• DocumentCode
    2913740
  • Title

    Enhancing the urban road traffic with Swarm Intelligence: A case study of Córdoba city downtown

  • Author

    García-Nieto, José ; Alba, Enrique ; Olivera, Ana Carolina

  • Author_Institution
    Dept. Lenguajes y Cienc. de la Comput., Univ. of Malaga, Malaga, Spain
  • fYear
    2011
  • fDate
    22-24 Nov. 2011
  • Firstpage
    368
  • Lastpage
    373
  • Abstract
    In current modern cities, the increasing number of traffic lights that control the vehicular traffic flow requires a highly complex scheduling. Thousands of red lights, that have to be optimally programmed, are nowadays operating in congested urban areas. Therefore, automatic intelligent systems are indispensable tools for optimally tackling this task. In this work, we propose a Swarm Intelligence approach that, coupled with the SUMO traffic simulator, is able to find successful cycle programs of traffic lights for large urban areas. In concrete, we have focused on a metropolitan area of the city downtown of Córdoba (in Spain). The experiments and comparisons with other techniques reveal that our proposed approach obtains significant profits in terms of traffic flow and global trip time.
  • Keywords
    automated highways; particle swarm optimisation; road traffic control; scheduling; traffic engineering computing; Cordoba city downtown; SUMO traffic simulator; automatic intelligent systems; complex scheduling; congested urban areas; metropolitan area; swarm intelligence approach; traffic lights; urban road traffic; vehicular traffic flow control; Algorithm design and analysis; Cities and towns; Color; Mathematical model; Optimization; Urban areas; Vehicles; Differential Evolution; Particle Swarm Optimization; SUMO Microscopic Simulator; Traffic Light Scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on
  • Conference_Location
    Cordoba
  • ISSN
    2164-7143
  • Print_ISBN
    978-1-4577-1676-8
  • Type

    conf

  • DOI
    10.1109/ISDA.2011.6121683
  • Filename
    6121683