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A model for estimating the optimal cycle length of demand responsive feeder transit services

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  • Chandra, Shailesh
  • Quadrifoglio, Luca

Abstract

The general lack of first/last mile connectivity is one of the main challenges faced by today’s public transit. One of the possible actions towards a solution to this problem is the planning, design and implementation of efficient feeder transit services. This paper develops an analytical model which allows for an easy computation of near optimal terminal-to-terminal cycle length of a demand responsive feeder service to maximize service quality provided to customers, defined as the inverse of a weighted sum of waiting and riding times. The model estimates the recommended cycle length by only plugging in geometrical parameters and demand data, without relying on extensive simulation analyses or rule of thumbs. Simulation experiments and comparisons with real services validate our model, which would allow planners, decision makers and practitioners to quickly identify the best feeder transit operating design of any given residential area.

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  • Chandra, Shailesh & Quadrifoglio, Luca, 2013. "A model for estimating the optimal cycle length of demand responsive feeder transit services," Transportation Research Part B: Methodological, Elsevier, vol. 51(C), pages 1-16.
    • Handle: RePEc:eee:transb:v:51:y:2013:i:c:p:1-16
    DOI: 10.1016/j.trb.2013.01.008
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    Cited by:

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    7. Ansari, Sina & Başdere, Mehmet & Li, Xiaopeng & Ouyang, Yanfeng & Smilowitz, Karen, 2018. "Advancements in continuous approximation models for logistics and transportation systems: 1996–2016," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 229-252.
    8. Kim, Myungseob (Edward) & Schonfeld, Paul, 2015. "Maximizing net benefits for conventional and flexible bus services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 116-133.
    9. Sayarshad, Hamid R. & Chow, Joseph Y.J., 2015. "A scalable non-myopic dynamic dial-a-ride and pricing problem," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 539-554.
    10. Qiu, Feng & Shen, Jinxing & Zhang, Xuechi & An, Chengchuan, 2015. "Demi-flexible operating policies to promote the performance of public transit in low-demand areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 215-230.
    11. Kim, Myungseob (Edward) & Schonfeld, Paul, 2014. "Integration of conventional and flexible bus services with timed transfers," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 76-97.
    12. Myungseob (Edward) Kim & Eungcheol Kim, 2023. "Joint Optimization of Distance-Based Fares and Headway for Fixed-Route Bus Operations," Sustainability, MDPI, vol. 15(21), pages 1-14, October.
    13. Chandra, Shailesh & Vadali, Sharada, 2014. "Evaluating accessibility impacts of the proposed America 2050 high-speed rail corridor for the Appalachian Region," Journal of Transport Geography, Elsevier, vol. 37(C), pages 28-46.
    14. Chandra, Shailesh & Bari, Muhammad Ehsanul & Devarasetty, Prem Chand & Vadali, Sharada, 2013. "Accessibility evaluations of feeder transit services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 47-63.
    15. Anastasios Charisis & Christina Iliopoulou & Konstantinos Kepaptsoglou, 2018. "DRT route design for the first/last mile problem: model and application to Athens, Greece," Public Transport, Springer, vol. 10(3), pages 499-527, December.
    16. Rick Grahn & Sean Qian & Chris Hendrickson, 2023. "Optimizing first- and last-mile public transit services leveraging transportation network companies (TNC)," Transportation, Springer, vol. 50(5), pages 2049-2076, October.
    17. Nicole Ronald & Russell Thompson & Stephan Winter, 2015. "Simulating Demand-responsive Transportation: A Review of Agent-based Approaches," Transport Reviews, Taylor & Francis Journals, vol. 35(4), pages 404-421, July.
    18. Shixiong Jiang & Wei Guan & Liu Yang & Wenyi Zhang, 2020. "Feeder Bus Accessibility Modeling and Evaluation," Sustainability, MDPI, vol. 12(21), pages 1-17, October.
    19. Xin Li & Wanying Liu & Jingyuan Qiao & Yanhao Li & Jia Hu, 2023. "An Enhanced Semi-Flexible Transit Service with Introducing Meeting Points," Networks and Spatial Economics, Springer, vol. 23(3), pages 487-527, September.
    20. Di Huang & Weiping Tong & Lumeng Wang & Xun Yang, 2019. "An Analytical Model for the Many-to-One Demand Responsive Transit Systems," Sustainability, MDPI, vol. 12(1), pages 1-17, December.
    21. Ansari Esfeh, Mohammad & Saidi, Saeid & Wirasinghe, S.C. & Kattan, Lina, 2022. "Waiting time and headway modeling considering unreliability in transit service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 219-233.
    22. Dikas, G. & Minis, I., 2014. "Scheduled paratransit transport systems," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 18-34.
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