Autonomous Driving Vehicle Design Based on BP Neural Network and Raspberry Pi
The accelerated advancement of sensor technology and artificial intelligence has prompted a heightened emphasis on research into autonomous vehicles,which is currently one of the most prominent topics in the field of robotics.This paper presents the design and implementation of an autonomous driving car,in which the Raspberry Pi is employed as the principal control core.A CMOS camera is utilized as the image acquisition module for the road and traffic lights,while DC decelerator motors and an L298N chip constitute the drive module.The BP neural network is designed to recognize lane lines in accordance with the prevailing road conditions,while the AdaBoost cascade classifier is employed to distinguish the road traffic lights,thereby enabling the automatic recognition between roads and traffic lights and the realization of autonomous driving.
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