Modeling of ERTMS Level 2 as an SoS and Evaluation of its Dependability Parameters Using Statecharts

Qiu, Siqi; Sallak, Mohamed; Schön, Walter; Cherfi‐Boulanger, Zohra

doi:10.1109/jsyst.2013.2297751

Cited by 19 publications

(7 citation statements)

References 27 publications

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“…For rail traffic management and control systems included in the highest fourth SIL (Safety Integrity Level), THR values should be in the range 8 9 10 10 − − < ≤ THR . In addition to the THR indicator mentioned above, rail traffic management and control systems (hardware, software) can be analyzed using FMEA, FTA or Markov chain, [8], [9], [14]. The latter uses continuous-time processes that correlate with the Poisson process.…”

Section: Fundamentals Of Safety Analysis Of Rail Traffic Management Amentioning

confidence: 99%

Telematics as a future method for improving the safety of rail transport

Lewiński

Perzyński

2019

TO - PK

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Section: Fundamentals Of Safety Analysis Of Rail Traffic Management Amentioning

confidence: 99%

Telematics as a future method for improving the safety of rail transport

Lewiński

Perzyński

2019

TO - PK

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“…CE occurs for the first time at the n-th period when the initial state is i and when the component stays in this state during n [24]. However, it directly models s specific railway system in order to evaluate its dependability parameters but it does not perform qualitative analysis using FT.…”

Section: Necessity Of a New Approach For Modelling The Critical Eventmentioning

confidence: 99%

Method for evaluating an extended Fault Tree to analyse the dependability of complex systems: Application to a satellite-based railway system

Nguyen

Beugin

Marais

2015

Reliability Engineering & System Safety

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a b s t r a c tEvaluating dependability of complex systems requires the evolution of the system states over time to be analysed. The problem is to develop modelling approaches that take adequately the evolution of the different operating and failed states of the system components into account. The Fault Tree (FT) is a wellknown method that efficiently analyse the failure causes of a system and serves for reliability and availability evaluations. As FT is not adapted to dynamic systems with repairable multi-state components, extensions of FT (eFT) have been developed. However efficient quantitative evaluation processes of eFT are missing. Petri nets have the advantage of allowing such evaluation but their construction is difficult to manage and their simulation performances are unsatisfactory. Therefore, we propose in this paper a new powerful process to analyse quantitatively eFT. This is based on the use of PN method, which relies on the failed states highlighted by the eFT, combined with a new analytical modelling approach for critical events that depend on time duration. The performances of the new process are demonstrated through a theoretical example of eFT and the practical use of the method is shown on a satellite-based railway system.

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“…In this sense, [17] presents a Unified Modeling Language (UML) model for the ERTMS Level 2. This model can be used to perform simulations and obtain the Reliability, Availability, and Maintainability (RAM) values in order to verify that the railway system is meeting specific RAM goals such as a specific value of unavailability.…”

Section: Related Workmentioning

confidence: 99%

Modelling and Simulation of ERTMS for Current and Future Mobile Technologies

Pinedo

Aguado

López

et al. 2015

International Journal of Vehicular Technology

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Nowadays, train control in-lab simulation tools play a crucial role in reducing extensive and expensive on-site railway testing activities. In this paper, we present our contribution in this arena by detailing the internals of our European Railway Train Management System in-lab demonstrator. This demonstrator is built over a general-purpose simulation framework, Riverbed Modeler, previously Opnet Modeler. Our framework models both ERTMS subsystems, the Automatic Train Protection application layer based on movement authority message exchange and the telecommunication subsystem based on GSM-R communication technology. We provide detailed information on our modelling strategy. We also validate our simulation framework with real trace data. To conclude, under current industry migration scenario from GSM-R legacy obsolescence to IP-based heterogeneous technologies, our simulation framework represents a singular tool to railway operators. As an example, we present the assessment of related performance indicators for a specific railway network using a candidate replacement technology, LTE, versus current legacy technology. To the best of our knowledge, there is no similar initiative able to measure the impact of the telecommunication subsystem in the railway network availability.

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Modeling of ERTMS Level 2 as an SoS and Evaluation of its Dependability Parameters Using Statecharts

Cited by 19 publications

References 27 publications

Telematics as a future method for improving the safety of rail transport

Telematics as a future method for improving the safety of rail transport

Method for evaluating an extended Fault Tree to analyse the dependability of complex systems: Application to a satellite-based railway system

Modelling and Simulation of ERTMS for Current and Future Mobile Technologies

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