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An online shortest path algorithm for reliable routing in schedule-based transit networks considering transfer failure probability

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  • Khani, Alireza

Abstract

Most schedule-based transit assignment models assume deterministic vehicle arrival/departure times, in contrast to random vehicle arrival assumption in frequency-based models. This assumption simplifies user route choice behavior and fails to capture users’ response to unreliable service. Moreover, the inherent inconvenience of transfers, primarily due to uncertain waiting time and failure probability, has always been a challenge in modeling transit networks, to the extent that determining an appropriate transfer penalty for heterogeneous user population is still a question when using planning models. This study aims to bridge the gap between frequency-based and schedule-based transit assignment models, and proposes a path algorithm in schedule-based transit networks with stochastic vehicle arrival times to model users’ adaptive behavior in response to unreliable service. Path reliability is modeled by link failure probability, and an online shortest path algorithm is developed to find a routing policy with minimum expected travel time given preferred arrival time to destination. Complexity analyses and computational tests indicate that the model has potential for application in large-scale transit networks. Numerical tests verify that the model assigns passengers to more reliable paths with lower transfer rate without a need for a large transfer penalty.

Suggested Citation

  • Khani, Alireza, 2019. "An online shortest path algorithm for reliable routing in schedule-based transit networks considering transfer failure probability," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 549-564.
    • Handle: RePEc:eee:transb:v:126:y:2019:i:c:p:549-564
    DOI: 10.1016/j.trb.2019.04.009
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    References listed on IDEAS

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    Cited by:

    1. Pramesh Kumar & Alireza Khani, 2021. "Adaptive Park-and-ride Choice on Time-dependent Stochastic Multimodal Transportation Network," Networks and Spatial Economics, Springer, vol. 21(4), pages 771-800, December.
    2. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    3. Redmond, Michael & Campbell, Ann Melissa & Ehmke, Jan Fabian, 2022. "Reliability in public transit networks considering backup itineraries," European Journal of Operational Research, Elsevier, vol. 300(3), pages 852-864.
    4. Gardner, Clara Brimnes & Nielsen, Sara Dorthea & Eltved, Morten & Rasmussen, Thomas Kjær & Nielsen, Otto Anker & Nielsen, Bo Friis, 2021. "Calculating conditional passenger travel time distributions in mixed schedule- and frequency-based public transport networks using Markov chains," Transportation Research Part B: Methodological, Elsevier, vol. 152(C), pages 1-17.
    5. López, David & Lozano, Angélica, 2020. "Shortest hyperpaths in a multimodal hypergraph with real-time information on some transit lines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 541-559.

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