Effect of pattern recognition features on detection for driver's cognitive distraction

Constituent technology of a driver monitor system using information of a driver's psychosomatic states is expected to create driver's states adaptive drive supporting system for the reduction of traffic accidents. In this study we identified a driver's distraction as one of major psychosomatic states which may result in a traffic accident by using Internet based survey on a questionnaire basis. Then we aimed at creating a methodology in use for detecting driver's cognitive distraction by means of using the AdaBoost which is capable of rapid and accurate classification. Furthermore we verified an effect of pattern recognition features such as interval between heart R-waves (hereafter, heart rate RRI) from an ECG (electrocardiogram), pupil diameter, and, gaze angle and head rotation angle.