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A comparison of stochastic and deterministic traffic assignment over congested networks

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  • Sheffi, Yosef
  • Powell, Warren

Abstract

The similarity between link flows obtained from deterministic and stochastic equilibrium traffic assignment models is investigated at different levels of congestion. A probit-based stochastic assignment is used (over a congested network) where the conditions for equilibrium are those given by Daganzo and Sheffi (1977). Stochastic equilibrium flows are generated using an iterative procedure with predetermined step sizes, and the resulting assignment is validated on the basis of the equilibrium criteria. The procedure is intended to assist in the choice of the most appropriate assignment algorithm for a given level of congestion.

Suggested Citation

  • Sheffi, Yosef & Powell, Warren, 1981. "A comparison of stochastic and deterministic traffic assignment over congested networks," Transportation Research Part B: Methodological, Elsevier, vol. 15(1), pages 53-64, February.
    • Handle: RePEc:eee:transb:v:15:y:1981:i:1:p:53-64
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    Cited by:

    1. D’Acierno, Luca & Gallo, Mariano & Montella, Bruno, 2012. "An Ant Colony Optimisation algorithm for solving the asymmetric traffic assignment problem," European Journal of Operational Research, Elsevier, vol. 217(2), pages 459-469.
    2. Antonio Comi & Antonio Polimeni, 2022. "Estimating Path Choice Models through Floating Car Data," Forecasting, MDPI, vol. 4(2), pages 1-13, June.
    3. Damberg, Olof & Lundgren, Jan T. & Patriksson, Michael, 1996. "An algorithm for the stochastic user equilibrium problem," Transportation Research Part B: Methodological, Elsevier, vol. 30(2), pages 115-131, April.
    4. Jiayang Li & Zhaoran Wang & Yu Marco Nie, 2023. "Wardrop Equilibrium Can Be Boundedly Rational: A New Behavioral Theory of Route Choice," Papers 2304.02500, arXiv.org, revised Feb 2024.
    5. Chen, Anthony & Pravinvongvuth, Surachet & Xu, Xiangdong & Ryu, Seungkyu & Chootinan, Piya, 2012. "Examining the scaling effect and overlapping problem in logit-based stochastic user equilibrium models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1343-1358.
    6. Nielsen, Otto Anker, 2000. "A stochastic transit assignment model considering differences in passengers utility functions," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 377-402, June.
    7. Alireza Ermagun & David M Levinson, 2019. "Development and application of the network weight matrix to predict traffic flow for congested and uncongested conditions," Environment and Planning B, , vol. 46(9), pages 1684-1705, November.
    8. François Gilbert & Patrice Marcotte & Gilles Savard, 2015. "A Numerical Study of the Logit Network Pricing Problem," Transportation Science, INFORMS, vol. 49(3), pages 706-719, August.
    9. Du, Muqing & Tan, Heqing & Chen, Anthony, 2021. "A faster path-based algorithm with Barzilai-Borwein step size for solving stochastic traffic equilibrium models," European Journal of Operational Research, Elsevier, vol. 290(3), pages 982-999.
    10. Connors, Richard D. & Sumalee, Agachai & Watling, David P., 2007. "Sensitivity analysis of the variable demand probit stochastic user equilibrium with multiple user-classes," Transportation Research Part B: Methodological, Elsevier, vol. 41(6), pages 593-615, July.
    11. Shahriar Afandizadeh & Arash Jahangiri & Navid Kalantari, 2013. "Identifying the optimal configuration of one-way and two-way streets for contraflow operation during an emergency evacuation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(3), pages 1315-1334, December.

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