IDEAS home Printed from https://ideas.repec.org/a/taf/cjutxx/v25y2018i2p143-161.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10630732.2018.1471874
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:cjutxx:v:25:y:2018:i:2:p:143-161. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/cjut20 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.