Vehicle Automatic Recognition of Collision Avoidance and Warning System in Foggy Conditions

In order to improve the driving security of automatic driving vehicles under bad weather, taking foggy circumstances as an example, a collision avoidance and warning platform for vehicles automatic recognition is constructed, which consists of vehicle visual environment information acquisition subsystem, road information acquisition subsystem, vehicle motion parameters acquisition subsystem, driver operation data acquisition subsystem, and data processing subsystem. This paper focused on the research of vehicle visual environment information acquisition subsystem. Through doing research on real-time fog scene image collected from vehicle vision sensors, drawing fog blurred image gray histogram, and measuring span value of gray value with distribution span of gray value that is closely related to the image contrast. As fog can cause degradation of image contrast, the foggy circumstances will be identified based on the concentration distribution of gray value. Research results show that this method plays a good role in fast recognizing vehicle running microenvironment and improving active safety performance of vehicles in foggy conditions.