Machine Learning Seminar
Impacts of automated vehicles: a traffic flow perspective
Department of Civil, Environmental, and Geo- Engineering
University of Minnesota
Wednesday, November 4, 2020
Online via zoom View recording here
This work is motivated by the possibility of a small number of automated vehicles (AVs) or partially automated vehicles that may soon be present on our roadways, and the impacts they will have on traffic flow. This automation may take the form of fully autonomous vehicles without human intervention (SAE Level 5) or, as is already the case in many modern vehicles, may take the form of driver assist features such as adaptive cruise control (ACC) or other SAE Level 1 features. Regardless of the extent of automation, the introduction of such vehicles has the potential to substantially alter emergent properties of the flow while also providing new opportunities for traffic state estimation. In this talk, I present some recent experimental and modeling work conducted to understand how AVs may be able to influence traffic flow.
Raphael Stern is an Assistant Professor in the Department of Civil, Environmental, and Geo- Engineering at the University of Minnesota. Prior to joining UMN, Dr. Stern was a postdoctoral researcher in the Department of Informatics at the Technical University of Munich. Dr. Stern has also spent time as a visiting researcher at the Institute for Software Integrated Systems at Vanderbilt University. Dr. Stern received a bachelor of science degree (2013), master of science degree (2015), and Ph.D. (2018) all in Civil Engineering from the University of Illinois at Urbana-Champaign. Dr. Stern was a visiting researcher at the Institute for Pure and Applied Mathematics at UCLA, and a recipient of the Dwight David Eisenhower Graduate Fellowship from the Federal Highway Administration. Dr. Stern's research interests are in the area of traffic control and estimation with autonomous vehicles in the flow.