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Delay Propagation on a Suburban Railway Network

EasyChair Preprint no. 2517

2 pagesDate: January 31, 2020

Abstract

Understanding and predicting delays is a central task for any railway system, but it is made much more difficult by interactions between trains. We propose a new model for the delay propagation phenomenon, which takes into account infrastructure constraints without assuming knowledge of the resource conflicts linking trains with one another. Our approach relies on a set of hidden variables called the network jam, structured as a Dynamic Bayesian Network to enable spatial propagation. We also present a statistical analysis of the minimax estimation error, a variational inference method and numerical tests on simulated and real data.

Keyphrases: Dynamic Bayesian Network, Railway Operations, Train delay prediction, variational inference

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:2517,
  author = {Guillaume Dalle and Yohann De Castro and Axel Parmentier},
  title = {Delay Propagation on a Suburban Railway Network},
  howpublished = {EasyChair Preprint no. 2517},

  year = {EasyChair, 2020}}
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