SAFER Seminar: Reinforcement Learning for Autonomous Driving
Welcome to a SAFER seminar with Dr. Pin Wang, California PATH at UC Berkeley, about Reinforcement Learning for Autonomous Driving
Dr. Pin Wang, researcher at California PATH, UC Berkeley, is visiting Chalmers and for two months, from mid-April to mid-June. Her research focus is on autonomous driving with machine learning algorithms, e.g. driving maneuver with reinforcement learning and inverse reinforcement learning, decision making with reinforcement learning, pedestrian intention prediction with generative models, intelligent signal control for multiple intersections.
Welcome to meet with Dr. Pin Wang, please sign up to the event below!
ABSTRACT
In this talk, I will first briefly introduce our research center, California PATH at UC Berkeley, and the research activities in Berkeley DeepDrive which is a consortium investigating state-of-the-art technologies in computer vision and machine learning for automotive applications. Second, I will introduce two research topics. One is Reinforcement Learning for lane change scenarios where we treat both the state space and action space as continuous, and the other is to combine Imitation Learning and Reinforcement Learning for learning human-like driving behaviors in a way of hybrid reward function and augmented dataset.
BIO
Dr. Pin Wang is a researcher at University of California, Berkeley. Her research focus is on autonomous driving with machine learning algorithms, e.g. driving maneuver with reinforcement learning and inverse reinforcement learning, decision making with reinforcement learning, etc. Her work also includes pedestrian intention prediction for autonomous driving, intelligent traffic signal control, assessment of advanced vehicular technologies for fuel efficiency, etc.
