Vision Sensor Based Fuzzy System for Intelligent Vehicles

Those in the automotive industry and many researchers have become interested in the development of pedestrian protection systems in recent years. In particular, vision-based methods for predicting pedestrian intentions are now being actively studied to improve the performance of pedestrian protection systems. In this paper, we propose a vision-based system that can detect pedestrians using an on-dash camera in the car, and can then analyze their movements to determine the probability of collision. Information about pedestrians, including position, distance, movement direction, and magnitude are extracted using computer vision technologies and, using this information, a fuzzy rule-based system makes a judgement on the pedestrian's risk level. To verify the function of the proposed system, we built several test datasets, collected by ourselves, in high-density regions where vehicles and pedestrians mix closely. The true positive rate of the experimental results was about 86%, which shows the validity of the proposed system.