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Using smartphone logging to gain insight about phone use in traffic
Swedish National Road and Transport Research Institute, Traffic and road users, Human Factors in the Transport System.ORCID iD: 0000-0003-4134-0303
Mobile Behaviour.
Designingenjörerna Sverige AB.
Designingenjörerna Sverige AB.
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2019 (English)In: Cognition, Technology & Work, ISSN 1435-5558, E-ISSN 1435-5566Article in journal (Refereed) Published
Abstract [en]

The prevalence of mobile phone usage in traffic has been studied by road-side counting, naturalistic driving data, surveillance cameras, smartphone logging, and subjective estimates via surveys. Here, we describe a custom-made smartphone logging application along with suggestions on how future such applications should be designed. The developed application logs’ start and end times of all phone interactions (mobile phone applications, incoming/outgoing phone calls and text messages, audio output, and screen activations). In addition, all movements are automatically classified into transport, cycling, walking, running, or stationary. The capabilities of the approach are demonstrated in a pilot study with 143 participants. Examples of results that can be gained from smartphone logging include prevalence in different transportation modes (here found to be 12% while driving, 4% while cycling, and 7% while walking), which apps are being used (here found to be 19% navigation, 12% talking, 12% social media, and 10% games) and on which road types (rural, urban, highway etc.). Smartphone logging was found to be an insightful complement to the other methods for assessing phone use in traffic, especially since it allows the analyses of which apps are used and where they are used, split into transportation mode and road type, all at a relatively low cost.

Place, publisher, year, edition, pages
Springer London , 2019.
Keywords [en]
Mobile phone, Use, Data acquisition, Mobile application, Transport mode
National Category
Applied Psychology
Research subject
80 Road: Traffic safety and accidents, 841 Road: Road user behaviour
Identifiers
URN: urn:nbn:se:vti:diva-13654DOI: 10.1007/s10111-019-00547-6Scopus ID: 2-s2.0-85061633847OAI: oai:DiVA.org:vti-13654DiVA, id: diva2:1316313
Available from: 2019-05-17 Created: 2019-05-17 Last updated: 2022-03-18Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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  • nn-NB
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  • Other locale
More languages
Output format
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