Wang, Yihan (Beijing Jiaotong University), Fan, Liqun (Shenzhen Metro Group co., Ltd.), Jia, Qingdong (Traffic control Technology co. L.td), Li, Kaixuan (Traffic Control Technology Co., Ltd.), Zhang, Kun (Traffic Control Technology Co., Ltd.), Liu, Hongjie (Beijing Jiaotong University), Luo, Xiaolin (Beijing Jiaotong University)

A Distributed Model Predictive Control Approach for Virtually Coupled Train Set with Communication Delays

Scheduled for presentation during the Invited Session "Control, Communication and Emerging Technologies in Smart Rail Systems I" (WeAT7), Wednesday, September 25, 2024, 11:50−12:10, Salon 15

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 14, 2024

Abstract

Virtual Coupling (VC) has been widely investigated in railways, due to its remarkable efficiency and adaptability. In VC, multiple train units form a Virtually Coupled Train Set (VCTS), while driving at a minimum distance yet without physically coupled. To this end, Train-To-Train (T2T) communication is necessary for VCTS to exchange information between units. However, considering the inevitable communication delays, it is still challenging to guarantee the tracking accuracy and safety-constraint satisfaction of VCTS. Thus, this paper proposes a Distributed Model Predictive Control (DMPC) approach integrated with a waiting mechanism to overcome the effects from communication delays. This approach ensures that the state of the preceding unit can be accurately predicted by following units, which greatly enhances tracking accuracy. Consequently, maintaining the desired spacing facilitates the satisfaction of safety constraints. Experimental results demonstrate that, compared with other methods, our method improves the performance of VCTS operation under communication delays.