Intelligent Traffic Signal Control Network for Optimizing Traffic Flow

Abstract

The increasing use of vehicles, combined with advancements in sensor technology and data analytics, presents new opportunities to enhance the efficiency and safety of transportation systems. This paper proposes a framework for implementing intelligent traffic signal control networks that leverage real-time data from vehicle-to-infrastructure (V2I) communications and adaptive algorithms to dynamically optimize traffic signal timing, particularly at four-way intersection, which consist of a main road and a secondary road. By integrating vehicle position and speed, the system can adjust signal phases and timings in response to real-time conditions, thereby reducing congestion, idling, and intersection-related collisions. The simulation will explore the core components of smart traffic signal control architecture, including sensor integration, data analysis, and adaptive algorithms. Results from simulation studies demonstrate improvements in traffic flow, reduced emissions, and enhanced safety. This highlights the importance of smart traffic management technologies in building safer and more sustainable urban environments.