The time delay in heavy-duty vehicle platoons due to actuators, sensors, and communication delays has significant effects on platoon performance; it is difficult to immediately ascertain the driver’s intention due to the time delay, so that there is a restriction on the intra-platoon spacing and the platoon’s performance is weakened. This study proposes a platooning control system that uses pedal information from the lead vehicle to overcome the time delay problem. Distributed Model Predictive Control (DMPC) is also used for the longitudinal control of the heavy-duty vehicle platoon to effectively address the time delay problem. The acceleration of the lead vehicle was estimated by its pedal information and a nonlinear vehicle dynamics model. The estimated acceleration was transmitted to the following vehicles and used as faster control input to the DMPC. The feasibility of the DMPC system for a heavy-duty vehicle platoon was verified by co-simulation on MATLAB-TruckSim using real pedal hardware. The performance of the control system was evaluated by comparing the results of using estimated acceleration with the TruckSim data. Furthermore, the improved platooning performance was confirmed by measuring the spacing error between successive vehicles, a tracking error index, and traffic flow.

中文翻译：

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基于铅踏板信息的重型汽车排模型预测纵向控制

由于执行器，传感器和通信延迟，重型车辆排的时间延迟对排的性能有重大影响；由于时间的延迟，难以立即确定驾驶员的意图，从而限制了排内的间隔并且降低了排行性能。这项研究提出了一种排班控制系统，该系统使用来自领先车辆的踏板信息来克服时延问题。分布式模型预测控制（DMPC）也用于重型车辆排的纵向控制，以有效解决时延问题。领先车辆的加速度通过其踏板信息和非线性车辆动力学模型进行估算。估计的加速度被传输到随后的车辆，并用作DMPC的更快控制输入。通过在MATLAB-TruckSim上使用真实的踏板硬件进行协同仿真，验证了DMPC系统用于重型车辆排的可行性。通过将使用估计加速度的结果与TruckSim数据进行比较，评估了控制系统的性能。此外，通过测量连续车辆之间的间距误差，跟踪误差指数和交通流量，可以确认改善的排性能。