IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i7p1853-d343951.html
   My bibliography  Save this article

Evaluating Line Capacity with an Analytical UIC Code 406 Compression Method and Blocking Time Stairway

Author

Listed:
  • Ruxin Wang

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Lei Nie

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Yuyan Tan

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

Abstract

Railways around the world are experiencing growth in traffic flow, but the problem concerning how to optimize the utilization of capacity is still demands significant research. To accommodate the increasing traffic demand, the high-speed railway operator in China is interested in understanding the potential benefit of adopting reasonable headway to balance the safety and efficiency of train operations. In this study, a compress timetable scheduling model based on the UIC Code 406 method is presented to evaluate the line capacity. In this model, train headway is not pre-fixed as in the existing research, but considers the actual operating conditions and is calculated using actual running data. The results of the case study show that refined headway calculations generally have positive capacity effects.

Suggested Citation

  • Ruxin Wang & Lei Nie & Yuyan Tan, 2020. "Evaluating Line Capacity with an Analytical UIC Code 406 Compression Method and Blocking Time Stairway," Energies, MDPI, vol. 13(7), pages 1-16, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1853-:d:343951
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/7/1853/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/7/1853/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Matthew E. H. Petering & Mojtaba Heydar & Dietrich R. Bergmann, 2016. "Mixed-Integer Programming for Railway Capacity Analysis and Cyclic, Combined Train Timetabling and Platforming," Transportation Science, INFORMS, vol. 50(3), pages 892-909, August.
    2. Li, Feng & Gao, Ziyou & Wang, David Z.W. & Liu, Ronghui & Tang, Tao & Wu, Jianjun & Yang, Lixing, 2017. "A subjective capacity evaluation model for single-track railway system with δ-balanced traffic and λ-tolerance level," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 43-66.
    3. Yan, Fei & Goverde, Rob M.P., 2019. "Combined line planning and train timetabling for strongly heterogeneous railway lines with direct connections," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 20-46.
    4. Abril, M. & Barber, F. & Ingolotti, L. & Salido, M.A. & Tormos, P. & Lova, A., 2008. "An assessment of railway capacity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 774-806, September.
    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. Zdenka Bulková & Jozef Gašparík & Jaroslav Mašek & Vladislav Zitrický, 2022. "Analytical Procedures for the Evaluation of Infrastructural Measures for Increasing the Capacity of Railway Lines," Sustainability, MDPI, vol. 14(21), pages 1-28, November.

    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. Xu, Xiaoming & Li, Chung-Lun & Xu, Zhou, 2021. "Train timetabling with stop-skipping, passenger flow, and platform choice considerations," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 52-74.
    2. Francesco Rotoli & Elena Navajas Cawood & Antonio Soria, 2016. "Capacity assessment of railway infrastructure: Tools, methodologies and policy relevance in the EU context," JRC Research Reports JRC100509, Joint Research Centre.
    3. Behiri, Walid & Belmokhtar-Berraf, Sana & Chu, Chengbin, 2018. "Urban freight transport using passenger rail network: Scientific issues and quantitative analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 227-245.
    4. Coviello, Nicola, 2015. "Modelling periodic operations on single track lines: Timetable design and stability evaluation," Research in Transportation Economics, Elsevier, vol. 54(C), pages 2-14.
    5. Oskar Fr�idh & Hans Sipil� & Jennifer Warg, 2014. "Capacity for express trains on mixed traffic lines," International Journal of Rail Transportation, Taylor & Francis Journals, vol. 2(1), pages 17-27, February.
    6. Bugalia, Nikhil & Maemura, Yu & Ozawa, Kazumasa, 2021. "Demand risk management of private High-Speed Rail operators: A review of experiences in Japan and Taiwan," Transport Policy, Elsevier, vol. 113(C), pages 67-76.
    7. Xu, Xin-yue & Liu, Jun & Li, Hai-ying & Jiang, Man, 2016. "Capacity-oriented passenger flow control under uncertain demand: Algorithm development and real-world case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 130-148.
    8. Ait Ali, Abderrahman & Warg, Jennifer & Eliasson, Jonas, 2020. "Pricing commercial train path requests based on societal costs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 452-464.
    9. Wenliang Zhou & Jing Kang & Jin Qin & Sha Li & Yu Huang, 2022. "Robust Optimization of High-Speed Railway Train Plan Based on Multiple Demand Scenarios," Mathematics, MDPI, vol. 10(8), pages 1-26, April.
    10. Maosheng Li & Zhengqiu Liu & Yonghong Zhang & Weijun Liu & Feng Shi, 2017. "Distribution analysis of train interval journey time employing the censored model with shifting character," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(4), pages 715-733, March.
    11. Line Blander Reinhardt & David Pisinger & Richard Lusby, 2018. "Railway capacity and expansion analysis using time discretized paths," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 712-739, December.
    12. Chen, Zebin & Li, Shukai & D’Ariano, Andrea & Yang, Lixing, 2022. "Real-time optimization for train regulation and stop-skipping adjustment strategy of urban rail transit lines," Omega, Elsevier, vol. 110(C).
    13. Zhang, Jiamin, 2015. "Analysis on line capacity usage for China high speed railway with optimization approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 336-349.
    14. Li, Feng & Gao, Ziyou & Wang, David Z.W. & Liu, Ronghui & Tang, Tao & Wu, Jianjun & Yang, Lixing, 2017. "A subjective capacity evaluation model for single-track railway system with δ-balanced traffic and λ-tolerance level," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 43-66.
    15. 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.
    16. Masoud Yaghini & Mohammadreza Sarmadi & Nariman Nikoo & Mohsen Momeni, 2014. "Capacity Consumption Analysis Using Heuristic Solution Method for Under Construction Railway Routes," Networks and Spatial Economics, Springer, vol. 14(3), pages 317-333, December.
    17. Talebian, Ahmadreza & Zou, Bo, 2015. "Integrated modeling of high performance passenger and freight train planning on shared-use corridors in the US," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 114-140.
    18. Gedik, Ridvan & Medal, Hugh & Rainwater, Chase & Pohl, Ed A. & Mason, Scott J., 2014. "Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 45-57.
    19. Zdenka Bulková & Jozef Gašparík & Jaroslav Mašek & Vladislav Zitrický, 2022. "Analytical Procedures for the Evaluation of Infrastructural Measures for Increasing the Capacity of Railway Lines," Sustainability, MDPI, vol. 14(21), pages 1-28, November.
    20. Sparing, Daniel & Goverde, Rob M.P., 2017. "A cycle time optimization model for generating stable periodic railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 198-223.

    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:jeners:v:13:y:2020:i:7:p:1853-:d:343951. 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.