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Autonomous driving technology has been widely used and studied in depth in recent years, and has become a hot field in the automotive industry. As one of the core methods to realize automatic driving, automatic control theory provides an important theoretical basis and practical guidance for automatic driving systems. This paper aims to explore the application of automatic control theory to autonomous driving and analyze its potential impact on improving driving safety, comfort and efficiency. This paper first introduces the basic principles and components of the autonomous driving system. Among them, automatic control theory plays an important role in decision-making and execution. Secondly, this paper discusses the specific application of automatic control theory in automatic driving. These include PID controller-based vehicle stability control, model predictive control (MPC) for path planning and trajectory tracking. These applications enable autonomous driving systems to respond in real time to environmental changes and maintain vehicle stability and safety. Finally, the paper discusses the challenges and future directions of automatic control theory in autonomous driving. Future research should focus on further improving the robustness and adaptability of automatic control algorithms to cope with complex driving scenarios and uncertainties. To sum up, automatic control theory plays an important role in automatic driving and has broad application prospects. Through continuous improvement and innovation, automatic control theory will make an important contribution to the realization of safer, more efficient, and more intelligent autonomous driving technology.
K. Wang (Mon,) studied this question.