Abstract
This paper considers evaluation of Key Performance Indicators (KPIs) for urban train systems equipped with regulation algorithms. We describe an efficient simulation model that can represent a network, animate metros, and integrate existing regulation schemes as black boxes. This macroscopic model allows efficient simulation of several hours of networks operations within a few seconds. We demonstrate the capacities of this simulation scheme on a case study and show how statistics can be derived during simulation campaigns. We then discuss possible improvements to increase accuracy of models.
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Notes
- 1.
Traffic is not immediately maximal but increases progressively as trains are inserted in the network.
- 2.
This value is the real value such that \(\mathbb {P}\left[ |N| \le \gamma _{\alpha } \right] = 1 - \alpha \), where N is a variable following a normal law \(\mathcal N(0,1)\). This value is not easily computable, but all statistical tools provide means to obtain \(\gamma _\alpha \), for instance using precalculated z-tables.
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Adeline, B., Dersin, P., Fabre, É., Hélouët, L., Kecir, K. (2017). An Efficient Evaluation Scheme for KPIs in Regulated Urban Train Systems. In: Fantechi, A., Lecomte, T., Romanovsky, A. (eds) Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification. RSSRail 2017. Lecture Notes in Computer Science(), vol 10598. Springer, Cham. https://doi.org/10.1007/978-3-319-68499-4_13
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