Research Review with Yiheng Feng, Ph.D. and Shuo Feng, Ph.D.
Speaker(s): Yiheng Feng, Ph.D., Assistant Research Scientist, U-M Transportation Research Institute (UMTRI)
Shuo Feng, Ph.D., Assistant Research Scientist, U-M Transportation Research Institute (UMTRI)
Presentation Title: Safety Assessment of Highly Automated Driving Systems — A New Framework
Date/Time: Tuesday, March 24th, 2020 | 2:00 PM ET
Continuing Education Units (CEU): .1*
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Abstract: There are three major safety assessment methods for transportation researchers: simulation, test track, and public roads. Test tracks provide a safe, cost-effective testing environment, but they typically cannot provide a level of background traffic that may be necessary for testing. Dr. Yiheng and Shuo Feng of U-M will present on a new safety assessment framework to address these limitations. This includes an augmented reality testing platform and a testing scenario library generation method that is implemented at the Mcity Test Facility, featuring SAE Level 4 vehicles.
Dr. Feng received his Ph.D. from the Department of Systems and Industrial Engineering at the University of Arizona in 2015. His research areas include connected and automated vehicles (CAVs) and smart transportation infrastructure, with a focus on intelligent traffic control and transportation system cybersecurity. He has served as PI and Co-PI in many research projects funded by NSF, USDOT, and USDOE. He has published more than 50 research articles, which appeared in top journals, including Nature Communications, Transportation Research Part B/C, and IEEE Transactions on ITS. He is the co-chair of the Traffic Signal Systems Committee Simulation Subcommittee at the Transportation Research Board and serves as an editorial board member of Transportation Research Part C. He is the recipient of the inaugural best dissertation award from the Chinese Overseas Transportation Association (COTA) in 2015 and INFORMS ITS best paper award in 2021.
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.