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Automatic Trip Detection with the Dutch Mobile Mobility Panel: Towards Reliable Multiple-Week Trip Registration for Large Samples

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  • Tom Thomas
  • Karst T. Geurs
  • Johan Koolwaaij
  • Marcel Bijlsma

Abstract

This paper examines the accuracy of trip and mode choice detection of the last wave of the Dutch Mobile Mobility Panel, a large-scale three-year, smartphone-based travel survey. Departure and arrival times, origins, destinations, modes, and travel purposes were recorded during a four week period in 2015, using the MoveSmarter app for a representative sample of 615 respondents, yielding over 60 thousand trips. During the monitoring period, respondents also participated in a web-based prompted recall survey and answered additional questions. This enables a comparison between automatic detected and reported trips. Most trips were detected with no clear biases in trip length or duration, and transport modes were classified correctly for over 80 percent of these trips. There is strong evidence that smartphone-based trip detection helps to reduce underreporting of trips, which is a common phenomenon in travel surveys. In the Dutch Mobile Mobility Panel, trip rates are substantially higher than trip-diary based travel surveys in the Netherlands, in particular for business and leisure trips which are often irregular. The rate of reporting also hardly decreased during the four-week period, which is a promising result for the use of smartphones in long duration travel surveys.

Suggested Citation

  • Tom Thomas & Karst T. Geurs & Johan Koolwaaij & Marcel Bijlsma, 2018. "Automatic Trip Detection with the Dutch Mobile Mobility Panel: Towards Reliable Multiple-Week Trip Registration for Large Samples," Journal of Urban Technology, Taylor & Francis Journals, vol. 25(2), pages 143-161, April.
    • Handle: RePEc:taf:cjutxx:v:25:y:2018:i:2:p:143-161
    DOI: 10.1080/10630732.2018.1471874
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    Cited by:

    1. de Jong, Tineke & Fyhri, Aslak, 2023. "Spatial characteristics of unpleasant cycling experiences," Journal of Transport Geography, Elsevier, vol. 112(C).
    2. Tineke de Jong & Lars Böcker & Christian Weber, 2023. "Road infrastructures, spatial surroundings, and the demand and route choices for cycling: Evidence from a GPS-based mode detection study from Oslo, Norway," Environment and Planning B, , vol. 50(8), pages 2133-2150, October.
    3. Ciccone, A. & Fyhri, A. & Sundfør, H.B., 2021. "Using behavioral insights to incentivize cycling: Results from a field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1035-1058.

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