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Determinants of passenger transfer waiting time at multi-modal connecting stations

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  • Hsu, Spring C.

Abstract

This paper formulates a model to represent the transfer waiting time for a connecting service at multi-modal stations, where waiting time considers the characteristics of both the connecting service and its feeder services. Numerical simulation results show that transfer waiting time is mainly affected by the capacities and headways of the connecting and feeder services. Simulations also show that compared with the effects of connecting service variables, the corresponding variables of the feeder service usually have greater influences on transfer waiting time. In general, simulation results suggest that multi-modal operations, transfer waiting time cannot be improved without operational coordination with the feeder service.

Suggested Citation

  • Hsu, Spring C., 2010. "Determinants of passenger transfer waiting time at multi-modal connecting stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 404-413, May.
    • Handle: RePEc:eee:transe:v:46:y:2010:i:3:p:404-413
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    Citations

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    Cited by:

    1. Sodachi, Majid & Sahraei, Pardis & Valilai, Omid Fatahi, 2020. "Public sustainable transportation planning with service level efficiency: Hamburg case study," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 97-127, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Juan Gabriel Brida & Juan Carlos Martín & Concepción Román & Raffaele Scuderi, 2017. "Air and HST Multimodal Products. A Segmentation Analysis for Policy Makers," Networks and Spatial Economics, Springer, vol. 17(3), pages 911-934, September.
    3. Román, Concepción & Martín, Juan Carlos, 2014. "Integration of HSR and air transport: Understanding passengers’ preferences," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 129-141.
    4. Huang, Hai-Jun & Xia, Tian & Tian, Qiong & Liu, Tian-Liang & Wang, Chenlan & Li, Daqing, 2020. "Transportation issues in developing China's urban agglomerations," Transport Policy, Elsevier, vol. 85(C), pages 1-22.
    5. Zhang, Zhenhao & Tafreshian, Amirmahdi & Masoud, Neda, 2020. "Modular transit: Using autonomy and modularity to improve performance in public transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    6. Yuan, Yalong & Yang, Min & Feng, Tao & Ma, Yafeng & Ren, Yifeng & Ruan, Xinpei, 2022. "Heterogeneity in the transfer time of air-rail intermodal passengers based on ticket booking data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 533-552.
    7. Chowdhury, Subeh & Ceder, Avishai (Avi), 2016. "Users’ willingness to ride an integrated public-transport service: A literature review," Transport Policy, Elsevier, vol. 48(C), pages 183-195.
    8. Mohammad Reza Amin-Naseri & Vahid Baradaran, 2015. "Accurate Estimation of Average Waiting Time in Public Transportation Systems," Transportation Science, INFORMS, vol. 49(2), pages 213-222, May.
    9. Aude Marzuoli & Isabelle Laplace & Eric Féron, 2013. "Multimodal, efficient transportation in airports and collaborative decision making," Post-Print hal-00874384, HAL.
    10. Panou, Konstantinos & Kapros, Seraphim & Polydoropoulou, Amalia, 2015. "How service bundling can increase the competitiveness of low market share transportation services," Research in Transportation Economics, Elsevier, vol. 49(C), pages 22-35.

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