Real Time Ackerman Steering Angle Control for Self-Driving Car Autonomous Navigation

Abstract

Unsupervised Ackermann’s principle is widely used in automobile market and other mobile vehicles to steer an autonomous vehicle. In real time self-driving car operation automatic lane detection and following is main task for autonomous navigation. Different type of sensors are being used for lane lines detection but cameras are the most cost effective and accurate sensory modality. This paper presents a novel method for lanes lines detection on a road and then controls the Ackermann Steering angle of the prototype car for autonomous navigation. A bird’s eye view input obtained from a monocular camera mounted at the head of car is fed to the processing unit.