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Design and evaluation of dynamic traffic management strategies for congested conditions

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  • Abu-Lebdeh, Ghassan
  • Benekohal, Rahim F.

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  • Abu-Lebdeh, Ghassan & Benekohal, Rahim F., 2003. "Design and evaluation of dynamic traffic management strategies for congested conditions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(2), pages 109-127, February.
  • Handle: RePEc:eee:transa:v:37:y:2003:i:2:p:109-127
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    References listed on IDEAS

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    1. Denos C. Gazis, 1964. "Optimum Control of a System of Oversaturated Intersections," Operations Research, INFORMS, vol. 12(6), pages 815-831, December.
    2. Robert L. Gordon, 1969. "A Technique for Control of Traffic at Critical Intersections," Transportation Science, INFORMS, vol. 3(4), pages 279-288, November.
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    Cited by:

    1. Bingsheng Huang & Fusheng Zhang, 2022. "Analysis of Traffic Oversaturation Based on Multi-Objective Data," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    2. 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.
    3. Sun, S. & Szeto, W.Y., 2021. "Multi-class stochastic user equilibrium assignment model with ridesharing: Formulation and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 203-227.
    4. Evers, Ruth & Proost, Stef, 2015. "Optimizing intersections," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 100-119.
    5. Simone Baldi & Iakovos Michailidis & Vasiliki Ntampasi & Elias Kosmatopoulos & Ioannis Papamichail & Markos Papageorgiou, 2019. "A Simulation-Based Traffic Signal Control for Congested Urban Traffic Networks," Service Science, INFORMS, vol. 53(1), pages 6-20, February.
    6. Ennio Cascetta & Mariano Gallo & Bruno Montella, 2006. "Models and algorithms for the optimization of signal settings on urban networks with stochastic assignment models," Annals of Operations Research, Springer, vol. 144(1), pages 301-328, April.

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