Research on Intelligent Decision-making and Control in Autonomous Driving Based on Deep Reinforcement Learning

In today's era of rapid advancement in autonomous driving technology, intelligent decision-making control based on deep reinforcement learning has become a focal point of research. Autonomous vehicles face the complex challenges of a dynamic road environment and real-time driving decisions, areas where traditional algorithms fall short in adapting to constant changes. Deep reinforcement learning, with its capabilities for self-learning and optimization, has demonstrated remarkable potential. By designing effective deep learning networks and reinforcement learning frameworks, and employing experience replay mechanisms, intelligent agents can make autonomous decisions in perpetually evolving environments, thereby enhancing the safety and efficiency of autonomous driving. These technological innovations not only propel the progress of autonomous vehicle technology but also offer fresh perspectives for intelligent decision-making in other fields.