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Exploring trade-offs in frequency allocation in a transit network using bus route patterns: Methodology and application to large-scale urban systems

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  • Verbas, İ. Ömer
  • Mahmassani, Hani S.

Abstract

Transit agencies seek to allocate their limited operational budget and fleet optimally to service routes in order to maximize user benefits. The Transit Network Frequency Setting Problem formulation developed in this study effectively captures the coupling between the routes and their prevailing patterns, which may have different subsets of stops visited at different times of the day. The number of riders is elastic to the prevailing number of bus trips at a given stop, which is the combination of different pattern dispatch frequencies. As a result, the study bridges the gap between the operator’s perspective where the decision unit is the pattern schedule, and the user’s perspective, which perceives frequencies at the route level. Two main formulations are introduced. The first one maximizes the number of riders and the total waiting time savings under budget, fleet, policy headway and bus loading constraints; the second minimizes the net cost under fleet, policy headway, bus loading, minimum ridership and minimum waiting time savings constraints. In both formulations, pattern headways are the decision variables. Spatial and temporal heterogeneity of ridership elasticity with respect to headway is captured. The formulations are applied to a large-scale test network for the Chicago area. The results show that a win–win solution is possible where both ridership and waiting time savings are increased, while the net cost is decreased.

Suggested Citation

  • Verbas, İ. Ömer & Mahmassani, Hani S., 2015. "Exploring trade-offs in frequency allocation in a transit network using bus route patterns: Methodology and application to large-scale urban systems," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 577-595.
  • Handle: RePEc:eee:transb:v:81:y:2015:i:p2:p:577-595
    DOI: 10.1016/j.trb.2015.06.018
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    References listed on IDEAS

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    Cited by:

    1. S. Mahmassani, Hani & F. Hyland, Michael, 2016. "Gap-based transit assignment algorithm with vehicle capacity constraints: Simulation-based implementation and large-scale applicationAuthor-Name: Verbas, Ömer," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 1-16.
    2. Chen, Jingxu & Liu, Zhiyuan & Wang, Shuaian & Chen, Xuewu, 2018. "Continuum approximation modeling of transit network design considering local route service and short-turn strategy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 165-188.
    3. Soto, Guillermo & Larrain, Homero & Muñoz, Juan Carlos, 2017. "A new solution framework for the limited-stop bus service design problem," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 67-85.
    4. Simon Bull & Jesper Larsen & Richard M. Lusby & Natalia J. Rezanova, 2019. "Optimising the travel time of a line plan," 4OR, Springer, vol. 17(3), pages 225-259, September.
    5. Gkiotsalitis, K. & Schmidt, M.E. & van der Hurk, E., 2021. "Subline frequency setting for autonomous minibusses under demand uncertainty," ERIM Report Series Research in Management ERS-2021-008-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Weiya Chen & Xin Liu & Dingfang Chen & Xin Pan, 2019. "Setting Headways on a Bus Route under Uncertain Conditions," Sustainability, MDPI, vol. 11(10), pages 1-13, May.

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