Dr. Shiyao Zhang
Institute Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
Date & Time Date: 25 Sep. 2024 Time: 14:30-15:30 Venue Zoom ID: 898 654 4121 Passcode: 123456
In the past decades, autonomous cooperative planning (ACP) is a promising technique to improve the efficiency and safety of multi-vehicle interactions for future intelligent transportation systems. In addition, realizing robust ACP is a challenge due to the aggregation of perception, motion, and communication uncertainties. In this talk, I will describe our recent work on proposing an autonomous vehicle (AV) motion planning strategy based on motion prediction and vehicle-to-vehicle (V2V)communication and introduce a novel multi-uncertainty aware ACP (MUACP) framework that simultaneously accounts for multiple types of uncertainties via regularized cooperative model predictive control (RCMPC). Experimental results and demonstrations will be presented to showcase how the proposed methods are designed to effectively enable the AV motion planning scheme in various scenarios; and how the proposed methods tackle the multiple uncertainty factors resulted from the imperfect knowledge of the environment.Finally, the future work along these directions will be briefly discussed.
Shiyao Zhang received the B.S. degree (Hons.) in Electrical and Computer Engineering from Purdue University, West Lafayette, IN, USA, in 2014, the M. S. degree in Electrical Engineering from University of Southern California, Los Angeles, CA, USA, in 2016, and the Ph.D. degree from the University of Hong Kong, Hong Kong, in 2020. He was a Post-Doctoral Research Fellow with the Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology from 2020 to 2022. He is currently a Research Assistant Professor with the Research Institute for Trustworthy Autonomous Systems (co-employed by Department of Computer Science and Engineering), Southern University of Science and Technology. His research interests include smart cities, intelligent transportation systems, vehicular electrification, and deep learning applications. He served as a Guest Editor for the Sustainability, and he is currently serving as a Guest Editor for the Electronics.
来源：智能交通学域
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