Complex delay dynamics on railway networks from universal laws to realistic modelling
dc.contributor.author | Monechi, B | |
dc.contributor.author | Gravino, P | |
dc.contributor.author | Di Clemente, R | |
dc.contributor.author | Servedio, VDP | |
dc.date.accessioned | 2020-01-29T09:50:28Z | |
dc.date.issued | 2018-09-17 | |
dc.description.abstract | Railways are a key infrastructure for any modern country. The reliability and resilience of this peculiar transportation system may be challenged by different shocks such as disruptions, strikes and adverse weather conditions. These events compromise the correct functioning of the system and trigger the spreading of delays into the railway network on a daily basis. Despite their importance, a general theoretical understanding of the underlying causes of these disruptions is still lacking. In this work, we analyse the Italian and German railway networks by leveraging on the train schedules and actual delay data retrieved during the year 2015. We use these data to infer simple statistical laws ruling the emergence of localized delays in different areas of the network and we model the spreading of these delays throughout the network by exploiting a framework inspired by epidemic spreading models. Our model offers a fast and easy tool for the preliminary assessment of the effectiveness of traffic handling policies, and of the railway network criticalities. | en_GB |
dc.description.sponsorship | John Templeton Foundation | en_GB |
dc.description.sponsorship | Austrian Research Promotion Agency FFG | en_GB |
dc.description.sponsorship | Newton International Fellowship | en_GB |
dc.description.sponsorship | The Royal Society | en_GB |
dc.description.sponsorship | The British Academy | en_GB |
dc.description.sponsorship | Academy of Medical Sciences | en_GB |
dc.identifier.citation | Vol. 7, article 35 | en_GB |
dc.identifier.doi | 10.1140/epjds/s13688-018-0160-x | |
dc.identifier.grantnumber | 51663 | en_GB |
dc.identifier.grantnumber | 857136 | en_GB |
dc.identifier.grantnumber | NF170505 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/40626 | |
dc.language.iso | en | en_GB |
dc.publisher | EDP Sciences with SpringerOpen and Società Italiana di Fisica | en_GB |
dc.rights | © The Author(s) 2018. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. | en_GB |
dc.subject | Complex systems | en_GB |
dc.subject | Networks | en_GB |
dc.subject | Delay dynamics | en_GB |
dc.subject | Modelling | en_GB |
dc.subject | Spreading | en_GB |
dc.title | Complex delay dynamics on railway networks from universal laws to realistic modelling | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-01-29T09:50:28Z | |
dc.description | This is the final version. Available from EDP Sciences via the DOI in this record. | en_GB |
dc.description | The datasets supporting the conclusions of this article are included within the article (and its additional files). | en_GB |
dc.identifier.journal | EPJ Data Science | en_GB |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2018-08-30 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2018-08-30 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-01-29T09:44:26Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2020-01-29T09:50:32Z | |
refterms.panel | B | en_GB |
refterms.depositException | publishedGoldOA |
Files in this item
This item appears in the following Collection(s)
Except where otherwise noted, this item's licence is described as © The Author(s) 2018. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.