Publication Detail

How Can Automated Vehicles Increase Access to Marginalized Populations and Reduce Congestion, Vehicle Miles Traveled, and Greenhouse Gas Emissions? A Case Study in the City of Los Angeles

UCD-ITS-RR-22-07

Research Report

National Center for Sustainable Transportation, 3 Revolutions Future Mobility Program

Suggested Citation:
Rodier, Caroline J., Ihab Kaddoura, Huajun Chai (2022) How Can Automated Vehicles Increase Access to Marginalized Populations and Reduce Congestion, Vehicle Miles Traveled, and Greenhouse Gas Emissions? A Case Study in the City of Los Angeles. Institute of Transportation Studies, University of California, Davis, Research Report UCD-ITS-RR-22-07

The research teamusedthe Los Angeles MATSim model to evaluate the travel, greenhouse gas(GHGs), and equity impacts of single-and multiple-passenger automated taxi scenarios, including free transit fares and a VMT tax. The results indicate that automated taxis increase VMT by about 20 percent across scenarios, and automated taxis mode shares more than offset reductions in personal vehicle travel. The automated taxi-only scenario also reducestransit travel by about 50 percent, but the addition of free transit fares reversed this decline and increased transit use somewhat. New empty passenger automated taxi travel compounds the impact of mode shifts in these scenarios and further increases vehicle travel. There is a slight change in mean vehicles speeds across all scenarios.When automated taxis are not battery electric vehicles (BEVs), GHG emissions increase from 16to 18percent across scenarios. However, GHGs decline by 23 to 26 percent when automated taxis are BEVs. The equity analysis shows that the automated taxis scenarios provide more accessibility benefits for travelers in three low-income classes than total benefits and benefits for the middle-and high-income travelers. The addition of free transit to the shared automated taxis-only scenario dramatically increases low-income benefits. The VMT tax eliminates almost all of the benefits from the automated taxi and free transit scenarios and creates losses for all three low-income groups.

Key words: Automated vehicles; ridehailing; pooled ridehailing; free transit; distance-based road charges; travel and equity impacts