As AI is increasingly used in transportation, it is important to understand how transportation professionals, the driving force behind AI Transportation applications, perceive AI’s potential efficiency and equity impacts. We surveyed 354 transportation professionals in the United States and conducted descriptive analysis and latent class cluster analysis based on the collected data.
Key words: AI, transportation, equity, latent class cluster analysis
Qian, Y., Polimetla, T., Sanchez, T., Yan, X. (2024). How do transportation professionals perceive the impacts of AI applications in transportation? A latent class cluster analysis.. Download Preprint.