Studies show that automated vehicles are likely to increase vehicle travel, resulting in more congestion and greenhouse gas emissions (GHGs). Pricing policies such as increasing the cost of driving and reducing the cost of alternative travel modes could lessen the negative impacts of automated vehicle deployment, although it is unclear to what extent. Cities located in the Westside Cities Council of Governments planning area in western Los Angeles County could be candidates for early deployment of automated vehicles because of their high travel volumes, well-maintained roads, and temperate weather conditions. Los Angeles County also faces high levels of poverty. Thus, the Westside Cities area presents an important opportunity to study how automated vehicles and associated pricing policies might affect congestion, vehicle miles traveled (VMT), and GHGs, and whether they might improve mobility for marginalized populations.
Researchers at the University of California, Davis and the Technical University of Berlin evaluated these questions by simulating three scenarios in the Westside Cities area using an open-source, dynamic, agent-based travel model called MATSim. The researchers then calculated the benefits of each scenario compared to the base case for various income groups, considering monetary travel costs and the value of travel time for each income group. This policy brief summarizes the findings from that research and provides policy implications.