Automated overtaking assistance system: a real-time approach using deep learning techniques

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

书目详细资料
Main Authors:	Moonjarin, Musarrat, Charu, Krity Haque, Nafis, Kh. Fardin Zubair, Sawly, Suraya Jahan
其他作者:	Rhaman, Md. Khalilur
格式:	Thesis
语言:	English
出版:	Brac University 2023
主题:	Image processing Overtaking Autonomous Distance measure SegNet model PINet Optical flow YOLO Deep learning Cognitive learning theory Machine learning
在线阅读:	http://hdl.handle.net/10361/21170

id	10361-21170
record_format	dspace
spelling	10361-211702023-09-24T21:04:11Z Automated overtaking assistance system: a real-time approach using deep learning techniques Moonjarin, Musarrat Charu, Krity Haque Nafis, Kh. Fardin Zubair Sawly, Suraya Jahan Rhaman, Md. Khalilur Reza, Md Tanzim Department of Computer Science and Engineering, Brac University Image processing Overtaking Autonomous Distance measure SegNet model PINet Optical flow YOLO Deep learning Cognitive learning theory Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 43-46). Road accidents are one of the major causes of fateful deaths in Bangladesh. In most cases it is caused by Overtaking on highways or on regular roads. In terms of overtaking the major task is to decide whether the overtaking is safe or not. There has been a lot of work considering autonomous communication in this field. However, the challenges in terms of Bangladesh, need different and user-friendly solutions. Considering the interest of researchers in this area and to introduce a different evolutionary trend in Bangladesh we approached this research. In this research our basic concept is to suggest the safe overtaking decision to the host drivers considering an overall idea of the environment. Our work aims to decrease early and unfortunate deaths caused by vehicle’s abrupt overtaking on Bangladesh’s Highways by assisting drivers based on deep learning techniques. Furthermore, the Autonomous system considers communication between vehicles to decide safe overtaking within minimum time.V Vehicle detection and classificationdetection and classification is done using the YOLO model. After measuring the distance and relative velocity, our model suggests the decision by using the help of other significant models used in our research. For distance measurement, we used SegNet and a distance measurement model. In addition, for getting relative velocity we have used optical flow and also for checking whether the driver is on the right lane or not, we have used the PiNet model for lane detection. Moreover, we have no use of other sensors besides the camera and kept only one camera in our proposed system. So in future, users will get this autonomous system in their vehicles at low cost as our system proposes. Experimental results from the proposed system show that deep learning process is better in terms of our country. Musarrat Moonjarin Krity Haque Charu Kh. Fardin Zubair Nafis Suraya Jahan Sawly B. Computer Science and Engineering 2023-09-24T05:29:51Z 2023-09-24T05:29:51Z 2023 2023-03 Thesis ID 19101586 ID 19101173 ID 19301007 ID 19101383 http://hdl.handle.net/10361/21170 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 46 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Image processing Overtaking Autonomous Distance measure SegNet model PINet Optical flow YOLO Deep learning Cognitive learning theory Machine learning
spellingShingle	Image processing Overtaking Autonomous Distance measure SegNet model PINet Optical flow YOLO Deep learning Cognitive learning theory Machine learning Moonjarin, Musarrat Charu, Krity Haque Nafis, Kh. Fardin Zubair Sawly, Suraya Jahan Automated overtaking assistance system: a real-time approach using deep learning techniques
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
author2	Rhaman, Md. Khalilur
author_facet	Rhaman, Md. Khalilur Moonjarin, Musarrat Charu, Krity Haque Nafis, Kh. Fardin Zubair Sawly, Suraya Jahan
format	Thesis
author	Moonjarin, Musarrat Charu, Krity Haque Nafis, Kh. Fardin Zubair Sawly, Suraya Jahan
author_sort	Moonjarin, Musarrat
title	Automated overtaking assistance system: a real-time approach using deep learning techniques
title_short	Automated overtaking assistance system: a real-time approach using deep learning techniques
title_full	Automated overtaking assistance system: a real-time approach using deep learning techniques
title_fullStr	Automated overtaking assistance system: a real-time approach using deep learning techniques
title_full_unstemmed	Automated overtaking assistance system: a real-time approach using deep learning techniques
title_sort	automated overtaking assistance system: a real-time approach using deep learning techniques
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/21170
work_keys_str_mv	AT moonjarinmusarrat automatedovertakingassistancesystemarealtimeapproachusingdeeplearningtechniques AT charukrityhaque automatedovertakingassistancesystemarealtimeapproachusingdeeplearningtechniques AT nafiskhfardinzubair automatedovertakingassistancesystemarealtimeapproachusingdeeplearningtechniques AT sawlysurayajahan automatedovertakingassistancesystemarealtimeapproachusingdeeplearningtechniques
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Automated overtaking assistance system: a real-time approach using deep learning techniques

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