Towards solving perception based autonomous driving assistant system

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Opis bibliograficzny
Główni autorzy:	Hossain, Md. Arafat, Rahman, Md. Sazidur, Islam, Md. Jisan Bin, Bhuiyan, Sazzad Alam
Kolejni autorzy:	Rahman, Md. Khalilur
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2022
Hasła przedmiotowe:	Object detection Prediction Max pooling Convolutional neural network Machine learning Neural networks (Computer science)
Dostęp online:	http://hdl.handle.net/10361/16322

id	10361-16322
record_format	dspace
spelling	10361-163222022-02-23T21:01:31Z Towards solving perception based autonomous driving assistant system Hossain, Md. Arafat Rahman, Md. Sazidur Islam, Md. Jisan Bin Bhuiyan, Sazzad Alam Rahman, Md. Khalilur Department of Computer Science and Engineering, Brac University Object detection Prediction Max pooling Convolutional neural network Machine learning Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 52-55). This thesis scrutinizes the problem of perception in the self-driving car system. Selfdriving car is the face of the future and the decade’s research focus. Tech giants like Google, Uber, Tesla, Commai, Intel MobilEye etc. are now immensely investing in this particular technology. In our work, we mainly address the perception problem of autonomous vehicle and try to solve it with only cameras and comparatively lower computational cost. Firstly, to detect the lane we propose QLD (Quick Lane Detection) model on CULane dataset which gives significantly improved results in the roads of countries like Bangladesh than other existing methods. Secondly, for object detection we propose our own dataset BDCO or Bangladeshi Common Objects, and merge it with MS COCO dataset to make it suitable for Bangladeshi roads. We train BDCO dataset in a CNN based object detection model (CbOD) which also gives very promising results in local roads. Finally, we cascade QLD and CbOD with our decision-making system which outputs the warnings based on the analysis of the inputs from cameras in the vehicle. Our hands-on evaluations show that, our cascaded network Bangladeshi Driving Assistant (BD-DA) attains performance competitive to the state-of-the-art systems on a indistinguishable benchmark. Md. Arafat Hossain Md. Sazidur Rahman Md. Jisan Bin Islam Sazzad Alam Bhuiyan B. Computer Science 2022-02-23T06:34:58Z 2022-02-23T06:34:58Z 2021 2021-09 Thesis ID 17201079 ID 17201089 ID 17201090 ID 17201092 http://hdl.handle.net/10361/16322 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. 57 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Object detection Prediction Max pooling Convolutional neural network Machine learning Neural networks (Computer science)
spellingShingle	Object detection Prediction Max pooling Convolutional neural network Machine learning Neural networks (Computer science) Hossain, Md. Arafat Rahman, Md. Sazidur Islam, Md. Jisan Bin Bhuiyan, Sazzad Alam Towards solving perception based autonomous driving assistant system
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Rahman, Md. Khalilur
author_facet	Rahman, Md. Khalilur Hossain, Md. Arafat Rahman, Md. Sazidur Islam, Md. Jisan Bin Bhuiyan, Sazzad Alam
format	Thesis
author	Hossain, Md. Arafat Rahman, Md. Sazidur Islam, Md. Jisan Bin Bhuiyan, Sazzad Alam
author_sort	Hossain, Md. Arafat
title	Towards solving perception based autonomous driving assistant system
title_short	Towards solving perception based autonomous driving assistant system
title_full	Towards solving perception based autonomous driving assistant system
title_fullStr	Towards solving perception based autonomous driving assistant system
title_full_unstemmed	Towards solving perception based autonomous driving assistant system
title_sort	towards solving perception based autonomous driving assistant system
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/16322
work_keys_str_mv	AT hossainmdarafat towardssolvingperceptionbasedautonomousdrivingassistantsystem AT rahmanmdsazidur towardssolvingperceptionbasedautonomousdrivingassistantsystem AT islammdjisanbin towardssolvingperceptionbasedautonomousdrivingassistantsystem AT bhuiyansazzadalam towardssolvingperceptionbasedautonomousdrivingassistantsystem
_version_	1814309572124344320

Towards solving perception based autonomous driving assistant system

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