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Density based traffic control system for a four way intersection

dc.contributor.advisorHossain Bhuian, Dr. Mohammed Belal
dc.contributor.authorChowdhury, Faizul Bari
dc.contributor.authorFaruqui, Tahmid Azim
dc.contributor.authorRazzaque, Rylah Marzia
dc.contributor.authorIqbal, Nayeem
dc.contributor.departmentDepartment of Electrical and Electronic Engineering
dc.date.accessioned2024-01-16T06:45:39Z
dc.date.available2024-01-16T06:45:39Z
dc.date.copyright2023
dc.date.issued2023-01
dc.descriptionCataloged from PDF version of final year design project.
dc.descriptionIncludes bibliographical references (pages 74-79).
dc.descriptionThis final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2023.en_US
dc.description.abstractIntelligent traffic system is not new to this modern world in order to mitigate traffic congestion. However, a proper management plan for a four way intersection lacks in our cities. An enhanced and optimized system is introduced in our project which in measure the density of all the vehicles plying on the road. The project is conducted on the Dhaka city where live traffic data has been collected from Shoinik Club Mor. A deep learning system is conducted where optimized YOLOv5 algorithm has been used to count the vehicles and the datasets for different vehicles are collected from COCO datasets and some datasets from BRTA (Bangladesh Road Transport Authority). After analyzing in different traffic situation for over 1260 frames at a rate of 30 FPS, we get around 88% accuracy in terms of detection. This operation sets the initial time for green signal as 16 seconds and then it changes according to the density occupied by vehicles of a particular road.en_US
dc.description.degreeB. Electrical and Electronic Engineering
dc.description.statementofresponsibilityFaizul Bari Chowdhury
dc.description.statementofresponsibilityTahmid Azim Faruqui
dc.description.statementofresponsibilityRylah Marzia Razzaque
dc.description.statementofresponsibilityNayeem Iqbal
dc.format.extent91 pages
dc.identifier.otherID: 16321168
dc.identifier.otherID: 17121072
dc.identifier.otherID: 17121079
dc.identifier.otherID: 181221047
dc.identifier.urihttp://hdl.handle.net/10361/22162
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University project reports 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.
dc.subjectArtificial intelligenceen_US
dc.subjectDeep learningen_US
dc.subjectYOLOv5en_US
dc.subjectDatasetsen_US
dc.subjectIoUen_US
dc.subjectNon max spressionen_US
dc.subject.lcshImage processing -- Digital techniques.
dc.subject.lcshCognitive learning theory (Deep learning)
dc.titleDensity based traffic control system for a four way intersectionen_US
dc.typeProject Reporten_US

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