Project Grant 2227185
- This National Science Foundation Project Grant of $2,090,572 will fund research at Georgia Tech Research Corporation from June 2022 to May 2025 to develop next-generation advanced driver assistance systems. The research aims to increase safety and performance of deep neural networks operating within feedback loops that include human drivers. Specifically, the grant will support research to utilize reinforcement learning and formal methods techniques to design systems that can accommodate...
- This $500,000 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will support research at The Ohio State University to develop situational awareness strategies for autonomous cyber-physical systems operating in dynamic, uncertain environments. The objectives of the six-month project beginning October 1, 2022 are to analyze environmental observability for multiple autonomous agents, develop on-the-fly adaptation strategies to refine...
- This $799,803 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a new framework named CRASH (Challenging Reinforcement-Learning Based Adversarial Scenarios for Safety Hardening) to effectively stress test and improve the safety of autonomous vehicle software. The framework leverages multi-agent adversarial deep reinforcement learning to automatically generate realistic and challenging...
- Federal Grant Award Summary Georgia Tech Research Corporation received a $691,375 Project Grant from the National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation under the Engineering program (CFDA 47.041), effective September 1, 2025 through August 31, 2028. This award supports fundamental research and development of defensive countermeasures against affine transformation-based false data injection attacks targeting networked robotic systems. The primary...
- Federal Grant Award Summary The National Science Foundation (NSF), Division of Computer and Network Systems, awarded $659,317 to the University of Florida (Award Date: June 1, 2026; Completion Date: May 31, 2031) under the Computer and Information Science and Engineering program (CFDA 47.070) to develop assured reinforcement learning methods for cyber-physical systems. The project will deliver foundational research and open-source algorithmic tools enabling autonomous systems—such as...
- This $120,000 Project Grant was awarded on July 1, 2024 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the Regents of the University of California at Riverside (UC Riverside). The funding will support a collaborative research project focused on enhancing the safety and reliability of autonomous driving systems through the development of advanced detection and countermeasure techniques at the application, system, and...
- This $500,000 project grant, awarded on January 1, 2024 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to address the urgent need for end-to-end safety in learning-enabled autonomous systems across various application scenarios, such as self-driving cars and urban air mobility. The project, titled "COLLABORATIVE RESEARCH: SLES: GUARANTEED TUBES FOR SAFE LEARNING ACROSS AUTONOMY ARCHITECTURES,"...
- This $298,747 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program will support collaborative research between the University of California, Irvine (UCI) and the Indian Institutes of Technology (IIT) in Kharagpur and Jodhpur. The project aims to investigate the security and robustness of Collaborative Autonomous Driving (COAD) systems, which consist of connected and autonomous vehicles (CAVs) and...
- This $175,000 Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will fund research at Texas Tech University from April 2022 to March 2024 related to developing novel modeling, control, and optimization methods for connected and automated vehicles. The research aims to improve the efficiency and sustainability of urban transportation systems while respecting individual...
- This $1,499,949 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to enhance the safety of autonomous vehicle (AV) systems. The key focus areas include: Developing rational machine learning (ML) models that can accurately predict driving decisions based on valid rationales, rather than inappropriate extrapolations from common scenarios. Integrating hardware reliability into the...
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 inputs and reward drops in reinforcement learning mechanisms. The research aims to limit exposure to vulnerable actions and observations while increasing the cost of deception. It will also develop stability, optimality, and robustness guarantees. Outcomes seek to increase confidence in autonomous technologies by curtailing accidents and apply to other smart systems domains. The grant will additionally train students through research and educational activities to appreciate efficient and autonomous low-cost designs.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 7/12/22 |