• DocumentCode
    2785341
  • Title

    Road traffic congestion detection through cooperative Vehicle-to-Vehicle communications

  • Author

    Bauza, Ramon ; Gozalvez, Javier ; Sanchez-Soriano, Joaquin

  • Author_Institution
    Ubiquitous Wireless Commun. Res. Lab., Univ. Miguel Hernandez of Elche, Elche, Spain
  • fYear
    2010
  • fDate
    10-14 Oct. 2010
  • Firstpage
    606
  • Lastpage
    612
  • Abstract
    Cooperative vehicular systems are being developed to improve traffic safety and management. Reducing road traffic congestion can be achieved through effective management strategies. In this sense, mechanisms for its rapid and accurate detection that allow evaluating the road network performance are crucial. Current Intelligent Transportation Systems (ITS) require the deployment of infrastructure sensors to monitor traffic conditions. Their installation is often expensive and their capability to provide accurate traffic information is limited. In this context, this paper proposes CoTEC (COperative Traffic congestion detECtion), a novel cooperative technique based on Vehicle-to-Vehicle (V2V) communications and fuzzy logic to detect road traffic congestion without the need to deploy infrastructure sensors. The proposed technique is also capable to accurately detect the traffic congestion intensity and length.
  • Keywords
    cooperative communication; road safety; road traffic; CoTEC; cooperative vehicle-to-vehicle communication; coperative traffic congestion detection; fuzzy logic; intelligent transportation system; road network performance; road traffic congestion detection; traffic information; traffic safety; Estimation; Frequency estimation; Fuzzy sets; Monitoring; Protocols; Roads; Vehicles; cooperative vehicular communications; traffic congestion detection; vehicle-to-vehicle (V2V) communications;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Local Computer Networks (LCN), 2010 IEEE 35th Conference on
  • Conference_Location
    Denver, CO
  • ISSN
    0742-1303
  • Print_ISBN
    978-1-4244-8387-7
  • Type

    conf

  • DOI
    10.1109/LCN.2010.5735780
  • Filename
    5735780