Application of Type-2 Fuzzy Logic to Signal Timing Control at Signalized Intersections: Addressing Traffic Data Uncertainty

Abstract

Urban intersections are increasingly congested as motorized vehicle volumes continue to rise, while fixed-time signal control often fails to respond to dynamic traffic conditions. This review examines the use of Type-2 Fuzzy Logic (FL-T2) for adaptive signal timing control under traffic uncertainty and its relevance to Indonesian urban intersections. A systematic literature review was conducted on recent studies published between 2021 and 2025. The reviewed studies show that FL-T2 is generally built on fuzzification, rule-base formulation, inference, and defuzzification, with uncertainty represented through the Footprint of Uncertainty. The synthesis indicates that FL-T2 performs better than fixed-time control and Type-1 fuzzy logic in reducing delay, queue length, and saturation level, especially under fluctuating traffic conditions. Hybrid FL-T2 models with optimization algorithms also show stronger performance in simulation studies. However, practical implementation in Indonesia still depends on detector availability, data quality, computational feasibility, and institutional readiness. FL-T2 is therefore a promising adaptive control framework, but further local simulation and pilot testing are needed before field deployment.