Detection of Emergency Braking Intention From Soft Braking and Normal Driving Intentions Using EMG Signals

Emergency braking intention detection has a vital practical value for improving driving safety. This paper proposed an electromyography (EMG)-based method to detect emergency braking intention from soft braking and normal driving intentions. Temporal and spectral signatures of EMG signals of emergency braking, soft braking, and normal driving intentions were investigated. Common spatial pattern (CSP) was used to generate virtual channels. The power spectrum density and linear envelope amplitude of EMG signals were used as features, respectively. Chi-square test (Chi) was used to select features. Regularized linear discrimination analysis was developed to detect emergency braking intention from the other two driving intentions. Experiment results showed significant differences in temporal and spectral domains between three kinds of driving. Furthermore, on average, the proposed method based on spectral features can detect emergency braking intention 155.70 ms before behavior under emergency situations with a system accuracy of 95.72%. The proposed method based on EMG signals for predicting emergency braking intention can be applied to develop active driving assistance systems and improve driving safety.