Emilio Frazzoli

Emilio Frazzoli
Prof. Dr.
Emilio Frazzoli
PI

Emilio Frazzoli is a Professor of Aeronautics and Astronautics with the Laboratory for Information and Decision Systems, and the Operations Research Center at the Massachusetts Institute of Technology. He received a Laurea degree in Aerospace Engineering from the University of Rome, “Sapienza” , Italy, in 1994, and a Ph. D. degree from the Department of Aeronautics and Astronautics of the Massachusetts Institute of Technology, in 2001. Before returning to MIT in 2006, he held faculty positions at the University of Illinois, Urbana-Champaign, and at the University of California, Los Angeles. He is currently the Director of the Transportation@MIT initiative, and the Lead Principal Investigator of the Future Urban Mobility IRG of the Singapore-MIT Alliance for Research and Technology (SMART). He was the recipient of the IEEE George S. Axelby award in 2015, and a NSF CAREER award in 2002. He is an Associate Fellow of the American Institute of Aeronautics and Astronautics and a Senior Member of the Institute for Electrical and Electronics Engineers.

Dr. Frazzoli's current research interests focus primarily on autonomous vehicles, mobile robotics, and transportation systems, and in general lie in the area of planning and control for mobile cyber-physical systems.

Scientific Publications

Published
How Bad is Selfish Driving? Bounding the Inefficiency of Equilibria in Urban Driving Games
IEEE Robotics and Automation Letters
Vol 8 No 4 Pages 2293
Published
Enhancing Efficiency and Reliability of Electric Vehicles via Adaptive E-Gear Control
(ITCS) IEEE 26th International Conference on Intelligent Transportation Systems
Published
A Self-Contained Karma Economy for the Dynamic Allocation of Common Resources
Dynamic Games and Applications
Published
Factorization of Multi-Agent Sampling-Based Motion Planning
62nd IEEE Conference on Decision and Control
Published
Factorization of Dynamic Games over Spatio-Temporal Resources
35th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)
Pages 13159 - 13166
Published
Task-driven modular co-design of vehicle control systems
2022 IEEE 61st Conference on Decision and Control (CDC)
Published
Co-Design to Enable User-Friendly Tools to Assess the Impact of Future Mobility Solutions
IEEE Transactions on Network Science and Engineering
Pages 1-18
Published
Categorification of Negative Information using Enrichment
5th Annual International Applied Category Theory Conference (ACT 2022)
Published
Analysis and Control of Autonomous Mobility-on-Demand Systems
Annual Review of Control, Robotics, and Autonomous Systems
Vol 5 Pages 633-658
Published
Posetal Games: Efficiency, Existence, and Refinement of Equilibria in Games With Prioritized Metrics
IEEE Robotics and Automation Letters
Vol 7 No 2 Pages 1292-1299
Published
Game Theory to Study Interactions between Mobility Stakeholders
24th IEEE International Conference on Intelligent Transportation Systems (ITSC)
Pages 2054-2061
Urban Driving Games With Lexicographic Preferences and Socially Efficient Nash Equilibria
IEEE Robotics and Automation Letters
Vol 6 No 3 Pages 4978 – 4985
Co-Design of Autonomous Systems: From Hardware Selection to Control Synthesis
IEEE European Control Conference
Game Theoretical Motion Planning - Tutorial session
IEEE International Conference on Robotics and Automation (ICRA)
Published
Co-design of embodied intelligence: A structured approach
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Pages 7536-7543

Research projects

Title
Principal Investigators

Dynamic population games for efficient autonomous mobility

Summary

We will demonstrate that multiple competitive agents can efficiently share a mobility infrastructure without the need for an external coordinator. Standard game-theoretic approaches to this problem fall short in case of dynamic systems as encountered in autonomous mobility, coordinated use of the mobility space, traffic congestion control, etc.  We will develop a new mathematical formalism and computational methods blending the concept of game-theoretic and dynamic equilibria. Autonomous mobility is an important application due to the importance of fairness and efficiency in resource use, the large number of interacting agents, and the need for automated and scalable solutions.

Dynamic population games for efficient autonomous mobility

We will demonstrate that multiple competitive agents can efficiently share a mobility infrastructure without the need for an external coordinator. Standard game-theoretic approaches to this problem fall short in case of dynamic systems as encountered in autonomous mobility, coordinated use of the mobility space, traffic congestion control, etc.  We will develop a new mathematical formalism and computational methods blending the concept of game-theoretic and dynamic equilibria. Autonomous mobility is an important application due to the importance of fairness and efficiency in resource use, the large number of interacting agents, and the need for automated and scalable solutions.

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