基于车-车通信的新型列控系统，通过等距离间隔、等时间间隔和变时距3种控制策略实现高效率的列车追踪控制。由于在车队控制中，领航车的控制具有随机性，如何保证不同控制策略中车队的稳定性至关重要。提出了一种基于随机价格时间博弈理论（stochastic priced timed game，SPTG）的车-车通信控制策略建模与验证方法。首先，针对不同控制策略要求，利用随机价格时间自动机，建立包含领航车和跟随车的车队控制模型，并进行稳定性验证；然后，以时间为成本函数，通过对建立车队随机价格时间博弈自动机模型，利用Q-learning强化学习方法得到车队的最优驾驶策略；最后，结合多车运行追踪场景，进行车队的稳定性仿真优化。结果表明：相比于车队的随机运行策略，该方法使得车队的稳定误差更小。
Next generation train control system（NGTC）based on Train-Train communication realizes highly efficient train tracking control through three control strategies of constant spacing, constant time interval, and dynamic headway. Since the leader train control is random in the platoon control, how to ensure the safety of the platoon in different control strategies is very important. This paper proposes a Train-Train communication control strategy modeling and verification method based on stochastic priced timed game（SPTG）. Firstly, according to the requirements of different control strategies, a platoon control model including a leader train and follower trains is established by using SPTG automata, and the stability is verified. Secondly, taking time as the cost function, Q-learning is used to obtain the optimal driving strategy of the platoon through the platoon's SPTG automata model. Finally, combined with multi-train operation tracking scenarios, the stability simulation optimization of the platoon is carried out. The result shows that the stability error of the platoon is smaller than that of the random operation of the platoon.
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