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A methodology to derive the critical demand density for designing and operating feeder transit services

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  • Quadrifoglio, Luca
  • Li, Xiugang
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    Abstract

    Feeder lines are one of the most often used types of flexible transit services connecting a service area to a major transit network through a transfer point. They often switch operations between a demand responsive and a fixed-route policy. In designing and running such systems, the identification of the condition justifying the operating switch is often hard to properly evaluate. In this paper, we propose an analytical model and solution of the problem to assist decision makers and operators in their choice. By employing continuous approximations, we derive handy but powerful closed-form expressions to estimate the critical demand densities, representing the switching point between the competing operating policies. Based on the results of one-vehicle and two-vehicle operations for various scenarios, in comparison to values generated from simulation, we verify the validity of our analytical modeling approach.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 43 (2009)
    Issue (Month): 10 (December)
    Pages: 922-935

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    Handle: RePEc:eee:transb:v:43:y:2009:i:10:p:922-935

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    Keywords: Feeder transit Flexible transit Demand responsive Continuous approximation Critical demand;

    References

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    1. Quadrifoglio, Luca & Dessouky, Maged M. & Ordóñez, Fernando, 2008. "A simulation study of demand responsive transit system design," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 718-737, May.
    2. Quadrifoglio, Luca & Dessouky, Maged M. & Ordonez, Fernando, 2008. "Mobility allowance shuttle transit (MAST) services: MIP formulation and strengthening with logic constraints," European Journal of Operational Research, Elsevier, vol. 185(2), pages 481-494, March.
    3. Hall, Randolph W., 1986. "Discrete models/continuous models," Omega, Elsevier, vol. 14(3), pages 213-220.
    4. Aldaihani, Majid M. & Quadrifoglio, Luca & Dessouky, Maged M. & Hall, Randolph, 2004. "Network design for a grid hybrid transit service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(7), pages 511-530, August.
    5. Wardman, Mark, 2004. "Public transport values of time," Transport Policy, Elsevier, vol. 11(4), pages 363-377, October.
    6. Daganzo, Carlos F., 1984. "Checkpoint dial-a-ride systems," Transportation Research Part B: Methodological, Elsevier, vol. 18(4-5), pages 315-327.
    7. Langevin, André & Mbaraga, Pontien & Campbell, James F., 1996. "Continuous approximation models in freight distribution: An overview," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 163-188, June.
    8. Cayford, Randall & Yim, Y. B. Youngbin, 2004. "Personalized Demand-Responsive Transit Service," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt29j111ts, Institute of Transportation Studies, UC Berkeley.
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    Cited by:
    1. 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.
    2. Curtin, Kevin M. & Biba, Steve, 2011. "The Transit Route Arc-Node Service Maximization problem," European Journal of Operational Research, Elsevier, vol. 208(1), pages 46-56, January.
    3. Campbell, James F., 2013. "A continuous approximation model for time definite many-to-many transportation," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 100-112.
    4. 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.

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