Project Grant 2313351
- 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 $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 $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 $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 $199,992 National Science Foundation Engineering Research Initiation project grant to Texas A&M University-Commerce will support research and education activities contributing to autonomous vehicle safety and privacy. The two-year award from the Division of Electrical, Communications and Cyber Systems begins June 1, 2023. The university will develop new knowledge and techniques for interpreting driver behavior and intentions using deep learning modeling of limited sensory data....
- 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 federal Project Grant award of $364,952 from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) aims to protect autonomous vehicles by developing methods that secure both high-level software for driving decisions and low-level hardware controlling physical actions. The project will address critical gaps in understanding security vulnerabilities resulting from the interactions between self-driving software and vehicle control systems,...
- This $300,726 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program supports research to investigate the security and resiliency of Collaborative Autonomous Driving (COAD) systems. The project, led by researchers at the University at Buffalo and UC Irvine in the U.S. and the Indian Institutes of Technology at Kharagpur and Jodhpur in India, aims to develop a comprehensive framework for examining new attack...
- This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program provides $338,536 to George Mason University to enhance the safety and reliability of autonomous vehicle systems. The project aims to identify and mitigate vulnerabilities in the control software and machine learning components of autonomous vehicles through a combination of model-based and data-driven approaches for end-to-end resilience assessment and...
- This $482,972 National Science Foundation (NSF) Engineering program (CFDA 47.041) grant supports fundamental research at North Carolina State University (NC State) to understand the behavior and interactions of mixed autonomous and human-driven vehicle traffic streams. The project aims to: (1) characterize the driving behaviors of human-driven and connected automated vehicles in conflicting traffic, (2) analyze the collective impact of mixed traffic on traffic flow, and (3) develop robust...
This Project Grant award from the National Science Foundation Division of Computer and Network Systems provides $148,867 to support research into cooperative neuro-inspired anomaly detection models for connected vehicles. Funded under the Computer and Information Science and Engineering program (CFDA #47.070), the two-year award to Texas State University aims to develop novel algorithmic methods and multi-agent models to identify anomalous sensor readings that could pose safety risks in increasingly networked and automated vehicles. The research will explore machine learning and consensus-based protocols to help connected vehicles quickly classify sensor failures, learn new anomalous patterns, assess risks, build reputational trust for information sharing and cooperative decision-making, and provide resilience amid disruptions. Initial evaluations will use computer simulations with publicly available connected vehicle and autonomous systems data sets. The funding supports the NSF's mission to advance computing and information sciences research and education.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $148.9k | 1/25/23 |