Traffic Camera

Traffic cameras are increasingly used for automated traffic monitoring and analysis, aiming to improve safety, efficiency, and management of transportation systems. Current research focuses on developing robust computer vision algorithms, including deep learning models like YOLO, transformers, and recurrent graph attention networks, to extract high-resolution data such as vehicle trajectories, speeds, and anomalous behaviors from camera feeds. This involves overcoming challenges like camera calibration, occlusion, and the need for explainable AI, leading to advancements in applications ranging from accident detection and prevention to optimizing traffic flow and understanding driver behavior. The resulting data contributes significantly to traffic engineering, urban planning, and the development of intelligent transportation systems.