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摘要
Mental fatigue affects driver's alertness and safe driving ability, which is easy to cause traffic safety problems. This paper intends to provide theoretical and experimental basis for building a driving fatigue detection system based on EEG recognition combining vehicle handling characteristics. Firstly, a driving simulation experiment was designed to collect the EEG signal and steering wheel handling data of the subject;then, aiming at the three-classification problem of fatigue degree, the features of EEG signal were extracted with wavelet packet transform and common spatial pattern methods. Moreover, the vehicle handling characteristics were used to estimate the degree of driving fatigue, and determine the criterion for EEG signal classification;Finally, support vector machine (SVM) was employed to discriminate the EEG signal and realize the qualitative analysis of the mental fatigue of drivers. The classification accuracy of up to 94.259% is achieved.
