Abstract

This paper presents a comprehensive survey of the development, methodologies, and applications of Type-2 Fuzzy Logic System (T2FLS) in Intelligent Transportation Systems (ITS) over the period 2012–2025. Rapid improvements in autonomous vehicles, electric mobility, sensor-driven traffic control, and large-scale transportation optimization have increased real-time decision uncertainty. T2FLS models ambiguity based on noisy data, human behavior, environmental volatility, and dynamic system interactions within a principled framework. Drawing on over 50 key studies, this paper demonstrates that T2FLS outperforms Type-1 Fuzzy Logic System (T1FLS) approaches and classical control techniques in traffic signal control, autonomous navigation, anti-lock braking, electric vehicle energy management, driver behavior modeling, and evacuation routing by synthesizing more than 50 key studies. The review also examines methodological trends, constraints, and future research needs, providing a path for next-generation ITS integration of hybrid T2FLS.

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