Intersection collision-avoiding method based on dynamic Bayes network

The invention discloses an intersection collision-avoiding method based on a dynamic Bayes network, and mainly solves the problems that an existing algorithm is not well adapted to the complex road layout of an intersection, a large amount of data processing is needed, and the calculation complexity is high and the time complexity is high. The method comprises the steps of: 1) determining vehicle states, road conditions and driver behavior information, and adopting the dynamic Bayes network to carry out modeling on vehicle state evolution; 2) determining the safe driving behavior of a target vehicle according to the current environment conditions; and 3) deriving the intention behavior of the driver at the intersection, carrying out risk estimation based on comparison between the safe driving behavior and the intention behavior, and when potential risks are detected, taking different measures according to the practical condition for avoiding a collision. According to the invention, the complex vehicle track prediction process is avoided, the calculation amount is reduced, the vehicle collision in other scenes can be flexibly avoided, and the method can be applied to an intelligent traffic system.