A Hierarchical Reinforcement Learning Framework with Spatial-Temporal Graph Attention for Autonomous Driving Decision-Making and Control
This paper presents a hierarchical framework that integrates spatial-temporal graph attention network (ST-GAT) with reinforcement learning for decision and control of autonomous driving. Inspired by the principles of human cognition, the framework decomposes the driving task into two complementary levels: a high-level...