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讲座丨密西根大学Gabor Orosz教授:利用网联与自动化技术提升道路交通效率

发布时间:2024-06-12

题目 / Title:Improving the efficiency of road transportation using connectivity and automation

主讲人 / Speaker:Gabor Orosz  密西根大学 教授

邀请人 / Inviter:庄瀚洋 助理研究员

时间 / Time:2024.06.14  10:00 - 11:30 am

地点 / Location:上海交通大学包玉刚图书馆,东翼楼200报告厅 


讲座摘要 / Abstract:


In this talk I will focus on the dynamics and control of connected automated vehicles in mixed traffic scenarios where CAVs interact with human-driven vehicles. I will highlight the concept of connected cruise control (CCC) which enables CAVs to improve their safety and energy efficiency by responding to the motion of multiple vehicles ahead. I will show how such benefits may be retained for low penetration of connectivity using infrastructure support. Finally, I will discuss how conflict analysis can be utilized to improve safety and efficiency while using intent information and negotiation. The theoretical results will be demonstrated using experiments with full-size vehicles on test tracks and public roads.


主讲人简介 / Biography:


Gabor Orosz received the MSc degree in Engineering Physics from the Budapest University of Technology, Hungary, in 2002 and the PhD degree in Engineering Mathematics from the University of Bristol, UK, in 2006. He held postdoctoral positions at the University of Exeter, UK, and at the University of California, Santa Barbara. In 2010, he joined the University of Michigan, Ann Arbor where he is currently a Professor in Mechanical Engineering and in Civil and Environmental Engineering. From 2017 to 2018 he was a Visiting Professor in Control and Dynamical Systems at the California Institute of Technology. In 2022 he was a Distinguished Guest Researcher in Applied Mechanics at the Budapest University of Technology and from 2023 to 2024 he was a Fulbright Scholar at the same institution. His research interests include nonlinear dynamics and control, time delay systems, machine learning, and data-driven systems with applications to connected and automated vehicles, traffic flow, and biological networks.

 

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