Impact of Connected and Autonomous Vehicles on Mobility of Highway Systems

Doctoral Candidate Name: 
Pengfei Liu
Program: 
Infrastructure and Environmental Systems
Abstract: 

Connected and autonomous vehicle (CAV) technologies are known as an effective way to improve safety and mobility of the transportation system. As a combination technology of connected vehicle and autonomous vehicle, CAVs share real time traffic data with each other, such as position, speed, and acceleration. CAV only needs a smaller lane width and headway which will lead to a higher roadway capacity. CAVs may have coordinated weaving maneuvers which will increase weaving section capacities. Also, CAVs enable the communication between vehicles and traffic signals. The coordinated operation among CAVs and the communication between CAVs and traffic signals will improve the throughput at signalized intersections and lead to a higher intersection capacity. To quantify the impact of CAVs on freeway capacity and intersection mobility, new guideline should be established in order to be suitable for use in conducting various types of analyses involving CAV strategies. The impact of different CAV penetration rates in the highway system on various facilities under different scenarios should be examined. The results of this research could lead to a better understanding of how CAVs will improve mobility on the highway systems.

Defense Date and Time: 
Tuesday, October 6, 2020 - 8:00am
Defense Location: 
Remote through Webex
Committee Chair's Name: 
Dr. Wei Fan
Committee Members: 
Dr. Jy Wu, Dr. Martin Kane, Dr. David Weggel, Dr. Jing Yang


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