Early Prediction of the Driver's Low Arousal State Using the Biological Information before and while Driving

Abstract

Many studies about estimating drivers' state while driving have been done so far. Now, people pay attention to not only estimation, but prediction of the drivers' state while driving in recent years. In this study, we proposed a method to predict the low arousal state early by using indexes which we could collect before the driver started to drive and also even the indexes which we could collect immediately after the driver started to drive. We simulated the before driving condition by control the drivers' sleeping hours. We used multiple linear regression to predict a time when the driver reaches the critical drowsiness level based on the biological information, vehicle operating information, and ability checks collected before and also while driving. As a result, our proposed method demonstrated the possibility to predict a time when the driver reaches the critical drowsiness level.