Topical Collection on "Large Language Models for Intelligent Transportation Systems"

A topical collection of Digital Technologies Research and Applications (DTRA) (E-ISSN: 2754-5687).
Deadline for manuscript submissions: 15th July 2026

Collection Editor: 

Dr. Hazrat Bilal
CAIR - Center for Artificial Intelligence Research, Department of ICT, University of Agder (UiA), Jon Lilletuns vei 9, 4879 Grimstad, Norway
E-mail: hbilal@mail.ustc.edu.cn

Inam Ullah
Department of Computer Engineering, Gachon University, Seongnam 13120, Republic of Korea
E-mail: inam@gachon.ac.kr

Muhammad Shamrooz Aslam
School of Computer Science and Technology/School of Artificial Intelligence;China University of Mining and Technology, 221116, Xuzhou, China.
E-mail: shamroz_aslam@cumt.edu.cn

Topical Collection Information:

Dear Colleagues,

Theme and Scope
Intelligent Transportation Systems (ITS) are at the core of next-generation smart cities, autonomous mobility, and sustainable transportation. With the rapid evolution of Large Language Models (LLMs) and foundation models, a new paradigm is emerging where transportation systems can reason, interact, learn, and adapt at an unprecedented level of intelligence.

LLMs enable semantic understanding, multi-modal perception, decision-making, and human-centric interaction across transportation infrastructures, connected vehicles, traffic management systems, and autonomous driving platforms. By integrating LLMs with vehicular networks, edge/cloud computing, sensor fusion, and cyber-physical transportation systems, ITS can move beyond traditional rule-based and shallow learning approaches toward truly cognitive and cooperative transportation intelligence.

Despite their promise, deploying LLMs in ITS introduces significant challenges, including real-time constraints, safety and reliability, explainability, robustness, privacy, energy efficiency, and domain adaptation. This Special Issue aims to bring together cutting-edge research that explores theoretical foundations, system architectures, and real-world applications of LLMs in Intelligent Transportation Systems.

Topics of Interest
Topics of interest include, but are not limited to:

• LLM-enabled perception, reasoning, and decision-making in ITS
• Multi-modal LLMs for traffic sensing, prediction, and control
• LLMs for autonomous driving and cooperative vehicle intelligence
• Natural language interaction between humans and transportation systems
• LLM-assisted traffic management and optimization
• Integration of LLMs with V2X, vehicular networks, and IoT
• Edge and cloud deployment of LLMs for real-time ITS applications
• LLM-driven digital twins for transportation systems
• Safety, reliability, and robustness of LLM-based ITS
• Explainable and trustworthy LLMs for transportation decision-making
• Privacy-preserving and secure LLM frameworks in ITS
• Energy-efficient and lightweight LLMs for vehicular and edge platforms
• LLMs for incident detection, fault diagnosis, and anomaly prediction
• Federated and collaborative learning with LLMs in ITS

Dr. Hazrat Bilal
Inam Ullah
Muhammad Shamrooz Aslam
Collection Editor

Keywords:

• Large Language Models (LLMs)
• Intelligent Transportation Systems (ITS)
• Autonomous Driving
• Traffic Management
• Edge Computing

Manuscript Submission Information:

Please visit the Submissions Guidelines page before submitting a manuscript. Submitted papers should be well formatted and use good English. Manuscripts should be submitted online through the online manuscript submission and editorial system. Additionally, please include a cover letter specifying that the manuscript is intended for the Topical Collection "Large Language Models for Intelligent Transportation Systems" when submitting it online. Manuscripts can be submitted until the submission deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the Topical Collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract can be sent to the Editor Mary Liu mary@ukscip.com for announcement on this website.

The Article Processing Charge (APC) for publication in this open access journal is 1800 USD. Authors who are unable to cover this cost or those who are invited to submit papers may be eligible for discounts or waivers.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process.

Published Papers:

This Topical Collection is now open for submission.