Skip to main content
SpringerLink
Log in

A DFT Modeling Approach for Infrastructure Reliability Analysis of Railway Station Areas

  • Conference paper
  • First Online:
Formal Methods for Industrial Critical Systems (FMICS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11687))

Abstract

Infrastructure failures—in particular in station and junction areas—are one of the most important causes for train delays in railway systems. Individually, subsystems, such as track circuits or radio communication, are well understood and have been analyzed using formal methods. However, verification of the capability of station areas to fulfill operational design specifications as a whole remains widely open.

In this paper, we present a fully automatic translation from station area infrastructure to dynamic fault trees (DFT) with special emphasis on field elements including switches, signals and track occupation detection systems. Reliability is assessed in terms of train routability, where feasible train routes consist of the set of train paths projected in the interlocking system including their requirements w.r.t. the state of field elements. Analysing the DFTs by probabilistic model checking techniques allows for new performance metrics based on, e.g., conditional events or the sequence of failures, which can serve to provide additional insights into the criticality of field elements.

We demonstrate the feasibility of the DFT-based analysis based on data for railway stations in Germany where the generated DFTs consist of hundreds of elements.

Supported by German Research Foundation (DFG) with Research Training Group 2236 “UnRAVeL” and Research Grant 283085490 “Integral capacity and reliability analysis of guided transport systems based on analytical models”.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Andrews, J., Prescott, D., Rozières, F.D.: A stochastic model for railway track asset management. Reliab. Eng. Syst. Saf. 130, 76–84 (2014)

    Article  Google Scholar 

  2. Baier, C., Hahn, E.M., Haverkort, B.R., Hermanns, H., Katoen, J.P.: Model checking for performability. Math. Struct. Comput. Sci. 23(4), 751–795 (2013)

    Article  MathSciNet  Google Scholar 

  3. Basile, D., ter Beek, M.H., Ciancia, V.: Statistical model checking of a moving block railway signalling scenario with Uppaal SMC. In: Margaria, T., Steffen, B. (eds.) ISoLA 2018. LNCS, vol. 11245, pp. 372–391. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03421-4_24

    Chapter  Google Scholar 

  4. Bemment, S.D., Goodall, R.M., Dixon, R., Ward, C.P.: Improving the reliability and availability of railway track switching by analysing historical failure data and introducing functionally redundant subsystems. Proc. Inst. Mech. Eng. Part F: J. Rail Rapid Transit 232(5), 1407–1424 (2017)

    Article  Google Scholar 

  5. Biagi, M., Carnevali, L., Paolieri, M., Vicario, E.: Performability evaluation of the ERTMS/ETCS – level 3. Transp. Res. Part C 82, 314–336 (2017)

    Article  Google Scholar 

  6. Birnbaum, Z.: On the importance of different components in a multicomponent system. In: Multivariate Analysis-II, pp. 581–592 (1969)

    Google Scholar 

  7. Bjørner, D.: New results and trends in formal techniques for the development of software for transportation systems. In: FORMS. L’Harmattan Hongrie (2003)

    Google Scholar 

  8. Boudali, H., Crouzen, P., Stoelinga, M.: Dynamic fault tree analysis using input/output interactive Markov chains. In: Proceedings of DSN, pp. 708–717. IEEE (2007)

    Google Scholar 

  9. Brünger, O., Gröger, T.: Fahrplantrassen managen und Fahrplanerstellung simulieren. In: 19. Verkehrswissenschaftliche Tage (VWT), Dresden, Germany (2003)

    Google Scholar 

  10. Busard, S., Cappart, Q., Limbrée, C., Pecheur, C., Schaus, P.: Verification of railway interlocking systems. Electron. Proc. Theor. Comput. Sci. 184, 19–31 (2015)

    Article  Google Scholar 

  11. Cappart, Q., Limbrée, C., Schaus, P., Quilbeuf, J., Traonouez, L., Legay, A.: Verification of interlocking systems using statistical model checking. In: HASE, pp. 61–68. IEEE Computer Society (2017)

