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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Neural network model for truck driver fatigue accident detection


    Contributors:


    Publication date :

    1995-01-01


    Size :

    348040 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Effect of driver fatigue on truck accident rates

    Saccomanno, F. F. / Yu, M. / Shortreed, J. H. | British Library Conference Proceedings | 1995



    Fatigue, Truck Driving and Accident Risk

    Smiley, A. | British Library Conference Proceedings | 1996


    Heavy Truck Accident Risk and the Role of Driver Fatigue - A Trucking Company Viewpoint

    Dolyniuk, R. | British Library Conference Proceedings | 1996


    Fatigue, safety and the truck driver

    McDonald, Nicholas | TIBKAT | 1984