Pothole Encounter

Research on pothole encounter focuses on improving the detection and mitigation of potholes, primarily through computer vision techniques. Current efforts utilize deep learning models, such as YOLO and various convolutional neural networks (CNNs), to automatically identify potholes from images and videos, often classifying them by size and integrating depth information for improved accuracy. This work is crucial for enhancing road safety, improving autonomous vehicle navigation, and optimizing road maintenance strategies by enabling proactive identification and repair of hazardous road conditions.