Development of an Autonomous Driving Car Prototype Using FPGA

An autonomous car is a vehicle that can operate and make decisions without human intervention. Our model is developed using DE10 NANO Field Programmable Gate Array (FPGA). FPGA is used to implement a range of functions, including sensor fusion, perception, decision-making, and control. Sensor fusion combines data from multiple sensors, such as cameras and LiDAR, to comprehensively view the vehicle’s surroundings. Open Source Computer Vision Library (OpenCV) environment and YOLO algorithms were used for perception and decision-making. Perception involves analyzing the data to identify objects and their characteristics, such as their position, speed, and trajectory. Making decisions entails using this knowledge to choose the best course of action, such as accelerating, braking, or steering. Verilog Hardware Description Language (HDL) is utilized for controlling and the Python programming language is employed for the remaining aspects of the model.