UAV -based Vehicle Detection Using RGB and Infrared Cameras with Artificial Intelligence for Traffic Monitoring and Road Management

UAV-based vehicle detection plays a crucial role in traffic monitoring and road management by identifying vehicle locations and types in aerial images. This technology is applied in various areas, including urban roads, highways, and parking lots, offering significant advantages for smart city infrastructure. However, accurately detecting vehicles, especially in complex lighting, weather, and location conditions, remains a key challenge. To address this, we propose an effective vehicle detection model that combines RGB and infrared images captured by UAVs. The model's performance is evaluated based on accuracy, sensitivity, and image fusion techniques, improving overall detection efficiency. Our method achieves high detection accuracy of approximately ۹۵% across various weather conditions. High-precision vehicle classification is essential for real-time traffic surveillance and hazard identification. Extensive experiments using aerial images from Shiraz city demonstrate the robustness of the model, ensuring reliable results for traffic management and road safety.

کلیدواژه ها:

UAV-based vehicle detection ، RGB and infrared cameras ، image fusion ، traffic monitoring ، road management