Non-Markovian Performability Evaluation of ERTMS/ETCS Level 3

The European Rail Traffic Management System/European Train Control System (ERTMS/ETCS) is an innovative standard introduced to enhance reliability, safety, performance, and interoperability of trans-European railways. In Level 3, the standard replaces fixed-block safety mechanisms, in which only one train at a time is allowed to be in each railway block, with moving blocks: a train proceeds as long as it receives radio messages ensuring that the track ahead is clear of other trains. This mechanism increases line capacity, but relies crucially on the communication link: if messages are lost, the train must stop within a safe deadline even if the track ahead is clear. We develop upon results of the literature to propose an approach for the evaluation of transient availability of the communication channel and probability of train stops due to lost messages. We formulate a non-Markovian model of communication availability and system operation, and leverage solution techniques of the ORIS Tool to provide experimental results in the presence of multiple concurrent activities with non-exponential durations.

[1]  Günter Hommel,et al.  A train control system case study in model-based real time system design , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[2]  Gianfranco Ciardo,et al.  A Characterization of the Stochastic Process Underlying a Stochastic Petri Net , 1994, IEEE Trans. Software Eng..

[3]  Mohamed Sallak,et al.  Modeling of ERTMS Level 2 as an SoS and Evaluation of its Dependability Parameters Using Statecharts , 2014, IEEE Systems Journal.

[4]  Andrea Bobbio,et al.  Markov regenerative SPN with non-overlapping activity cycles , 1995, Proceedings of 1995 IEEE International Computer Performance and Dependability Symposium.

[5]  Lorenzo Ridi,et al.  Transient analysis of non-Markovian models using stochastic state classes , 2012, Perform. Evaluation.

[6]  Jörn Freiheit,et al.  Petri Net Modelling and Performability Evaluation with TimeNET 3.0 , 2000, Computer Performance Evaluation / TOOLS.

[7]  David Parker,et al.  Symbolic Representations and Analysis of Large Probabilistic Systems , 2004, Validation of Stochastic Systems.

[8]  Enrico Vicario,et al.  Static Analysis and Dynamic Steering of Time-Dependent Systems , 2001, IEEE Trans. Software Eng..

[9]  P. Glynn.  A GSMP formalism for discrete event systems , 1989, Proc. IEEE.

[10]  Gerald S. Shedler,et al.  Numerical Analysis of Deterministic and Stochastic Petri Nets with Concurrent Deterministic Transitions , 1996, Perform. Evaluation.

[11]  Günter Hommel,et al.  Towards modeling and evaluation of ETCS real-time communication and operation , 2005, Journal of Systems and Software.

[12]  Laura Carnevali,et al.  Using Stochastic State Classes in Quantitative Evaluation of Dense-Time Reactive Systems , 2009, IEEE Transactions on Software Engineering.

[13]  Francesco Flammini,et al.  UML Based Reverse Engineering for the Verification of Railway Control Logics , 2006, 2006 International Conference on Dependability of Computer Systems.

[14]  Laura Carnevali,et al.  Stochastic Time Petri Nets , 2008 .

[15]  J. Ben Atkinson,et al.  Modeling and Analysis of Stochastic Systems , 1996 .

[16]  Kishor S. Trivedi,et al.  SPNP: stochastic Petri net package , 1989, Proceedings of the Third International Workshop on Petri Nets and Performance Models, PNPM89.

[17]  Kishor S. Trivedi.  Probability and Statistics with Reliability, Queuing, and Computer Science Applications , 1984 .

[18]  Christel Baier,et al.  Validation of Stochastic Systems , 2004, Lecture Notes in Computer Science.

[19]  Kishor S. Trivedi,et al.  SHARPE at the age of twenty two , 2009, PERV.

[20]  Axel Thümmler,et al.  Transient Analysis of Deterministic and Stochastic Petri Nets with Concurrent Deterministic Transitions , 1999, Perform. Evaluation.

[21]  Stefano Marrone,et al.  Enabling the usage of UML in the verification of railway systems: The DAM-rail approach , 2013, Reliab. Eng. Syst. Saf..

[22]  William H. Sanders,et al.  Stochastic Activity Networks: Formal Definitions and Concepts , 2002, European Educational Forum: School on Formal Methods and Performance Analysis.

[23]  M. Diaz,et al.  Modeling and Verification of Time Dependent Systems Using Time Petri Nets , 1991, IEEE Trans. Software Eng..

[24]  Christian Kelling.  A framework for rare event simulation of stochastic Petri nets using “RESTART” , 1996, Winter Simulation Conference.

[25]  Jan Magott,et al.  Dependability and Safety Analysis of ETCS Communication for ERTMS Level 3 Using Performance Statecharts and Analytic Estimation , 2014, DepCoS-RELCOMEX.

[26]  Hoon Choi,et al.  Markov Regenerative Stochastic Petri Nets , 1994, Perform. Evaluation.

[27]  William H. Sanders,et al.  Möbius 2.3: An extensible tool for dependability, security, and performance evaluation of large and complex system models , 2009, 2009 IEEE/IFIP International Conference on Dependable Systems & Networks.

[28]  Francesco Flammini,et al.  Modelling system reliability aspects of ERTMS/ETCS by fault trees and Bayesian networks , 2006 .

[29]  Jan Trowitzsch,et al.  Using UML state machines and petri nets for the quantitative investigation of ETCS , 2006, valuetools '06.

[30]  Francesco Flammini,et al.  A MULTIFORMALISM MODULAR APPROACH TO ERTMS/ETCS FAILURE MODELING , 2014 .

[31]  William J. Stewart,et al.  Introduction to the numerical solution of Markov Chains , 1994 .

[32]  Miklós Telek,et al.  Numerical Analysis of Large Markov Reward Models , 1999, Perform. Evaluation.

[33]  Holger Hermanns,et al.  From StoCharts to MoDeST: a comparative reliability analysis of train radio communications , 2005, WOSP '05.

[34]  Holger Hermanns,et al.  MODEST: A Compositional Modeling Formalism for Hard and Softly Timed Systems , 2006, IEEE Transactions on Software Engineering.

[35]  Laura Carnevali,et al.  A Framework for Simulation and Symbolic State Space Analysis of Non-Markovian Models , 2011, SAFECOMP.

[36]  Armin Zimmermann.  Dependability evaluation of complex systems with TimeNET , 2010 .