Open AccessSelf-Driving Car Using Machine Learning and Neural Network
Author(s) -
Haroon Ijaj Hublikar,
Atharva Ajit Keny,
Rahul Dilip Ghonge,
Khan Sawood Iftekhar Ahmed
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40505
Subject(s) - automation , controller (irrigation) , convolutional neural network , self driving , computer science , process (computing) , artificial neural network , artificial intelligence , automotive engineering , embedded system , control engineering , simulation , engineering , operating system , mechanical engineering , agronomy , biology
Self-driving cars are autonomous vehicles that can run on their own without human intervention and could represent a technological revolution in the next decade. This work presents the development of a low-cost prototype of a miniature selfdriving car model using simple and out-of-the-box technology. The idea is to use only camera modules to create self-driving cars that move between destinations with minimal human intervention. The purpose of this project is to accelerate the process of driving a car through automation. The results of this project will definitely reduce the number of car accidents that occur today. This project uses NVIDIA Jetson Nano as the main controller and has a processing power of about 500 gigaflops. The controller is mounted on the car platform itself and performs all the calculations needed to drive the car on board. The car uses a trained convolutional neural network (CNN) that predicts all the parameters that the car needs to drive smoothly. These are directly connected to the main steering mechanism and the output of the deep learning model determines the steering angle of the vehicle. Keywords: CNN, NVIDIA Jetson Nano, Self-driving, automation, deep learning