A hybrid Bayesian Network approach to detect driver cognitive distraction
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چکیده
Article history: Received 22 May 2013 Received in revised form 23 October 2013 Accepted 23 October 2013
منابع مشابه
PROCEEDINGS of the Seventh International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design USING A LAYERED ALGORITHM TO DETECT DRIVER COGNITIVE DISTRACTION
Detection of cognitive distraction presents an indispensable function for driver distraction mitigation systems. In this study, we developed a layered algorithm that integrated two data mining methods—Dynamic Bayesian Network (DBN) and supervised clustering method—to identify cognitive distraction from drivers’ eye movements and driving performance measures. We used the data collected in a simu...
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Driver cognitive distraction is a hazard state, which can easily lead to traffic accidents. This study focuses on detecting the driver cognitive distraction state based on driving performance measures. Characteristic parameters could be directly extracted from Controller Area NetworkCANBus data, without depending on other sensors, which improves real-time and robustness performance. Three cogni...
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تاریخ انتشار 2013