This 90-minute webinar introduces agentic Artificial Intelligence (AI) and explores its potential applications in transportation.

Agents are expanding what AI can do by performing multi-step tasks and interacting with external systems. These capabilities create new opportunities for transportation professionals to apply AI to complex planning, data, and modeling challenges.

Hosted by the Transportation Research Board (TRB), presenters will share a framework for agentic transportation systems and demonstrate applications for personalized trip planning, data augmentation, and travel behavior modeling.

Learning Objectives:

• Explain the key characteristics of agentic AI and how it differs from other AI applications
• Identify potential applications of agentic AI in transportation

Presenters:

• Jiangbo Yu, McGill University
• Alaa Khamis, King Fahd University of Petroleum & Minerals
• Tianming Liu, University of Michigan
• Paul Anderson, Texas A&M Transportation Institute (Moderator)
  
  

Complimentary registration is available for employees of TRB sponsors, standing technical committee chairs, involved CRP panel members, tribal government employees, media, congressional staff, & TRB or National Academies staff.

Register to Attend