is significantly reduced. While many commentators have been hesitant to think that this shift will lead to large-scale shifts in police tactics or a significant reduction in abuses, they have at least highlighted that possibility.

While CAVs and other new technology may lead to a shift in police tactics, they alone will not eliminate, and may not even reduce, biased policing. Unless addressed through changes to underlying structures of taxation or spending, the financial imperative to turn the police force into a revenue generator will continue to drive over-policing of minor violations. Without addressing implicit bias, this over-policing will continue to disproportionately target minority communities. The CAV era may channel these pressures in new directions. But cities that wish to address the ongoing challenge of racially biased policing must initiate structural changes, rather than merely hope that technology will save them.

City design has long been shaped by modes of transportation. The transition is easy to spot as you move westward across America. Relatively compact eastern cities initially grew up in the 18th and 19th centuries, when people traveled by foot or by horse. Scattered across the plains, and particularly throughout the vast expanses of Texas and the Southwest, are cities filled with wide thoroughfares and sprawling suburbs, designed to match the rise of car culture. A large-scale shift to autonomous vehicle transportation will once again mold our cities in new ways. I wrote recently about this coming shift, focusing in particular on the reuse of space currently dominated by parking. This post will build on that theme by exploring the ways in which big data generated by new transportation technologies will guide city planners and business strategists in creating new urban environments.

Many cities already take advantage of more traditional forms of transportation data to improve urban planning. For example, analysis of population density and traffic patterns facilitated Moscow’s 50% increase in public transit capacity, which enabled the city to reduce driving lanes in favor of more space for pedestrians and cyclists. Looking to the future, New York University’s Center for Urban Science and Progress seeks to help cities harness the power of big data to “become more productive and livable.” Today, more data exists regarding our transportation habits than ever before. Ride-hailing services such as Uber and Lyft, along with the popularity of “check-in” apps such as Foursquare, have exponentially increased the amount of data collected as we go through our daily routines. The advent of CAVs, along with smaller scale technologies such as bike-share and scooter-share programs, will only accelerate this trend.

Currently, most of this data is collected and held by private companies. This valuable information is already being aggregated and used by companies such as Sasaki, a design firm that uses data from Yelp, Google, and others to help businesses and developers understand how their planned projects can best fit in with a community’s existing living patterns. The information is able to help businesses understand, on a block-by-block basis, where their target market lives, shops, and travels. As companies such as Uber and Waymo roll out fleets of autonomous vehicles in the coming years that collect data on more and more people, such information will increasingly drive business planning.

Just as this wealth of data is impacting business decisions, making it available to the public sector would mark a significant upgrade in the capabilities of urban planners. To be sure, granting the government easy access to such fine-grained information about our daily lives comes with its own set of challenges, which my colleague Ian Williams has explored in a previous post. From the perspective of planning utility however, the benefits are clear. By better understanding exactly what times and locations present the worst traffic challenges, cities can target infrastructure improvements, tollways, or carpool benefits to alleviate the problem. A more detailed understanding of which routes people take to and from home, work, shopping, and entertainment districts can allow for more efficient zoning and the development of more walkable neighborhoods. This type of improvement has the potential to improve the livability of city centers so as to guard against the danger that CAVs will facilitate a new round of exurban flight.

As with previous shifts in transportation, the widespread move to CAVs expected in the coming years will be a key driver of the future shape of our cities. Urban planners and business strategists will play a featured role in determining whether this technology ushers in a new round of sprawl, or facilitates the growth and attractiveness of metropolitan centers. The intelligent and conscientious use of data generated by CAVs and other emerging technologies can help fuel smart development to ensure that our downtown spaces, and the communities they support, continue to thrive.

 

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.