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A train timetable rescheduling approach based on multi-train tracking optimization of high-speed railways
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Rongsheng Wang, Tao Zhang, Zhiming Yuan, Shuxin Ding, Qi Zhang
Railway Sciences | 2023, 2(3) : 358 - 370
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Railway Sciences | 2023, 2(3): 358-370
• Research paper •
A train timetable rescheduling approach based on multi-train tracking optimization of high-speed railways
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Rongsheng Wang, Tao Zhang, Zhiming Yuan, Shuxin Ding, Qi Zhang
Affiliations
  • Scientific and Technological Information Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
  • Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
  • Traffic Management Laboratory for High-Speed Railway, National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit, Beijing, China
  • Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
Published: 2023-09-10 doi: 10.1108/RS-05-2023-0022
Outline
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Purpose

This paper aims to propose a train timetable rescheduling (TTR) approach from the perspective of multi-train tracking optimization based on the mutual spatiotemporal information in the high-speed railway signaling system.

Design/methodology/approach

Firstly, a single-train trajectory optimization (STTO) model is constructed based on train dynamics and operating conditions. The train kinematics parameters, including acceleration, speed and time at each position, are calculated to predict the arrival times in the train timetable. A STTO algorithm is developed to optimize a single-train time-efficient driving strategy. Then, a TTR approach based on multi-train tracking optimization (TTR-MTTO) is proposed with mutual information. The constraints of temporary speed restriction (TSR) and end of authority are decoupled to calculate the tracking trajectory of the backward tracking train. The multi-train trajectories at each position are optimized to generate a time-efficient train timetable.

Findings

The numerical experiment is performed on the Beijing-Tianjin high-speed railway line and CR400AF. The STTO algorithm predicts the train's planned arrival time to calculate the total train delay (TTD). As for the TSR scenario, the proposed TTR-MTTO can reduce TTD by 60.60% compared with the traditional TTR approach with dispatchers' experience. Moreover, TTR-MTTO can optimize a time-efficient train timetable to help dispatchers reschedule trains more reasonably.

Originality/value

With the cooperative relationship and mutual information between train rescheduling and control, the proposed TTR-MTTO approach can automatically generate a time-efficient train timetable to reduce the total train delay and the work intensity of dispatchers.

High-speed railway  /  Train timetable rescheduling  /  Multi-train trajectory optimization  /  Train operation control  /  Integration of train rescheduling and control
Rongsheng Wang, Tao Zhang, Zhiming Yuan, Shuxin Ding, Qi Zhang. A train timetable rescheduling approach based on multi-train tracking optimization of high-speed railways[J]. Railway Sciences, 2023 , 2 (3) : 358 -370 . DOI: 10.1108/RS-05-2023-0022
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Funding
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  • the National Natural Science Foundation of China(62203468)
  • the Young Elite Scientist Sponsorship Program by China Association for Science and Technology (CAST)(2022QNRC001)
  • the Technological Research and Development Program of China Railway Corporation Limited(K2021X001)
  • the Foundation of China Academy of Railway Sciences Corporation Limited(2021YJ043)
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Year 2023 volume 2 Issue 3
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Article Info
doi: 10.1108/RS-05-2023-0022
  • Receive Date：2023-05-10
  • Online Date：2026-06-11
  • Published：2023-09-10
Article Data
Affiliations
History
  • Received：2023-05-10
  • Revised：2023-08-05
  • Accepted：2023-08-07
Funding
the National Natural Science Foundation of China(62203468)
the Young Elite Scientist Sponsorship Program by China Association for Science and Technology (CAST)(2022QNRC001)
the Technological Research and Development Program of China Railway Corporation Limited(K2021X001)
the Foundation of China Academy of Railway Sciences Corporation Limited(2021YJ043)
Affiliations
    Scientific and Technological Information Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
    Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China
    Traffic Management Laboratory for High-Speed Railway, National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit, Beijing, China
    Signal and Communication Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China

Corresponding:

Qi Zhang can be contacted at:
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