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A stochastic transit assignment model using a dynamic schedule-based network

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  • Tong, C.O.
  • Wong, S.C.

Abstract

Using the schedule-based approach, in which scheduled time-tables are used to describe the movement of vehicles, a dynamic transit assignment model is formulated. Passengers are assumed to travel on a path with minimum generalized cost which consists of four components: in-vehicle time; waiting time; walking time; and a time penalty for each line change. With the exception of in-vehicle time, each of the other cost components is weighted by a sensitivity coefficient which varies among travelers and is defined by a density function. This time-dependent and stochastic minimum path is generated by a specially developed branch and bound algorithm. The assignment procedure is conducted over a period in which both passenger demand and train headways are varying. Due to the stochastic nature of the assignment problem, a Monte Carlo approach is employed to solve the problem. A case study using the Mass Transit Railway System in Hong Kong is given to demonstrate the model and its potential applications.

Suggested Citation

  • Tong, C.O. & Wong, S.C., 1998. "A stochastic transit assignment model using a dynamic schedule-based network," Transportation Research Part B: Methodological, Elsevier, vol. 33(2), pages 107-121, April.
    • Handle: RePEc:eee:transb:v:33:y:1998:i:2:p:107-121
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    References listed on IDEAS

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    1. Spiess, Heinz & Florian, Michael, 1989. "Optimal strategies: A new assignment model for transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 23(2), pages 83-102, April.
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    3. Carraresi, Paolo & Malucelli, Federico & Pallottino, Stefano, 1996. "Regional mass transit assignment with resource constraints," Transportation Research Part B: Methodological, Elsevier, vol. 30(2), pages 81-98, April.
    4. Wong, S. C. & Tong, C. O., 1998. "Estimation of time-dependent origin-destination matrices for transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 32(1), pages 35-48, January.
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    Cited by:

    1. Xiao Fu & William Lam, 2014. "A network equilibrium approach for modelling activity-travel pattern scheduling problems in multi-modal transit networks with uncertainty," Transportation, Springer, vol. 41(1), pages 37-55, January.
    2. Sumalee, Agachai & Tan, Zhijia & Lam, William H.K., 2009. "Dynamic stochastic transit assignment with explicit seat allocation model," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 895-912, September.
    3. Hamdouch, Younes & Ho, H.W. & Sumalee, Agachai & Wang, Guodong, 2011. "Schedule-based transit assignment model with vehicle capacity and seat availability," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1805-1830.
    4. Ahmad Tavassoli & Mahmoud Mesbah & Mark Hickman, 2020. "Calibrating a transit assignment model using smart card data in a large-scale multi-modal transit network," Transportation, Springer, vol. 47(5), pages 2133-2156, October.
    5. Kang, Jee Eun & Chow, Joseph Y.J. & Recker, Will W., 2013. "On activity-based network design problems," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 398-418.
    6. Ahmad Tavassoli & Mahmoud Mesbah & Mark Hickman, 2018. "Application of smart card data in validating a large-scale multi-modal transit assignment model," Public Transport, Springer, vol. 10(1), pages 1-21, May.
    7. Guangming Xu & Shuo Zhao & Feng Shi & Feilian Zhang, 2017. "Cell transmission model of dynamic assignment for urban rail transit networks," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-31, November.
    8. Wen Hua & Ghim Ping Ong, 2018. "Effect of information contagion during train service disruption for an integrated rail-bus transit system," Public Transport, Springer, vol. 10(3), pages 571-594, December.
    9. Hamdouch, Younes & Szeto, W.Y. & Jiang, Y., 2014. "A new schedule-based transit assignment model with travel strategies and supply uncertainties," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 35-67.
    10. Li, Qianfei & (Will) Chen, Peng & (Marco) Nie, Yu, 2015. "Finding optimal hyperpaths in large transit networks with realistic headway distributions," European Journal of Operational Research, Elsevier, vol. 240(1), pages 98-108.

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