Trajectory planning and control of autonomous vehicle based on reinforcement learning algorithm - Wang, Jia (Procedia computer science, 2025)
In order to explore the trajectory planning and control method of autonomous vehicle based on reinforcement learning algorithm, this paper designs an advanced control system by combining the basic characteristics of autonomous vehicle with the advantages of reinforcement learning. The system can intelligently plan the optimal driving trajectory according to the real-time road information, traffic conditions and the vehicle’s own state, and realize the smooth and safe driving of the vehicle through the precise control algorithm. Experiments have proved that the system can perform well in a variety of complex road conditions, effectively improving the driving efficiency and safety of autonomous vehicles. Compared with traditional trajectory planning methods, the system has stronger adaptive ability and can cope with unexpected situations and uncertainties better.