Large Language Model Technologies in Transportation: A Systematic Literature Review and Bibliometric Analysis
Paper in proceeding, 2025

In recent years, large language models (LLMs) have been extensively utilized in the transportation sector, resulting in substantial progress. This study conducts a systematic literature review and extensive bibliometric analysis of LLM applications in transportation to clarify their practical impact. We systematically examine the historical development and background of LLM technologies, characterize their transportation-specific applications, reveal implementation strategies and outcomes, and highlight prevalent challenges. Furthermore, the bibliometric study delineates publishing trends, important authors, and extensively cited publications. These findings are utilized to map the evolutionary path of LLMs in transportation, providing both academics and practitioners with a refined comprehension of contemporary trends and prospective applications in the domain.

Bibliometric analysis

Transportation

Systematic literature review Introduction

Large Language Models

Author

Yongzhi Liu

Wuhan University of Technology

Da Wu

Wuhan University of Technology

Feng Ma

Wuhan University of Technology

Wengang Mao

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

8th International Conference on Transportation Information and Safety Transportation Artificial Intelligence and Green Energy Making A Sustainable World Ictis 2025

330-336
9798331592486 (ISBN)

8th International Conference on Transportation Information and Safety, ICTIS 2025
Granada, Spain,

Subject Categories (SSIF 2025)

Information Systems, Social aspects

Other Social Sciences not elsewhere specified

DOI

10.1109/ICTIS68762.2025.11214874

More information

Latest update

12/1/2025