Abstract
Under the background of increasing car ownership and frequent traffic accidents, this paper focuses on fatigue driving, an important cause of traffic accidents, and mainly discusses the detection method of driver fatigue driving. This paper first sorts out the traditional subjective and objective detection indicators and judgment standards for fatigue driving, analyzes the advantages and disadvantages of the traditional detection methods, and lists the commonly used public data sets; At the same time, this paper further summarizes the commonly used driver facial feature recognition and extraction methods, list new fatigue driving detection methods based on machine learning and deep learning to improve the shortcomings of traditional detection and improve detection accuracy, and finally summarize and prospect the fatigue driving detection technology. The research believes that fatigue driving detection methods based on deep learning are the general trend, which can achieve high-precision, real-time and fast fatigue detection.
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