Artificial Intelligence in Multimodal Transport: A Bibliometric Review

ABSTRACT

This study reviews the rapidly growing use of artificial intelligence (AI) in multimodal transportation. It analyses 226 publications indexed in the Web of Science Core Collection (SCI‐E/SSCI) and Scopus from 2001 to 2025 using bibliometric methods. Annual publication trends indicate a sharp rise in research activity in recent years, showing increasing scholarly attention to the convergence of AI and multimodal transport. The study further examines productive and influential journals, countries, institutions and authors and maps their collaboration networks to reveal the field's knowledge structure and cooperative patterns. In addition, keyword co‐occurrence analysis is conducted to identify major research clusters, emerging topics and likely future directions. The results highlight logistics optimisation as a central and fast‐developing theme, providing strong evidence that AI‐enabled approaches can enhance the efficiency, reliability and sustainability of multimodal transportation systems. To better grasp the direction of the research and support the in‐depth growth of this subject, this review offers scholars a comprehensive viewpoint on the state of the art and future prospects of AI use in multimodal transportation.