Abstract
In this paper we propose an exact symbolic simulation method to compute the impact of delays in railway systems. We use macroscopic railway infrastructure models and model primary delays of trains in a timetable by discrete probability distributions. Our method is capable of computing exact probabilistic quantities like delay probability distributions and expected delays for timetable trains, or expected capacity usage of infrastructure elements within a given finite time window. In turn, these quantities allow us to examine timetable robustness and to identify problematic infrastructure elements. We evaluate our approach on realistic case studies and discuss possible further improvements.
This research is funded by the German Research Council (DFG) – Research Training Group UnRAVeL (RTG 2236).
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Notes
- 1.
Actually, in \(\textit{block}[x]\) we do not need all details stored in the train instances; all what we need is a unique representation of a track-blocking until a certain time point. We store the train instances here to have a unique data type for the global sets \(\textit{occupy}[x]\), \(\textit{block}[x]\) and \(\textit{req}[x]\).
- 2.
In contrast to edges, arrival and departure times might be equal for vertices, i.e. the train might not want to stop at the given vertex but move on directly to the next infrastructure element. Processing vertices first allows us to implement entering the vertex first and entering the outgoing edge afterwards for the same time point.
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Haehn, R., Ábrahám, E., Nießen, N. (2021). Symbolic Simulation of Railway Timetables Under Consideration of Stochastic Dependencies. In: Abate, A., Marin, A. (eds) Quantitative Evaluation of Systems. QEST 2021. Lecture Notes in Computer Science(), vol 12846. Springer, Cham. https://doi.org/10.1007/978-3-030-85172-9_14
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