Adaptive Cruise Control Method for Automobiles Based on Dynamic Spacing Strategy & PID

Traditional cruise control systems often require frequent driver intervention in complex traffic scenarios. To address this issue, this study proposes an Adaptive Cruise Control (ACC) system based on a Proportional-Integral-Derivative (PID) control algorithm. The system optimizes vehicle speed and following distance control through a dynamic safety distance strategy. By utilizing radar and camera sensors to perceive the status of preceding vehicles in real time, the PID control system enables smooth acceleration adjustment. Experimental results indicate that, in scenarios simulating dynamic speed changes of the leading vehicle, the proposed system can quickly respond and steadily track the target speed while maintaining a safe distance above the threshold. This verifies the effectiveness of the system in terms of safety, tracking accuracy, and driving comfort. Compared to traditional cruise control methods, the PID algorithm combined with the dynamic spacing strategy significantly enhances the robustness and adaptability of the system. With the advancement of autonomous driving technology, future research will focus on the integration of multi-sensor fusion and artificial intelligence algorithms to further enhance the intelligence level and the ability to handle complex scenarios in ACC systems.