Abstract
Vehicle safety evaluation is a systematic and comprehensive process involving vehicles, road environments, and driver behaviours. In real road conditions, due to great uncertainty, evaluation based on singular information source lacks in sufficient accuracy and stability. In this paper, the authors proposed a vision-based real-time vehicle safety evaluation system using lane and driver's eye information, which were modelled in the framework of evidence theory. Vehicle safety was assessed via hierarchical fusion of driver drowsiness detection and distracted and impaired driving performance. The system was validated in real world scenarios. Experimental results demonstrate that it is promising to improve the robustness and temporal response of vigilance of vehicle safety.
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