A system for automated traffic accident detection in intersections was designed. The input to the system is a 3-s segment of audio signal. The system can be operated in two modes: the two-class and multiclass modes. The output of the two-class mode is a label of “crash” or “noncrash.” In the multiclass mode of operation, the system identifies crashes as well as several types of noncrash incidents, including normal traffic and construction sounds. The system is composed of three main signal processing stages: feature extraction, feature reduction, and classification. Five methods of feature extraction were investigated and compared; these are based on the discrete wavelet transform, fast Fourier transform, discrete cosine transform, real cepstral transform, and mel frequency cepstral transform. Statistical methods are used for feature optimization and classification. Three types of classifiers are investigated and compared; these are the nearest-mean, maximum-likelihood, and nearest-neighbor methods. The results of the study show that the optimum design uses wavelet-based features in combination with the maximum-likelihood classifier. The system is computationally inexpensive relative to the other methods investigated, and the system consistently results in accident detection accuracies of 95% to 100% when the audio signal has a signal-to-noise-ratio of at least 0 decibels.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Automated Accident Detection in Intersections via Digital Audio Signal Processing


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2003-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Development of an Automated Accident Detection System at Intersections

    Zhang, Y. / Hu, R. Q. / ASCE | British Library Conference Proceedings | 2004


    Development of an automated accident detection system at intersections

    Zhang, Yunlong / Hu, Rose Q. | Tema Archive | 2004


    Accident Detection at Intersections for ITS

    Stephanedes, Y. J. / Vasilakis, G. / American Society of Civil Engineers et al. | British Library Conference Proceedings | 1995


    Traffic monitoring and accident detection at intersections

    Kamijo, S. / Matsushita, Y. / Ikeuchi, K. et al. | Tema Archive | 2000