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A Rule-Based Smart Control for Fail-Operational Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11606))

Abstract

When systems become smarter they have to cope with faults occurring during operation in an intelligent way. For example, an autonomous vehicle has to react appropriately in case of a fault occurring during driving on a highway in order to assure safety for passengers and other humans in its surrounding. Hence, there is a need for fail-operational systems that extend the concept of fail-safety. In this paper, we introduce a method that relies on rules for controlling a system. The rules specify the behavior of the system including behavioral redundancies. In addition, the method provides a runtime execution engine that selects the rules accordingly to reach a certain goal. In addition, we present a language and an implementation of the method and discuss its capabilities using a case study from the mobile robotics domain. In particular, we show how the rule-based fail-operational system can adapt to a fault occurring at runtime.

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Acknowledgments

The research was supported by ECSEL JU under the project H2020 737469 AutoDrive - Advancing fail-aware, fail-safe, and fail-operational electronic components, systems, and architectures for fully automated driving to make future mobility safer, affordable, and end-user acceptable. AutoDrive is funded by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT) under the program “ICT of the Future” between May 2017 and April 2020. More information https://iktderzukunft.at/en/ . The financial support by the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development is gratefully acknowledged.

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Correspondence to Martin Zimmermann .

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Engel, G., Schweiger, G., Wotawa, F., Zimmermann, M. (2019). A Rule-Based Smart Control for Fail-Operational Systems. In: Wotawa, F., Friedrich, G., Pill, I., Koitz-Hristov, R., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2019. Lecture Notes in Computer Science(), vol 11606. Springer, Cham. https://doi.org/10.1007/978-3-030-22999-3_13

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  • DOI: https://doi.org/10.1007/978-3-030-22999-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22998-6

  • Online ISBN: 978-3-030-22999-3

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