Density Based Traffic Control System

This paper introduces a density-based traffic control system aimed at optimizing traffic management at intersections. Utilizing Arduino mega 2560, sensor technology, and an LCD display, the system dynamically adjusts signal timings in response to varying traffic densities. By incorporating infrared sensors for vehicle detection and a sound sensor to prioritize emergency vehicles, the system intelligently allocates green light durations to different roadways, minimizing congestion and ensuring smoother traffic flow. Categorizing traffic into high, moderate, and low-density scenarios enhances the system's adaptability to changing traffic conditions. Overall, this paper offers a practical solution for enhancing road safety, reducing travel times, and improving transportation efficiency in urban environments through intelligent traffic control with visual feedback provided by the LCD display.

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Publication Details

Published
2025-02-13
DOI
https://doi.org/10.1109/ic363308.2025.10956740
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
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article

Density Based Traffic Control System

Koppula Manjusha, Yadala Pavankumar, Bonthu Bhoomika, Banoth Sariyu
Neural Networks and Applications
article

Density Based Traffic Control System

Koppula Manjusha, Yadala Pavankumar, Bonthu Bhoomika, Banoth Sariyu
article en

Abstract

This paper introduces a density-based traffic control system aimed at optimizing traffic management at intersections. Utilizing Arduino mega 2560, sensor technology, and an LCD display, the system dynamically adjusts signal timings in response to varying traffic densities. By incorporating infrared sensors for vehicle detection and a sound sensor to prioritize emergency vehicles, the system intelligently allocates green light durations to different roadways, minimizing congestion and ensuring smoother traffic flow. Categorizing traffic into high, moderate, and low-density scenarios enhances the system's adaptability to changing traffic conditions. Overall, this paper offers a practical solution for enhancing road safety, reducing travel times, and improving transportation efficiency in urban environments through intelligent traffic control with visual feedback provided by the LCD display.

National Institute of Technology Andhra Pradesh (IN)
Openalex Percentile: Top 97%
Neural Networks and Applications
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