By Nat Bottingheimer, February 4, 2014
Autonomous, self-driving vehicles are getting more attention from the media, but little from transportation planners. Given the technology's potential impacts on our transportation network, it's time for planners to start thinking about it.
Self-driving cars have the potential to reduce both car crashes and traffic congestion, and to use wasted time driving for work or entertainment. These are benefits usually attributed to transit; as a result, autonomous vehicles could strengthen arguments for designing for more cars in our cities and suburbs, instead of more pedestrians, cyclists, and placemaking.
Transportation planners aren't talking publicly about driverless cars
By contrast, online searches for "transportation planning" and "self-driving cars" turn up thoughtful, if skeptical reviews by urbanists Todd Litman and Jarrett Walker; a sober, academic summary of key issues by the Eno Center for Transportation; and a thorough debate from 2011 on the issue here on GGW; and an article from Governing Magazine that exemplifies the public preoccupation with regulating driverless cars rather than planning and policy issues.
There isn't a lot of evidence of transportation planners at public agencies giving serious attention to the matter, at least not publicly. A recent blog entry from Bacon's Rebellion also concludes that transportation planners are not paying attention. Though, to be fair, the topic was covered at a recent Florida Department of Transportation conference and the Transportation Research Board a few weeks ago.
Self-driving cars address many of the safety and travel efficiency objections that Smart Growth advocates often make about road expansion, or the use of limited street space. As a result, planners and placemaking advocates will need to step up their game.
They need to better define in what environments bike- and pedestrian-oriented designs are still appropriate even when we can solve our congestion problems with self-driving cars. They need to promote street and intersection that can work for bikes and pedestrians as well as for self-driving cars; and to make a strong cases for Smart Growth and TOD that are based on diverse benefits, not just on the ability to move people.
Capital planning decisions last for thirty years and beyond. The officials responsible for parking lot and garage building, transit system growth, bike lane construction, intersection expansions, sidewalk improvements, and road widenings need to analyze quantitatively how self-driving cars could affect their plans, and to prepare alternatives in case things change.
How could self-driving cars disrupt the planning process?
Here are two examples of situations where planners may need to adapt to self-driving cars:
Self-driving cars coupled with "smart intersections" that communicate with vehicles to let them pass without traditional stoplight timing could result in less congestion, but may speed up cars in places where cyclists and pedestrians are competing for space. The cars will be faster, but also safer to be around. The question is whether a more efficient auto network outweighs the negative impacts to other parts of the urban environment.
They may also make car use more competitive with bus transit in low-density settings and may erode the demand and need for transit (and paratransit). On the other hand, changed transit economics resulting from driverless buses could mean that extending transit into new areas will make more economic sense in the future than it makes today.
Ways to prepare for self-driving cars
So, what could the region's planners do now to anticipate the potentially sweeping changes that self-driving cars will cause? How can planners today insure that scarce infrastructure dollars are spent on things that might be less needed in the near future?
For example, if intersections can handle more vehicles per hour with self-driving cars than with human-driven cars, they may not need to be widened. Or if transit commuters can get to the station in a self-driving car, park-and-rides may not be necessary, because the car will just drive itself back home.
First, land use, highway, and transit planners should simply acknowledge the issue. They should begin to define how large different impacts may be, when those impacts are likely to occur, what the range of public responses will need to include, and when those public responses may have to start occurring.
Self-driving cars will change patterns of car ownership and travel. Planners need to examine how travel forecasting tools that are based on current patterns of car ownership and use will need to change to adapt to new statistical relationships between population, car ownership, trip-making, car-sharing, and travel patterns.
Because cars that can drive themselves won't stay parked all day, builders and regulators should think about how new parking structures should be designed for adaptive reuse if future parking demand declines.
State and local DOTs should measure how smart intersections could increase the number of vehicles that can use an intersection per hour, and how to design roads and intersections that work for self-driving cars, as well as pedestrians, bicyclists, and the creation of public spaces.
Finally, the region's transit agencies should study how driverless operations could affect operating costs for bus, rail, and paratransit services, and should update their long-range capital and operating needs forecasts to reflect what they learn.
Many aspects of the self-driving car world remain in doubt. That is not, however, a reason to avoid thinking about how to benefit from the capabilities that self-driving vehicles offer. Even if planners are only able to do general studies rather than detailed forecasts, that would still be a useful exercise. Understanding how to adapt our communities for the benefits and challenges of self-driving cars would be a huge step forward.