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

CPS：协同：协作研究：管理安全关键航空系统设计中的不确定性

• 批准号: 1329390
• 负责人: Peter Seiler
• 金额: $ 47.36万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1329390&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Managing

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.

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。 研究重点是三个创新的想法，以支持这一目标。首先，概率技术将被引入到指定系统级的要求和约束的动态组件的性能。 这将降低与复杂航空系统相关的设计成本，这些系统由许多独立工程组织生产的紧密集成部件组成。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，极值理论的技术将应用于开发自适应验证和确认程序。 这将有助于尽早引进新的和先进的航空系统。这些系统最初的能力有限，但这些限制将逐渐放宽，因为这些限制将通过不断记录在役产品的数据来证明。三个主要研究目标将导致大大减少部署新航空系统所需的成本和时间。例如，这将使下一代空中交通管制系统能够安全和快速地实施，该系统有可能在不降低安全性的情况下将空域容量增加两倍。 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化高速公路。 该研究还包括一项教育计划，旨在培养能够设计安全关键系统的高技能劳动力。该计划围绕两个主要活动：（a）创建本科生实验室，专注于安全关键系统，（B）将安全关键概念集成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，以激励学生学习。