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Suitability Evaluation of a Train’s Scheduled Section Travel Time

Author

Listed:
  • Maosheng Li

    (School of traffic and transportation engineering, Central South University, Changsha 410083, China)

  • Qing Huang

    (School of traffic and transportation engineering, Central South University, Changsha 410083, China)

  • Lixuan Yao

    (School of traffic and transportation engineering, Central South University, Changsha 410083, China)

  • Yongliang Wang

    (School of traffic and transportation engineering, Central South University, Changsha 410083, China)

Abstract

Two methods used to evaluate the suitability of a train’s scheduled section travel time (TSSTT) are theoretical modeling and data analysis. The first is suitable for newly constructed railway projects, the second can reveal the reliability of the train section running time (TSRT) under an instruction of TSSTT in cases where the train operation data are provided. A suitability evaluation method of TSSTT is proposed by calculating the possibility that a train completes a task within the time windows, centering on the TSSTT given in advance. The TSRTs between two adjacent stations are classified into four groups based on whether the train dwells at the two end stations of the railway section, and then subdivided secondly into subgroups by the instruction of TSSTT given. The kurtosis of each subgroup data of TSRT is larger than 3, so Weibull distribution is selected to fit the TSRT distribution of subgroup data due to good fitness based on root measurement of the least square (SRLSM). A busy high-speed railway line in the Wuhan area of China is used to validate the presented approach. Each railway section has its own suitable TSSTT in which TSRT might achieve 96% reliability of arriving within 2.5 minutes centering on suitable TSSTT, otherwise which might not obtain 10% reliability.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2399-:d:334303
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    1. 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.
    2. 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.
    3. A. Higgins & E. Kozan, 1998. "Modeling Train Delays in Urban Networks," Transportation Science, INFORMS, vol. 32(4), pages 346-357, November.
    4. 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.
    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. 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.
    7. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    8. Ye, Hongbo & Liu, Ronghui, 2016. "A multiphase optimal control method for multi-train control and scheduling on railway lines," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 377-393.
    9. Espinosa-Aranda, José Luis & García-Ródenas, Ricardo & Ramírez-Flores, María del Carmen & López-García, María Luz & Angulo, Eusebio, 2015. "High-speed railway scheduling based on user preferences," European Journal of Operational Research, Elsevier, vol. 246(3), pages 772-786.
    10. Albrecht, Amie & Howlett, Phil & Pudney, Peter & Vu, Xuan & Zhou, Peng, 2016. "The key principles of optimal train control—Part 1: Formulation of the model, strategies of optimal type, evolutionary lines, location of optimal switching points," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 482-508.
    11. 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.
    12. 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.
    13. Vansteenwegen, P. & Oudheusden, D. Van, 2006. "Developing railway timetables which guarantee a better service," European Journal of Operational Research, Elsevier, vol. 173(1), pages 337-350, August.
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