Smart Traffic Signal Control System Based on Fuzzy Logic Control
Keywords:
Adaptive traffic management, Fuzzy logic controller, Intelligent transportation system, Traffic signal controlAbstract
Traffic congestion at urban intersections is rapidly increasing due to the continuous growth in vehicle population and urbanization, creating serious challenges for existing traffic management systems. Conventional traffic signal controllers generally operate on fixed-time cycles that do not consider real-time traffic conditions, resulting in inefficient traffic flow, increased vehicle waiting time, unnecessary fuel consumption, and higher environmental pollution. To address these limitations, this study proposes a fuzzy-logic-based adaptive traffic signal control system that dynamically adjusts signal timing based on multiple traffic parameters, including queue length, time of day, night traffic conditions, and the presence of emergency vehicles. The system also integrates a no-vehicle detection mechanism, which monitors vehicle activity at an intersection and automatically switches the signal after 10 seconds of inactivity, thereby eliminating unnecessary red-light waiting when no vehicles are present. A fuzzy inference system (FIS) is designed and simulated using the MATLAB Fuzzy Logic Toolbox to model human-like decision-making for signal control under uncertain and varying traffic conditions. The proposed system enhances flexibility, responsiveness, and efficiency compared to traditional fixed-time approaches. Simulation results demonstrate a significant improvement in traffic flow efficiency, reduction in average waiting time, and better utilization of intersection capacity, making the system suitable for implementation in intelligent transportation systems and smart city environments.
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