IDEAS home Printed from https://ideas.repec.org/a/spr/pubtra/v9y2017i1d10.1007_s12469-017-0157-z.html
   My bibliography  Save this article

Railway disruption management challenges and possible solution directions

Author

Listed:
  • Nadjla Ghaemi

    (Delft University of Technology)

  • Oded Cats

    (Delft University of Technology)

  • Rob M. P. Goverde

    (Delft University of Technology)

Abstract

This paper investigates the challenges of railway traffic controllers in dealing with big disruptions and the kind of support tools that could help to improve their task in terms of performance, lead time and workload. The disruption handling process can be partitioned into three phases resembling a bathtub. For each phase the essential decision making process has been identified. Currently, the support to rail traffic controllers in case of severe disruptions is limited to predefined contingency plans that are not always feasible or applicable. In the literature, models and algorithms have been identified that could be used in the different parts of the three phases of the disruption handling process. This paper investigates the processes of disruption management in practice and the challenges that traffic controllers are facing during a disruption. The literature of models applicable to disruption management is reviewed and classified based on the three phases of the traffic state during disruptions. Finally, a rescheduling optimization model is applied to a case of complete blockage on a corridor of the Dutch railway network. The case study shows how a microscopic model could support the traffic controllers by providing real-time solutions for different phases of a disruption.

Suggested Citation

  • Nadjla Ghaemi & Oded Cats & Rob M. P. Goverde, 2017. "Railway disruption management challenges and possible solution directions," Public Transport, Springer, vol. 9(1), pages 343-364, July.
    • Handle: RePEc:spr:pubtra:v:9:y:2017:i:1:d:10.1007_s12469-017-0157-z
    DOI: 10.1007/s12469-017-0157-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12469-017-0157-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12469-017-0157-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter J. Zwaneveld & Leo G. Kroon & H. Edwin Romeijn & Marc Salomon & Stéphane Dauzère-Pérès & Stan P. M. Van Hoesel & Harrie W. Ambergen, 1996. "Routing Trains Through Railway Stations: Model Formulation and Algorithms," Transportation Science, INFORMS, vol. 30(3), pages 181-194, August.
    2. G. Caimi & F. Chudak & M. Fuchsberger & M. Laumanns & R. Zenklusen, 2011. "A New Resource-Constrained Multicommodity Flow Model for Conflict-Free Train Routing and Scheduling," Transportation Science, INFORMS, vol. 45(2), pages 212-227, May.
    3. Lucas P. Veelenturf & Martin P. Kidd & Valentina Cacchiani & Leo G. Kroon & Paolo Toth, 2016. "A Railway Timetable Rescheduling Approach for Handling Large-Scale Disruptions," Transportation Science, INFORMS, vol. 50(3), pages 841-862, August.
    4. Richard Lusby & Jesper Larsen & David Ryan & Matthias Ehrgott, 2011. "Routing Trains Through Railway Junctions: A New Set-Packing Approach," Transportation Science, INFORMS, vol. 45(2), pages 228-245, May.
    5. 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.
    6. Meng, Lingyun & Zhou, Xuesong, 2011. "Robust single-track train dispatching model under a dynamic and stochastic environment: A scenario-based rolling horizon solution approach," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 1080-1102, August.
    7. 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.
    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. Noguchi, Hiroki & Fuse, Masaaki, 2020. "Rethinking critical node problem for railway networks from the perspective of turn-back operation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    2. Zhu, Yongqiu & Goverde, Rob M.P., 2019. "Railway timetable rescheduling with flexible stopping and flexible short-turning during disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 149-181.
    3. Zhu, Yongqiu & Goverde, Rob M.P., 2020. "Integrated timetable rescheduling and passenger reassignment during railway disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 282-314.
    4. Bešinović, Nikola & Ferrari Nassar, Raphael & Szymula, Christopher, 2022. "Resilience assessment of railway networks: Combining infrastructure restoration and transport management," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    5. 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.
    6. Knoester, Max J. & Bešinović, Nikola & Afghari, Amir Pooyan & Goverde, Rob M.P. & van Egmond, Jochen, 2024. "A data-driven approach for quantifying the resilience of railway networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    7. Ghaemi, Nadjla & Cats, Oded & Goverde, Rob M.P., 2017. "A microscopic model for optimal train short-turnings during complete blockages," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 423-437.
    8. Gkiotsalitis, K. & Cats, O., 2021. "At-stop control measures in public transport: Literature review and research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    9. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    10. Joshua Auld & Hubert Ley & Omer Verbas & Nima Golshani & Josiane Bechara & Angela Fontes, 2020. "A stated-preference intercept survey of transit-rider response to service disruptions," Public Transport, Springer, vol. 12(3), pages 557-585, October.
    11. Wen Hua & Ghim Ping Ong, 2018. "Effect of information contagion during train service disruption for an integrated rail-bus transit system," Public Transport, Springer, vol. 10(3), pages 571-594, December.
    12. Eva König, 2020. "A review on railway delay management," Public Transport, Springer, vol. 12(2), pages 335-361, June.
    13. van Lieshout, R.N. & Bouman, P.C. & Huisman, D., 2018. "Determining and Evaluating Alternative Line Plans in (Near) Out-of-Control Situations," Econometric Institute Research Papers EI2018-20, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Åse Jevinger & Jan A. Persson, 2019. "Exploring the potential of using real-time traveler data in public transport disturbance management," Public Transport, Springer, vol. 11(2), pages 413-441, August.

