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A Study for Self-adapting Urban Traffic Control

Part of the Lecture Notes in Computer Science book series (LNAI,volume 10022)

Abstract

Nowadays, managing traffic in cities is a complex problem involving considerable physical and economical resources. However, traffic can be simulated by multi-agent systems (MAS), since cars and traffic lights can be modeled as agents that interact to obtain an overall goal: to reduce the average waiting times for the traffic users. In this paper, we present a self-organizing solution to efficiently manage urban traffic. We compare our proposal with other classical and alternative self-organizing approaches, observing that ours provides better results. Then, we present the main contributions of the paper that analyze the effects of different traffic conditions over our cheap and easy-to-implement method for self-organizing urban traffic management. We consider several scenarios where we explore the effects of dynamic traffic density, a reduction in the percentage of sensors needed to support the traffic management system, and the possibility of using communication among cross-points.

Keywords

  • Urban traffic control
  • Multi-agent system
  • Self-organization

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Notes

  1. 1.

    The source code is available at URLs: http://hb-sotl.sourceforge.net and http://ccl.northwestern.edu/netlogo/models/community/HB-SOTL_8_10.

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Acknowledgment

The authors are supported by the Galician Regional Government under project CN 2012/260 (Consolidation of Research Units: AtlantTIC).

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Correspondence to J. C. Burguillo .

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Rodríguez-Hernández, P.S., Burguillo, J.C., Costa-Montenegro, E., Peleteiro, A. (2016). A Study for Self-adapting Urban Traffic Control. In: Montes y Gómez, M., Escalante, H., Segura, A., Murillo, J. (eds) Advances in Artificial Intelligence - IBERAMIA 2016. IBERAMIA 2016. Lecture Notes in Computer Science(), vol 10022. Springer, Cham. https://doi.org/10.1007/978-3-319-47955-2_6

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  • DOI: https://doi.org/10.1007/978-3-319-47955-2_6

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