Congestion pricing in a world of self-driving vehicles: An analysis of different strategies in alternative future scenarios

University of Texas, March 28, 2018

The introduction of autonomous (self-driving) and shared autonomous vehicles (AVs and SAVs) will affect travel destinations and distances, mode choice, and congestion. This work develops multiple CP and tolling strategies in alternative future scenarios, and investigates their effects on the Austin, Texas network conditions and traveler welfare, using the agent-based simulation model MATSim. Results suggest that, while all pricing strategies reduce congestion, their social welfare impacts differ in meaningful ways.

https://www.caee.utexas.edu/prof/kockelman/public_html/TRB19CBCP_with_AVs.pdf