Research Review with Henry Liu, Ph.D. and Shuo Feng, Ph.D.
Speaker(s): Henry Liu, Ph.D., Director, Center for Connected and Automated Transportation (CCAT)
Professor of Civil and Environmental Engineering, University of Michigan
Shuo Feng, Ph.D., Assistant Research Scientist, U-M Transportation Research Institute (UMTRI)
Presentation Title: Safety Assessment of Autonomous Vehicles with a Naturalistic and Adversarial Driving Environment
Date/Time: Wednesday, June 9th, 2021 | 1:00 PM ET
Continuing Education Units (CEU): .1*
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Abstract: Safety performance testing is critical to the development and deployment of automated vehicles (AVs). The prevailing approach includes life-like simulations of our driving environment. However, due to high dimensionality and the rareness of safety-critical events, hundreds of millions of miles would be required to demonstrate an AV’s safety performance.
This research proposes a naturalistic and adversarial driving environment (NADE) that can significantly reduce the required number of miles driven, while simultaneously maintaining unbiasedness. Drs. Henry Liu and Shuo Feng will demonstrate the effectiveness of this in a highway-driving simulation. This NADE is currently in the process of being implemented at the American Center for Mobility (ACM) at the historic Willow Run site.
Speaker Bios:
Henry Liu is currently a Professor in Civil and Environmental Engineering at the University of Michigan, Ann Arbor. He is also a Research Professor at the University of Michigan Transportation Research Institute (UMTRI). Prior to joining the University of Michigan, Dr. Liu was an Associate Professor of Civil Engineering at the University of Minnesota, Twin Cities. Dr. Liu received his Ph.D. in Civil and Environmental Engineering from the University of Wisconsin at Madison in 2000 and his Bachelor degree in Automotive Engineering from Tsinghua University (China) in 1993. Dr. Liu’s research focuses on traffic network monitoring, modeling, and control, which includes traffic flow modeling and simulation, traffic signal operations, network traffic assignment, and mobility applications with connected and automated vehicles. Dr. Liu is a managing editor of the Journal of Intelligent Transportation Systems and an associate editor of Transportation Research Part C. He is also on the editorial board of Transportation Research Part B, Network and Spatial Economics, Transportmetrica Part B, and IET Journal of Intelligent Transportation Systems.
Dr. Shuo Feng is an Assistant Research Scientist at the University of Michigan Transportation Research Institute (UMTRI). He received his bachelor’s and Ph.D. degrees in the Department of Automation at Tsinghua University, China, in 2014 and 2019, respectively. Before joining UMTRI, Dr. Feng was a postdoctoral research fellow in the Department of Civil and Environmental Engineering at the University of Michigan, Ann Arbor. His research interests lie in the development and validation of safety-critical machine learning, particularly for connected and automated vehicles. Dr. Feng has published more than 20 articles in refereed journals including Nature Communications and IEEE Transactions on Intelligent Transportation Systems. He has served as the associate editor of IEEE Transactions on Intelligent Vehicles and academic editor of Automotive Innovation. He was the recipient of the “Best Ph.D. Dissertation Award” from the IEEE Intelligent Transportation Systems Society (ITSS) in 2020 and the Intelligent Transportation Systems Best Paper Award from the INFORMS Transportation Science and Logistics society in 2021.