Path planning and decision optimization of automated driving based on reinforcement learning

This paper discusses the application of reinforcement learning in automatic driving path planning and decision optimization. Firstly, the background of autonomous driving technology, the importance of path planning and decision optimization, and the advantages of reinforcement learning are introduced. Then, the composition of the automatic driving system, the principle of path planning and the goal of decision optimization are expounded. Then, the theoretical basis of reinforcement learning is discussed, including the basic concepts, algorithm classification and characteristics. Finally, the path planning method and decision optimization strategy based on reinforcement learning are introduced in detail, and its performance evaluation indexes and challenges are analyzed.