Autonomous Braking System for Automobile Powered by Artificial Intelligence and Reinforcement Learning

Abstract-The rising number of accidents and injuries on the roads has created a pressing need for systems that can provide safety and protection to passengers while ensuring high performance in adverse conditions. Traditional braking systems may not always respond in time to prevent collisions, particularly in adverse conditions or emergencies. These systems rely on the driver to apply the brakes manually, which can result in delayed response times or even complete failure to apply the brakes in time. Additionally, these systems do not take into account factors such as road conditions, vehicle speed, and driver reaction time. To overcome these limitations and meet the needs, the Autonomous Braking System has been introduced in commercial vehicles, providing rapid brake response according to the driver’s need and safety. This system employs an intelligent control strategy that uses image processing technology based on object detection with the help of haarcascading object detection technique. Computer vision, a crucial component of this system, allows for the detection of path which is being followed by vehicle using Canny’s lane detection technique, obstacles and objects in the vehicle’s path. This information is then used to make decisions about when and how to apply the brakes, ensuring quick and safe stops. Reinforcement learning is also a key element of the system, allowing it to learn from its experiences and make better decisions over time. This involves providing feedback on the system’s performance and using it to adjust its behavior and improve its performance over a period of time. The haarcascading technique here recognizes captured objects as potential obstacles, feeding this information into the algorithm to take appropriate decisions. Overall, the Intelligent Braking System promises to significantly improve safety and performance in commercial vehicles.