This paper considers the cooperative adaptive cruise control (CACC) problem of heterogeneous vehicle platoons and proposes a data-driven optimal CACC approach for the heterogeneous platoon with unknown dynamics. To cope with the unknown dynamics of the vehicle CACC platoon system, the adaptive dynamic programming is used to design an online iteration policy for optimal CACC of the platoon. Using the predecessor-following topology, the CACC controllers are computed by employing the desired spacing errors, relative velocities, and accelerations of the vehicles. The stability of the closed-loop CACC system and the iteration algorithm are presented. Furthermore, the string stability of the platoon with the CACC system is established in terms of the acceleration transfer function between adjacent vehicles in frequent domain. Finally, the effectiveness of the proposed method is verified in two complex scenarios of varying speed cruise.

本文考虑了异构车辆排的协同自适应巡航控制（CACC）问题，并针对动力学未知的异构车辆提出了一种数据驱动的最优CACC方法。为了应对车辆CACC排系统的未知动态，自适应动态编程用于设计在线迭代策略，以优化排的CACC。使用先前的跟随拓扑，可以通过使用所需的间距误差，相对速度和车辆加速度来计算CACC控制器。给出了闭环CACC系统的稳定性和迭代算法。此外，根据频繁领域中相邻车辆之间的加速度传递函数，建立了带有CACC系统的排的弦稳定性。最后，