Applying fuzzy method to vision-based lane detection and departure warning system

As the high growth of population of vehicles, the traffic accidents are becoming more and more serious in recent years. Most occurrences of the car accidents results from the distraction, inattention and driving fatigue of the driver. Hence, in order to avoid the driver being in danger as much as possible. In the lane detection, in order to enhance lane boundary information and to suitable for various light conditions all day, we combine the self-clustering algorithm (SCA), fuzzy C-mean and fuzzy rules to process the spatial information and Canny algorithms to get good edge detection. In the lane departure warning, the system uses instantaneous information from the lane detection to calculate angle relations of the boundaries. The system sends a suitable warning signal to drivers, according to degree different of the departure. These experiments have been successfully evaluated on the PC platform of 3.2-GHz CPU and the average frame rate is up to 14 fps.