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Mobility service design via joint optimization of transit networks and demand-responsive services

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  • Liu, Yining
  • Ouyang, Yanfeng

Abstract

This paper proposes a modeling framework to design an integrated mobility service system that is composed of a local demand-responsive transportation (DRT) component and a fixed-route transit network component. The region is partitioned into disjoint local zones, and a trip is characterized into an intra- or inter-zonal one based on whether its origin and destination belong to the same zone. The transit network provides backbone line-haul service to inter-zonal trips, while the DRT system targets intra-zonal trips as well as the first-mile and last-mile legs of inter-zonal trips. The system components can be broadly defined, and this paper considers, as examples, conventional non-shared taxi or ride-sharing for the DRT service, and regular bus, bus rapid transit (BRT), or metro for the backbone network. For quantitative analysis of the DRT services, new aspatial queuing network models are developed to capture various DRT operations for serving trips with randomly distributed origins and destinations (i.e., intra-zonal trips) and those with origins or destinations concentrated at a set of fixed transit stations (i.e., first- or last-mile trip legs) at the same time. Each queuing model is integrated with the transit network design model, through proper service region partition, to derive closed-form formulas for the agency and passenger costs. Then, we formulate constrained non-linear programs that simultaneously optimize the zone partition, the fleet size and repositioning operation for the local DRT service, as well as the spacing and headway of a grid transit network. We apply the proposed models to a variety of transit technologies and application scenarios, so as to demonstrate applicability of the models, and to show promising performance of the proposed systems.

Suggested Citation

  • Liu, Yining & Ouyang, Yanfeng, 2021. "Mobility service design via joint optimization of transit networks and demand-responsive services," Transportation Research Part B: Methodological, Elsevier, vol. 151(C), pages 22-41.
  • Handle: RePEc:eee:transb:v:151:y:2021:i:c:p:22-41
    DOI: 10.1016/j.trb.2021.06.005
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    Cited by:

    1. Yining Liu & Yanfeng Ouyang, 2022. "Planning ride-pooling services with detour restrictions for spatially heterogeneous demand: A multi-zone queuing network approach," Papers 2208.02219, arXiv.org, revised Jun 2023.
    2. Liu, Yining & Ouyang, Yanfeng, 2023. "Planning ride-pooling services with detour restrictions for spatially heterogeneous demand: A multi-zone queuing network approach," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    3. Hao, Wu & Martin, Layla, 2022. "Prohibiting cherry-picking: Regulating vehicle sharing services who determine fleet and service structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    4. Mohamed Amjath & Laoucine Kerbache & James MacGregor Smith, 2024. "A Closed Queueing Networks Approach for an Optimal Heterogeneous Fleet Size of an Inter-Facility Bulk Material Transfer System," Logistics, MDPI, vol. 8(1), pages 1-38, March.
    5. Cortina, Mélanie & Chiabaut, Nicolas & Leclercq, Ludovic, 2023. "Fostering synergy between transit and Autonomous Mobility-on-Demand systems: A dynamic modeling approach for the morning commute problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).

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