• DocumentCode
    2111872
  • Title

    Detecting expressway traffic incident by traffic flow and robust statistics

  • Author

    Yang, Zhengling ; Song, Yanwen ; Wang, Teng ; Li, Yan

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
  • fYear
    2012
  • fDate
    21-23 April 2012
  • Firstpage
    2537
  • Lastpage
    2540
  • Abstract
    In order to detect expressway traffic incidents veritably, the probabilistic identifying results are suggested to demonstrate the traffic jam/congestion detection by traffic flow. First, the noise series in a traffic flow is decomposed by wavelet denoising and by second kind Fourier analysis denoising respectively. Second, hypothesis testing by chi-squared distribution is employed to sort out the robust variance (scale) estimators. Last, assuming that the detected flow point with possible congestion follows a normal distribution with the mean of the decomposed signal and the variance estimated from the decomposed noise series previously, the confidence levels of congestions are generated in a probabilistic form. Numerical experiments show that the probabilistic identifying results by this three steps method are reliable and reasonable.
  • Keywords
    Fourier analysis; automated highways; estimation theory; image denoising; normal distribution; object detection; road traffic; wavelet transforms; chi-squared distribution; congestion confidence levels; expressway traffic incident detection; hypothesis testing; noise series; normal distribution; probabilistic form; robust statistics; robust variance estimators; second kind Fourier analysis denoising; signal decomposition mean; traffic flow; traffic jam-congestion detection; variance estimation; wavelet denoising; Noise reduction; Probabilistic logic; Robustness; Time series analysis; Wavelet analysis; White noise; congestion; expressway traffic flow; robust statistics; time series; traffic incident detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
  • Conference_Location
    Yichang
  • Print_ISBN
    978-1-4577-1414-6
  • Type

    conf

  • DOI
    10.1109/CECNet.2012.6201448
  • Filename
    6201448