The advent of autonomous vehicles is fraught with uncertainty, especially when it comes to their impacts on traffic, travel choices, and the broader transportation system.
They offer many potential benefits, but many potential negative impacts, depending in part on how they are deployed. While widespread adoption may still be decades away, significant numbers will begin to be on the roads in less than 10 years, according to manufacturers and other observers. Ultimately, many expect them to have major transformational effects on our transportation systems and built environment.
Today’s policymakers have an opportunity to implement plans that will guide the efficient usage of AVs and rider choices that may affect us for generations. To do so, it’s worth considering AV impacts as a potential transportation demand management problem – and preparing TDM-type policies to address them.
When it comes to the most pressing issues to be addressed in the deployment of autonomous vehicles, safety and infrastructure do not necessarily top the list of urgent needs. Federal and state policies are already looking to address these. Since safety is one of the major motivations for adopting autonomous technologies, and a top concern for skeptical consumers, agencies and automakers are prioritizing it. Either they will be made safe, or they won’t be on the roads.
Meanwhile, the exact impacts to communities and traffic systems are poorly understood, and have not been addressed in the ongoing conversation to the extent that they should be. Ironically, the efficiency of AVs has long been touted as a solution to traffic, but new research is beginning to suggest that AVs will, in fact, generate more of it. Simply put, there is no guarantee the traffic effects of AVs will be handled. It is entirely possible that they will spread widely and, without adequate policies, many places may never manage their impacts. We never fully anticipated the impacts of conventional cars as they were being developed, and we have been living with many unintended consequences in the form of our communities for the last 100 years.
What we do know is that AVs will create an unprecedented convenience in driving. By eliminating most of the hassles of driving, such as parking and lost productivity time, AVs will induce not only more trips, but longer ones. Additionally, AVs waiting to pick up new riders will add “deadheading” miles. For traffic, the only thing worse than a single-occupant vehicle is a zero-occupant vehicle. Placed all together, this suggests they will almost certainly increase vehicle-miles traveled, energy use, and emissions. These impacts might be locked in by further sprawl and other shifts toward less efficient land-use patterns.
How people start to use AVs will matter in terms of the traffic impacts they create. Personal autonomous vehicles, according to a landmark 2015 Urban Mobility study by the International Transit Forum and Corporate Partnership Board, will generate up to 35 percent more VMT than conventional personal cars. Those in a shared “fleet” model would generate less. Meanwhile, AVs in a taxi model, carrying single passengers all the way to their destinations, would create 90 percent more VMT than typical taxies. Using those taxis as a connection to transit with multiple passengers, however, would only produce 6 percent more VMT.
To avoid the worst of these traffic scenarios, policy needs to be deployed with an eye towards minimizing the added miles and the demand for situations involving zero-occupant vehicles.
When it comes down to it, the demand guiding AV impacts is a hybrid of a person’s choice, as in their decision to initiate the trip, and the self-driving technology itself. Both together could be regarded as the typical “commuter” of modern TDM thinking. Whereas traditional TDM focuses on commuter choices, AV TDM might address the ways in which the AV technology is employed and how those cars carry passengers.
In short, policymakers should adapt transportation demand management principles to autonomous vehicles, using a mix of incentives and disincentives to guide choices.
As with TDM best practices, a few ideas should form a hierarchy of priorities for states, cities, and transportation agencies. First off, policies should always seek to encourage AVs that move more people in fewer vehicles. While the driverless technologies make point-to-point drop-offs possible, the realities of cities and highways means that they simply cannot accommodate one AV per person.
Second, similar incentives should be in place to guide people and employers towards more efficient choices. The deployment and pricing models offered by automotive and tech companies should be structured to make shared AVs, not personal AVs, the model of choice. This is a complicated endeavor, but important to the success of AVs in providing improved mobility and not increased congestion. As mentioned above, AVs that feed into transit systems create the lowest amount of VMT and, in many cases, might expand the reach and usefulness of those transit systems. Current TDM policies, such as employer transit benefits that make transit more affordable and useful to commuters, might help guide their use of AVs as a complement to transit, too.
Lastly, policymakers should seek to create pricing policies in anticipation of the traffic-inducing effects of personal AVs. The program might be created in escalating prices, as to disincentivize the least efficient choices. A VMT fee would discourage longer trips in general, while a higher single-occupant fee would encourage AV riders to share rides. Lastly, a zero-occupant fee, addressing the miles added by AVs circling between pick-ups or headed home to park, would warrant the highest fee. “ZOV” miles represent an entirely new congestion danger, as they may be generated from the mere convenience of AV owners asking their cars to circle while they pick up groceries, but can add up to significant traffic consequences.
The national dialogue around AV policy is a unique chance to rethink how we prioritize our transportation systems and the incentives within it. A century ago, when the internal combustion engine automobile began to proliferate, cities missed this opportunity to guide how they affected communities.
Rather than adapting places around AVs, modern policies need to shape AV usage and behaviors to keep building better communities.
Photos: Top, an autonomous Uber test vehicle in Pittsburgh (Foo Conner, Flickr, Creative Commons). Embedded, a Google AV on a California highway (Phil Hollenback, Flickr, Creative Commons).
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