A Hybrid Approach for Detection in Foggy Environments for Self Driving Cars: YOLO and MSRCR Techniques

A self-driving car is a topic deserving of intense attention from both research & development folks and industry experts as self-driving cars have latent potential to revolutionize transportation systems around the whole car-driving world. Safety and reliability of the automobile are the topics most important to people when they talk about self-driving cars, which heavily rely on accurate and robust object detection in a myriad of environmental conditions. So, an approach for improving the capability of self-driving cars for object detection being driven in smoggy conditions is put forth. Detecting objects & vehicles on the road is a core part of driverless car technology as it requires high accuracy and real-time processing to ensure safety in various driving scenarios. This research proposes an approach that has been improved and is related to the YOLO (You Only Look Once) algorithm to understand the presence of vehicles & objects on the road when the weather is foggy. Our approach involves integrating & incorporating one component for dehazing into the YOLO model to improve restoring of image info which we achieved with the help of a technology called MSRCR (Multi-Scale Retinex with Colour Restoration). We have trained the updated scenario using augmented data processed with MSRCR to improve its stability and performance. We conducted extensive evaluations on a publicly available dataset and the results clearly indicate that our enhanced YOLO model outperforms conventional YOLO in detecting vehicles in foggy weather conditions. Our findings highlight the latent possibility of mixing multiple technologies to improve object detection for self-driving cars which could improve vehicle safety and vehicle reliability of autonomous vehicles for users in the future. Our approach can be further extended to other applications that require accurate and robust object detection in extreme conditions such as in robotics, surveillance systems, security systems & satellite imagery.