A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning
Jinning Li Liting Sun Jianyu Chen Masayoshi Tomizuka Wei Zhan Jinning Li Liting Sun Jianyu Chen Masayoshi Tomizuka Wei Zhan
Autonomous vehicles need to handle various traffic conditions and make safe and efficient decisions and maneuvers. However, on the one hand, a single optimization/sampling-based motion planner cannot efficiently generate safe trajectories in real time, particularly when there are many interactive vehicles near by. On the other hand, end-to-end learning methods cannot assure the safety of the outco...