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Determining the Role of Alternative Roads in Traffic Congestion using Neural Networks

Published: 21 September 2022 Publication History

Abstract

As developing nations progress it leads to more vehicles on the road.
Vehicles are necessary to transport people and goods which ultimately leads to road congestion. Current methodologies in traffic congestion prediction are still inadequate, especially in developing nations. In this paper, we propose a use case of combining neural networks with computer vision using existing CCTV camera installations to obtain the necessary information for traffic congestion prediction.

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ICEBT '22: Proceedings of the 2022 6th International Conference on E-Education, E-Business and E-Technology
June 2022
130 pages
ISBN:9781450397216
DOI:10.1145/3549843
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 21 September 2022

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