Traffic Light Detection

Traffic light detection is a crucial component of autonomous driving and advanced driver-assistance systems, aiming to reliably identify traffic signals under diverse conditions for safe navigation. Current research emphasizes improving robustness across varied weather (snow, rain, fog), lighting, and viewing angles, often employing deep learning models like YOLO and transformers, along with multi-modal approaches integrating audio and multiple cameras to overcome occlusions. This field is vital for enhancing the safety and reliability of autonomous vehicles, with ongoing efforts focused on improving accuracy, especially for small or distant lights, and achieving real-time performance on resource-constrained embedded systems.