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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

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.

Suggested Citation

  • Quadrifoglio, Luca & Li, Xiugang, 2009. "A methodology to derive the critical demand density for designing and operating feeder transit services," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 922-935, December.
  • Handle: RePEc:eee:transb:v:43:y:2009:i:10:p:922-935
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    References listed on IDEAS

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    1. Daganzo, Carlos F., 1984. "Checkpoint dial-a-ride systems," Transportation Research Part B: Methodological, Elsevier, vol. 18(4-5), pages 315-327.
    2. 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.
    3. 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.
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    6. Hall, Randolph W., 1986. "Discrete models/continuous models," Omega, Elsevier, vol. 14(3), pages 213-220.
    7. 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.
    8. 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.
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Yu, Yao & Machemehl, Randy B. & Xie, Chi, 2015. "Demand-responsive transit circulator service network design," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 76(C), pages 160-175.
    5. repec:eee:transb:v:107:y:2018:i:c:p:229-252 is not listed on IDEAS
    6. 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.
    7. repec:eee:transb:v:104:y:2017:i:c:p:36-57 is not listed on IDEAS
    8. Ellegood, William A. & Campbell, James F. & North, Jeremy, 2015. "Continuous approximation models for mixed load school bus routing," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 182-198.
    9. Stiglic, M. & Agatz, N.A.H. & Savelsbergh, M.W.P. & Gradisar, M., 2016. "Enhancing Urban Mobility: Integrating Ride-sharing and Public Transit," ERIM Report Series Research in Management ERS-2016-006-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.
    10. 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.
    11. An, Kun & Lo, Hong K., 2015. "Robust transit network design with stochastic demand considering development density," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 737-754.
    12. 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.

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