CPS: Synergy: Collaborative Research: Managing Uncertainty in the Design of Safety-Critical Aviation Systems

该项目的目标是研究管理安全关键航空系统设计和认证过程中的不确定性的工具。研究集中在三个创新的想法来支持这一目标。首先，将引入概率技术来指定系统级需求并约束动态组件的性能。这将降低由许多独立工程组织生产的紧密集成组件组成的复杂航空系统的设计成本。其次，将创建一个框架，用于开发使用概率执行来建模和管理软件故障风险的软件组件。这些技术将使软件更加健壮，降低验证代码更改的成本，并允许软件质量顺利集成到整个系统级分析中。第三，将应用极值理论的技术来开发自适应验证和验证程序。这将使早期引进新的先进航空系统成为可能。这些系统最初的功能将受到限制，但这些限制将随着持续记录现役产品的数据而逐渐放宽。这三个主要研究目标将显著降低部署新航空系统所需的成本和时间。例如，这将使安全、快速地实施下一代空中交通管制系统成为可能，使空域容量增加两倍而不降低安全性。所提出的方法也适用于其他复杂系统，包括智能电网和自动公路。整合到研究中的是一项教育计划，旨在培养能够设计安全关键系统的高技能劳动力。该计划围绕两项主要活动展开：(a)建立专注于安全关键系统的本科实验室；(b)将安全关键概念整合到全国机器人扫雪机竞赛中。这些活动将提供鼓舞人心的，现实世界的应用，以激励学生的学习。

The objective of this project is to research tools to manage uncertainty in the design and certification process of safety-critical aviation systems. The research focuses on three innovative ideas to support this objective. First, probabilistic techniques will be introduced to specify system-level requirements and bound the performance of dynamical components. These will reduce the design costs associated with complex aviation systems consisting of tightly integrated components produced by many independent engineering organizations. Second, a framework will be created for developing software components that use probabilistic execution to model and manage the risk of software failure. These techniques will make software more robust, lower the cost of validating code changes, and allow software quality to be integrated smoothly into overall system-level analysis. Third, techniques from Extreme Value Theory will be applied to develop adaptive verification and validation procedures. This will enable early introduction of new and advanced aviation systems. These systems will initially have restricted capabilities, but these restrictions will be gradually relaxed as justified by continual logging of data from in-service products. The three main research aims will lead to a significant reduction in the costs and time required for fielding new aviation systems. This will enable, for example, the safe and rapid implementation of next generation air traffic control systems that have the potential of tripling airspace capacity with no reduction in safety. The proposed methods are also applicable to other complex systems including smart power grids and automated highways. Integrated into the research is an education plan for developing a highly skilled workforce capable of designing safety critical systems. This plan centers around two main activities: (a) creation of undergraduate labs focusing on safety-critical systems, and (b) integration of safety-critical concepts into a national robotic snowplow competition. These activities will provide inspirational, real-world applications to motivate student learning.