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Volume 10 Issue 9
Sep.  2023

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2023  >  10(9): 1822-1833
W. Xu, C. Zhao, J. Cheng, Y. Wang, Y. Q. Tang, T. Zhang, Z. M. Yuan, Y. S. Lv, and F.-Y. Wang, “Transformer-based macroscopic regulation for high-speed railway timetable rescheduling,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 9, pp. 1822–1833, Sept. 2023. doi: 10.1109/JAS.2023.123501
Citation: W. Xu, C. Zhao, J. Cheng, Y. Wang, Y. Q. Tang, T. Zhang, Z. M. Yuan, Y. S. Lv, and F.-Y. Wang, “Transformer-based macroscopic regulation for high-speed railway timetable rescheduling,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 9, pp. 1822–1833, Sept. 2023. doi: 10.1109/JAS.2023.123501
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Transformer-Based Macroscopic Regulation for High-Speed Railway Timetable Rescheduling

doi: 10.1109/JAS.2023.123501
Funds:  This work was supported partially by the National Natural Science Foundation of China (61790573, 61790575), the Center of National Railway Intelligent Transportation System Engineering and Technology (RITS2019KF03), China Academy of Railway Sciences Corporation Limited, China Railway Project (N2019G020), China Railway Project (L2022X002), and the Key Project of Science and Technology Research Plan of China Academy of Railway Sciences Group Co. Ltd. (2022YJ326)
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    Abstract
  • Unexpected delays in train operations can cause a cascade of negative consequences in a high-speed railway system. In such cases, train timetables need to be rescheduled. However, timely and efficient train timetable rescheduling is still a challenging problem due to its modeling difficulties and low optimization efficiency. This paper presents a Transformer-based macroscopic regulation approach which consists of two stages including Transformer-based modeling and policy-based decision-making. Firstly, the relationship between various train schedules and operations is described by creating a macroscopic model with the Transformer, providing the better understanding of overall operation in the high-speed railway system. Then, a policy-based approach is used to solve a continuous decision problem after macro-modeling for fast convergence. Extensive experiments on various delay scenarios are conducted. The results demonstrate the effectiveness of the proposed method in comparison to other popular methods.

     

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    Highlights

    • This paper analyzes the existing Train timetable rescheduling（TTR） methods of high-speed railway in complex network operating environment under emergencies
    • This paper presents a Transformer-based macroscopic regulation approach which consists of two stages including Transformer-based modeling and policy-based decision making
    • Experimental results show that the proposed approach outperforms other compared methods in terms of robustness and effectiveness in reducing train delays

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