Testing the Use of Connected and Automated Vehicle Technology to Smooth Traffic Flow and Reduce Congestion in California

Research Team: Alexandre Bayen (lead), Susan Shaheen, Betty Deakin, Karen Frick, Jonathan Lee, Yashar Farid, UC Berkeley; Dan Sperling, UC Davis

University: UC Berkeley, UC Davis

Problem Statement: The energy footprint of traffic congestion is a growing problem around the world. Typical market-based methods of addressing the problem currently involve either demand-side (e.g., variable pricing, carpooling) or supply-side (e.g., traffic signal control, Variable Speed Limits, lane-use control) strategies. But much of the energy waste from congestion is actually the result of uneven traffic flow. By limiting reliance on human drivers, the new technology of connected and autonomous vehicles (CAVs) can smooth traffic flow and achieve energy savings up to 40%. These dramatic results have been achieved employing only a small percentage (≤10%) of CAVs in flow-smoothing experiments.

Project Description: This research will test different techniques of flow smoothing through a series of traffic simulations with CAVs modelled on the I-210 Highway in Los Angeles. The results will be extrapolated to other freeways with known bottlenecks, and potential state-wide impacts estimated. The research will also evaluate new policies to support flow smoothing in California.

Status: In Progress

Budget: $76,999

Project Partner(s): California Department of Transportation, Los Angeles County Metropolitan Transportation Authority