Traffic Signal Detection System for Autonomous Vehicles in Abnormal Environmental Conditions

This paper presents a new autonomous driving vehicle capable of detecting traffic signals in abnormal environmental conditions. The system uses advanced machine learning algorithms and CNN to accurately identify and interpret traffic signals in challenging conditions, such as poor lighting, rain, or fog. The authors demonstrate the system's effectiveness and robustness in various real-world scenarios through extensive testing and evaluation. The paper comprehensively analyzes the system's performance, including its ability to detect traffic signals in abnormal environmental conditions and adapt to the environment. The study shows how technology plays a vital role in the safety and efficiency of autonomous vehicles and helps advance the development of autonomous driving technology.