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Aligning, Interoperating, and Co-executing Air Traffic Control Rules Across PSOA RuleML and IDP

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Rules and Reasoning (RuleML+RR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11784))

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Abstract

This paper studies Knowledge Bases (KBs) in PSOA RuleML and IDP, aligning, interoperating, and co-executing them for a use case of Air Traffic Control (ATC) regulations. We focus on the common core of facts and rules in both languages, explaining basic language features. The used knowledge sources are regulations specified in (legal) English, and an aircraft data schema. In the modeling process, inconsistencies in both sources were discovered. We present the discovery process utilizing both specification languages, and highlight their unique features. We introduce three extensions to this ATC KB core: (1) While the current PSOA RuleML does not distinguish the ontology separately from the instance level, IDP does. Hence, we specify a vocabulary-enriched version of ATC KB in IDP for knowledge validation. (2) While the current IDP uses relational modeling, PSOA additionally supports graph modeling. Hence, we specify a relationally interoperable graph version of ATC KB in PSOA. (3) The KB is extended to include optimization criteria to allow the determination of an optimal sequence of more than two aircraft.

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Notes

  1. 1.

    For specific references see http://blog.ruleml.org/post/132677817-decisioncamp-and-ruleml-rr-will-meet-again-in-luxembourg.

  2. 2.

    See the PSOA ATC KB sources at http://users.ntua.gr/mitsikas/ATC_KB/.

  3. 3.

    http://psoa.ruleml.org/transrun/1.4.2/local/.

  4. 4.

    Separation minima for flights on Visual Flight Rules (VFR) are time-based [8, 11].

  5. 5.

    The minima set out at Table 1 shall be applied when e.g. both aircraft are using the same runway, or parallel runways separated by less than 760 m (2 500 ft) [11].

  6. 6.

    In the ATC domain the regulations are stable and new types of aircraft e.g. in the Super category are not currently in active development. Therefore, we do not consider this a major problem.

  7. 7.

    The IDP language typically offers more expressivity than DMN decision tables. Current work focuses on an extension to DMN to strengthen the link IDP\(\rightarrow \)DMN.

References

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Acknowledgments

The author of the Hellenic Civil Aviation Authority wants to thank his colleagues for discussions about the domain-expert knowledge. Any deficiencies are ours and we make this disclaimer: the described work constitutes an informative computational model of ATC regulations and is not intended for use in real aviation environments. The authors of KU Leuven are partially supported by the Flemish Agency for Innovation and Entrepreneurship (HBC.2017.0039).

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Authors and Affiliations

  1. KU Leuven, Sint-Katelijne Waver, Belgium

    Marjolein Deryck & Joost Vennekens

  2. National Technical University of Athens, Athens, Greece

    Theodoros Mitsikas, Sofia Almpani, Petros Stefaneas & Panayiotis Frangos

  3. Hellenic Civil Aviation Authority, Heraklion Airport, Heraklion, Greece

    Iakovos Ouranos

  4. University of New Brunswick, Fredericton, Canada

    Harold Boley

Authors
  1. Marjolein Deryck
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  2. Theodoros Mitsikas
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  3. Sofia Almpani
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  4. Petros Stefaneas
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  5. Panayiotis Frangos
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  6. Iakovos Ouranos
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  7. Harold Boley
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  8. Joost Vennekens
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Corresponding authors

Correspondence to Marjolein Deryck or Theodoros Mitsikas .

Editor information

Editors and Affiliations

  1. Stony Brook University, Stony Brook, NY, USA

    Paul Fodor

  2. Free University of Bozen-Bolzano, Bolzano, Italy

    Marco Montali

  3. Free University of Bozen-Bolzano, Bolzano, Italy

    Diego Calvanese

  4. SINTEF AS, Oslo, Norway

    Dumitru Roman

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Deryck, M. et al. (2019). Aligning, Interoperating, and Co-executing Air Traffic Control Rules Across PSOA RuleML and IDP. In: Fodor, P., Montali, M., Calvanese, D., Roman, D. (eds) Rules and Reasoning. RuleML+RR 2019. Lecture Notes in Computer Science(), vol 11784. Springer, Cham. https://doi.org/10.1007/978-3-030-31095-0_4

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  • DOI: https://doi.org/10.1007/978-3-030-31095-0_4

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