Abstract
This paper studies the correlation between driver fatigue state detection and dangerous driving behavior. The fatigue measurement method adopts the gold standard of the industry, namely EEG fatigue detection method. The driver's original EEG signal was preprocessed, the EEG signal artifacts were removed, four typical EEG rhythm waves were constructed by wavelet packet decomposition and reconstruction algorithm, and the frequency band energy ratio was calculated to judge the fatigue degree. Aiming at the dangerous driving behavior induced by fatigue, the data of steering wheel Angle, vehicle acceleration and speed collected synchronously were processed and analyzed by sample entropy algorithm. Based on Pearson correlation coefficient, the co3rrelation between EEG frequency band energy ratio and dangerous driving behavior index was analyzed. It is found that the steering wheel Angle control is most susceptible to the influence of fatigue and fluctuates dangerous driving behavior, and the correlation between the sample entropy of steering wheel Angle of dangerous driving behavior and driver fatigue state is the strongest.
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