IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i8p2351-d224283.html
   My bibliography  Save this article

Dispatching High-Speed Rail Trains via Utilizing the Reverse Direction Track: Adaptive Rescheduling Strategies and Application

Author

Listed:
  • Sairong Peng

    (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China)

  • Xin Yang

    (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China)

  • Hongwei Wang

    (National Research Center of Railway Safety Assessment, Beijing Jiaotong University, Beijing 100044, China)

  • Hairong Dong

    (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China)

  • Bin Ning

    (State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China)

  • Haichuan Tang

    (CRRC Institute, CRRC Corporation Limited, Beijing 100067, China)

  • Zhipeng Ying

    (China Academy of Railway Sciences, Beijing 100081, China)

  • Ruijun Tang

    (Hohhot Urban Rail Transit Construction Management Corporation Limited, Hohhot 010010, China)

Abstract

This paper studies the train rescheduling problem on high-speed railway corridor in the situation where contingencies occur and lead to sudden deceleration of some trains. First, we develop an adaptive rescheduling strategy (AR-S) which allows normal trains to use reverse direction track to overtake front decelerating trains based on delay comparison under different path choices. Second, the traditional rescheduling strategy (TR-S) which does not allow any trains to switch tracks is mentioned as a sharp contrast to AR-S. Furthermore, a performance evaluation criterion is designed to evaluate the effectiveness of the train rescheduling approaches. Finally, numerical experiments carried out on Beijing-Tianjin intercity high-speed railway show that AR-S can reduce the total delay of trains up to 24% in comparison with TR-S.

