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Review of GPS Travel Survey and GPS Data-Processing Methods

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  • Li Shen
  • Peter R. Stopher

Abstract

Global positioning system (GPS) devices have been utilised in travel surveys since the late 1990s. Because GPS devices are very accurate at recording time and positional characteristics of travel, they can correct the trip-misreporting issue resulting from self-reports of travel and improve the accuracy of travel data. Although the initial idea of using GPS surveys in transport data collection was just to replace paper-based travel diaries, GPS surveys currently are being applied in a number of transport fields. Several general reviews have been done about GPS surveys in the literature review sections in some papers, but a detailed systematic review from GPS data collection to the whole procedure of GPS data processing has not been undertaken. This paper comprehensively reviews the development of GPS surveys and their applications, and GPS data processing. Different from most reviews in GPS research, this paper provides a detailed and systematic comparison between different methods from trip identification to mode and purpose detection, introduces the methods that researchers and planners are currently using, and discusses the pros and cons of those methods. Based on this review, researchers can choose appropriate methods and endeavour to improve them.

Suggested Citation

  • Li Shen & Peter R. Stopher, 2014. "Review of GPS Travel Survey and GPS Data-Processing Methods," Transport Reviews, Taylor & Francis Journals, vol. 34(3), pages 316-334, May.
    • Handle: RePEc:taf:transr:v:34:y:2014:i:3:p:316-334
    DOI: 10.1080/01441647.2014.903530
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    References listed on IDEAS

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    1. Kevin Krizek & Ahmed El-Geneidy & Kristin Thompson, 2007. "A detailed analysis of how an urban trail system affects cyclists’ travel," Transportation, Springer, vol. 34(5), pages 611-624, September.
    2. Broach, Joseph & Dill, Jennifer & Gliebe, John, 2012. "Where do cyclists ride? A route choice model developed with revealed preference GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1730-1740.
    3. Menghini, G. & Carrasco, N. & Schüssler, N. & Axhausen, K.W., 2010. "Route choice of cyclists in Zurich," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 754-765, November.
    4. Paul Kelly & Patricia Krenn & Sylvia Titze & Peter Stopher & Charlie Foster, 2013. "Quantifying the Difference Between Self-Reported and Global Positioning Systems-Measured Journey Durations: A Systematic Review," Transport Reviews, Taylor & Francis Journals, vol. 33(4), pages 443-459, July.
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    Cited by:

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