Professor Jun Chen

Associate Professor, Oakland University

Personalized MPC for Autonomous Vehicle Lateral Motion Control via Inverse Reinforcement Learning

This talk will present a personalized lane change control framework that combines the maximum entropy inverse reinforcement learning (MaxEnt IRL) with model predictive control (MPC). Instead of manually tuning the MPC cost weight, the proposed method learns a cost function from expert driving demonstrations using interpretable trajectory features. The learned weights are incorporated into the MPC formulation to generate personalized lane change trajectories that mimic the expert driving style. Simulation results in CARLA show that the IRL-trained MPC controller can reproduce distinct driving styles and matches expert behaviors in heading, lateral motion, and steering. Furthermore, real world on-road testing on an ISUZU truck demonstrated that the proposed controller generalizes well to unseen initial conditions. Overall, the proposed approach reduces manual calibration efforts, eliminates the need for explicit path planning, improves controller interpretability, and enables personalized driver behavior replication.

Bio

Jun Chen (S'11-M'14-SM'20) received his Bachelor's degree in Automation from Zhejiang University, Hangzhou China, in 2009, and Ph.D. in Electrical Engineering from Iowa State University, Ames IA, USA, in 2014. He was with Idaho National Laboratory from 2014 to 2016 and with General Motors from 2017 to 2020. Dr. Chen joined Oakland University in 2020, where he is currently an associate professor at the ECE department. His research interests include advanced control and optimization, model predictive control, artificial intelligence, and stochastic hybrid systems, with applications in intelligent vehicles, robotics, and energy systems. Dr. Chen is a recipient of the NSF CAREER Award, the Best Paper Award from IEEE Transactions on Automation Science and Engineering, the Best Paper Award from IEEE International Conference on Electro Information Technology, the Best Paper Award from IEEE Cyber Awareness & Research Symposium, the New Investigator Research Excellence Award and Outstanding Graduate Mentor Award from Oakland University, the Publication Achievement Award from Idaho National Laboratory, the Research Excellence Award from Iowa State University, and the Outstanding Student Award from Zhejiang University. He is currently a Senior Member of the IEEE.