Real-Time Electric Vehicle Collision Avoidance System Under Foggy Environment Using Raspberry Pi Controller and Image Processing Algorithm

During winter season, in foggy environment, accidents are evident on national highways and many people succumb to death due to these accidents especially in Northern and Eastern region of India. To avoid such accidents, the authors have proposed a Raspberry Pi-based image processing approach to save the life of human being. An ultrasonic sensor detects the obstacle/vehicle and measures the distance. Once the obstacle is within the range, the edge detection algorithm processes the fog image and produces enhanced quality images displayed to the vehicle driver. The advantage of the proposed approach is that with the information achieved from ultrasonic sensor, the driver may have to apply the sudden brake to avoid accidents with the front-side vehicles but the backside vehicle may collide with his/her vehicle. But the enhanced image spatial information is useful to the driver in taking the decision whether to apply the brake or overtake the obstacle form left/right side to avoid accidents from backside vehicles also. Further, the high processing capacity of Raspberry Pi produces results within fraction of seconds (real time) to give sufficient amount of time to the driver to take appropriate decision to save life.