Implementation of Autonomous Vehicle using Real-Time Image processing and Computer Vision Algorithm

The recent development of autonomous vehicles has grown significantly, offering the possibility of safer and more effective modes of transportation. Enabling cars to travel and operate autonomously in real-world settings is a crucial obstacle to reaching complete autonomy. The proposed article uses image processing approaches and computer vision (CV) to resolve the difficulty of navigation and control in autonomous vehicles. Here in proposed investigate cutting-edge techniques for image processing and CV to retrieve useful data from the environment around the vehicle. It consists of obstacle recognition, lane detection, and object detection using different sensors like cameras.The proposed model aims to improve the vehicle’s decision-making capabilities by utilizing the image processing approach. The autonomous vehicle is able to make well-informed decisions regarding its speed, trajectory, and collision avoidance because it has an accurate perception of its surroundings. In addition, look into real-time image optimization and analysis to make sure the system is dependable and responsive in changing situations. The proposed model will improve global transportation system efficiency and safety while also advancing the field of autonomous vehicle technology.