Optimizing Urban Mobility: A Comprehensive Study on Intelligent Traffic Signal Control Systems

This paper explores the application of Adaptive Traffic Signal Control (ATSC) systems integrated with Information and Communication Technology (ICT) and the Internet of Things (IoT) to improve urban traffic management. ATSC systems utilize real-time traffic data from various sensors and cameras to adjust signal timings dynamically, aiming to reduce congestion and enhance flow efficiency. The study highlights how these systems process and react to live traffic conditions, discussing the implementation of machine learning models and optimization algorithms that refine signal timing strategies based on traffic density and flow patterns. Challenges like data accuracy, system integration, cybersecurity, and environmental impacts on sensor performance are examined, alongside the potential for improving urban mobility and reducing environmental effects through smarter traffic management solutions. The paper concludes by emphasizing the importance of continuous advancements in technology and infrastructure to support the scalability and effectiveness of ATSC systems in modern cities.