Application of Data Clustering to Railway Delay Pattern Recognition
Joint Authors
Cerreto, Fabrizio
Nielsen, Bo Friis
Nielsen, Otto Anker
Harrod, Steven S.
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-29
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
K-means clustering is employed to identify recurrent delay patterns on a high traffic railway line north of Copenhagen, Denmark.
The clusters identify behavioral patterns in the very large (“big data”) datasets generated automatically and continuously by the railway signal system.
The results reveal the conditions where corrective actions are necessary, showing the cases where recurrent delay patterns take place.
Delay profiles and delay change profiles are generated from timestamps to compare different train runs and to partition the set of observations into groups of similar elements.
K-means clustering can identify and discriminate different patterns affecting the same stations, which is otherwise difficult in previous approaches based on visual inspection.
Classical methods of univariate analysis do not reveal these patterns.
The demonstrated methodology is scalable and can be applied to any system of transport.
American Psychological Association (APA)
Cerreto, Fabrizio& Nielsen, Bo Friis& Nielsen, Otto Anker& Harrod, Steven S.. 2018. Application of Data Clustering to Railway Delay Pattern Recognition. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1181499
Modern Language Association (MLA)
Harrod, Steven S.…[et al.]. Application of Data Clustering to Railway Delay Pattern Recognition. Journal of Advanced Transportation No. 2018 (2018), pp.1-18.
https://search.emarefa.net/detail/BIM-1181499
American Medical Association (AMA)
Cerreto, Fabrizio& Nielsen, Bo Friis& Nielsen, Otto Anker& Harrod, Steven S.. Application of Data Clustering to Railway Delay Pattern Recognition. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-18.
https://search.emarefa.net/detail/BIM-1181499
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181499