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 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 National Science Foundation (NSF) Engineering program (CFDA 47.041) $518,552 project grant award to the Regents of the University of Minnesota will fund research to leverage artificial intelligence (AI) to improve the efficiency of transportation control infrastructure. The key objectives are to: (i) develop methods to rapidly identify individual vehicle driving signatures from low-rank characterizations of time-series driving data, (ii) create an AI-guided modeling framework that uses...
The Massachusetts Institute of Technology (MIT) received a $800,000 Project Grant from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant will support the development of an online learning framework to optimize transportation systems as emerging mobility options like connected and automated vehicles alter travel demand and efficiency. Specifically, MIT...
Georgia Tech Research Corporation was awarded a $320,000 project grant from the National Science Foundation to develop data-driven robustness and safety methods for reinforcement learning algorithms applied to traffic signal control systems. Under the grant, researchers will advance foundational methodologies to enable safe and robust reinforcement learning-based solutions for smart transportation systems. The technical work includes developing robust reinforcement learning solutions...
This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports research by the Massachusetts Institute of Technology (MIT) to accelerate the design of controllers for large-scale engineering systems, focusing on transportation applications. The $400,000 award, made on February 1, 2025, aims to utilize extensive offline datasets and offline reinforcement learning to develop efficient and adaptive control systems, such as improved cruise control for...
This $547,447 National Science Foundation project grant supports research at Northwestern University toward developing an integrative machine learning approach for traffic management. The three-year award, issued on September 1, 2022 under the Engineering program (CFDA 47.041), will create and test hybrid machine learning methods tailored for transportation domain problems involving hierarchical optimization of ridesharing and traffic flows. The grantee will introduce a novel framework combining...
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 of $600,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support a collaborative research project at Vanderbilt University to accelerate the design of controllers for large-scale transportation systems using offline reinforcement learning. The key objectives of the project are to bridge the gap between simulated cyber environments and real-world physical operations, enhance safety,...
The University of Illinois was awarded a $392,408 project grant from the National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation to develop switching control techniques with minimal data from August 1, 2021 to July 31, 2024. The grant is part of NSF's Engineering program (CFDA 47.041), which seeks to improve quality of life and economic strength through engineering research and education. Specifically, the University will research switching control methods that...