Digitalization in Sustainable Transportation Operations: A Systematic Review of AI, IoT, and Blockchain Applications for Future Mobility

Despite increasing interest in AI, IoT, and blockchain for sustainable transportation, existing reviews remain fragmented—focusing on single technologies, descriptive benefits, or narrow applications—without providing an integrated synthesis across domains. This study conducts a systematic literature review (SLR) following the PRISMA 2020 guidelines and a bibliometric analysis of 102 peer-reviewed papers to provide the concurrent integrative synthesis of AI, IoT, and blockchain in enabling sustainable transport. Data were drawn from Scopus, Web of Science, PubMed, Semantic Scholar, and Google Scholar, and analyzed using VOSviewer to identify research clusters, emerging themes, and knowledge gaps. The results reveal three thematic clusters: smart traffic systems for congestion management, sustainable logistics and supply chains, and data-driven urban governance. Across these clusters, AI is more mature in predictive modeling, IoT remains fragmented in interoperability, and blockchain is still at a pilot stage with governance and scalability issues. The analysis highlights synergies (e.g., AI–IoT integration for real-time optimization) and persistent challenges (e.g., standardization, data security). This review contributes a strategic research roadmap linking bibliometric hotspots with policy and practice implications. By explicitly identifying gaps in governance, interoperability, and cross-domain integration, the study offers actionable directions for both researchers and policymakers to accelerate digital transitions in transport.