DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-11,Issue-11 ( Nov, 2023 ) | |||||||||
Paper Title |
Intelligent Traffic Management System Using CNN | |||||||||
Author Name |
Ashna Merin Philip | |||||||||
Affilition |
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Pages |
1-5 | |||||||||
Abstract |
In today's world, we're seeing more and more vehicles on the roads, especially in cities. There isn't always enough space or money to build new roads, and this is causing problems. There's a big difference between how much traffic there is and how well we can handle it. Traffic lights are an important part of how we manage traffic in cities. They help control the flow of cars on the road. We have an idea for a smart traffic system that can make traffic lights even smarter. This system can figure out which lanes have the most traffic and give them the green light more often. Here’s how it works: We put cameras at each lane of an intersection to take pictures of the traffic. These pictures are sent to a small computer, like a Raspberry Pi, which uses computer vision (a kind of smart technology) to figure out how many cars are in each lane. By doing this, we can make sure that the lanes with the most cars get the greenest lights. This can help reduce traffic jams and make our cities run more smoothly. In addition to this, we introduced a Adaptive Signal Synchronization mechanism. Keywords - Intelligent traffic Signaling System, Raspberry PI, Computer Vision | |||||||||
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