*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Atlanta, GA | Posted: December 14, 2017
Jackie Nemeth
School of Electrical and Computer Engineering
404-894-2906
Summary Sentence:
ECE Assistant Professor Sam Coogan received the IEEE Transactions on Control of Network Systems Best Paper Award at the 56th IEEE Conference on Decision and Control, which took place December 12-15, 2017 in Melbourne, Australia.
Full Summary:
ECE Assistant Professor Sam Coogan received the IEEE Transactions on Control of Network Systems Best Paper Award at the 56th IEEE Conference on Decision and Control, which took place December 12-15, 2017 in Melbourne, Australia.
Sam CooganSam Coogan received the IEEE Transactions on Control of Network Systems Best Paper Award at the 56th IEEE Conference on Decision and Control, which took place December 12-15, 2017 in Melbourne, Australia. He is an assistant professor in the Georgia Tech School of Electrical and Computer Engineering.
Coogan’s coauthors on the paper are Ebru Aydin Gol (Middle East Technical University), Murat Arcak (University of California, Berkeley), and Calin Belta (Boston University). Entitled “Traffic network control from temporal logic specifications,” this paper proposes an approach for controlling a traffic network of signalized intersections to accomplish complex control objectives specified in a formal language known as temporal logic.
Temporal logic allows for specifying precisely and unambiguously the desired behavior of the network and can accommodate goals such as congestion avoidance and fair service of all queues in the network. The paper further identifies and exploits structural properties particular to the dynamics of traffic flow that allow for efficient computation of feedback controllers that can be formally shown to satisfy these objectives.
