Driver's Cognitive Distraction Detection Using Visual Attention

To reduce traffic fatalities, it is effective to detect driver's cognitive distraction. In this study, to detect driver's cognitive distraction, we focus on the difference between the measured gaze points and the visual attention maps indicating the objects to be gazed at estimated from the deep learning model. In order to verify the effectiveness of the proposed method, the BDD-A dataset of in-vehicle camera videos is used. As a result, it is confirmed that the proposed method can detect driver's cognitive distraction with high accuracy.