Dr. Tianjia Yang is a postdoctoral scholar in the Smart Mobility Lab. His research applies AI to automated vehicles, including reinforcement learning for vehicle control and lane keeping assistance. He also leads the lab’s Pennsylvania DEP project on medium- and heavy-duty zero-emission vehicles. He received his Ph.D. in Infrastructure and Environmental Systems from the University of North Carolina at Charlotte (2024), his M.S. in Transportation Planning and Management from Tongji University (2012), and his B.S. in Transportation from Huazhong University of Science and Technology (2009). His interests include connected and autonomous vehicles, machine learning, intelligent transportation systems, transportation electrification, operations research, and traffic flow theory.
Publications
Lightweight LiDAR-Based Cooperative Localization Model for Asymmetric Leader-Follower Cooperative Driving Automation System
Morning Commute in a Y-Shaped Traffic Network with Early and Late Arrivals
Public or Private? A Unified Demand–Supply Coupled Framework for EV Infrastructure Investment
Optimizing Maintenance Routes for Highway Infrastructure Using Leader-Follower Autonomous Vehicles
Equitable Urban Electric Vehicle Charging: Feasibility and Benefits of Streetlight Charging in Kansas City Right-of-Way
SimLKAS: A Simulation-Based Framework for the Verification and Validation of Lane Keeping Assistance Systems