Project Grant 2240982
Award Date
6/1/23
Completion Date
5/31/26
Dollars Obligated
$320K
Federal Agency
Division of Civil, Mechanical, and Manufacturing Innovation
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Atlanta, GA 30332, USA
Similar Awards
The Regents of the University of Michigan received a $480,000 project grant from the National Science Foundation under the Engineering federal grant program (CFDA 47.041) to develop foundational advances in robust reinforcement learning solutions and safe, constrained reinforcement learning methods with provable guarantees. The research will focus on advancing algorithmic solutions for reinforcement learning-based control in cyber-physical systems, using smart traffic signal control systems as...
The National Science Foundation (NSF) awarded a $194,000 Project Grant under the Engineering program (CFDA 47.041) to Georgia Tech Research Corp to conduct research on safe reinforcement learning. The project aims to develop new approaches for training, improving, and evaluating reinforcement learning policies that are robust to distribution shift and non-stationarity, with the goal of ensuring safety in applications such as robotics, autonomous driving, and power systems. Key innovations...
This EAGER (Early-Concept Grants for Exploratory Research) project, awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041), will identify gaps in translating traffic control theoretical research into practical traffic controls used in real-world settings. The $300,000 project, running from September 1, 2024 to August 31, 2026, will attempt to discover scientific reasons for the disconnect between academic traffic control research and the legacy theories and models...
This Project Grant award from the National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation, under the Engineering program (CFDA 47.041), will provide $400,329 to the Georgia Tech Research Corporation to explore the application of tools and methods from complexity science to better understand and control urban congestion. The research aims to develop a framework for describing and modeling traffic flow systems, incorporating elements from traffic flow...
The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded a $217,276 project grant to The University of North Carolina at Charlotte to support research titled "COLLABORATIVE RESEARCH: LEARNING-BASED SCALABLE PREDICTIVE CONTROL STRATEGIES FOR HETEROGENEOUS TRAFFIC NETWORKS." The two-year project beginning January 1, 2022 falls under the NSF Engineering Program (CFDA #47.041), which aims to improve quality of life and economic strength through...
This federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $193,000 to the Trustees of Princeton University over a 3-year period starting September 1, 2024. The funding supports collaborative research on developing safe reinforcement learning techniques that can be applied in domains like robotics, autonomous driving, and power systems. The key research thrusts include: 1) training robust policies using distributionally robust approaches;...
This $250,000 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to address challenges in stochastic nonlinear control and learning for dynamical systems through a novel "Spectral Dynamic Embedding" approach. Led by the Georgia Tech Research Corporation, the research intends to develop computationally efficient control algorithms suitable for applications in robotics, aerospace, manufacturing, and beyond. The key innovations involve...
The National Science Foundation awarded a $250,000 Project Grant to the Georgia Tech Research Corporation from October 1, 2022 to September 30, 2025 under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research to develop proactive and reactive adversarial learning techniques for cyber-physical-human systems, with a focus on increasing resilience in autonomous vehicles. Key outcomes include policies to provide robustness against adversarial...
This National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems award, CFDA 47.041 Engineering, will provide $193,000 from September 1, 2024 to August 31, 2027 to New York University (NYU) to develop new theories and methodologies for safe reinforcement learning in domains such as robotics, autonomous driving, and power systems. The key products and services to be delivered under this Project Grant include: 1) Formulating safety measures as general objectives...
The University of California, Berkeley received a $276,684 project grant from the National Science Foundation Division of Electrical, Communications and Cyber Systems to support research titled "COLLABORATIVE RESEARCH: LEARNING-BASED SCALABLE PREDICTIVE CONTROL STRATEGIES FOR HETEROGENEOUS TRAFFIC NETWORKS." The research aims to develop learning-based predictive control strategies for heterogeneous traffic networks and will be conducted from January 1, 2022 to December 31, 2024. The...