    Google Scholar 

  12. CENELEC: EN 50128: Railway applications - Communication, signalling and processing systems - Software for railway control and protection systems (2012), EN 50129: Railway applications - Communication, signalling and processing systems - Safety related electronic systems for signalling (2017), EN 50159: Railway applications - Communication, signalling and processing systems - Safety-related communication in transmission systems (2011)

    Google Scholar 

  13. CENELEC: EN 50126–1/50126-2: Railway applications - The specification and demonstration of reliability, availability, maintainability and safety (rams) (2018)

    Google Scholar 

  14. Chen, S., Ho, T., Mao, B.: Reliability evaluations of railway power supplies by fault-tree analysis. IET Electric Power Appl. 1(2), 161–172 (2007)

    Article  Google Scholar 

  15. Cimatti, A., Roveri, M., Tonetta, S.: Requirements validation for hybrid systems. In: Bouajjani, A., Maler, O. (eds.) CAV 2009. LNCS, vol. 5643, pp. 188–203. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02658-4_17

    Chapter  Google Scholar 

  16. Coleman, I.: In2Rail Project Innovative Intelligent Rail, Deliverable D2.1 - Development of Novel S&C Motion/Locking Mechanisms: Design Concept Report. Technical report, Network Rail (NWR) (2015)

    Google Scholar 

  17. Dugan, J.B., Bavuso, S.J., Boyd, M.A.: Fault trees and sequence dependencies. In: Proceedings of RAMS, pp. 286–293 (1990)

    Google Scholar 

  18. Fantechi, A.: Twenty-five years of formal methods and railways: what next? In: Counsell, S., Núñez, M. (eds.) SEFM 2013. LNCS, vol. 8368, pp. 167–183. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-05032-4_13

    Chapter  Google Scholar 

  19. Ferrari, A., Magnani, G., Grasso, D., Fantechi, A.: Model checking interlocking control tables. In: Schnieder, E., Tarnai, G. (eds.) FORMS/FORMAT 2010, pp. 107–115. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-14261-1_11

    Chapter  Google Scholar 

  20. Ghadhab, M., Junges, S., Katoen, J.P., Kuntz, M., Volk, M.: Safety analysis for vehicle guidance systems with dynamic fault trees. Reliab. Eng. Syst. Saf. 186, 37–50 (2019)

    Article  Google Scholar 

  21. Guck, D., Katoen, J.P., Stoelinga, M., Luiten, T., Romijn, J.: Smart railroad maintenance engineering with stochastic model checking. In: Proceedings of RAILWAYS. Civil-Comp Press (2014)

    Google Scholar 

  22. Hassankiadeh, S.J.: Failure analysis of railway switches and crossings for the purpose of preventive maintenance. MA thesis, KTH Stockholm (2011)

    Google Scholar 

  23. Henry, J.: Automatic fault tree construction for railway safety systems. Ph.D. thesis, Loughborough University (1996)

    Google Scholar 

  24. Hermanns, H., Jansen, D.N., Usenko, Y.S.: From StoCharts to MoDeST. In: Proceedings of WOSP. ACM Press (2005)

    Google Scholar 

  25. Iliasov, A., Romanovsky, A.B.: Formal analysis of railway signalling data. In: HASE, pp. 70–77. IEEE Computer Society (2016)

    Google Scholar 

  26. Iliasov, A., Taylor, D., Laibinis, L., Romanovsky, A.: Formal verification of signalling programs with SafeCap. In: Gallina, B., Skavhaug, A., Bitsch, F. (eds.) SAFECOMP 2018. LNCS, vol. 11093, pp. 91–106. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99130-6_7

    Chapter  Google Scholar 

  27. Junges, S., Guck, D., Katoen, J.P., Rensink, A., Stoelinga, M.: Fault trees on a diet: automated reduction by graph rewriting. Formal Asp. Comput. 29, 1–53 (2017)

    Article  MathSciNet  Google Scholar 

  28. Junges, S., Guck, D., Katoen, J.P., Stoelinga, M.: Uncovering dynamic fault trees. In: Proceedings of DSN, pp. 299–310. IEEE (2016)

