Project Grant 2527305
Award Date 1/1/26
Completion Date 12/31/28
Dollars Obligated $600K
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
Troy, NY, USA
Similar Awards
- This EAGER: Quantum Algorithmic Foundations for Reliable Transportation Networks project is a $299,986 award from the National Science Foundation's Engineering program (CFDA 47.041). The project, awarded to the University of Connecticut, will explore the use of quantum computing to improve the reliability of transportation networks. Specifically, the research will develop quantum simulation and optimization algorithms to model stochastic transportation networks and solve reliability-based...
- 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 $249,358 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research by Amherst College on non-local microscopic and macroscopic traffic flow models. The investigator will construct and analyze multi-scale non-local mathematical models to more accurately capture driver behavior by integrating downstream information, compared to traditional local traffic flow models. The project aims to perform mathematical...
- 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...
- This National Science Foundation Project Grant award of $538,633 supports fundamental research in modeling stochastic traffic flows for smart mobility systems through February 2026. Funded under the Engineering program (CFDA 47.041), the award to the University of Maryland, College Park aims to develop machine learning and traffic flow theory to better estimate and predict mobility patterns. The grantee will fuse classical transportation models with learning techniques using transportation...
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research at Vanderbilt University to develop deep learning-based methodologies for modeling traffic dynamics, particularly with the inclusion of connected and automated vehicles (CAVs). The $149,998 project aims to transform the field by transitioning from conventional traffic studies to an automated, data-driven paradigm for discovering the governing equations of traffic flow. Key...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded a $212,099 Project Grant to the Illinois Institute of Technology from January 1, 2022 to December 31, 2024. The grant supports collaborative research on learning-based scalable predictive control strategies for heterogeneous traffic networks under the NSF Engineering program (CFDA 47.041). The research aims to develop scalable predictive control methods to optimize traffic flow across diverse...
- This National Science Foundation (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) project grant award of $550,000, effective March 1, 2024 through February 28, 2026, aims to develop vehicle technologies that can improve traffic flow and reduce energy use by allowing automated vehicles to dynamically adjust their speeds based on real-time traffic conditions. The project will create a system to automatically detect and filter out erroneous traffic information to enable the safe...
- This National Science Foundation (NSF) Project Grant award of $199,637.00 to the Rochester Institute of Technology (RIT), under the NSF Directorate for Engineering (CFDA 47.041) program, aims to enhance the robustness and efficiency of quantum computing hardware and applications. The key objectives are to: 1) Apply machine learning techniques to extract useful information from the noisy output of quantum computers, enabling their practical use despite hardware limitations, and 2) Identify...
- This $550,000 federal Project Grant, awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041), supports research at Lehigh University to develop and analyze quantum optimization techniques for solving structured optimization problems in process systems engineering. The project aims to explore how novel quantum computing methodologies can be leveraged to outperform classical computers in solving complex decision-making problems in areas such as supply chain management,...