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Calibrating travel time thresholds with cluster analysis and AFC data for passenger reasonable route generation on an urban rail transit network

Author

Listed:
  • Wei Zhu

    (Tongji University
    Tongji University)

  • Wei-li Fan

    (Tongji University
    Tongji University)

  • Amr M. Wahaballa

    (Aswan University)

  • Jin Wei

    (Tongji University
    Tongji University)

Abstract

Estimating the route choice patterns for transit passengers is important to improve service reliability. The size and composition of a route choice set affects the choice model estimation and passenger flow calculations for urban rail transit (URT) networks. With the existing threshold decision method, there will be omissions or excess routes in the generated route set, which lead to a significant deviation in passenger flow assignments. This paper proposes a data-driven approach to calibrate the travel time thresholds when generating reasonable route choice sets. First, an automatic fare collection (AFC) data-driven framework is established to more accurately calibrate and dynamically update travel time thresholds with changes in the URT system. The framework consists of four steps: data preprocessing, origin–destination-based threshold calculation, cluster analysis-based calibration, and calibrated result output and update. Second, the proposed approach is applied to the Beijing subway as a case study, and several promising results are analyzed that allow the optimization of existing travel time thresholds. The obtained results help in the estimation of route choice behavior to validate current rail transit assignment models. This study is also applicable for other rail transit networks with AFC systems to record passenger passage times at both entry and exit gates.

Suggested Citation

  • Wei Zhu & Wei-li Fan & Amr M. Wahaballa & Jin Wei, 2020. "Calibrating travel time thresholds with cluster analysis and AFC data for passenger reasonable route generation on an urban rail transit network," Transportation, Springer, vol. 47(6), pages 3069-3090, December.
    • Handle: RePEc:kap:transp:v:47:y:2020:i:6:d:10.1007_s11116-019-10040-8
    DOI: 10.1007/s11116-019-10040-8
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    References listed on IDEAS

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    1. Coldren, Gregory M. & Koppelman, Frank S., 2005. "Modeling the competition among air-travel itinerary shares: GEV model development," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(4), pages 345-365, May.
    2. van der Zijpp, N.J. & Fiorenzo Catalano, S., 2005. "Path enumeration by finding the constrained K-shortest paths," Transportation Research Part B: Methodological, Elsevier, vol. 39(6), pages 545-563, July.
    3. Nguyen, S. & Pallottino, S., 1988. "Equilibrium traffic assignment for large scale transit networks," European Journal of Operational Research, Elsevier, vol. 37(2), pages 176-186, November.
    4. Piet Bovy & Sascha Hoogendoorn-Lanser, 2005. "Modelling route choice behaviour in multi-modal transport networks," Transportation, Springer, vol. 32(4), pages 341-368, July.
    5. Carlos F. Daganzo & Yosef Sheffi, 1977. "On Stochastic Models of Traffic Assignment," Transportation Science, INFORMS, vol. 11(3), pages 253-274, August.
    6. Swait, Joffre & Ben-Akiva, Moshe, 1987. "Incorporating random constraints in discrete models of choice set generation," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 91-102, April.
    7. Hironori Kato & Yuichiro Kaneko & Masashi Inoue, 2010. "Comparative analysis of transit assignment: evidence from urban railway system in the Tokyo Metropolitan Area," Transportation, Springer, vol. 37(5), pages 775-799, September.
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    Cited by:

    1. Tomhave, Benjamin J. & Khani, Alireza, 2022. "Refined choice set generation and the investigation of multi-criteria transit route choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 484-500.

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