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A Comprehensive Review on Type-2 Fuzzy Logic in Intelligent Transportation Systems

by Gaurav Kemwal, Sunil Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 75
Year of Publication: 2026
Authors: Gaurav Kemwal, Sunil Kumar
10.5120/ijca2026926287

Gaurav Kemwal, Sunil Kumar . A Comprehensive Review on Type-2 Fuzzy Logic in Intelligent Transportation Systems. International Journal of Computer Applications. 187, 75 ( Jan 2026), 23-33. DOI=10.5120/ijca2026926287

@article{ 10.5120/ijca2026926287,
author = { Gaurav Kemwal, Sunil Kumar },
title = { A Comprehensive Review on Type-2 Fuzzy Logic in Intelligent Transportation Systems },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2026 },
volume = { 187 },
number = { 75 },
month = { Jan },
year = { 2026 },
issn = { 0975-8887 },
pages = { 23-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number75/a-comprehensive-review-on-type-2-fuzzy-logic-in-intelligent-transportation-systems/ },
doi = { 10.5120/ijca2026926287 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-01-20T22:56:31.151271+05:30
%A Gaurav Kemwal
%A Sunil Kumar
%T A Comprehensive Review on Type-2 Fuzzy Logic in Intelligent Transportation Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 75
%P 23-33
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
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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Index Terms

Computer Science
Information Sciences

Keywords

Type-2 fuzzy logic Interval Type-2 fuzzy sets Intelligent transportation system Uncertainty handling Adaptive control Sustainable mobility

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