Vehicle Blind Spot Detection and Tracking System Based on Machine Learning Model

Car accidents often happen when vehicles change lanes, turn at intersections, back up, or park in a parking lotthat is especially dangerous. Therefore, detecting people in the blind spots of cars is a significant issue. There are many methods to detect people. However, those problems do not completelysolve the problem. To solve the problem, the article proposes a system to recognize people entering the blind spot behind acar. The method that we use is to combine image processing algorithms with microwave radar sensors to collect information about the vehicle's surroundings. We use the Yolo-fastest module to extract human detection through the parts of the human body (arms, legs, head, torso), combined to increase recognition ability. Besides, using microwave radar sensors are used to detect moving objects. The results on cars have achieved 91.63% accuracy and have potential applications in self-driving cars and advanced driver assistance systems.