    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. Ghaemi, Nadjla & Cats, Oded & Goverde, Rob M.P., 2017. "A microscopic model for optimal train short-turnings during complete blockages," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 423-437.
    2. Leonardo Lamorgese & Carlo Mannino & Mauro Piacentini, 2016. "Optimal Train Dispatching by Benders’-Like Reformulation," Transportation Science, INFORMS, vol. 50(3), pages 910-925, August.
    3. Dewilde, Thijs & Sels, Peter & Cattrysse, Dirk & Vansteenwegen, Pieter, 2014. "Improving the robustness in railway station areas," European Journal of Operational Research, Elsevier, vol. 235(1), pages 276-286.
    4. Zhan, Shuguang & Xie, Jiemin & Wong, S.C. & Zhu, Yongqiu & Corman, Francesco, 2024. "Handling uncertainty in train timetable rescheduling: A review of the literature and future research directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    5. Lu, Gongyuan & Ning, Jia & Liu, Xiaobo & Nie, Yu (Marco), 2022. "Train platforming and rescheduling with flexible interlocking mechanisms: An aggregate approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    6. 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).
    7. 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.
    8. 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.
    9. 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.
    10. Burggraeve, Sofie & Vansteenwegen, Pieter, 2017. "Robust routing and timetabling in complex railway stations," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 228-244.
    11. Rajnish Kumar & Goutam Sen & Samarjit Kar & Manoj Kumar Tiwari, 2018. "Station Dispatching Problem for a Large Terminal: A Constraint Programming Approach," Interfaces, INFORMS, vol. 48(6), pages 510-528, November.
    12. 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.
    13. Zhou, Wenliang & Teng, Hualiang, 2016. "Simultaneous passenger train routing and timetabling using an efficient train-based Lagrangian relaxation decomposition," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 409-439.
    14. Zhu, Yongqiu & Goverde, Rob M.P., 2019. "Railway timetable rescheduling with flexible stopping and flexible short-turning during disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 149-181.
    15. Zhang, Yongxiang & D'Ariano, Andrea & He, Bisheng & Peng, Qiyuan, 2019. "Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 237-278.
    16. 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.
    17. Zhu, Yongqiu & Goverde, Rob M.P., 2020. "Integrated timetable rescheduling and passenger reassignment during railway disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 282-314.
    18. 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.
    19. Wang, Dian & D’Ariano, Andrea & Zhao, Jun & Zhong, Qingwei & Peng, Qiyuan, 2022. "Integrated rolling stock deadhead routing and timetabling in urban rail transit lines," European Journal of Operational Research, Elsevier, vol. 298(2), pages 526-559.
    20. Schön, Cornelia & König, Eva, 2018. "A stochastic dynamic programming approach for delay management of a single train line," European Journal of Operational Research, Elsevier, vol. 271(2), pages 501-518.

    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:spr:pubtra:v:9:y:2017:i:1:d:10.1007_s12469-017-0157-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.