Provably Safe and Human-like Car-following Model for Automated Vehicles

This presentation will navigate the intricacies of driving tasks, whether for human-driven or automated vehicles, involves a tripartite framework: sensing, planning, and action. While the action stage demonstrates commendable precision and the sensing stage grapples with stochastic variables amid fervent development, the trajectory planning stage emerges as a linchpin in ensuring safe operations within the realm of sensor uncertainties and inaccuracies. Presently, prevailing paradigms rooted in artificial intelligence, advanced driving assistance systems, and car-following models remain bereft of a rigorous mathematical safety proof and the ability to replicate human-like acceleration and deceleration patterns.

Dr. Wenlong Jin (BS in Automatic Control, University of Science and Technology of China, 1998; PhD in Applied Mathematics, UC Davis, 2003) is a Professor of Civil and Environmental Engineering at the Institute of Transportation Studies, UC Irvine. With a profound passion for the intricate workings of transportation and mobility systems, his expertise lies in the exploration of fundamental principles, concepts, models, and methods. Throughout his career, Dr. Jin has delved deep into various facets of transportation, including the comprehensive study of network traffic flow theory, capacity drop and lane-changing models, connected vehicle systems theory, and eco-friendly driving strategies.