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Monitoring Driver Behaviour with BackPocketDriver

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Mobile Web and Intelligent Information Systems (MobiWIS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11673))

Abstract

Road safety is an international public health issue with youth drivers being grossly overrepresented in road crash fatalities and injuries. Our work centres on the use of smartphone technology to deliver an intervention that aims to improve driving behaviour. In this paper we describe the technical design of our BackPocketDriver app, which monitors key facets of driver behaviour: speed and acceleration. We present the app’s requirements that were elicited through engagement with stakeholders and end users, and describe how the app has been designed to satisfy the requirements. In addition, we report on a quantitative evaluation of the app and show that in addition to meeting the requirements, a contemporary smartphone has sufficient sensory fidelity for building driver behaviour apps.

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Notes

  1. 1.

    https://www.vboxautomotive.co.uk/index.php/en/products/modules/inertial-measurement-unit.

  2. 2.

    https://en.wikipedia.org/wiki/World_Geodetic_System.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Auckland, Auckland, New Zealand

    Ian Warren, Andrew Meads & Chong Wang

  2. National Institute for Health Innovation, University of Auckland, Auckland, New Zealand

    Robyn Whittaker

Authors
  1. Ian Warren
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  2. Andrew Meads
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  3. Chong Wang
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  4. Robyn Whittaker
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Corresponding author

Correspondence to Ian Warren .

Editor information

Editors and Affiliations

  1. University of Bradford, Bradford, UK

    Irfan Awan

  2. Oxford Brookes University, Oxford, UK

    Muhammad Younas

  3. Teknopark Ankara, Ankara, Turkey

    Perin Ünal

  4. ABB AG Forschungszentrum, Ladenburg, Germany

    Markus Aleksy

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Warren, I., Meads, A., Wang, C., Whittaker, R. (2019). Monitoring Driver Behaviour with BackPocketDriver. In: Awan, I., Younas, M., Ünal, P., Aleksy, M. (eds) Mobile Web and Intelligent Information Systems. MobiWIS 2019. Lecture Notes in Computer Science(), vol 11673. Springer, Cham. https://doi.org/10.1007/978-3-030-27192-3_5

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  • DOI: https://doi.org/10.1007/978-3-030-27192-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27191-6

  • Online ISBN: 978-3-030-27192-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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