A systematic review of inclusive intelligent transportation systems in smart cities

Abstract

Ensuring equitable mobility for individuals with disabilities remains a critical yet under-addressed challenge in Intelligent Transportation Systems (ITS) and smart-city development. While prior ITS reviews have explored technological advancements and, in some cases, interdisciplinary perspectives, limited attention has been given to a comprehensive, accessibility-driven synthesis that integrates artificial intelligence (AI), policy frameworks, ethical considerations, datasets, and real-world deployment challenges. This study presents a systematic review of 2253 studies published between 2021 and 2026, providing a structured, multidimensional analysis of disability-inclusive ITS research. Unlike existing surveys, this work combines rigorous PRISMA-based systematic review methodology with advanced bibliometric analysis to uncover not only research trends but also structural gaps, interdisciplinary disconnects, and limitations in current ITS development. The findings reveal a strong concentration on general accessibility frameworks (66.0%), with significantly lower attention to disability-specific solutions—particularly for cognitive (10.2%) and mobility impairments (5.5%). Although AI and deep learning are increasingly adopted, most proposed systems remain simulation-based, with limited real-world validation, user-centered evaluation, and scalability. The analysis further highlights critical shortcomings, including the lack of accessibility-aware datasets, the absence of standardized evaluation metrics, insufficient policy integration, and the underrepresentation of developing regions. Ethical challenges, including algorithmic bias, data privacy, and transparency, are also inadequately addressed in current ITS implementations. To address these limitations, this review advances a unified framework that integrates technological, human-centered, and policy-driven perspectives for inclusive ITS design. It synthesizes insights across transportation engineering, healthcare, urban planning, and AI to propose actionable directions for developing adaptive, explainable, and accessibility-aware mobility systems. The study also identifies key performance indicators (KPIs) and emphasizes the importance of interdisciplinary collaboration, inclusive field validation, and ethical AI governance. By bridging the gap between technological innovation and real-world accessibility needs, this work provides a comprehensive foundation for future research. It supports the development of scalable, inclusive, and sustainable transportation systems that ensure equitable mobility for all.