This study introduces the Smart Traffic Management System (STMS), which by combining cutting-xedge technologies and extensive data sources, has the potential to completely transform urban transportation. The goal of this strategy is to build a more resilient and effective urban infrastructure that tackles the various issues brought on by growing traffic congestion. One of the most important elements affecting traffic flow is the traffic controller. To meet the increasing demand, traffic control systems urgently need to be optimized. An urgent issue, traffic congestion is made worse by cities’ expanding populations and growing car populations. In addition to causing traffic jams and driver stress, it significantly raises fuel consumption and air pollution levels. Megacities are particularly affected by this issue, and its persistent nature necessitates real-time road traffic density calculations for improved signal control and efficient traffic management. Furthermore, considering factors such as pedestrian flow and public transportation routes is crucial. These elements significantly influence traffic patterns and need to be seamlessly integrated into the overall traffic management system. By incorporating pedestrian and public transportation data, the system can provide comprehensive solutions that cater to the diverse mobility needs of the urban population. Our proposed solution leverages live feeds from traffic junction cameras, employing advanced image processing and AI techniques to accurately assess traffic density. The system also focuses on developing an algorithm that dynamically adjusts traffic lights based on vehicle density, aiming to alleviate congestion, provide swifter transit for commuters, and mitigate pollution levels.


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    Title :

    Smart Traffic Management System


    Contributors:


    Publication date :

    2024-10-25


    Size :

    1132325 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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