Deep Learning and PID Integrated Lane Keeping Control Method

Lane keeping is a key aspect of autonomous driving technology, which requires vehicles to be able to maintain stable driving in the lane in complex and changing road environments. Traditional lane keeping algorithms are mostly based on image processing and control theory, but these methods have limitations in dealing with complex scenes and uncertain factors. In recent years, deep learning algorithms have made significant progress in fields such as image recognition and natural language processing, providing new ideas and methods for the research of lane keeping systems. This article will explore lane keeping systems based on deep learning algorithms, design comparative experiments for verification, and deploy PID controllers to the lane keeping control system. The experiment shows that the lane keeping control system based on deep learning and PID algorithm control designed in this article can be applied and has good lane keeping control effect.