Suggested Citation

  • Sairong Peng & Xin Yang & Hongwei Wang & Hairong Dong & Bin Ning & Haichuan Tang & Zhipeng Ying & Ruijun Tang, 2019. "Dispatching High-Speed Rail Trains via Utilizing the Reverse Direction Track: Adaptive Rescheduling Strategies and Application," Sustainability, MDPI, vol. 11(8), pages 1-20, April.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:8:p:2351-:d:224283
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/8/2351/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/8/2351/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paulus T. Aditjandra & Thomas H. Zunder & Dewan Md Zahurul Islam & Roberto Palacin, 2016. "Green Rail Transportation: Improving Rail Freight to Support Green Corridors," International Series in Operations Research & Management Science, in: Harilaos N. Psaraftis (ed.), Green Transportation Logistics, edition 127, chapter 0, pages 413-454, Springer.
    2. Lvhua Wang & Yongxue Liu & Liang Mao & Chao Sun, 2018. "Potential Impacts of China 2030 High-Speed Rail Network on Ground Transportation Accessibility," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
    3. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    4. Pellegrini, Paola & Marlière, Grégory & Rodriguez, Joaquin, 2014. "Optimal train routing and scheduling for managing traffic perturbations in complex junctions," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 58-80.
    5. Xu, Peijuan & Corman, Francesco & Peng, Qiyuan & Luan, Xiaojie, 2017. "A train rescheduling model integrating speed management during disruptions of high-speed traffic under a quasi-moving block system," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 638-666.
    6. Cacchiani, Valentina & Furini, Fabio & Kidd, Martin Philip, 2016. "Approaches to a real-world Train Timetabling Problem in a railway node," Omega, Elsevier, vol. 58(C), pages 97-110.
    7. Xu, Xiaoming & Li, Keping & Yang, Lixing, 2015. "Scheduling heterogeneous train traffic on double tracks with efficient dispatching rules," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 364-384.
    8. Mu, Shi & Dessouky, Maged, 2013. "Efficient dispatching rules on double tracks with heterogeneous train traffic," Transportation Research Part B: Methodological, Elsevier, vol. 51(C), pages 45-64.
    9. Cacchiani, Valentina & Caprara, Alberto & Toth, Paolo, 2010. "Scheduling extra freight trains on railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 215-231, February.
    10. Samà, Marcella & Pellegrini, Paola & D’Ariano, Andrea & Rodriguez, Joaquin & Pacciarelli, Dario, 2016. "Ant colony optimization for the real-time train routing selection problem," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 89-108.
    11. Šemrov, D. & Marsetič, R. & Žura, M. & Todorovski, L. & Srdic, A., 2016. "Reinforcement learning approach for train rescheduling on a single-track railway," Transportation Research Part B: Methodological, Elsevier, vol. 86(C), pages 250-267.
    12. Jiang, Feng & Cacchiani, Valentina & Toth, Paolo, 2017. "Train timetabling by skip-stop planning in highly congested lines," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 149-174.
    13. Zhan, Shuguang & Kroon, Leo G. & Veelenturf, Lucas P. & Wagenaar, Joris C., 2015. "Real-time high-speed train rescheduling in case of a complete blockage," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 182-201.
    14. Shiwei Lu & Yaping Huang & Zhiyuan Zhao & Xiping Yang, 2018. "Exploring the Hierarchical Structure of China’s Railway Network from 2008 to 2017," Sustainability, MDPI, vol. 10(9), pages 1-15, September.
    15. Meng, Lingyun & Zhou, Xuesong, 2014. "Simultaneous train rerouting and rescheduling on an N-track network: A model reformulation with network-based cumulative flow variables," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 208-234.
    16. Xu, Xiaoming & Li, Chung-Lun & Xu, Zhou, 2018. "Integrated train timetabling and locomotive assignment," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 573-593.
    17. Bettinelli, Andrea & Santini, Alberto & Vigo, Daniele, 2017. "A real-time conflict solution algorithm for the train rescheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 237-265.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Yihui & Zhao, Kangqi & D’Ariano, Andrea & Niu, Ru & Li, Shukai & Luan, Xiaojie, 2021. "Real-time integrated train rescheduling and rolling stock circulation planning for a metro line under disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 87-117.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaoming Xu & Keping Li & Lixing Yang & Ziyou Gao, 2019. "An efficient train scheduling algorithm on a single-track railway system," Journal of Scheduling, Springer, vol. 22(1), pages 85-105, February.
    2. Yin, Jiateng & Yang, Lixing & Tang, Tao & Gao, Ziyou & Ran, Bin, 2017. "Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 182-213.
    3. Li, Wenqing & Ni, Shaoquan, 2022. "Train timetabling with the general learning environment and multi-agent deep reinforcement learning," Transportation Research Part B: Methodological, Elsevier, vol. 157(C), pages 230-251.
    4. Yin, Jiateng & Tang, Tao & Yang, Lixing & Gao, Ziyou & Ran, Bin, 2016. "Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 178-210.
    5. Zhou, Wenliang & Tian, Junli & Xue, Lijuan & Jiang, Min & Deng, Lianbo & Qin, Jin, 2017. "Multi-periodic train timetabling using a period-type-based Lagrangian relaxation decomposition," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 144-173.
    6. Zhan, Shuguang & Kroon, Leo G. & Zhao, Jun & Peng, Qiyuan, 2016. "A rolling horizon approach to the high speed train rescheduling problem in case of a partial segment blockage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 32-61.
    7. Luan, Xiaojie & Wang, Yihui & De Schutter, Bart & Meng, Lingyun & Lodewijks, Gabriel & Corman, Francesco, 2018. "Integration of real-time traffic management and train control for rail networks - Part 1: Optimization problems and solution approaches," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 41-71.
    8. M. Shakibayifar & A. Sheikholeslami & F. Corman & E. Hassannayebi, 2020. "An integrated rescheduling model for minimizing train delays in the case of line blockage," Operational Research, Springer, vol. 20(1), pages 59-87, March.
    9. Zhang, Yongxiang & Peng, Qiyuan & Yao, Yu & Zhang, Xin & Zhou, Xuesong, 2019. "Solving cyclic train timetabling problem through model reformulation: Extended time-space network construct and Alternating Direction Method of Multipliers methods," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 344-379.
    10. Zhang, Chuntian & Gao, Yuan & Yang, Lixing & Gao, Ziyou & Qi, Jianguo, 2020. "Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 64-92.
    11. Xu, Peijuan & Corman, Francesco & Peng, Qiyuan & Luan, Xiaojie, 2017. "A train rescheduling model integrating speed management during disruptions of high-speed traffic under a quasi-moving block system," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 638-666.
    12. Bettinelli, Andrea & Santini, Alberto & Vigo, Daniele, 2017. "A real-time conflict solution algorithm for the train rescheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 237-265.
    13. Xu, Xiaoming & Li, Keping & Yang, Lixing, 2015. "Scheduling heterogeneous train traffic on double tracks with efficient dispatching rules," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 364-384.
    14. Zhang, Chuntian & Gao, Yuan & Cacchiani, Valentina & Yang, Lixing & Gao, Ziyou, 2023. "Train rescheduling for large-scale disruptions in a large-scale railway network," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    15. Luan, Xiaojie & De Schutter, Bart & Meng, Lingyun & Corman, Francesco, 2020. "Decomposition and distributed optimization of real-time traffic management for large-scale railway networks," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 72-97.
    16. Lamorgese, Leonardo & Mannino, Carlo & Natvig, Erik, 2017. "An exact micro–macro approach to cyclic and non-cyclic train timetabling," Omega, Elsevier, vol. 72(C), pages 59-70.
    17. Tian, Xiaopeng & Niu, Huimin, 2020. "Optimization of demand-oriented train timetables under overtaking operations: A surrogate-dual-variable column generation for eliminating indivisibility," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 143-173.
    18. Pellegrini, Paola & Pesenti, Raffaele & Rodriguez, Joaquin, 2019. "Efficient train re-routing and rescheduling: Valid inequalities and reformulation of RECIFE-MILP," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 33-48.
    19. Gao, Yuan & Kroon, Leo & Yang, Lixing & Gao, Ziyou, 2018. "Three-stage optimization method for the problem of scheduling additional trains on a high-speed rail corridor," Omega, Elsevier, vol. 80(C), pages 175-191.
    20. Xue, Hongjiao & Jia, Limin & Li, Jian & Guo, Jianyuan, 2022. "Jointly optimized demand-oriented train timetable and passenger flow control strategy for a congested subway line under a short-turning operation pattern," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:11:y:2019:i:8:p:2351-:d:224283. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.