Self-organizing traffic lights at multiple-street intersections

Authors

  • Carlos Gershenson,

    Corresponding author
    1. Departamento de Ciencias de la Computación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, México 01000, D.F., México
    • Departamento de Ciencias de la Computación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, A.P. 20-726, México 01000, D.F., México
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  • David A. Rosenblueth

    1. Departamento de Ciencias de la Computación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, México 01000, D.F., México
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Abstract

The elementary cellular automaton following rule 184 can mimic particles flowing in one direction at a constant speed. Therefore, this automaton can model highway traffic qualitatively. In a recent paper, we have incorporated intersections regulated by traffic lights to this model using exclusively elementary cellular automata. In such a paper, however, we only explored a rectangular grid. We now extend our model to more complex scenarios using an hexagonal grid. This extension shows first that our model can readily incorporate multiple-way intersections and hence simulate complex scenarios. In addition, the current extension allows us to study and evaluate the behavior of two different kinds of traffic-light controller for a grid of six-way streets allowing for either two- or three-street intersections: a traffic light that tries to adapt to the amount of traffic (which results in self-organizing traffic lights) and a system of synchronized traffic lights with coordinated rigid periods (sometimes called the “green-wave” method). We observe a tradeoff between system capacity and topological complexity. The green-wave method is unable to cope with the complexity of a higher-capacity scenario, while the self-organizing method is scalable, adapting to the complexity of a scenario and exploiting its maximum capacity. Additionally, in this article, we propose a benchmark, independent of methods and models, to measure the performance of a traffic-light controller comparing it against a theoretical optimum. © 2011 Wiley Periodicals, Inc. Complexity, 2012

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