Paper Title
Driver's State Monitoring By Function Of Facial Expression Detection For Autonomous Driving

driver may be angry when a traffic congestion happens. Anger is thought as crucial risk factor which may result in severe traffic accidents. Driver’s psychosomatic state adaptive driving support safety function may play effective role to prevent that kind of traffic accidents. Consequently, detection technology of anger is highly expected. This research firstly clarified root cause of traffic incidents experiences by means of executing Internet survey. From statistical analysis of the traffic incidents experiences, major psychosomatic state just before traffic incidents were identified as haste, distraction, drowsiness and anger. This research focused anger of a driver while driving. By means of using Kohonen neural network, this research created a technology to detect angry state of a driver in high accuracy. Recently autonomous driving of vehicle is said to be introduced into commercial market in the near future. A novel driver’s psychosomatic state adaptive driving support safety function is proposed in combination with an autonomous driving unit to reduce the number of traffic accidents. Keywords— Traffics incidents, Anger state of driver, Driver’s state monitoring, Kohonen Neural Network, ITS, ASV