    Google Scholar 

  29. Junges, S., Katoen, J.-P., Stoelinga, M., Volk, M.: One net fits all. In: Khomenko, V., Roux, O.H. (eds.) PETRI NETS 2018. LNCS, vol. 10877, pp. 272–293. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91268-4_14

    Chapter  Google Scholar 

  30. Kalvakunta, R.G.: Reliability modelling of ERTMS/ETCS. MA thesis, NTNU (2017)

    Google Scholar 

  31. Kassa, E.: Analysis of failures within switches and crossings using failure modes and effects analysis methodology. In: Proceedings of Intelliswitch Symposium (2017)

    Google Scholar 

  32. Luteberget, B., Johansen, C.: Efficient verification of railway infrastructure designs against standard regulations. Formal Methods Syst. Des. 52(1), 1–32 (2018)

    Article  Google Scholar 

  33. Morant, S.: New generation of turnouts promises to improve reliability and reduce costs. IRJ Int. Rail. J. 56(12) (2016)

    Google Scholar 

  34. Nash, A., Huerlimann, D., Schütte, J., Krauss, V.: RailML - a standard data interface for railroad applications, pp. 3–10. WIT Press, Southampton (2004)

    Chapter  Google Scholar 

  35. ORR - Office of Road and Rail: Online data portal, Rail infrastructure, assets and environmental (2013). https://dataportal.orr.gov.uk/. Accessed 01 May 2019

  36. Ou, Y., Dugan, J.B.: Approximate sensitivity analysis for acyclic Markov reliability models. IEEE Trans. Rel. 52(2), 220–230 (2003)

    Article  Google Scholar 

  37. Platzer, A., Quesel, J.-D.: European train control system: a case study in formal verification. In: Breitman, K., Cavalcanti, A. (eds.) ICFEM 2009. LNCS, vol. 5885, pp. 246–265. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-10373-5_13

    Chapter  Google Scholar 

  38. Prescott, D., Andrews, J.: Modelling maintenance in railway infrastructure management. In: Proceedings of RAMS, pp. 1–6. IEEE (2013)

    Google Scholar 

  39. Ruijters, E., Guck, D., van Noort, M., Stoelinga, M.: Reliability-centered maintenance of the electrically insulated railway joint via fault tree analysis: a practical experience report. In: Proceedings of DSN. IEEE (2016)

    Google Scholar 

  40. Ruijters, E., Stoelinga, M.: Fault tree analysis: a survey of the state-of-the-art in modeling, analysis and tools. Comput. Sci. Rev. 15–16, 29–62 (2015)

    Article  MathSciNet  Google Scholar 

  41. Stamatelatos, M., Vesely, W., Dugan, J.B., Fragola, J., Minarick, J., Railsback, J.: Fault Tree Handbook with Aerospace Applications. NASA Headquarters (2002)

    Google Scholar 

  42. Volk, M., Junges, S., Katoen, J.P.: Fast dynamic fault tree analysis by model checking techniques. IEEE Trans. Ind. Inform. 14(1), 370–379 (2018)

    Article  Google Scholar 

  43. Weik, N., Nießen, N.: Performability analysis of railway systems. In: 2018 International Conference on Intelligent Rail Transportation (ICIRT). IEEE (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Chair of Software Modeling and Verification, RWTH Aachen University, Aachen, Germany

    Matthias Volk & Joost-Pieter Katoen

  2. Institute of Transport Science, RWTH Aachen University, Aachen, Germany

    Norman Weik & Nils Nießen

Authors
  1. Matthias Volk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Norman Weik
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Joost-Pieter Katoen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nils Nießen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthias Volk .

Editor information

Editors and Affiliations

  1. Aalborg University, Aalborg, Denmark

    Kim Guldstrand Larsen

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Tim Willemse

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Volk, M., Weik, N., Katoen, JP., Nießen, N. (2019). A DFT Modeling Approach for Infrastructure Reliability Analysis of Railway Station Areas. In: Larsen, K., Willemse, T. (eds) Formal Methods for Industrial Critical Systems. FMICS 2019. Lecture Notes in Computer Science(), vol 11687. Springer, Cham. https://doi.org/10.1007/978-3-030-27008-7_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27008-7_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27007-0

  • Online ISBN: 978-3-030-27008-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation