Towards a framework for certification of reliable autonomous systems

Fisher, Michael; Mascardi, Viviana; Rozier, Kristin Yvonne; Schlingloff, Bernd-Holger; Winikoff, Michael; Yorke-Smith, Neil

doi:10.26686/wgtn.13490913.v1

Cited by 5 publications

(4 citation statements)

References 105 publications

(5 reference statements)

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“…The above-mentioned standards do not specifically address autonomy, such as adaptations to regulations for certification of aerospace systems incorporating different levels of autonomy [6]. However, in the context of autonomy, artificial intelligence, and machine learning in particular, EASA has recently published new guidance documents [7][8][9][10].…”

Section: Related Work: Aerospace Regulationsmentioning

confidence: 99%

“…From a certification perspective, the aircraft is not safe. However, the operation may be safe if flights only occur in unpopulated areas, so the operation is therefore at an even higher level of abstraction than the aircraft.The above-mentioned standards do not specifically address autonomy, such as adaptations to regulations for certification of aerospace systems incorporating different levels of autonomy [6]. However, in the context of autonomy, artificial intelligence, and machine learning in particular, EASA has recently published new guidance documents [7][8][9][10].…”

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confidence: 99%

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A Hierarchy of Monitoring Properties for Autonomous Systems

Schirmer

Torens

Dauer

et al. 2023

AIAA SCITECH 2023 Forum

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Monitoring capabilities play a central role in mitigating safety risks of current, and especially future autonomous aircraft systems. These future systems are likely to include complex components such as neural networks for environment perception, which pose a challenge for current verification approaches; they are considered as black-box components. To assure that these black-boxes comply with their specification, they must be monitored to detect violations during execution with respect to their input and output behaviors. Such behavioral properties often include more complex aspects such as temporal or spatial notions. The outputs can also be compared to data from other assured sensors or components of the aircraft, making monitoring an integral part of the system, which ideally has access to all available resources to assess the overall health of the operation. Current approaches using handwritten code for monitoring functions run the risk of not being able to keep up with these challenges. Therefore, in this paper, we present a hierarchy of monitoring properties that provides a perspective for overall health. We also present a categorization of monitoring properties and show how different monitoring specification languages can be used for formalization. These monitoring languages represent a higher abstraction of general-purpose code and are therefore more compact and easier for a user to write and read, and we can validate their implementations independently from the systems they reason about. They improve the maintainability of monitoring properties that is required to handle the increased complexity of future autonomous aircraft systems.applied monitoring based on specification languages. Next, we present a hierarchy of monitoring properties that ranges from low-level sensor properties to high-level operation properties, giving a holistic perspective on possibilities for system monitoring. Further, we categorize different types of monitoring properties and showcase different monitoring specification languages. Finally, we discuss the advantages and disadvantage of using such formal languages. Related Work: Aerospace RegulationsAviation standards and regulations offer a perspective on target systems that informs their monitoring. For instance, Aerospace Recommended Practice (ARP) 4754A [3] from SAE International is the guidelines document for development of civil aircraft and systems. Additionally, SAE International's ARP4761 [4] provides guidelines for conducting the safety assessment process on civil airborne systems and equipment. The terms used in both documents for developing an aircraft as well as performing a safety assessment on the different process levels are item, system, and aircraft. An item, is one or more hardware and/or software elements treated as a unit. An item is the lowest level of abstraction during development. A system is a combination of inter-related items arranged to perform a specific function. A system therefore represents a higher abstraction level than an item. The aircraft is...

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Section: Related Work: Aerospace Regulationsmentioning

confidence: 99%

mentioning

confidence: 99%

A Hierarchy of Monitoring Properties for Autonomous Systems

Schirmer

Torens

Dauer

et al. 2023

AIAA SCITECH 2023 Forum

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“…It is worth mentioning that CPS are often associated with the concepts of distributed embedded systems and smart systems, with which they share aspects of complexity, autonomy and criticality [17]. The interest in resilient CPS has grown in the last years as witnessed by the numerous projects and publications on related topics [7].…”

Section: From Cyber-physical System Resilience To Trustworthy Autonomymentioning

confidence: 99%

“…While predictability was the key for the assessment of legacy systems such as trains or airplanes, nowadays there is a paradigm shift toward smarter systems based on artificial intelligence (AI), which have the advantage of learning and adapting to new situations; however, those characteristics also introduce a high level of uncertainty that complicates their analysis and certification [7]. Therefore, we are witnessing an apparent paradox where systems have the potential of becoming more dependable due to their higher intelligence, but that can also reduce the level of trust we hold in those systems.…”

Section: Introductionmentioning

confidence: 99%

Digital twins as run-time predictive models for the resilience of cyber-physical systems: a conceptual framework

Flammini

2021

Phil. Trans. R. Soc. A.

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Digital twins (DT) are emerging as an extremely promising paradigm for run-time modelling and performability prediction of cyber-physical systems (CPS) in various domains. Although several different definitions and industrial applications of DT exist, ranging from purely visual three-dimensional models to predictive maintenance tools, in this paper, we focus on data-driven evaluation and prediction of critical dependability attributes such as safety. To that end, we introduce a conceptual framework based on autonomic systems to host DT run-time models based on a structured and systematic approach. We argue that the convergence between DT and self-adaptation is the key to building smarter, resilient and trustworthy CPS that can self-monitor, self-diagnose and—ultimately—self-heal. The conceptual framework eases dependability assessment, which is essential for the certification of autonomous CPS operating with artificial intelligence and machine learning in critical applications. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

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Specification, Synthesis and Validation of Strategies for Collaborative Embedded Systems

Schlingloff

2020

Lecture Notes in Computer Science

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Towards a framework for certification of reliable autonomous systems

Cited by 5 publications

References 105 publications

A Hierarchy of Monitoring Properties for Autonomous Systems

A Hierarchy of Monitoring Properties for Autonomous Systems

Digital twins as run-time predictive models for the resilience of cyber-physical systems: a conceptual framework

Specification, Synthesis and Validation of Strategies for Collaborative Embedded Systems

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