The rapid growth of urban populations has led to a surge in vehicular traffic, posing significant challenges for conventional traffic management systems. Traditional traffic lights, with their fixed time allocations for each road, often struggle to accommodate fluctuating traffic volumes, resulting in frustrating delays for drivers. In response to this issue, our proposed traffic light control system offers a tailored solution. By utilizing advanced sensors to measure real-time vehicle density in each lane, our system dynamically adjusts signal timings. Roads are categorized into low, medium, and high-density zones, with green light durations corresponding to the current traffic conditions. This adaptive approach aims to alleviate congestion and improve overall traffic flow efficiency, providing a smoother driving experience for commuters. Furthermore, our system integrates priority control features for emergency vehicles such as ambulances and fire trucks. Equipped with radio frequency (RF) transmitters and global positioning system (GPS) modules, these vehicles can activate a special signal to grant them priority passage through the traffic lights. This ensures rapid response times during emergencies, enhancing public safety and emergency services’ effectiveness in urban areas. In conclusion, our traffic light control system offers a flexible and responsive solution to the challenges posed by increasing urban traffic. By optimizing signal timings based on real-time data and prioritizing emergency vehicles, it contributes to safer and more efficient transportation networks in cities.


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    Title :

    IoT-Based Smart Signal System for Traffic Density Management and Emergency Vehicle Priority


    Contributors:


    Publication date :

    2024-10-25


    Size :

    1324403 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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