Predicting interlocking malfunctions for the railway network in Germany

Interlockings generate a major part of all malfunctions on the German railway network infrastructure. Therefore, predictions of future malfunctions are essential to optimize the distribution of available maintenance and renewal funds. This work compares different regression methods to predict the nu...

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Bibliographic Details
Published in:Transportation research procedia (Online) 2023, Vol.72, p.3481-3488
Main Authors: Emunds, Tamme, Wink, Christopher, Lempp, Martin, Monem, Karim, Dickenbrok, Björn, Nießen, Nils
Format: Article
Language:English
Subjects:
data analysis
intelligent asset management systems
interlocking maintenance
life-cycle assessment
Malfunction prediction
railway operation
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Summary:Interlockings generate a major part of all malfunctions on the German railway network infrastructure. Therefore, predictions of future malfunctions are essential to optimize the distribution of available maintenance and renewal funds. This work compares different regression methods to predict the number of malfunctions on individual interlockings. These methods are trained and tested on a data set provided by the German infrastructure manager ‘DB Netz AG’. Using the obtained models, the importance of available feature data to the prediction quality is analyzed.
ISSN:2352-1465
2352-1465
DOI:10.1016/j.trpro.2023.11.765