TD3 Tuned PID Controller for Autonomous Vehicle Platooning

The main objective of platoon control is coordinated motion of autonomous vehicle platooning with small intervehicle spacing while maintaining the same speed and acceleration as the leading vehicle, which can save energy consumption and improve traffic throughput. The conventional platoon control methods are confronted with the problem of manual parameter tuning. In order to addres this isue, a novel bifold platoon control approach leveraging a deep reinforcement learning-based model is proposed, which enables the platoon adapt to the complex traffic environment, and guarantees the safety of platoon. The upper layer controller based on the TD3 tuned PID algorithm outputs the desired acceleration. This integration mitigates the inconvenience of frequent manual parameter tuning asociated with the conventional PID algorithm. The lower layer controller tracks the desired acceleration based on the inverse vehicle dynamics model and feedback control. Through this dynamic inverse model, the desired acceleration of the platoon vehicle is transformed into a feedforward control input. This input is then supplemented by feedback from a PID controller. A comprehensive validation of the proposed approach is conducted through a collaborative simulation experiment using Carmaker/Simulink. The results show the trajectory of the desired acceleration is smooth, indicating a ride comfort of vehicle. Moreover, the platoon vehicle is able to make a quick response to the speed change of the predecesor. The maximum error in the distance between vehicles in the platoon is 2.5m. In summary, the proposed control method of connected and automated vehicle platoon based on TD3 tuned PID effectively realizes cooperative control of platoon vehicles.