A Prototype Autonomous Driving System using Raspberry-Pi

Self-Driving technology has revolutionized various fields, striving to make transportation safer, more efficient, and accessible. This project leverages a Raspberry-Pi to develop a prototype self-driving prototype, showcasing the potential of affordable, compact computing in autonomous systems. The system integrates computer vision, machine learning, and robotics, enabling the vehicle to perceive its environment, make informed decisions, and navigate autonomously. The prototype consists of a four-wheeled vehicle, a camera for live image capture, and sensors for environmental detection. At the heart of the system, the Raspberry-Pi processes data and executes decision-making algorithms. Through image processing, the vehicle identifies lanes, detects curves, and plans its trajectory. The software, written in Python, utilizes powerful libraries like OpenCV and TensorFlow to control vehicle movement and interactions seamlessly. This project aims to demonstrate the Raspberry-Pi’s capability to drive innovation in self-driving technology, making it an accessible platform for education, research, and hobbyists. The insights gained contribute to the growing field of autonomous systems and pave the way for future advancements.