• DocumentCode
    2944297
  • Title

    Research on Traffic Flow Base on Neural Network

  • Author

    Li, Xiaoying ; Li, Yongzhi ; Liu, JianXin

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
  • Volume
    3
  • fYear
    2009
  • fDate
    11-12 April 2009
  • Firstpage
    302
  • Lastpage
    304
  • Abstract
    The traffic flow according to toll vehicle type classification spends greatly and the data is inaccurate. But the traffic flow according to traffic investigation classification may obtain easily from intelligent toll station. Using neural networks ways transform charge flow into traffic investigation flow, building-up transformation model, programming in MATLAB, Obtaining error ratio of each kind of vehicle type and total error ratio. It can utilize fully the advantage of the toll-gate. Every toll-gate has the charge record to all kinds of vehicles type in the process charging. The research can cut down the cost of the traffic survey,and make full use of the traffic survey data.
  • Keywords
    automated highways; mathematics computing; neural nets; pattern classification; road traffic; road vehicles; traffic engineering computing; MATLAB; intelligent toll station; neural network; toll vehicle type classification; toll-gate; traffic flow; traffic investigation classification; transformation model; Communications technology; Costs; Fluid flow measurement; Intelligent systems; MATLAB; Neural networks; Radial basis function networks; Telecommunication traffic; Traffic control; Vehicles; MATLAB; error ratio; radial basis function; traffic flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
  • Conference_Location
    Zhangjiajie, Hunan
  • Print_ISBN
    978-0-7695-3583-8
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2009.296
  • Filename
    5203206