Estimation and monitoring of city-to-city travel times using call detail records

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Kujala, Rainer Aledavood, Talayeh Saramäki, Jari 2017-05-11T07:35:59Z 2017-05-11T07:35:59Z 2016-12-01
dc.identifier.citation Kujala , R , Aledavood , T & Saramäki , J 2016 , ' Estimation and monitoring of city-to-city travel times using call detail records ' EPJ DATA SCIENCE , vol 5 , no. 1 , 6 . DOI: 10.1140/epjds/s13688-016-0067-3 en
dc.identifier.issn 2193-1127
dc.identifier.other PURE UUID: 62949e81-3c6a-47f8-b14e-92eaa38695a5
dc.identifier.other PURE ITEMURL:
dc.identifier.other PURE LINK:
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dc.description.abstract Whenever someone makes or receives a call on a mobile telephone, a Call Detail Record (CDR) is automatically generated by the operator for billing purposes. CDRs have a wide range of applications beyond billing, from social science to data-driven development. Recently, CDRs have been increasingly used to study human mobility, whose understanding is crucial e.g. for planning efficient transportation infrastructure. A major difficulty in analyzing human mobility using CDR data is that the location of a cell phone user is not recorded continuously but typically only when a call is initiated or a text message is sent. In this paper we address this problem, and develop a method for estimating travel times between cities based on CDRs that relies not on individual trajectories of people, but their collective statistical properties. We apply our method to data from Senegal, released by Sonatel and Orange for the 2014 Data for Development Challenge. We turn CDR mobility traces to estimates on travel times between Senegalese cities, filling an existing gap in knowledge. Moreover, the proposed method is shown to be highly valuable for monitoring travel conditions and their changes in near real-time, as demonstrated by measuring the decrease in travel times due to the opening of the Dakar-Diamniadio highway. Overall, our results indicate that it is possible to extract reliable de facto information on typical travel times that is useful for a variety of audiences ranging from casual travelers to transport infrastructure planners. en
dc.format.extent 16
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries EPJ DATA SCIENCE en
dc.relation.ispartofseries Volume 5, issue 1 en
dc.rights openAccess en
dc.subject.other Computer Science Applications en
dc.subject.other Computational Mathematics en
dc.subject.other Modelling and Simulation en
dc.subject.other 113 Computer and information sciences en
dc.title Estimation and monitoring of city-to-city travel times using call detail records en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Computer Science
dc.subject.keyword call detail records
dc.subject.keyword data for development
dc.subject.keyword mobile phones
dc.subject.keyword near real-time monitoring
dc.subject.keyword travel time estimation
dc.subject.keyword Computer Science Applications
dc.subject.keyword Computational Mathematics
dc.subject.keyword Modelling and Simulation
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201705113937
dc.identifier.doi 10.1140/epjds/s13688-016-0067-3
dc.type.version publishedVersion

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