Driver’s anger state identification by using facial expression in cooperation with artificial intelligence
Preventive safety system of vehicle is highlighted to reduce the number of traffic accidents. Driver’s state adaptive driving safety system may be one of candidates of the safety system. Identifying driver’s psychosomatic states is indispensable to establish those safety systems. Anger of driver state is often seen in traffic congestion which may be involved in severe traffic accidents. This research adopted Kohonen neural network as classification algorithm to identify anger state of driver by using facial expression. We adopted six types of facial expression which are ordinary, drowsiness, anger, sorrow, delight and surprise according previous research. We classified six types of facial expressions by using KNN. Finally, this research proposes driver’s anger state alert function by using facial expression classification in cooperation with artificial intelligence to prevent potential risks of traffic accidents.
Keywords: driver’s anger; facial expression; Kohonen neural network; artificial intelligence.