A Self-Driving Car Platform Using Raspberry Pi and Arduino
Vikrant Shahane, Hrushikesh Jadhav, Mihir Sansare, Prathmesh Gunjgur
Abstract
Cars that can drive themselves have long been the stuff of science fiction. However, this fiction will become a reality thanks to the self-driving automobile within the next several years. Self-driving cars are vehicles that navigate to a destination without the assistance of a human. Numerous prominent firms and developers have invested heavily in this field, creating their own self driving car systems. The fascinating topic of self-driving cars served as the inspiration for this study, which aims to develop a self-driving platform. This paper proposes a working model of a Self Driving car using Raspberry Pi, Arduino Uno and a camera based approach. The three major modules that the car uses to perform are lane detection, obstacle detection, and traffic sign detection. The camera module, which is installed on the car's roof, captures the live stream images and sends them to the Raspberry Pi, which processes them and sends them to all three modules. Algorithms such as Canny Edge Detection and the Hough Transform are utilised for Lane Detection. Based on the results of these algorithms, the car predicts the direction it wants to move in. The Traffic Sign Detection Module identifies traffic signs using a CNN and OpenCV-based approach. Obstacle Detection uses the HAAR Cascade technique to detect objects that may be encountered on the road, such as cars and pedestrians. These modules integrated onto the self-driving car moves it autonomously with maximum accuracy ranging from 95 to 97%.