Transportation planning plays a vital role in developing efficient and sustainable transportation systems to meet the evolving needs of communities. As technology advances, the field of transportation planning could benefit from the use of generative artificial intelligence (AI) models (e.g., ChatGPT, Gemini, Copilot, Jasper) to enhance decision-making processes. Generative AI models have the potential to significantly influence transportation planning by generating synthetic data, forecasting future scenarios, and optimizing decision-making. However, fundamental knowledge gaps and other challenges must be addressed before transportation planners can use and apply generative AI models for network- and project-level transportation planning activities. The objective of this project is to develop a primer for using generative AI models in transportation planning. The primer will advance the knowledge and understanding of the use of generative AI models in transportation planning.
Generative AI for Traffic Planning
Summary
Related Publications
- Zhao, Y., Zhao, Y., Du, H. and Yang, H.F., Personalized Decision Modeling: Utility Optimization or Textualized-Symbolic Reasoning. In The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025, Conference Spotlight). https://openreview.net/forum?id=RDt0crdC7N
