Presented By: Center for Connected and Automated Transportation
Roadway Friction Screening and Measurement with Automated Vehicle Telematics and Control — CCAT Research Review
Drs. Xiaopeng Li and Heye Huang
This project develops an automated roadway friction screening and measurement system using telematics-based cooperative perception and customized AV control. The system offers a low-cost, automated alternative to traditional friction measurement methods, enabling frequent, wide-area monitoring without the need for dedicated instrument calibration.
Leveraging Physics-Enhanced Residual Learning (PERL), the AV control module achieves high slip ratios at peak Tire-Road Friction Coefficient (TRFC) values, improving estimation accuracy. Cooperative perception aggregates telematics data from connected AVs and regular vehicles (RVs), mitigating individual measurement errors and expanding coverage across diverse road conditions. A network smart routing strategy is proposed to optimize AV deployment for friction sensing, utilizing real-time traffic and environmental data without incurring extra resource costs. Field validation will be conducted at the Level-3 CAV testbed at the University of Wisconsin–Madison, using vehicles equipped with FHWA CDA CARMA capabilities.
More on this research: https://myumi.ch/XGxQX
---
About the speakers:
Dr. Xiaopeng (Shaw) Li is currently a Professor in the Department of Civil and Environmental Engineering and an affiliate in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison (UW-Madison). He served as the director of National Institute for Congestion Reduction (NICR) before. He is a recipient of a National Science Foundation (NSF) CAREER award. He has published over 110 peer-reviewed journal papers. He has served as the PI or a co-PI for a number of federal, state, and industry grants, with a total budget of around $30 million. His major research interests include automation, connectivity, and sensing in transportation and related systems. He received a B.S. degree (2006) in civil engineering with a minor in computer engineering from Tsinghua University, China, an M.S. degree (2007), and a Ph.D. (2011) degree in civil engineering along with an M.S. degree (2010) in applied mathematics from the University of Illinois at Urban- Champaign, USA.
Dr. Heye Huang is a Research Associate with the Connected & Autonomous Transportation Systems Lab, University of Wisconsin–Madison. She received her Ph.D. degree in Vehicle Engineering from Tsinghua University in 2023. She was invited as a Visiting Scholar at the Department of Cognitive Robotics, Delft University of Technology, from 2021 to 2022. Her current research interests include connected and automated vehicles, risk assessment, decision-making, and human-centered AI. She has authored over 30 SCI/EI-indexed journal papers, and is a co-holder of over 40 invention patents. Dr. Huang was a recipient of Outstanding Ph.D. Graduate, Outstanding Academic Star, and the National Scholarship at Tsinghua University. She received the Best Paper Award at the International Symposium on Accident Analysis & Prevention (2021), the Journal Cover Paper Award for Engineering (2021), the Best Research Award for Risk and Uncertainty in Engineering Systems (2022), and the Best Paper Award at IEEE DSInS (2023).
Leveraging Physics-Enhanced Residual Learning (PERL), the AV control module achieves high slip ratios at peak Tire-Road Friction Coefficient (TRFC) values, improving estimation accuracy. Cooperative perception aggregates telematics data from connected AVs and regular vehicles (RVs), mitigating individual measurement errors and expanding coverage across diverse road conditions. A network smart routing strategy is proposed to optimize AV deployment for friction sensing, utilizing real-time traffic and environmental data without incurring extra resource costs. Field validation will be conducted at the Level-3 CAV testbed at the University of Wisconsin–Madison, using vehicles equipped with FHWA CDA CARMA capabilities.
More on this research: https://myumi.ch/XGxQX
---
About the speakers:
Dr. Xiaopeng (Shaw) Li is currently a Professor in the Department of Civil and Environmental Engineering and an affiliate in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison (UW-Madison). He served as the director of National Institute for Congestion Reduction (NICR) before. He is a recipient of a National Science Foundation (NSF) CAREER award. He has published over 110 peer-reviewed journal papers. He has served as the PI or a co-PI for a number of federal, state, and industry grants, with a total budget of around $30 million. His major research interests include automation, connectivity, and sensing in transportation and related systems. He received a B.S. degree (2006) in civil engineering with a minor in computer engineering from Tsinghua University, China, an M.S. degree (2007), and a Ph.D. (2011) degree in civil engineering along with an M.S. degree (2010) in applied mathematics from the University of Illinois at Urban- Champaign, USA.
Dr. Heye Huang is a Research Associate with the Connected & Autonomous Transportation Systems Lab, University of Wisconsin–Madison. She received her Ph.D. degree in Vehicle Engineering from Tsinghua University in 2023. She was invited as a Visiting Scholar at the Department of Cognitive Robotics, Delft University of Technology, from 2021 to 2022. Her current research interests include connected and automated vehicles, risk assessment, decision-making, and human-centered AI. She has authored over 30 SCI/EI-indexed journal papers, and is a co-holder of over 40 invention patents. Dr. Huang was a recipient of Outstanding Ph.D. Graduate, Outstanding Academic Star, and the National Scholarship at Tsinghua University. She received the Best Paper Award at the International Symposium on Accident Analysis & Prevention (2021), the Journal Cover Paper Award for Engineering (2021), the Best Research Award for Risk and Uncertainty in Engineering Systems (2022), and the Best Paper Award at IEEE DSInS (2023).
Related Links
Co-Sponsored By
Explore Similar Events
-
Loading Similar Events...
