Traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| Idioma: | English |
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Brac University
2022
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| Acesso em linha: | http://hdl.handle.net/10361/16668 |
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10361-16668 |
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10361-166682022-05-25T21:01:31Z Traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics Hossain, Md. Shahriyar Bhuiyan, Md. Imtiaz Dulali, Marjahan Akther Alam, Md. Ashraful Department of Computer Science and Engineering, Brac University AITS ITSC Deep learning Image recognition Self-adaptive traffic system ATS City Traffic Fluid dynamics Numerical simulation Traffic simulation Object detection Optical flow Traffic flow Image processing -- Digital techniques. Machine learning Cognitive learning theory (Deep learning) Fluid dynamics -- Computer programs. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 29-33). Bangladesh has been suffering a severe traffic congestion issue ever since it has been on a high paced development roadmap. Researches regarding solving such traffic issue has been in the talks but has never reached a proper conclusion and far from implementation. It has slowly grown into a towering challenge to overcome. And with an aim to topple that tower, we propose a 3 layer architecture to solve this problem. The proposed model consists of object detection, speed measurement and decision based on traffic flow. Using neural network object detection algorithms, it will detect congestion and the speed of the congestion. Then, it will use fluid dynamics based model to get the traffic flow, pass data between other signals and provide correct traffic signals. All signals would interact with each other like hive mind to maximize the traffic flow in any intersection. With the working model we had at our hand, we ran rigorous experiments to check whether our model works or not. Our results indicate that our model surpasses all other similarly implemented models by a noticeably large margin. Md. Shahriyar Hossain Md. Imtiaz Bhuiyan Marjahan Akther Dulali B. Computer Science 2022-05-25T04:18:34Z 2022-05-25T04:18:34Z 2022 2022-01 Thesis ID 21141017 ID 18101688 ID 17301010 http://hdl.handle.net/10361/16668 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. 33 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
AITS ITSC Deep learning Image recognition Self-adaptive traffic system ATS City Traffic Fluid dynamics Numerical simulation Traffic simulation Object detection Optical flow Traffic flow Image processing -- Digital techniques. Machine learning Cognitive learning theory (Deep learning) Fluid dynamics -- Computer programs. |
| spellingShingle |
AITS ITSC Deep learning Image recognition Self-adaptive traffic system ATS City Traffic Fluid dynamics Numerical simulation Traffic simulation Object detection Optical flow Traffic flow Image processing -- Digital techniques. Machine learning Cognitive learning theory (Deep learning) Fluid dynamics -- Computer programs. Hossain, Md. Shahriyar Bhuiyan, Md. Imtiaz Dulali, Marjahan Akther Traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Alam, Md. Ashraful |
| author_facet |
Alam, Md. Ashraful Hossain, Md. Shahriyar Bhuiyan, Md. Imtiaz Dulali, Marjahan Akther |
| format |
Thesis |
| author |
Hossain, Md. Shahriyar Bhuiyan, Md. Imtiaz Dulali, Marjahan Akther |
| author_sort |
Hossain, Md. Shahriyar |
| title |
Traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics |
| title_short |
Traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics |
| title_full |
Traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics |
| title_fullStr |
Traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics |
| title_full_unstemmed |
Traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics |
| title_sort |
traffic congestion detection and optimizing traffic flow using object detection, optical flow and fluid dynamics |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/16668 |
| work_keys_str_mv |
AT hossainmdshahriyar trafficcongestiondetectionandoptimizingtrafficflowusingobjectdetectionopticalflowandfluiddynamics AT bhuiyanmdimtiaz trafficcongestiondetectionandoptimizingtrafficflowusingobjectdetectionopticalflowandfluiddynamics AT dulalimarjahanakther trafficcongestiondetectionandoptimizingtrafficflowusingobjectdetectionopticalflowandfluiddynamics |
| _version_ |
1814309432528470016 |