Design and Implementation of Autonomous Vehicle with Lane Tracking and Sign Detection using Machine Learning
Abstract
The autonomous vehicle or the driverless vehicle referred to a Self-driving car in simple language. In this project, the primary goal is to develop a prototype of a vehicle that follows a lane and, at the same time, detects, understands, and responds to traffic signs. Image Processing and Machine learning algorithms are applied to detect roads and traffic signs using Raspberry Pi, Arduino, and open-source software. The Canny Edge Detection algorithm is applied to track lanes, and the Haar-Cascade algorithms are used to detect traffic signs. Raspberry Pi collects inputs from a camera module and processes them for lane detection, traffic sign detection, predictions sent to the Arduino for vehicle control.