Abstract:

Urban traffic congestion has become a critical issue worldwide, impacting commuter time, fuel consumption, and road safety. Traditional traffic signal control methods are often rigid, leading to inefficiencies and delays during peak hours. This study explores the design and implementation of intelligent traffic signal control systems (ITSCS) that optimize traffic flow while enhancing road safety. By integrating real-time traffic data with adaptive signal timing algorithms, the system can dynamically adjust signal phases based on vehicle density, queue length, and pedestrian movement. A mixed-methods approach was adopted, combining simulation modeling, field data collection, and performance evaluation across multiple intersections in Chennai, India. The results indicate a significant reduction in average waiting time, improved vehicle throughput, and a decrease in accident probability. The study proposes a scalable framework for urban traffic management that can be adopted by municipalities to improve efficiency and sustainability in urban transport systems.
Keywords: Keywords: Intelligent Traffic System, Traffic Signal Optimization, Urban Congestion, Adaptive Signal Control, Road Safety, Traffic Simulation