Project Grant 2132060
Award Date
2/1/22
Completion Date
1/31/24
Dollars Obligated
$200K
Federal Agency
Office of Integrative Activities
Federal Grant Program
47.083
Assistance Type
Project Grant
Place of Performance
Stanford, CA 94305, USA
Similar Awards
This $316,963 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support research to enhance the safety and reliability of autonomous vehicles. The project aims to thoroughly examine and improve the controller and machine learning components of autonomous driving systems through a combination of model-based and data-driven approaches. The research will focus on identifying spatial and temporal vulnerabilities that...
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 $272,238 Project Grant, awarded on July 15, 2024 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to enhance the safety and reliability of autonomous vehicles. The project aims to identify vulnerabilities in the software and machine learning components of autonomous vehicle systems, and develop mitigation techniques to improve their overall resilience. The research will combine model-based and...
This five-year National Science Foundation Project Grant of $1,238,246 will fund research at Carnegie Mellon University toward developing safe autonomous systems. The goal is to enable robots and other autonomous systems to operate safely while interacting closely with humans, as required for applications like next-generation manufacturing infrastructure. The university will develop a new algorithmic framework for assuring safety in autonomous robotic systems. The framework aims to optimize...
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...
This $270,913 federal Project Grant award, funded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program, supports research to develop qualitative and quantitative methodologies for assessing the safety of learning-enabled autonomous systems. The project, led by the Augusta University Research Institute, Inc. (AURI), will target foundational challenges in capturing uncertainties from environments and providing timely, comprehensive, and...
This $235,187 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports research to develop principled algorithms and practical tools for systematically discovering and repairing unsafe behavior in multi-module autonomous vehicle systems. The key objectives are to: (1) create an automated method for constructing test scenarios that decouple high-level semantics and low-level details; (2) develop a search-based testing approach to efficiently...
This $350,961 National Science Foundation project grant supports the development of algorithms and design principles to enable safe and secure collaboration between artificial intelligence systems and human operators in autonomous vehicles. Funded under the Computer and Information Science and Engineering program, the objectives are to maintain human vigilance through secondary in-vehicle tasks calibrated to AI decision uncertainty levels, develop a fault-tolerant AI capable of assessing its own...
This federal Project Grant award of $800,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) is supporting research to develop methods for certifying the safety of autonomous systems that use deep learning-enabled perception, prediction, and control components. The key goals of the project are: (1) to develop techniques for learning safety certificates and control policies for these types of learning-enabled autonomous...
This $425,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop a framework for ensuring the safety of future robotic systems. The research project, led by The Trustees of Princeton University, aims to lay the foundation for safe robot autonomy by enabling robots to continually prove the safety of their actions under a wide range of operating conditions, from complex physical...