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

在航空电子领域，一项通过使用人工智能(AI)技术赋予飞机“思维”能力的进化正在进行中。这种发展是由高性能嵌入式硬件平台的可用性推动的，这些平台通常是多核机器的形式，并配备了可以加速某些计算的加速器。不幸的是，航空电子软件认证过程没有跟上这种发展的步伐。这些进程植根于时间和空间分区这两个概念：防止不同的系统组件在执行(时间)和访问内存(空间)时相互干扰。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，要高效地实现组件隔离要困难得多。这一事实指出了一个迫在眉睫的两难境地：除非在这种情况下能够提供合理的部件隔离概念，否则认证基于人工智能的航空电子系统可能是不切实际的。这个项目将通过在实时系统、安全、自主和CPS系统架构的CPS核心研究领域进行多方面的研究来解决这一困境。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程序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。它将通过瞄准必须表现出可证明的安全和可靠行为的自动驾驶飞机的设计，为安全和自主做出贡献。它将通过设计新的方法将复杂的面向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，从而为CPS系统架构做出贡献。该项目的智力优势在于在基于AI的航空电子用例中生成了一个支持多核+加速器平台上的组件的框架。该框架将平衡在时间和空间上隔离组件的需要和高效执行的需要。组件供应取决于各个程序的执行时间范围。为了在不同的安全水平下获得这些界限，将产生新的时间分析方法。还将研究在将感知、规划和控制的有限人工智能计算重构为组件时产生的性能/及时性/准确性权衡。拟议框架的实验评估将使用自动飞机模拟器、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，该项目将有助于继续推动航空电子设备中更多的半自动和自主功能。这一努力始于40年前的自动驾驶功能，今天正受到人工智能软件进步的推动。这个项目将集中在认证该软件的一个关键方面：验证实时正确性。产生的成果将通过开放源码软件向全世界提供。该软件将包括以隔离方式支持组件的操作系统扩展，以及用于形成组件并评估其时序正确性的机制。此外，将特别强调针对代表性不足的群体的外展努力，以及在本科水平增加女性对计算机的参与。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.