Developing Markov chain models for train delay evolution in winter climate
The traffic on Swedish railways is increasing and punctuality is of important matter for both passenger and freight trains. The problem of modeling train delay evolution is complex since conflicts between trains can occur and since a delay can have a wide variety of causes. Swedish railways faces in...
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Umeå universitet, Institutionen för fysik
2021
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ftumeauniv:oai:DiVA.org:umu-179526 2023-10-09T21:53:13+02:00 Developing Markov chain models for train delay evolution in winter climate Sundqvist, Frej 2021 application/pdf http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-179526 eng eng Umeå universitet, Institutionen för fysik http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-179526 info:eu-repo/semantics/openAccess Markov chains Train delay Probability Theory and Statistics Sannolikhetsteori och statistik Other Computer and Information Science Annan data- och informationsvetenskap Student thesis info:eu-repo/semantics/bachelorThesis text 2021 ftumeauniv 2023-09-22T13:53:28Z The traffic on Swedish railways is increasing and punctuality is of important matter for both passenger and freight trains. The problem of modeling train delay evolution is complex since conflicts between trains can occur and since a delay can have a wide variety of causes. Swedish railways faces in addition harsh winter climate. Studies of railways in Scandinavia have shown that harsh winter climate decreases the punctuality of trains. This thesis work investigates the possibilities of modeling train delay evolution as continuous time Markov processes and which specific modeling choices are preferable. It also further assesses the impact of a harsh winter climate on the delay evolution. The studied segments are Stockholm - Umeå and Luleå - Kiruna. Both over one winter season. It was found that a change in the time schedule, which in a way redefines the delay, allows for a better fit and better prediction capabilities. It reduced the MSE of the prediction by 50 %. As for the weather variables, four variables were included together with their week long moving averages. Low temperatures were found to increase the risk of a delay (Hazard ratio of 1.10) as well as to decrease the chance of recovering from a delay (Hazard ratio of 0.91). No other significant weather impacts were found. Bachelor Thesis Kiruna Luleå Luleå Luleå Umeå University: Publications (DiVA) Kiruna |
institution |
Open Polar |
collection |
Umeå University: Publications (DiVA) |
op_collection_id |
ftumeauniv |
language |
English |
topic |
Markov chains Train delay Probability Theory and Statistics Sannolikhetsteori och statistik Other Computer and Information Science Annan data- och informationsvetenskap |
spellingShingle |
Markov chains Train delay Probability Theory and Statistics Sannolikhetsteori och statistik Other Computer and Information Science Annan data- och informationsvetenskap Sundqvist, Frej Developing Markov chain models for train delay evolution in winter climate |
topic_facet |
Markov chains Train delay Probability Theory and Statistics Sannolikhetsteori och statistik Other Computer and Information Science Annan data- och informationsvetenskap |
description |
The traffic on Swedish railways is increasing and punctuality is of important matter for both passenger and freight trains. The problem of modeling train delay evolution is complex since conflicts between trains can occur and since a delay can have a wide variety of causes. Swedish railways faces in addition harsh winter climate. Studies of railways in Scandinavia have shown that harsh winter climate decreases the punctuality of trains. This thesis work investigates the possibilities of modeling train delay evolution as continuous time Markov processes and which specific modeling choices are preferable. It also further assesses the impact of a harsh winter climate on the delay evolution. The studied segments are Stockholm - Umeå and Luleå - Kiruna. Both over one winter season. It was found that a change in the time schedule, which in a way redefines the delay, allows for a better fit and better prediction capabilities. It reduced the MSE of the prediction by 50 %. As for the weather variables, four variables were included together with their week long moving averages. Low temperatures were found to increase the risk of a delay (Hazard ratio of 1.10) as well as to decrease the chance of recovering from a delay (Hazard ratio of 0.91). No other significant weather impacts were found. |
format |
Bachelor Thesis |
author |
Sundqvist, Frej |
author_facet |
Sundqvist, Frej |
author_sort |
Sundqvist, Frej |
title |
Developing Markov chain models for train delay evolution in winter climate |
title_short |
Developing Markov chain models for train delay evolution in winter climate |
title_full |
Developing Markov chain models for train delay evolution in winter climate |
title_fullStr |
Developing Markov chain models for train delay evolution in winter climate |
title_full_unstemmed |
Developing Markov chain models for train delay evolution in winter climate |
title_sort |
developing markov chain models for train delay evolution in winter climate |
publisher |
Umeå universitet, Institutionen för fysik |
publishDate |
2021 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-179526 |
geographic |
Kiruna |
geographic_facet |
Kiruna |
genre |
Kiruna Luleå Luleå Luleå |
genre_facet |
Kiruna Luleå Luleå Luleå |
op_relation |
http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-179526 |
op_rights |
info:eu-repo/semantics/openAccess |
_version_ |
1779316458262626304 |