• DocumentCode
    131659
  • Title

    Research on Traffic Flow Algorithm

  • Author

    Xiaoying Li

  • Author_Institution
    Col. of Electr. & Informational Eng, Changsha Univ. of Sci. & Technol., Changsha, China
  • fYear
    2014
  • fDate
    10-11 Jan. 2014
  • Firstpage
    556
  • Lastpage
    560
  • Abstract
    With the development of highway toll system is more and more perfect, the intelligent toll system attracts more and more attentions and gets very wide application. With the development of computer, communication and network technology communication technology, the toll system also has intelligent and network management. Tool system collects unremittingly a lot of toll flow date and other traffic information. We can predict traffic flow using the date of toll system base on neural network. At the paper, using the BP network and RBF network algorithm respectively, obtaining error ratio of each kind of vehicle type and total error ratio. Comparing result show which algorithm has low error rate.
  • Keywords
    backpropagation; intelligent transportation systems; radial basis function networks; road pricing (tolls); road traffic; BP network; RBF network algorithm; intelligent toll system; neural network; traffic flow algorithm; traffic flow prediction; Error analysis; MATLAB; Mathematical model; Radial basis function networks; Training; Vehicles; BP Network; Error Ratio; RBF Network; Toll System; Traffic Flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation (ICMTMA), 2014 Sixth International Conference on
  • Conference_Location
    Zhangjiajie
  • Print_ISBN
    978-1-4799-3434-8
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2014.135
  • Filename
    6802753