CPS: Medium: GOALI: Enabling Scalable Real-Time Certification for AI-Oriented Safety-Critical Systems

在航空电子领域，通过使用人工智能（AI）技术赋予飞机“思考”能力的发展正在进行。高性能嵌入式硬件平台的可用性推动了这种演变，通常以带有加速器的多核机器的形式出现，这些加速器可以加速某些计算。不幸的是，航空电子软件认证过程并没有跟上这种发展的步伐。这些进程根植于时间和空间分区的双重概念：不同的系统组件在执行（时间）和访问内存（空间）时被防止相互干扰。在单处理器机器上，可以简单地应用这些概念将系统分解为可以单独指定、实现和理解的较小组件。然而，在多核+加速器平台上，组件隔离很难有效地实现。这一事实指出了一个迫在眉睫的困境：除非在这种情况下能够提供合理的组件隔离概念，否则基于人工智能的航空电子系统的认证可能是不切实际的。该项目将通过在实时系统、安全性、自主性和CPS系统架构等CPS核心研究领域的多方面研究来解决这一难题。它将通过为必须通过实时认证的基于组件的航空电子应用生产新的基础设施和分析工具，为实时系统和安全做出贡献。它将通过针对必须表现出可认证的安全和可靠行为的自主飞机的设计，为安全和自主做出贡献。它将通过设计将复杂的面向ai的航空电子工作负载分解为在空间和时间上隔离的组件的新方法，为CPS系统架构做出贡献。这个项目的智力价值在于为基于人工智能的航空电子用例中的多核+加速器平台上的支持组件提供一个框架。该框架将平衡在时间和空间上隔离组件的需求与高效执行的需求。组件供应取决于单个程序的执行时间限制。新的时间分析方法将产生，以获得这些边界在不同的安全水平。研究还将对性能/时效性/准确性的权衡进行研究，这些权衡是在将有时间限制的人工智能计算重构为感知、计划和控制组件时出现的。对拟议框架的实验评估将使用自主飞机模拟器、商用无人机和诺斯罗普·格鲁曼公司的设施进行。更广泛地说，该项目将有助于不断推动航空电子设备中更多的半自主和自主功能。这一趋势始于40年前的自动驾驶功能，如今又被人工智能软件的进步所推动。本项目将重点关注验证该软件的一个关键方面：验证实时正确性。所产生的结果将通过开源软件向全世界提供。该软件将包括操作系统扩展，用于以隔离的方式支持组件，以及用于形成组件和评估其时间正确性的机制。此外，将特别强调针对代表性不足的群体的外展努力，以及增加女性在本科阶段对计算机的参与。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

In avionics, an evolution is underway to endow aircraft with “thinking” capabilities through the use of artificial-intelligence (AI) techniques. This evolution is being fueled by the availability of high-performance embedded hardware platforms, typically in the form of multicore machines augmented with accelerators that can speed up certain computations. Unfortunately, avionics software certification processes have not kept pace with this evolution. These processes are rooted in the twin concepts of time and space partitioning: different system components are prevented from interfering with each other as they execute (time) and as they access memory (space). On a single-processor machine, these concepts can be simply applied to decompose a system into smaller components that can be specified, implemented, and understood separately. On a multicore+accelerator platform, however, component isolation is much more difficult to achieve efficiently. This fact points to a looming dilemma: unless reasonable notions of component isolation can be provided in this context, certifying AI-based avionics systems will likely be impractical. This project will address this dilemma through multi-faceted research in the CPS Core Research Areas of Real-Time Systems, Safety, Autonomy, and CPS System Architecture. It will contribute to Real-Time Systems and Safety by producing new infrastructure and analysis tools for component-based avionics applications that must pass real-time certification. It will contribute to Safety and Autonomy by targeting the design of autonomous aircraft that must exhibit certifiably safe and dependable behavior. It will contribute to CPS System Architecture by designing new methods for decomposing complex AI-oriented avionics workloads into components that are isolated in space and time.The intellectual merit of this project lies in producing a framework for supporting components on multicore+accelerator platforms in AI-based avionics use cases. This framework will balance the need to isolate components in time and space with the need for efficient execution. Component provisioning hinges on execution time bounds for individual programs. New timing-analysis methods will be produced for obtaining these bounds at different safety levels. Research will also be conducted on performance/timeliness/accuracy tradeoffs that arise when refactoring time-limited AI computations for perception, planning, and control into components. Experimental evaluations of the proposed framework will be conducted using an autonomous aircraft simulator, commercial drones, and facilities at Northrop Grumman Corp. More broadly, this project will contribute to the continuous push toward more semi-autonomous and autonomous functions in avionics. This push began 40 years ago with auto-pilot functions and is being fueled today by advances in AI software. This project will focus on a key aspect of certifying this software: validating real-time correctness. The results that are produced will be made available to the world at large through open-source software. This software will include operating-system extensions for supporting components in an isolated way and mechanisms for forming components and assessing their timing correctness. Additionally, a special emphasis will be placed on outreach efforts that target underrepresented groups, and on increasing female participation in computing at the undergraduate level.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.