Platoon Control of Connected Vehicles via Safe Reinforcement Learning Based on Lyapunov Based Soft Actor Critic Algorithm - Luo, Xiaoyuan; Hao, Tiankuo; Li, Shaobao (Chinese Control and Decision Conference, 2024)
This paper addresses the platoon control problem of connected vehicular systems subject to safety constraints. A constrained Markov Decision Process model is established. A novel safe-reinforcement-learning control method based on the Lyapunov-based Soft Actor-Critic (LSAC) algorithm is developed, where the LSAC algorithm is designed to maximize the reward while minimizing the safety cost, ensuring minimal risk of collisions. Comparisons between the safe-reinforcement-learning control via LSAC algorithm and Soft Actor-Critic (SAC) algorithm are conducted to demonstrate the effectiveness of the proposed algorithm.