CHAMP: Integrated Logic with Reinforcement Learning for Hybrid Decision Making for Autonomous Vehicle Planning

A Cognitive Hybrid Autonomous Motion Planner (CHAMP) is developed for autonomous driving applications in challenging driving scenarios. The proposed hybrid planner unifies a hierarchical rule-based decision-making architecture with Reinforcement Learning (RL). For challenging intersection scenarios, RL agents are trained to replace a subset of the rules in the logical planner. The hybrid planner is systematically tested and benchmarked to demonstrate its effectiveness in handling challenging road scenario with congested and chaotic traffic conditions.