University of Texas at Austin


David Fridovich-Keil Wins NSF CAREER to Develop Game Theory Models for Improved Traffic Flow

By Rebecca Riley, Kendra Harris

Published Jan. 31, 2024

David Fridovich-Keil

David Fridovich-Keil, affiliated faculty member at the Oden Institute for Computational Engineering and Science, has been honored with a National Science Foundation (NSF) Faculty Early Career Development Program (CAREER) award for 2024. The NSF CAREER award is among the most prestigious offered to junior faculty, providing up to five years of funding to those who exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of education and research within the context of their organizations' missions.

A researcher in the Oden Institute’s Center for Autonomy, Dr. Fridovich-Keil was awarded for his proposal, “Game Theoretic Models for Robust Cyber-Physical Interactions: Inference and Design under Uncertainty.” 

This proposal is his plan to develop flexible modeling frameworks and efficient algorithms for cyber-physical systems (CPS) – autonomous systems that interact with people, the environment, and other similar systems. Think of your GPS guiding you through city streets – that's a CPS in action. These systems blend computer algorithms with real-world processes, enabling devices to adapt in real-time. From smart homes adjusting to weather changes to self-driving cars navigating traffic, CPS are the invisible wizards behind our interconnected world.

This technology is not, however, infallible. Currently, many of these systems are being designed and analyzed separately from human interaction and the environment. For example, a person might be directed through a quiet neighborhood by a map guidance system, creating traffic congestion in unanticipated or unsafe locations. Or worse, a data-spoofing attack might lead to traffic being rerouted in the wrong direction. 

Over the next five years, David Fridovich-Keil will use the funding allotted to him through his CAREER award to develop new and improved models for CPS.


This graphic represents the performance of Fridovich-Keil's recent game-theoretic objective estimation scheme in a five-care highway driving scenario.

Fridovich-Keil, a game theory expert, aims to improve models like these by studying current traffic systems and identifying their weaknesses due to the limited knowledge of how players, in this case, humans, interact with the CPS. Ultimately, the goal is to develop new and improved models that use long-term strategies by predicting the interactions and behavior of the players, instead of only reacting to a problem after it has arisen.

One example is to develop a tolling system that is designed to work around traffic flow during different times of day, which could help avoid congestion during rush hour.

“We want to model the way people will interact with these systems like they are playing a game,” said Fridovich-Keil. “For example, with tollways, we can set the tolls one way in the morning, and then change them in the early afternoon to preemptively clear the routes we think people are going to take. It’s very similar to planning ahead several moves in the game of chess.”

The overall goal of this research is to answer fundamental questions in dynamic game theory within cyber-physical transportation systems. The algorithms and theoretic models developed by Fridovich-Keil and his team will provide fundamental building blocks for the future development of transportation models and other cyber-physical applications.

More broadly, Fridovich-Keil said that his team’s efforts will provide tools that can be used in urban planning and regulation to help design new and improved transit systems. This can help reduce greenhouse gas emissions, improve road safety and minimize time wasted due to traffic congestion and flight delays.