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.
Neural network model for truck driver fatigue accident detection
Proceedings 1995 Canadian Conference on Electrical and Computer Engineering ; 1 ; 362-365 vol.1
1995-01-01
348040 byte
Conference paper
Electronic Resource
English
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