Join us for a compelling speaker series featuring distinguished researchers from the University of Minnesota, who will present cutting-edge work spanning shared autonomous vehicles, generative AI applications, traffic flow modeling, transit trends, and accessibility-driven solutions. Their talks explore how data, intelligent systems, and new technologies are reshaping the future of transportation—both in urban and rural contexts.
Talk 1: Modeling and Control of Mixed-Autonomy Traffic Flow | Speaker: Dr. Raphael Stern
Dr. Stern investigates how partially and fully automated vehicles affect traffic flow and interact with human drivers. His work focuses on how automation features like adaptive cruise control can be used to improve system-wide traffic behavior and stability.
Talk 2: Maximum-throughput Dispatch of Shared Automated Vehicles | Speaker: Dr. Michael Levin
As shared autonomous vehicles begin to serve public mobility needs, a key challenge is how to optimally assign vehicles to waiting passengers. Dr. Levin introduces a novel Markov decision process formulation that accounts for uncertainty in future demand, and derives policies with provable performance guarantees.
Talk 3: Generative AI for Transportation Operations and Management | Speaker: Dr. Seongjin Choi
Dr. Choi explores how Generative AI models can learn from transportation data to simulate pedestrian and vehicle movement and generate demand patterns. He highlights the use of large language and vision-language models as planning and control modules for traffic systems and autonomous vehicles.
Talk 4: Transit Gaps, Ridership Trends, and Opportunities for Technological Solutions | Speaker: Dr. Alireza Khani
Dr. Khani presents an analysis of transit ridership trends in the wake of COVID-19 and explores emerging technologies like AMoD, MaaS, and freight-on-bus systems. He discusses how these solutions could address evolving service needs and support accessible, resilient transit networks.
