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

Author

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  • 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
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    References listed on IDEAS

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    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. 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.
    3. 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.
    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.
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    Cited by:

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