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Statistical Model Checking of a Moving Block Railway Signalling Scenario with Uppaal SMC

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Leveraging Applications of Formal Methods, Verification and Validation. Verification (ISoLA 2018)

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Abstract

We present an experience in modelling and statistical model checking a satellite-based moving block signalling scenario from the railway industry with Uppaal SMC. This demonstrates the usability and applicability of Uppaal SMC in the railway domain. We also propose a promising direction for future work, in which we envision spatio-temporal analysis with Uppaal SMC.

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Notes

  1. 1.

    In timed automata, an urgent state (indicated with a ‘\(\cup \)’ inside the state) is a state with no delay, which allows to reduce the number of clocks in a model, and thus the analysis’ complexity.

  2. 2.

    We assume that the considered graphs are symmetric, although this is not generally needed in spatial model checking, especially not in the research line of [22].

  3. 3.

    cf. https://github.com/vincenzoml/topochecker and http://topochecker.isti.cnr.it.

  4. 4.

    http://people.cs.aau.dk/~adavid/smc/cases.html.

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Acknowledgements

This work was partially funded by the Tuscany Region project SISTER and by the ASTRail project, which received funding from the Shift2Rail Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 777561. The content of this paper reflects only the authors’ view, and the Shift2Rail Joint Undertaking is not responsible for any use that may be made of the included information.

We thank our colleagues in the Formal Methods and Tools research group at ISTI-CNR, and the partners in these projects, for discussions on the models analysed in this paper.

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Basile, D., ter Beek, M.H., Ciancia, V. (2018). Statistical Model Checking of a Moving Block Railway Signalling Scenario with Uppaal SMC. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation. Verification. ISoLA 2018. Lecture Notes in Computer Science(), vol 11245. Springer, Cham. https://doi.org/10.1007/978-3-030-03421-4_24

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