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Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata

Author

Listed:
  • Jorge L. Zapotecatl
  • David A. Rosenblueth
  • Carlos Gershenson

Abstract

Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.

Suggested Citation

  • Jorge L. Zapotecatl & David A. Rosenblueth & Carlos Gershenson, 2017. "Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata," Complexity, Hindawi, vol. 2017, pages 1-15, May.
  • Handle: RePEc:hin:complx:7691370
    DOI: 10.1155/2017/7691370
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    References listed on IDEAS

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    1. Richard Steinberg & Willard I. Zangwill, 1983. "The Prevalence of Braess' Paradox," Transportation Science, INFORMS, vol. 17(3), pages 301-318, August.
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    Cited by:

    1. Mauricio Verardo & Pedro P. B. de Oliveira, 2019. "A Fully Operational Framework for Handling Cellular Automata Templates," Complexity, Hindawi, vol. 2019, pages 1-11, April.

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