Zhaohui Liu received her M.S. degree in Vehicle Application Engineering, in 2004, and her Ph.D. in Traffic Environment and Safety Technology, in 2007, all from Jilin University, Changchun, China. She has worked at the State Key Laboratory of Automotive Simulation and Control (ASCL), China, and the University of Toronto (UT), Canada, in intelligent coordination and safety control of Human-Vehicle-Environment system. Now working at the college of Transportation, Shandong University of Science and Technology, she is a leader of the Institute of Traffic Behavior and Traffic Safety. She has published more than 63 academic papers, published three academic works, and holds more than 37 patents. Her research interests are mainly in traffic safety technology, environmental perception and collaborative decision for driverless vehicles in adverse weather conditions, as well as cooperative vehicle infrastructure system (CVIS).

Jiaxu Zhang graduated from Anhui Jianzhu University, China, in 2022 with a Bachelor's degree in Traffic Engineering. He is currently pursuing a Master's degree in Transportation Engineering at Shandong University of Science and Technology. His current research interests include autonomous driving environment perception under adverse weather conditions and multi-sensors fusion.

Xiaojun Zhang received the B.S. degree from Shandong University of Science and Technology, Qingdao, China, in 2024, where he is currently pursuing the M.S. degree in transportation engineering at the College of Transportation. His current research interests include environmental perception for autonomous driving under adverse weather conditions and multi-sensors fusion.

Hongle Song graduated from Shandong University of Science and Technology in 2023 and obtained his Bachelor's degree in Traffic Engineering. He is currently pursuing his Master's degree in Traffic and Transportation Engineering at Shandong University of Science and Technology, and his current research interests include environmental perception for autonomous driving and multi-sensor fusion under adverse weather conditions.