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AUTOMATIC TRAFFIC OVERCROWDING USING DEEP LEARNING

NALLAMSETTY SRI RAMYA SRI RAMYA

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Abstract

A prototype used to handle issues with traffic congestion is the traffic control management. One of the major variables affecting the traffic flow is the traffic lights. Traffic congestion causes accidents in which people may perish. The research involves autonomously calculating the green light period based on current traffic at the signal and identifying license plates of vehicles that violate traffic laws. The proposed system includes a feature that looks for the license plate of a car that is disobeying traffic signals. Additionally, the proposed system has autonomous traffic light switching based on vehicle density.Depending on how many vehicles are in the line, the signal will change automatically. As opposed to the way with less traffic, the direction with more traffic will receive a green signal for a longer period of time because of this. When cars disregard traffic signals, their license plates are photographed.In order to do this, we use camera footage as our input and identify the moving objects that are disobeying the law. We also offer an automatic traffic light adjustment.Depending on the density of the vehicles, we adjust the signals. By doing this, we can lessen the amount of times cars violate traffic signals. Additionally, we can lessen accidents brought on by high traffic.

Copyright

Copyright © 2023 NALLAMSETTY SRI RAMYA. This is an open access article distributed under the Creative Commons Attribution License.

Paper Details
Paper ID: IJPREMS30400011489
ISSN: 2321-9653
Publisher: ijprems
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