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Properties of a traffic control policy which ensure the existence of a traffic equilibrium consistent with the policy

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  • Smith, M. J.

Abstract

The paper considers the traffic assignment problem when there are junctions controlled by traffic signals, and the traffic capacity of each junction is limited. We give certain properties of a control policy. If a particular policy possesses these properties then (under natural conditions) any feasible assignment problem has a solution consistent with that policy. In the mathematical model, traffic flows at one junction do not affect costs at others; this is the most important restriction on the work presented here.

Suggested Citation

  • Smith, M. J., 1981. "Properties of a traffic control policy which ensure the existence of a traffic equilibrium consistent with the policy," Transportation Research Part B: Methodological, Elsevier, vol. 15(6), pages 453-462, December.
  • Handle: RePEc:eee:transb:v:15:y:1981:i:6:p:453-462
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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. Yu, Hao & Ma, Rui & Zhang, H. Michael, 2018. "Optimal traffic signal control under dynamic user equilibrium and link constraints in a general network," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 302-325.
    3. Watling, David, 1996. "Asymmetric problems and stochastic process models of traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 30(5), pages 339-357, October.
    4. Lee, Seunghyeon & Wong, S.C. & Varaiya, Pravin, 2017. "Group-based hierarchical adaptive traffic-signal control part I: Formulation," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 1-18.
    5. Meneguzzer, Claudio, 1995. "An equilibrium route choice model with explicit treatment of the effect of intersections," Transportation Research Part B: Methodological, Elsevier, vol. 29(5), pages 329-356, October.
    6. Claudio Meneguzzer, 1998. "Stochastic user equilibrium assignment with traffic-responsive signal control," ERSA conference papers ersa98p337, European Regional Science Association.
    7. David Levinson & Ajay Kumar, 1994. "Integrating Feedback into the Transportation Planning Mode," Working Papers 199404, University of Minnesota: Nexus Research Group.
    8. Ferrari, Paolo, 1997. "Capacity constraints in urban transport networks," Transportation Research Part B: Methodological, Elsevier, vol. 31(4), pages 291-301, August.
    9. Evers, Ruth & Proost, Stef, 2015. "Optimizing intersections," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 100-119.
    10. Guo, Jianhua & Kong, Ye & Li, Zongzhi & Huang, Wei & Cao, Jinde & Wei, Yun, 2019. "A model and genetic algorithm for area-wide intersection signal optimization under user equilibrium traffic," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 92-104.
    11. 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.
    12. L. Montero & J. Barceló, 1996. "A simplicial decomposition algorithm for solving the variational inequality formulation of the general traffic assignment problem for large scale networks," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 4(2), pages 225-256, December.
    13. Lee, Seunghyeon & Wong, S.C., 2017. "Group-based approach to predictive delay model based on incremental queue accumulations for adaptive traffic control systems," Transportation Research Part B: Methodological, Elsevier, vol. 98(C), pages 1-20.

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