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Simulations for train traffic flow on single-track railways with speed limits and slopes

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  • Xiaoming Xu
  • Lixing Yang
  • Ziyou Gao
  • Jiancheng Long

Abstract

It might be assumed that a train should run as fast as possible to finish its trip on railway section in the shortest time. However, because of the complex operation constraints, such as speed limits, slopes, and interactions among trains, it is a difficult work to determine an optimal speed profile for a train under the consideration of saving time. This paper develops an efficient algorithm to generate the train speed profile with the minimum section trip time. Moreover, a discrete event model-based simulation approach is proposed to observe the traffic flow on single-track railways with speed limits and slopes in the moving block mode system. Extensive case studies are implemented to demonstrate the effectiveness of the proposed approach and investigate the influence that time headway and dwelling time bring to energy consumption and line clear time.

Suggested Citation

  • Xiaoming Xu & Lixing Yang & Ziyou Gao & Jiancheng Long, 2017. "Simulations for train traffic flow on single-track railways with speed limits and slopes," Journal of Simulation, Taylor & Francis Journals, vol. 11(4), pages 346-356, November.
    • Handle: RePEc:taf:tjsmxx:v:11:y:2017:i:4:p:346-356
    DOI: 10.1057/s41273-016-0040-y
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    Cited by:

    1. Andrzej Chudzikiewicz & Ignacy Góra & Juraj Gerlici & Seweryn Koziak & Andrzej Krzyszkowski & Anna Stelmach, 2024. "Model of Electric Locomotive Simulator Cabin Excitations," Energies, MDPI, vol. 17(12), pages 1-18, June.
    2. Yang, Xingxing & Li, Yang & Guo, Xin & Ding, Meiling & Yang, Jingxuan, 2023. "Simulation of energy-efficient operation for metro trains: A discrete event-driven method based on multi-agent theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    3. Li, Yang & Yang, Xin & Wu, Jianjun & Sun, Huijun & Guo, Xin & Zhou, Li, 2021. "Discrete-event simulations for metro train operation under emergencies: A multi-agent based model with parallel computing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    4. Emilia Koper & Andrzej Kochan, 2020. "Testing the Smooth Driving of a Train Using a Neural Network," Sustainability, MDPI, vol. 12(11), pages 1-14, June.

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