Experimental Lane Keeping Assist for an Autonomous Vehicle Based on Optimal PID Controller

Abstract

Detection of the lane boundary is the primary task in order to control the trajectory of an autonomous car. In this paper, three methodologies for lane detection are discussed with experimental illustration: Blob analysis, Hough transformation and Birds eye view. The next task after receiving the boundary points is to apply a control law in order to trigger the steering and velocity control to the motors efficiently. In the following, a comparative analysis is made between different tuning criteria to tune PID controller for Lane Keeping Assist (LKA). In order to receive the information of the environment a camera is used that sends wireless data to Simulink through Raspberry-Pi (R-Pi). The data is processed by the controller that transmits the desired output control to arduino through serial communication.