The autonomous vehicle parking problem

Abstract

Autonomous vehicles (AVs) have no need to park close to their destination, or even to park at all. Instead, AVs can seek out free on-street parking, return home, or cruise (circle around). Because cruising is less costly at lower speeds, a game theoretic framework shows that AVs also have the incentive to implicitly coordinate with each other in order to generate congestion. Using a traffic microsimulation model and data from downtown San Francisco, this paper suggests that AVs could more than double vehicle travel to, from and within dense, urban cores. New vehicle trips are generated by a 90% reduction in effective parking costs, while existing trips become longer because of driving to more distant parking spaces and cruising. One potential policy response—subsidized peripheral parking—would likely exacerbate congestion through further reducing the cost of driving. Instead, this paper argues that the rise of AVs provides the opportunity and the imperative to implement congestion pricing in urban centers. Because the ability of AVs to cruise blurs the boundary between parking and travel, congestion pricing programs should include two complementary prices—a time-based charge for occupying the public right-of-way, whether parked or in motion, and a distance- or energy-based charge that internalizes other externalities from driving.