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A prototypic implementation of self-driving cars based on computer vision and deep learning

TL152.8.N87 2019

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Main Author: Nurul Fatin Nadiah Abdul Aziz
Format: text::Final Year Project
Language:English
Published: 2024
Subjects:
Autonomous vehicles
Computer vision
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spelling my.uniten.dspace-317142024-03-31T02:02:36Z A prototypic implementation of self-driving cars based on computer vision and deep learning Nurul Fatin Nadiah Abdul Aziz Autonomous vehicles Computer vision TL152.8.N87 2019 Malaysia is one of the developed countries in South Asia. Proves that the local technologies in automobile industry growth widely such as Proton Holding and Produa Sendirian Berhad became one of the factors on selecting the title, a prototypic self-driving car using deep learning and computer vision. Besides that, the idea of this project also coming from many traffic congestions and accidents throughout the year recorded all over the world including Malaysia. Thus, to overcome this issue, this research project is purposed. This project focusing on three main goals which to train a set of data using neural network and achieve 70% of accuracy, design a self-driving car using remote-control (RC) car, Raspberry Pi, Pi Camera and Arduino and implementing a deep learning and computer vision and make it an autonomous RC car. Deep learning architecture was introduced to train set of data and achieve up to 70% accuracy. In this project, two models were presented. The models are You Only Look Once (YOLO) and Visual Geometry Group 16 (VGG16), the sub architecture from Single Shoot Multibox Detector. YOLO model is a model mean for training from scratch technique while VGG16 model is a model used for fine-tuning. As a result, VGG16 model is producing high accuracy compare to YOLO model. In designing a self-driving car using remote-control (RC) car, few components are involved. The components used are Raspberry Pi, Arduino, Pi Camera, RC car and Ultrasonic sensor. The connection of the elements is discussed in subsequence chapter under Methodology part. This experiment was differentiating between two design where the first design was constructed using commercial RC car available in the market and the second design was built by assembling mentioned components. The last objective is implementing a deep learning and computer vision and make it an autonomous RC car by simply combining the trained dataset with the designed RC car. 2024-03-29T09:15:00Z 2024-03-29T09:15:00Z 2019 Resource Types::text::Final Year Project https://irepository.uniten.edu.my/handle/123456789/31714 en application/pdf
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
topic Autonomous vehicles
Computer vision
spellingShingle Autonomous vehicles
Computer vision
Nurul Fatin Nadiah Abdul Aziz
A prototypic implementation of self-driving cars based on computer vision and deep learning
description TL152.8.N87 2019
format Resource Types::text::Final Year Project
author Nurul Fatin Nadiah Abdul Aziz
author_facet Nurul Fatin Nadiah Abdul Aziz
author_sort Nurul Fatin Nadiah Abdul Aziz
title A prototypic implementation of self-driving cars based on computer vision and deep learning
title_short A prototypic implementation of self-driving cars based on computer vision and deep learning
title_full A prototypic implementation of self-driving cars based on computer vision and deep learning
title_fullStr A prototypic implementation of self-driving cars based on computer vision and deep learning
title_full_unstemmed A prototypic implementation of self-driving cars based on computer vision and deep learning
title_sort prototypic implementation of self-driving cars based on computer vision and deep learning
publishDate 2024
_version_ 1806427843524034560
score 13.214268

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