Intelligent road recognition system for automous vehicle

An autonomous vehicle is a self-driving vehicle, that requires no operator to be involve in performing the set tasks. It is developed to assist humans in everyday tasks with the advantages of eliminating errors and reducing the need for human observation. For an autonomous vehicle to move with...

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Bibliographic Details
Main Author: Soon, Adrian Bee Toing
Format: Thesis
Language:English
English
English
Published: 2013
Subjects:
Online Access:http://eprints.uthm.edu.my/2132/
Abstract Abstract here
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author Soon, Adrian Bee Toing
author_facet Soon, Adrian Bee Toing
author_sort Soon, Adrian Bee Toing
description An autonomous vehicle is a self-driving vehicle, that requires no operator to be involve in performing the set tasks. It is developed to assist humans in everyday tasks with the advantages of eliminating errors and reducing the need for human observation. For an autonomous vehicle to move with flexibility or to adapt to a new road environment, it needs to have human-like perception and intelligence. This project proposes an intelligent visual perception system for an autonomous vehicle. It consists of a camera vision system that captures the road image. The image features are extracted using simple image processing algorithms and are trained using artificial neural network (ANN). The trained system is able to recognize some predetermined road patterns. Further experimental tests are designed to justify the performance of the system settings. An optimized set of image quality and the ANN network structures are chosen.
format Thesis
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institution Universiti Tun Hussein Onn Malaysia
language English
English
English
publishDate 2013
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spelling uthm-21322021-10-31T02:42:37Z http://eprints.uthm.edu.my/2132/ Intelligent road recognition system for automous vehicle Soon, Adrian Bee Toing TL Motor vehicles. Aeronautics. Astronautics TL1-484 Motor vehicles. Cycles An autonomous vehicle is a self-driving vehicle, that requires no operator to be involve in performing the set tasks. It is developed to assist humans in everyday tasks with the advantages of eliminating errors and reducing the need for human observation. For an autonomous vehicle to move with flexibility or to adapt to a new road environment, it needs to have human-like perception and intelligence. This project proposes an intelligent visual perception system for an autonomous vehicle. It consists of a camera vision system that captures the road image. The image features are extracted using simple image processing algorithms and are trained using artificial neural network (ANN). The trained system is able to recognize some predetermined road patterns. Further experimental tests are designed to justify the performance of the system settings. An optimized set of image quality and the ANN network structures are chosen. 2013-01 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/2132/1/24p%20SOON%20ADRIAN%20BEE%20TIONG.pdf text en http://eprints.uthm.edu.my/2132/2/SOON%20ADRIAN%20BEE%20TIONG%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/2132/3/SOON%20ADRIAN%20BEE%20TIONG%20WATERMARK.pdf Soon, Adrian Bee Toing (2013) Intelligent road recognition system for automous vehicle. Masters thesis, Universiti Tun Hussein Onn Malaysia.
spellingShingle TL Motor vehicles. Aeronautics. Astronautics
TL1-484 Motor vehicles. Cycles
Soon, Adrian Bee Toing
Intelligent road recognition system for automous vehicle
thesis_level Master
title Intelligent road recognition system for automous vehicle
title_full Intelligent road recognition system for automous vehicle
title_fullStr Intelligent road recognition system for automous vehicle
title_full_unstemmed Intelligent road recognition system for automous vehicle
title_short Intelligent road recognition system for automous vehicle
title_sort intelligent road recognition system for automous vehicle
topic TL Motor vehicles. Aeronautics. Astronautics
TL1-484 Motor vehicles. Cycles
url http://eprints.uthm.edu.my/2132/
work_keys_str_mv AT soonadrianbeetoing intelligentroadrecognitionsystemforautomousvehicle