Thursday, April 25, 2019, 12:00PM (ET)
Control of Connected Autonomous Vehicles in Mixed Traffic: Modeling and Field Experiments
Advanced connected and automated vehicle (CAV) technologies can be utilized to achieve precise vehicle trajectory control and render unprecedented opportunities to improve transportation system performance in safety, mobility and sustainability. However, it is quite challenging to fully realize these advantages from CAV in mixed traffic environment due to stochastic and uncertain human-driven vehicle (HV) behavior. This study presents several key models for CAV control in both longitudinal and latitudinal directions considering coordination with infrastructure units (e.g., traffic signals) in mixed traffic environment. The fundamental idea of these models is to use learning based methods to estimate and predict HV behavior and use fast heuristic to plan and control the AV trajectory in a near-optimal manner. These models are validated with field experiments on a large-scale testbed in mixed traffic settings. These field studies are the first of its kind involving both longitudinal and latitudinal controls in mixed traffic. The results show that the proposed control models can safely and efficiently implement key AV control functions in mixed traffic. Download Handout
Presenter: Xiaopeng Li, Ph.D., Assistant Professor, Department of Civil and Environmental Engineering, University of South Florida
Dr. Xiaopeng (Shaw) Li is currently associate professor and the Susan A. Bracken Faculty Fellow in the Department of Civil and Environmental Engineering at the University of South Florida (USF). His major research interests include traffic modeling, control and advanced network systems with applications in connected autonomous vehicles, shared mobility and electric vehicles. He is a recipient of a National Science Foundation (NSF) CAREER award. He has published 47 journal papers. He has served as members on the Transportation Network Modeling Committee (ADB30) and the Traffic Flow Theory and Characteristics (AHB45) of the Transportation Research Board (TRB). He has served as a departmental associate editor for Institute of Industrial and Systems Engineers Transactions and the editorial board for Transportation Research Part C.
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