UC Berkeley Partners for Advanced Transportation Technology (PATH) researchers Hao Liu, Xiao-Yun Lu, Steven E. Shladover, and Zhitong Huang recently completed a case study for the U.S. Department of Transportation Federal Highway Adminstration regarding the development of effecttive analysis, modeling, and simulation tools for connected automated vehicles: Developing Analysis, Modeling, and Simulation Tools for Connected Automated Vehicle Applications: A Case Study on SR 99
Abstract: The purpose of this report is to document a simulation-based case study investigating the effectiveness of SAE J3016 Level 1 automation technology for mitigating or solving existing transportation problems related to congestion, fuel consumption, and emissions.(1) This case study examined the impacts of cooperative adaptive cruise control (CACC) vehicle string operations on traffic performance and fuel consumption on the 13-mi SR 99 northbound corridor from Elk Grove Boulevard to SR 50 near Sacramento. The research team evaluated the performance of the busy urban corridor under various CACC market penetration scenarios, traffic demand inputs, and CACC management strategies. Specifically, the research team examined average vehicle speed, average vehicle miles traveled per gallon of fuel consumed, average string length, and CACC vehicle string probability (i.e., the probability of a CACC vehicle operating in a string) at CACC market penetration rates of 0, 20, 40, 60, 80, and 100 percent. The study investigated the corridor's spatiotemporal traffic patterns under the existing traffic demand and with the demand increased by 20 percent. Additionally, it analyzed CACC string operation after vehicle awareness device and CACC managed lane strategies were implemented.