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Trip extraction for traffic analysis using cellular network data
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-0353-6284
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5961-5136
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-6405-5914
Former Tele2.
2017 (English)In: 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) / [ed] IEEE Italy Section, Naples, 2017, 321-326 p.Conference paper, Published paper (Refereed)
Abstract [en]

To get a better understanding of people’s mobility, cellular network signalling data including location information, is a promising large-scale data source. In order to estimate travel demand and infrastructure usage from the data, it is necessary to identify the trips users make. We present two trip extraction methods and compare their performance using a small dataset collected in Sweden. The trips extracted are compared with GPS tracks collected on the same mobiles. Despite the much lower location sampling rate in the cellular network signalling data, we are able to detect most of the trips found from GPS data. This is promising, given the relative simplicity of the algorithms. However, further investigation is necessary using a larger dataset and more types of algorithms. By applying the same methods to a second dataset for Senegal with much lower sampling rate than the Sweden dataset, we show that the choice of the trip extraction method tends to be even more important when the sampling rate is low. 

Place, publisher, year, edition, pages
Naples, 2017. 321-326 p.
Keyword [en]
Global Positioning System, cellular radio, data communication, telecommunication traffic, Sweden, cellular network data, signalling data, traffic analysis, trip extraction, Antennas, Cellular networks, Data mining, Global Positioning System, Google, History, Spatial resolution
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:liu:diva-140906DOI: 10.1109/MTITS.2017.8005688ISBN: 978-1-5090-6484-7 (electronic)OAI: oai:DiVA.org:liu-140906DiVA: diva2:1141579
Conference
Models and Technologies for Intelligent Transportation Systems (MT-ITS), 26-28 June 2017, Naples, Italy
Projects
MOFT
Funder
VINNOVA
Available from: 2017-09-15 Created: 2017-09-15 Last updated: 2017-09-21Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf