Date: 1 December 2023, Friday
Time: 4:30 PM
Venue: YEUNG B5-211, City University of Hong Kong
Zoom Meeting ID: 967 1968 0176
Password: 123456
Speaker: Dr Huan Yu, Hong Kong University of Science and Technology (Guangzhou)
From macro to microscopic: leveraging connected automated vehicles for traffic control
Dr Huan Yu, Hong Kong University of Science and Technology (Guangzhou)
Abstract: Emerging technologies in communications and autonomous driving technologies will enable vehicles that are “physically-connected” via car-following to be “cyber-connected” via wireless communications. As one of the most important cyber-physical systems (CPS) applications, connected automated vehicles (CAV) have been envisioned to greatly enhance efficiency, stability and safety of transportation systems. This talk will focus on CAV-based control problems in mixed traffic that consist of human-driven vehicles (HV). Cruising control strategies of CAVs are developed to not only guarantee smooth and safe driving behaviors of the ego vehicle, but also to stabilize the surrounding HVs. This talk begins with conventional traffic control of which actuation and sensing are conducted from a macroscopic viewpoint. A methodological Partial Differential Equation model-based control design for stop-and-go traffic stabilization will be discussed. Motivated by the proposed fixed-boundary traffic control, I will discuss how CAV-based sensing and control can be designed for a string of vehicles. In particular, a safety-critical traffic control framework will be introduced, employing control barrier functions to impart collision-free safety guarantees for both the CAV and HVs. Data validations using vehicle trajectory will demonstrate the efficacy of our designs. I will also highlight how the data can enhance theoretical control designs in intelligent transportation systems using physics-informed machine learning.
Speaker’s Bio: Dr. Huan Yu is an Assistant Professor at the Hong Kong University of Science and Technology (Guangzhou), jointly appointed with the Intelligent Transportation Thrust and the Robotics and Autonomous Systems Thrust, and also an Affiliate Assistant Professor in the Department of Civil and Environmental Engineering at the Hong Kong University of Science and Technology (HKUST). She received the B.Sc. degree from Northwestern Polytechnical University, and the M.Sc. and Ph.D. degrees in Mechanical and Aerospace Engineering from the University of California, San Diego, United States. She was a visiting scholar at University of California, Berkeley and Massachusetts Institute of Technology. Her research has been focused on finding safe, stable and robust solutions that combine control theory, machine learning, and traffic flow theory to advance the boundaries of intelligent transportation systems.
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