Driving support by estimating vehicle behavior

Many accidents at intersection are happend due to judgment errors, which are caused from blind spots of drivers. We propose a method for generating warning messages related to the accidents predicted between blind spots of drivers and vehicle behaviors by using surveillance camera and on-board camera. In this method, vehicle behaviors of straight, right turn, left turn, change to right lane, and change to left lane are predited by applying hidden markov model (HMM). Direction sequences of behaviors are used for training HMMs which represent each behavior by Baum-Welch algorithm. Behavior information enables the drivers to recieve our intelligent support and allows drivers to recognize behaviors of other vehicles easily. From a result of behavior prediction, our system could recognize 80% of behavior, correctly.