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Congested multimodal transit network design

Author

Listed:
  • Quentin K. Wan

    (Napier University)

  • Hong K. Lo

    (Hong Kong University of Science and Technology)

Abstract

The planning of transit services is vital to transit-oriented metropolises. It is a complex, multi-objective decision process, especially for services operated by the private sector. Traveler’s desire for direct, affordable, and quality services often conflicts with the profit-making objective of private operators. In a multi-modal network, partly collaborative and partly competitive interactions among transit modes further complicate the problem. To simplify the planning problem, existing studies generally consider transit network design from the perspective of a single mode while neglecting the modal interactions. The lack of a comprehensive approach across transit modes may result in an unbalanced supply of transit services, weakening the financial viability of the services and, more importantly, adding unnecessarily to congestion, especially in already congested districts. This study explicitly considers these interactions in a multi-modal network framework. We develop a systematic phase-wise methodology for multi-modal network design, considering both the effect of congestion and integration of modal transfers. Inter-route and inter-modal transfers are modeled through the State Augmented Multi-modal (SAM) network approach developed in earlier studies. An illustrative example is included to demonstrate the design procedure and its salient features.

Suggested Citation

  • Quentin K. Wan & Hong K. Lo, 2009. "Congested multimodal transit network design," Public Transport, Springer, vol. 1(3), pages 233-251, August.
  • Handle: RePEc:spr:pubtra:v:1:y:2009:i:3:d:10.1007_s12469-009-0015-8
    DOI: 10.1007/s12469-009-0015-8
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    References listed on IDEAS

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    Cited by:

    1. Fan, Wenbo & Mei, Yu & Gu, Weihua, 2018. "Optimal design of intersecting bimodal transit networks in a grid city," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 203-226.
    2. An, Kun & Lo, Hong K., 2016. "Two-phase stochastic program for transit network design under demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 157-181.
    3. Amirali Zarrinmehr & Mahmoud Saffarzadeh & Seyedehsan Seyedabrishami & Yu Marco Nie, 2016. "A path-based greedy algorithm for multi-objective transit routes design with elastic demand," Public Transport, Springer, vol. 8(2), pages 261-293, September.
    4. Cancela, Héctor & Mauttone, Antonio & Urquhart, María E., 2015. "Mathematical programming formulations for transit network design," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 17-37.
    5. Javier Durán-Micco & Pieter Vansteenwegen, 2022. "A survey on the transit network design and frequency setting problem," Public Transport, Springer, vol. 14(1), pages 155-190, March.
    6. An, Kun & Lo, Hong K., 2015. "Robust transit network design with stochastic demand considering development density," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 737-754.
    7. Javier Duran & Lorena Pradenas & Victor Parada, 2019. "Transit network design with pollution minimization," Public Transport, Springer, vol. 11(1), pages 189-210, June.
    8. Yuan, Yun & Yu, Jie, 2018. "Locating transit hubs in a multi-modal transportation network: A cluster-based optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 85-103.

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