Abstract:This paper considers the challenge of validating railway timetables and investigates how formal methods can be used for that. The paper presents a re-configurable, formal model which can be configured with a timetable for a railway network, properties of that network, and various timetabling parameters (such as station and line capacities, headways, and minimum running times) constraining the allowed train behaviour. The formal model describes the system behaviour of trains driving according to the given railw… Show more
“…It should be noted here that a number of studies have addressed the assessment of railway safety properties, while tackling different use cases. In [43] and [44], the reliability of railway interlocking systems is considered, while [45] deals with the analysis of railway timetables. In [46], a moving block signaling system endowed with autonomous driving is modeled and analyzed, while considering various driving strategies.…”
This research has received funding from the Shift2Rail Joint Undertaking (JU) under the European Union's Horizon 2020 research and innovation program under Grant Agreement N. 101015416 (PERFORMINGRAIL). The JU receives support from the European Union's Horizon 2020 research and innovation program and the Shift2Rail JU members other than the Union.
“…It should be noted here that a number of studies have addressed the assessment of railway safety properties, while tackling different use cases. In [43] and [44], the reliability of railway interlocking systems is considered, while [45] deals with the analysis of railway timetables. In [46], a moving block signaling system endowed with autonomous driving is modeled and analyzed, while considering various driving strategies.…”
This research has received funding from the Shift2Rail Joint Undertaking (JU) under the European Union's Horizon 2020 research and innovation program under Grant Agreement N. 101015416 (PERFORMINGRAIL). The JU receives support from the European Union's Horizon 2020 research and innovation program and the Shift2Rail JU members other than the Union.
“…Statistical model checking has also been used to verify the reliability of railway interlocking systems [19] and Uppaal has been used to verify railway timetables [34]. Uppaal Stratego has been applied to a few other case studies belonging to the transport domain, such as traffic light controllers [3], cruise control [38], and railway scheduling [37].…”
Moving block railway systems are the next generation signalling systems currently under development as part of the Shift2Rail European initiative, including autonomous driving technologies. In this paper, we model a suitable abstraction of a moving block signalling system with autonomous driving as a stochastic priced timed game. We then synthesise safe and optimal driving strategies for the model by applying advanced techniques that combine statistical model checking with reinforcement learning as provided by Uppaal Stratego. Hence, we show the applicability of Uppaal Stratego in this concrete case study.
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