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Dynamic programming—neural network real-time traffic adaptive signal control algorithm

Author

Listed:
  • Dušan Teodorović
  • Vijay Varadarajan
  • Jovan Popović
  • Mohan Chinnaswamy
  • Sharath Ramaraj

Abstract

In this paper, an “intelligent” isolated intersection control system was developed. The developed “intelligent” system makes “real time” decisions as to whether to extend (and how much) current green time. The model developed is based on the combination of the dynamic programming and neural networks. Many tests show that the outcome (the extension of the green time) of the proposed neural network is nearly equal to the best solution. Practically negligible CPU times were achieved, and were thus absolutely acceptable for the “real time” application of the developed algorithm. Copyright Springer Science + Business Media, Inc. 2006

Suggested Citation

  • Dušan Teodorović & Vijay Varadarajan & Jovan Popović & Mohan Chinnaswamy & Sharath Ramaraj, 2006. "Dynamic programming—neural network real-time traffic adaptive signal control algorithm," Annals of Operations Research, Springer, vol. 143(1), pages 123-131, March.
    • Handle: RePEc:spr:annopr:v:143:y:2006:i:1:p:123-131:10.1007/s10479-006-7376-z
    DOI: 10.1007/s10479-006-7376-z
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    Cited by:

    1. Manuel Castejón-Limas & Joaquín Ordieres-Meré & Ana González-Marcos & Víctor González-Castro, 2011. "Effort estimates through project complexity," Annals of Operations Research, Springer, vol. 186(1), pages 395-406, June.

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