Project Grant 2106965
Award Date
10/1/21
Completion Date
9/30/24
Dollars Obligated
$200K
Federal Agency
Office of Advanced Cyberinfrastructure
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
San Diego, CA 92182, USA
Similar Awards
The University of Maryland, College Park will receive $296,575 from the National Science Foundation Office of Advanced Cyberinfrastructure through September 2024 to develop a stochastic simulation platform under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The platform aims to examine the efficiency, reliability, and safety of autonomous vehicles in winter conditions through dynamic modeling of vehicle behavior and prediction of potential safety...
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 $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 $572,778 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award will support research and development at North Carolina State University (NC State) to address fundamental challenges in simulation-based testing of autonomous driving systems (ADS). The key objectives are to: 1) Improve the efficiency and effectiveness of simulation-based ADS testing by leveraging...
This $260,118 federal Project Grant was awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The project aims to advance the state-of-the-art in cyber-physical systems (CPS) research related to autonomous vehicle integration and highway safety. Specifically, the research team will develop new methods and tools to enable safe and harmonious coordination among highway vehicles with heterogeneous levels of human and...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $193,000 to San Diego State University Foundation to develop predictive models and software capabilities to enhance the resilience and reliability of autonomous cyber-physical systems (A-CPS) such as self-driving vehicles, environmental monitoring drones, and search-and-rescue robots. The project aims to enable these systems to better navigate challenging...
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...
The National Science Foundation (NSF) awarded a $109,992 Project Grant under its Computer and Information Science and Engineering (CFDA 47.070) program to the University of Texas at Dallas (UTD). This 2-year grant, effective July 1, 2024, focuses on enhancing the safety and reliability of autonomous driving systems. Key objectives include: Developing advanced detection and countermeasure techniques at the application, system, and hardware layers to ensure self-driving cars can make safe...
This $199,822 National Science Foundation project grant, awarded under the Integrative Activities program, will fund research at West Virginia University and Stanford University to develop algorithms for safety validation of autonomous systems. The goal is to build trust in AI-enabled complex systems for safety-critical applications by leveraging information from multiple sources. The researchers will develop tools using data-driven optimization and reinforcement learning algorithms to...
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...