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 accurate safety evaluations at the system level. Key outcomes are expected to boost the trustworthiness and adaptability of learning-enabled systems, such as autonomous vehicles, robotics, and industrial automation, to operate safely in unfamiliar or unprecedented environments. The research efforts will focus on developing a new probabilistic specification language and efficient computational methods to verify safety properties of learning-enabled deep neural network components. The project will validate the proposed safety assessment methods and tools using a small-scale autonomous vehicle testbed. The award period runs from December 1, 2023, to November 30, 2026.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $270.9k | 9/18/23 |