Advertisement

An Integrated Approach for Availability and QoS Evaluation in Railway Systems

  • Antonino Mazzeo
  • Nicola Mazzocca
  • Roberto Nardone
  • Luca D’Acierno
  • Bruno Montella
  • Vincenzo Punzo
  • Egidio Quaglietta
  • Immacolata Lamberti
  • Pietro Marmo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6894)

Abstract

Prediction of service availability in railway systems requires an increasing attention by designers and operators in order to satisfy acceptable service quality levels offered to passengers. For this reason it is necessary to reach high availability standards, relying on high-dependable system components or identifying effective operational strategies addressed to mitigate failure effects. To this purpose, in this paper an innovative architecture is proposed to simulate railway operation in order to conduct different kinds of analysis. This architecture encompasses a set of components considering, in an integrated way, several system features. Finally an application to a first case study demonstrates the impact on quality of service and service availability of different recovery strategies. Complexity of a railway system requires a heterogeneous working group composed of experts in transport and in computer science areas, with the support of industry.

Keywords

quality of service prediction service availability prediction railway simulation failures mitigation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Kettner, M., Prinz, R., Sewcyk, B.: NEMO – Netz – Evaluations-Modell bei den OBB. Eisenbahntechnische Rundschau (ETR) 3, 117–121 (2001)Google Scholar
  2. 2.
    Kettner, M., Sewcyk, B.: A model for Transportation Planning and Railway Network Evaluation. In: Proceedings of the 9th World Congress on Intelligent Transport Systems, Chicago, USA (October 14-17, 2002)Google Scholar
  3. 3.
    Marinov, M., Viegas, J.: A mesoscopic simulation modelling methodology for analyzing and evaluating freight train operations in a rail network. Simulation Modelling Practice and Theory 19, 516–539 (2011)CrossRefGoogle Scholar
  4. 4.
    Nash, A., Huerlimann, D.: Railroad Simulation using Open-Track. In: Computers in Railways IX. WIT Press, Southampton (2004)Google Scholar
  5. 5.
    Siefer, T., Radtke, A.: Railway Simulation, Key for Operation and Optimal Use. In: Proceedings of the 1st International seminar of Railway and Operations Modelling and Analysis, Delft, the Netherlands (June 8-10, 2005)Google Scholar
  6. 6.
    Kotler, P.: Marketing Management, Analysis, Planning, Implementation and Control. Prentice Hall, Englewood Cliffs (1991)Google Scholar
  7. 7.
    Cascetta, E.: Transportation System Analyses, models and applications. Springer, New York (2009)CrossRefzbMATHGoogle Scholar
  8. 8.
    CENELEC: Railway applications – Specification and demonstration of reliability, availability, maintainability and safety (RAMS). EN 50126 (1999)Google Scholar
  9. 9.
    AFNOR Group, http://www.afnor.org (last access 15.03.2011)
  10. 10.
    Hagalisletto, A.M., Bjork, J., Chieh Yu, I., Enger, P.: Constructing and Refining Large-Scale Railway Models Represented by Petri Nets. IEEE Trans. On System, Man and Cybernetics-Part C: Applications and Reviews 37(4), 444–460 (2007)CrossRefGoogle Scholar
  11. 11.
    Grupe, P., Nunez, F., Cipriano, A.: An event-driven simulator for multi-line metro system and its application to Santiago de Chile metropolitan rail network. Simulation Modelling Practice and Theory 19(1), 393–405 (2009)CrossRefGoogle Scholar
  12. 12.
    Kaakai, F., Hayat, S., El Moudni, A.: A hybrid Petri nets-based simulation model for evaluating the design of railway transit stations. Simulation Modelling Practice and Theory 15(8), 935–969 (2007)CrossRefGoogle Scholar
  13. 13.
    Vittorini, V., Iacono, M., Mazzocca, N., Franceschinis, G.: The OsMoSys approach to multi-formalism modeling of systems. Software and Systems Modeling 3(1), 68–81 (2003)CrossRefGoogle Scholar
  14. 14.
    Flammini, F., Marrone, S., Mazzocca, N., Vittorini, V.: A new modeling approach to the safety evaluation of N-modular redundant computer systems in presence of imperfect maintenance. Reliability Engineering & System Safety 94(9), 1422–1432 (2007); ESREL 2007, the 18th European Safety and Reliability Conference (2007)CrossRefGoogle Scholar
  15. 15.
    Flamini, F., Mazzocca, N., Moscato, F., Pappalardo, A., Pragliola, C., Vittorini, V.: Multiformalism techniques for critical infrastructure modelling. International Journal of System of Systems Engineering 2(1), 19–37 (2010)CrossRefGoogle Scholar
  16. 16.
    Quaglietta, E., Punzo, V., Montella, B., Nardone, R., Mazzocca, N.: Towards a hybrid mesoscopic-microscopic railway simulation model. In: 2nd International Conference on Models and Technologies for ITS (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Antonino Mazzeo
    • 1
  • Nicola Mazzocca
    • 1
  • Roberto Nardone
    • 1
    • 3
  • Luca D’Acierno
    • 2
  • Bruno Montella
    • 2
  • Vincenzo Punzo
    • 2
  • Egidio Quaglietta
    • 2
  • Immacolata Lamberti
    • 3
  • Pietro Marmo
    • 3
  1. 1.Dipartimento di Informatica e SistemisticaUniversity of Naples “Federico II”NaplesItaly
  2. 2.Dipartimento di Ingegneria dei TrasportiUniversity of Naples “Federico II”NaplesItaly
  3. 3.Ansaldo STSRAMS - Transportation Solutions Business UnitNaplesItaly

Personalised recommendations