Available online at: https://trid.trb.org/view/1573028
Bischoff, Joschka, Caroline J. Rodier, Elham Pourrahmani, Miguel Jaller, Anmol Pahwa, Michal Maciejewski (2019) Competition among Automated Taxis, Transit, and Conventional Passenger Vehicles: Traffic Effects in the San Francisco Bay Area. Transportation Research Board 98th Annual Meeting
At the end of 2017, Waymo, Google’s autonomous vehicle spinoff, announced the launch of its ride-hailing service. Since then, it has been testing its “Early Rider” service with its autonomous vehicles, without back-up drivers, in Phoenix, Arizona (U.S.), areas. In this paper, the authors simulate the effects of the introduction of a similar service on conventional personal vehicle and transit travel in the San Francisco Bay Area region. The authors call this service “automated taxis” and use new research on the costs of automated vehicles to represent plausible per mile automated taxi fares. Alternative automated taxi (AT) scenarios are simulated with a regionally calibrated agent-based model using the MATSim framework. This model uses baseline travel demand data from the region’s official activity-based travel model and dynamically assigns vehicles on road and transit networks by time of day. The authors' results indicate that the introduction of automated taxis may have a significant impact on transit use (reducing it by more than half), vehicle miles of travel (increasing by 18%), and congestion. Automated taxis out compete transit travel in the outer areas of the region and produce more and longer vehicles trips on roadways (including deadhead travel), which tends to increase congestion in specific areas. This research highlights the significant threat of low cost AT services to suburban transit providers and efforts to reduce vehicle miles of travel (VMT) and congestion.
Key words: Autonomous vehicles, competition, private passenger vehicles, public transit, ridership, ridesharing, simulation, taxicabs, traffic congestion, vehicle miles of travel