Effects of Autonomous Vehicle Ownership on Trip, Mode, and Route Choice

Abstract

Autonomous vehicles (AVs) may significantly change traveler behavior and network congestion. Empty repositioning trips allow travelers to avoid parking fees or share the vehicle with other household members. Computer precision and reaction times may also increase road and intersection capacities. AVs are currently being test driven on public roads and may be publicly available within the next two decades; they therefore may be within the span of 20- to 30-year planning analyses. Despite this time scale, AV behavior has yet to be incorporated into planning models. This paper presents a multiclass, four-step model that includes AV repositioning to avoid parking fees (although incurring additional fuel costs) and increases in link capacity as a function of the proportion of AVs on the link. Demand is divided into classes by value of time and AV ownership. Mode choice—parking, repositioning, or transit—is determined through a nested logit model. Traffic assignment is based on a generalized cost function of time, fuel, and tolls. The results on a city network show that transit ridership decreases and the number of personal vehicle trips sharply increases as a result of repositioning. However, increases in link capacity offset the additional congestion. Although link volume increases significantly, only modest decreases in average link speeds are observed.