Adaptive traffic light control system with real-time data collection of urban traffic

Authors

  • Elzabeth Moreira da Silva Fatec de Cotia

Keywords:

Smart Traffic Light, Urban mobility, Data collect, Real-time data science

Abstract

This paper presents an approach for collecting and processing real-time urban traffic data, with the aim of dynamically adjusting traffic light timings based on current traffic conditions. The proposed methodology uses the OpenCV library in a Python environment to capture traffic images, which are processed by a YOLO (You Only Look Once) neural network to extract information, such as the types and number of vehicles passing on the roads. Next, an algorithm was developed to dynamically adjust traffic light times according to real-time traffic conditions. The effectiveness of the system was evaluated through a simulator containing a four-way intersection and through simulations that compared a dynamic traffic light system with a static system. Simulation results demonstrated that the dynamic system reduced the average vehicle waiting time at intersections and increased the number of vehicles crossing the intersection per unit time, highlighting the importance of real-time data science in creating control systems intelligent traffic systems, capable of meeting the demands of a modern and efficient urban infrastructure.

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Published

2025-06-30

How to Cite

MOREIRA DA SILVA, E. Adaptive traffic light control system with real-time data collection of urban traffic. Portugues, [S. l.], v. 7, n. 1, p. 3 - 13, 2025. Disponível em: https://www.fateccampinas.com.br/rbti/index.php/fatec/article/view/150. Acesso em: 16 aug. 2025.

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Section

Artigos