• DocumentCode
    616578
  • Title

    Road traffic density estimation in vehicular networks

  • Author

    Ruixue Mao ; Guoqiang Mao

  • Author_Institution
    Sch. of Electr. & Inf. Eng., Univ. of Sydney, Sydney, NSW, Australia
  • fYear
    2013
  • fDate
    7-10 April 2013
  • Firstpage
    4653
  • Lastpage
    4658
  • Abstract
    Road traffic density estimation provides important information for road planning, intelligent road routing, road traffic control, vehicular network traffic scheduling, routing and dissemination. The ever increasing number of vehicles equipped with wireless communication capabilities provide new means to estimate the road traffic density more accurately and in real time than traditionally used techniques. In this paper, we consider the problem of road traffic density estimation where each vehicle estimates its local road traffic density using some simple measurements only, i.e. the number of neighboring vehicles. A maximum likelihood estimator of the traffic density is obtained based on a rigorous analysis of the joint distribution of the number of vehicles in each hop. Analysis is also performed on the accuracy of the estimation and the amount of neighborhood information required for an accurate road traffic density estimation. Simulations are performed which validate the accuracy and the robustness of the proposed density estimation algorithm.
  • Keywords
    planning; radio networks; road traffic control; scheduling; vehicle routing; vehicular ad hoc networks; intelligent road routing; road planning; road traffic control; road traffic density estimation; traffic dissemination; traffic routing; vehicular network traffic scheduling; vehicular networks; wireless communication; Accuracy; Algorithm design and analysis; Equations; Estimation; Manganese; Roads; Vehicles; Intelligent transportation systems; vehicle density estimation; vehicle-to-vehicle communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications and Networking Conference (WCNC), 2013 IEEE
  • Conference_Location
    Shanghai
  • ISSN
    1525-3511
  • Print_ISBN
    978-1-4673-5938-2
  • Electronic_ISBN
    1525-3511
  • Type

    conf

  • DOI
    10.1109/WCNC.2013.6555328
  • Filename
    6555328