Traffic assignment and signal control in saturated road networks

https://doi.org/10.1016/0965-8564(94)E0007-VGet rights and content

Abstract

This article presents a model and a procedure for determining traffic assignment and optimizing signal timings in saturated road networks. Both queuing and congestion are explicitly taken into account in predicting equilibrium flows and setting signal split parameters for a fixed pattern of origin-to-destination trip demand. The model is formulated as a bilevel programming problem. The lower-level problem represents a network equilibrium model involving queuing explicitly on saturated links, which predicts how drivers will react to any given signal control pattern. The upper-level problem is to determine signal splits to optimize a system objective function, taking account of drivers' route choice behavior in response to signal split changes. Sensitivity analysis is implemented for the queuing network equilibrium problem to obtain the derivatives of equilibrium link flows and equilibrium queuing delays with respect to signal splits. The derivative information is then used to develop a gradient descent algorithm to solve the proposed bilevel traffic signal control problem. A numerical example is included to demonstrate the potential application of the assignment model and signal optimization procedure.

References (28)

  • V.F. Hurdle

    Signalized intersection delay model — a primer for the uninitiated

    Transpn. Res. Rec.

    (1985)
  • H. Inouye

    Equilibrium traffic assignment on a network with congested flows

    Infrastructure Planning Rev.

    (1986)
  • H. Inouye

    Traffic equilibrium in congested networks and their numerical solution

  • P. Marcott

    Network optimization with continuous control parameters

    Transpn. Sci.

    (1983)
  • Cited by (274)

    • Backpressure or no backpressure? Two simple examples

      2024, Transportation Research Part C: Emerging Technologies
    • The capacity constraint physarum solver

      2022, Journal of Computational Science
    View all citing articles on Scopus
    View full text