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The vehicle senses its surroundings using sensors like radar, lidar, camera and GPS. This paper focuses on modifying an available All-Terrain Vehicle (ATV), quad bike using various actuation mechanisms into an autonomous driving vehicle.

World is moving towards self-driving vehicles due to its’ safety and comfort. The primary motive of this work is to modify a manual All-Terrain quad bike to an autonomous one; by altering some mechanical features and sensor integration using Autoware.AI software. The LiDAR-Camera-IMU sensor system constitutes the primary sensors of the vehicle. The terrain mapping in this project is performed with Kalman Filter algorithm, known as Linear Quadratic Estimation (LQE). The bike is driven manually to create the required map data. Understanding the static and dynamic obstacles is done by this trial run of the vehicle. With Autoware.AI, the strict path and lanes can be defined that the vehicle will follow in the actual run. In the next stage, the actuators are programming to drive the bike based on the terrain conditions as analysed by the software system. SLAM (Simultaneous Localization and Mapping) algorithm is another handy tool for this project.