This research explores how Large Language Models can transform transportation systems by leveraging their knowledge and reasoning capabilities beyond simple text generation.

• Positions LLMs as versatile task solvers for addressing complex transportation challenges
• Identifies applications in traffic prediction, system modeling, and infrastructure optimization
• Examines how LLMs can integrate heterogeneous transportation data for improved decision-making
• Outlines a roadmap for future LLM implementation in intelligent transportation systems

For engineering teams, this research provides a structured framework to harness LLM capabilities in developing next-generation transportation solutions that can adapt to increasing demand and dynamic environments.

Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and Roadmap