Advanced Driving Assistance System for an Electric Vehicle Based on Deep Learning

Abstract

This chapter deals with a design of a new speed control method using artificial intelligence techniques applied to an autonomous electric vehicle. In this research, we develop an Advanced Driver Assistance System (ADAS) which aims to enhance the driving manner and the safety, especially when traveling too fast. The proposed model is a complete end-to-end vehicle speed system controller that proceeds from a detected speed limit sign to the regulation of the motor's speed. It recognizes the speed limit signs before extracting from them, a speed information that will be sent, as reference, to a NARMA-L2 based controller. The study is developped specially for electric vehicle using Brushless Direct Current (BLDC) motor. The simulation results, implemented using Matlab-Simulink, show that the speed of the electric vehicle is controlled successfully with different speed references coming from the image processing unit.