Managing Autonomous Transportation Demand
Bryant Walker Smith
Stanford Law School
December 19, 2012
Santa Clara Law Review, Vol. 52, No. 4, December 2012
“Today we are well underway to a solution of the traffic problem.” This claim, made by Robert Moses in 1948, is as true today as it was then. Which is to say, not at all. In the middle of the last century, the preferred solution to “the traffic problem” was more cement: new highways, bridges, and lanes. Today, the sensible solution includes more sensors and better computers: highly automated vehicles that use existing roadways and roadway networks much more efficiently. This automation, we are told, will make vehicular congestion a “thing of the past.” As in the past, however, this prediction presumes that more capacity necessarily means less congestion. Today’s transportation planners recognize that the relationship between these two concepts is much more complex.
This Article argues that automation could significantly increase motor vehicle travel and that this increase could have important consequences for the physical and legal infrastructures in which tomorrow’s vehicles will operate. The next part discusses four key traffic engineering concepts: vehicle miles traveled (VMT), capacity, demand, and the time-cost of travel. Part II explains why automation could increase VMT and then shows how this increase could undermine some of the claims made with respect to congestion and emissions. Part III identifies the potential effects of increased VMT on rural and urban land use and argues that the law can help manage these effects by better internalizing the costs and benefits of motor vehicle travel. Part IV offers preliminary recommendations.
A more cautious appraisal of these likely costs and benefits in no way diminishes the immense value of the coming transportation revolution. All transportation and communication innovations — whether cars, carriages, canals, or cables — have involved great uncertainty. Innovation invites speculation.
Number of Pages in PDF File: 23
Keywords: vehicle automation, autonomous driving, autonomous vehicles, automated vehicles, transportation demand management, land use, traffic modeling, sprawl, VMT taxAccepted Paper Series
Date posted: July 31, 2013
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