Presented By: Center for Connected and Automated Transportation
Safety Assessment of Autonomous Vehicles with a Naturalistic and Adversarial Driving Environment
Henry Liu & Shuo Feng
Safety performance testing is critical to the development and deployment of autonomous vehicles (AVs). The prevailing approach life-like simulations of our driving environment. However, due to its high dimensionality and the rareness of safety-critical events, hundreds of millions of miles would be required to demonstrate an AV's safety performance.
The research in this presentation proposes a naturalistic and adversarial driving environment 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.
Learn more about the proposed research: https://myumi.ch/BoQ2Q
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About the speakers:
Dr. Henry Liu is a professor in the Department of Civil and Environmental Engineering at the University of Michigan, a Research Professor at the University of Michigan Transportation Research Institute (UMTRI), and the Director for the Center for Connected and Automated Transportation (CCAT). Professor Liu conducts interdisciplinary research at the interface of transportation engineering, automotive engineering, and artificial intelligence. Specifically, his scholarly interests concern traffic flow monitoring, modeling, and control, as well as testing and evaluation of connected and automated vehicles (CAVs). He has published more than 120 refereed journal papers on these topics and his work has been widely recognized in the public media for promoting smart transportation innovations. He has appeared on media outlets including CNBC, Forbes, Technode, and more. In 2019, Professor Liu was invited to testify on the nation's transportation research agenda in front of the US House Subcommittee on Research and Technology. Professor Liu has nurtured a new generation of scholars, and some of his Ph.D. students and postdocs have joined first-class universities such as Columbia, Purdue, and RPI. Professor Liu is also the managing editor of the Journal of Intelligent Transportation Systems.
Dr. Shuo Feng is a postdoctoral research fellow in the Department of Civil and Environmental Engineering at the University of Michigan, Ann Arbor. He received his bachelor’s and Ph.D. degrees in the Department of Automation at Tsinghua University, China, in 2014 and 2019, respectively. He was also a visiting scholar at the University of Michigan from 2017 to 2019. His research interests lie in the testing and evaluation of connected and automated vehicles (CAVs), cooperative automation, and traffic environment modeling. Dr. Feng has published around 20 articles in refereed journals including Nature Communications, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Control Systems Technology, and Transportation Research Part C: Emerging Technologies. He has served as a member in the SAE ORAD V&V committee and workshop organizer of the IEEE 2021 Intelligent Vehicles Symposium. He received the “Best Ph.D. Dissertation Award” from the IEEE Intelligent Transportation Systems Society (ITSS) in 2020.
The research in this presentation proposes a naturalistic and adversarial driving environment 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.
Learn more about the proposed research: https://myumi.ch/BoQ2Q
---
About the speakers:
Dr. Henry Liu is a professor in the Department of Civil and Environmental Engineering at the University of Michigan, a Research Professor at the University of Michigan Transportation Research Institute (UMTRI), and the Director for the Center for Connected and Automated Transportation (CCAT). Professor Liu conducts interdisciplinary research at the interface of transportation engineering, automotive engineering, and artificial intelligence. Specifically, his scholarly interests concern traffic flow monitoring, modeling, and control, as well as testing and evaluation of connected and automated vehicles (CAVs). He has published more than 120 refereed journal papers on these topics and his work has been widely recognized in the public media for promoting smart transportation innovations. He has appeared on media outlets including CNBC, Forbes, Technode, and more. In 2019, Professor Liu was invited to testify on the nation's transportation research agenda in front of the US House Subcommittee on Research and Technology. Professor Liu has nurtured a new generation of scholars, and some of his Ph.D. students and postdocs have joined first-class universities such as Columbia, Purdue, and RPI. Professor Liu is also the managing editor of the Journal of Intelligent Transportation Systems.
Dr. Shuo Feng is a postdoctoral research fellow in the Department of Civil and Environmental Engineering at the University of Michigan, Ann Arbor. He received his bachelor’s and Ph.D. degrees in the Department of Automation at Tsinghua University, China, in 2014 and 2019, respectively. He was also a visiting scholar at the University of Michigan from 2017 to 2019. His research interests lie in the testing and evaluation of connected and automated vehicles (CAVs), cooperative automation, and traffic environment modeling. Dr. Feng has published around 20 articles in refereed journals including Nature Communications, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Control Systems Technology, and Transportation Research Part C: Emerging Technologies. He has served as a member in the SAE ORAD V&V committee and workshop organizer of the IEEE 2021 Intelligent Vehicles Symposium. He received the “Best Ph.D. Dissertation Award” from the IEEE Intelligent Transportation Systems Society (ITSS) in 2020.
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