Yun Cong Lu
ABSTRACT
Abstract: Abnormal driving is a serious problem leading to a large number of serious and even fatal road accidents worldwide every year. It is difficult for the traffic police department to effectively supervise these situations through the traditional methods of patrol and monitoring, and there are great safety risks. In order to solve the above problems, this paper built an abnormal driving detection model based on Yolov5 model and face keypoints detection algorithm. The results show that the comprehensive accuracy of the model is 97.02%, and the average detection time is 16.5ms, which can meet the supervision demand of abnormal driving behavior.
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Index Terms
- Driver Abnormal Driving Detection Model based on Deep Learning
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