IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v44y2017i4p715-733.html
   My bibliography  Save this article

Distribution analysis of train interval journey time employing the censored model with shifting character

Author

Listed:
  • Maosheng Li
  • Zhengqiu Liu
  • Yonghong Zhang
  • Weijun Liu
  • Feng Shi

Abstract

The theoretical framework of limited dependent variable models is extended to accommodate a shifting character and thus fit the distribution of train journey time on sections of urban rail network. Data of actual train arrival and departure time at each station are used to calculate the journey time of each railway interval of multi-class trains. The log-normal distribution and normal distribution among a group of theoretical distributions are the most and second most suitable latent distributions of the train interval journey time in the censored models with shifting character. This modified distribution is described by four parameters, namely, the expectation and variance of the latent distribution and the upper and lower bound of the migration interval. The square root of the least square measurement (SRLSM) is taken as a measure, and a traversal search is adopted to determine the above four parameters according to the SRLSM. The average of the SRLSM of the theoretical train interval journey time distribution obtained by using the proposed method on all railway sections is 0.0905. The theoretical framework is the basis of storing hidden rules in data instead of past data of train travel time and optimizing the existing management of rail transit operation.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:44:y:2017:i:4:p:715-733
    DOI: 10.1080/02664763.2016.1182134
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2016.1182134
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2016.1182134?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. Kroon, Leo & Maróti, Gábor & Helmrich, Mathijn Retel & Vromans, Michiel & Dekker, Rommert, 2008. "Stochastic improvement of cyclic railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 42(6), pages 553-570, July.
    2. Li, Feng & Gao, Ziyou & Li, Keping & Yang, Lixing, 2008. "Efficient scheduling of railway traffic based on global information of train," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 1008-1030, December.
    3. Goossens, Jan-Willem & van Hoesel, Stan & Kroon, Leo, 2006. "On solving multi-type railway line planning problems," European Journal of Operational Research, Elsevier, vol. 168(2), pages 403-424, January.
    4. Chang, Yu-Hern & Yeh, Chung-Hsing & Shen, Ching-Cheng, 2000. "A multiobjective model for passenger train services planning: application to Taiwan's high-speed rail line," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 91-106, February.
    5. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    6. Huisman, Tijs & Boucherie, Richard J., 2001. "Running times on railway sections with heterogeneous train traffic," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 271-292, March.
    7. Vromans, Michiel J.C.M. & Dekker, Rommert & Kroon, Leo G., 2006. "Reliability and heterogeneity of railway services," European Journal of Operational Research, Elsevier, vol. 172(2), pages 647-665, July.
    8. A. Higgins & E. Kozan, 1998. "Modeling Train Delays in Urban Networks," Transportation Science, INFORMS, vol. 32(4), pages 346-357, November.
    9. 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.
    10. Meester, Ludolf E. & Muns, Sander, 2007. "Stochastic delay propagation in railway networks and phase-type distributions," Transportation Research Part B: Methodological, Elsevier, vol. 41(2), pages 218-230, February.
    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. Yi Zhao & Ronghui Liu & Xi Zhang & Anthony Whiteing, 2018. "A chance-constrained stochastic approach to intermodal container routing problems," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-22, February.

    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. Maosheng Li & Qing Huang & Lixuan Yao & Yongliang Wang, 2020. "Suitability Evaluation of a Train’s Scheduled Section Travel Time," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    2. Krier, Betty & Liu, Chia-Mei & McNamara, Brian & Sharpe, Jerrod, 2014. "Individual freight effects, capacity utilization, and Amtrak service quality," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 163-175.
    3. Jovanović, Predrag & Kecman, Pavle & Bojović, Nebojša & Mandić, Dragomir, 2017. "Optimal allocation of buffer times to increase train schedule robustness," European Journal of Operational Research, Elsevier, vol. 256(1), pages 44-54.
    4. Repolho, Hugo M. & Church, Richard L. & Antunes, António P., 2016. "Optimizing station location and fleet composition for a high-speed rail line," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 437-452.
    5. Yang, Lixing & Qi, Jianguo & Li, Shukai & Gao, Yuan, 2016. "Collaborative optimization for train scheduling and train stop planning on high-speed railways," Omega, Elsevier, vol. 64(C), pages 57-76.
    6. Yang, Lixing & Zhou, Xuesong & Gao, Ziyou, 2014. "Credibility-based rescheduling model in a double-track railway network: a fuzzy reliable optimization approach," Omega, Elsevier, vol. 48(C), pages 75-93.
    7. Jens Parbo & Otto Anker Nielsen & Carlo Giacomo Prato, 2016. "Passenger Perspectives in Railway Timetabling: A Literature Review," Transport Reviews, Taylor & Francis Journals, vol. 36(4), pages 500-526, July.
    8. Lusby, Richard M. & Larsen, Jesper & Bull, Simon, 2018. "A survey on robustness in railway planning," European Journal of Operational Research, Elsevier, vol. 266(1), pages 1-15.
    9. 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.
    10. 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.
    11. Vansteenwegen, Pieter & Dewilde, Thijs & Burggraeve, Sofie & Cattrysse, Dirk, 2016. "An iterative approach for reducing the impact of infrastructure maintenance on the performance of railway systems," European Journal of Operational Research, Elsevier, vol. 252(1), pages 39-53.
    12. 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.
    13. Lee, Yusin & Lu, Li-Sin & Wu, Mei-Ling & Lin, Dung-Ying, 2017. "Balance of efficiency and robustness in passenger railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 142-156.
    14. Yang, Xin & Chen, Anthony & Ning, Bin & Tang, Tao, 2017. "Bi-objective programming approach for solving the metro timetable optimization problem with dwell time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 22-37.
    15. Leachman, Robert C. & Jula, Payman, 2012. "Estimating flow times for containerized imports from Asia to the United States through the Western rail network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 296-309.
    16. Harshad Khadilkar, 2017. "Data-Enabled Stochastic Modeling for Evaluating Schedule Robustness of Railway Networks," Transportation Science, INFORMS, vol. 51(4), pages 1161-1176, November.
    17. Gábor Maróti, 2017. "A branch-and-bound approach for robust railway timetabling," Public Transport, Springer, vol. 9(1), pages 73-94, July.
    18. M. D. Yap & N. Oort & R. Nes & B. Arem, 2018. "Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective," Transportation, Springer, vol. 45(4), pages 1161-1180, July.
    19. 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.
    20. Högdahl, Johan & Bohlin, Markus & Fröidh, Oskar, 2019. "A combined simulation-optimization approach for minimizing travel time and delays in railway timetables," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 192-212.

    More about this item

    Statistics

    Access and download statistics

    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:taf:japsta:v:44:y:2017:i:4:p:715-733. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.