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Towards an Ontological Methodology for Dynamic Dependability Management of Unmanned Aerial Vehicles

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Published:13 April 2023Publication History

ABSTRACT

Dynamic Dependability Management (DDM) is a promising approach to guarantee and monitor the ability of safety-critical Automated Systems (ASs) to deliver the intended service with an acceptable risk level. However, the non-interpretability and lack of specifications of the Learning-Enabled Component (LEC) used in ASs make this mission particularly challenging. Some existing DDM techniques overcome these limitations by using probabilistic environmental perception knowledge associated with predicting behavior changes for the agents in the environment. Ontology-based methods allow using a formal and traceable representation of AS usage scenarios to support the design process of the DDM component of such ASs. This paper presents a methodology to perform this design process, starting from the AS specification stage and including threat analysis and requirements identification. The present paper focuses on the formalization of an ontology modeling language allowing the interpretation of logical usage scenarios, i.e., a formal description of the scenario represented by state variables. The proposed supervisory system also considers the uncertainty estimation and interaction between AS components through the whole perception-planning-control pipeline. This methodology is illustrated in this paper on a use case involving Unmanned Aerial Vehicles (UAVs).

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            • Published in

              cover image ACM Other conferences
              RAPIDO '23: Proceedings of the DroneSE and RAPIDO: System Engineering for constrained embedded systems
              January 2023
              94 pages
              ISBN:9798400700453
              DOI:10.1145/3579170

              Copyright © 2023 ACM

              Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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              Publication History

              • Published: 13 April 2023

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