Truck accidents account for a disproportionately high number of deaths and personal injuries on the highway network. Driver fatigue is perceived to be a major cause of these accidents. However, the presence of fatigue as documented in truck accident police reports does not support the commonly held perception that it is a problem. Either fatigue is not as much of a problem as perceived, or more likely, police accident reports significantly underestimate the involvement of driver fatigue in truck accidents. A neural network (NN) model provides a comprehensive method for identifying presence of fatigue in truck accidents from supplementary information in police report. A NN model is proposed to classify truck accident into fatigue and nonfatigue related. The model was able to learn the required function efficiently and a very high performance was observed.


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    Titel :

    Neural network model for truck driver fatigue accident detection


    Beteiligte:
    Hamouda, G. (Autor:in) / Saccomanno, F.F. (Autor:in)


    Erscheinungsdatum :

    01.01.1995


    Format / Umfang :

    348040 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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