IDEAS home Printed from
   My bibliography  Save this article

Increasing the accuracy of trip rate information from passive multi-day GPS travel datasets: Automatic trip end identification issues


  • Du, Jianhe
  • Aultman-Hall, Lisa


With the availability of Global Positioning System (GPS) receivers to capture vehicle location, it is now feasible to easily collect multiple days of travel data automatically. However, GPS-collected data are not ready for direct use in trip rate or route choice research until trip ends are identified within large GPS data streams. One common parameter used to divide trips is dwell time, the time a vehicle is stationary. Identifying trips is particularly challenging when there is trip chaining with brief stops, such as picking up and dropping off passengers. It is hard to distinguish these stops from those caused by traffic controls or congestion. Although the dwell time method is effective in many cases, it is not foolproof and recent research indicates use of additional logic improves trip dividing. While some studies incorporating more than dwell time to identify trip ends having been conducted, research including actual trip ends to evaluate the success of trip dividing methods used have been limited. In this research, 12 ten-day real-world GPS travel datasets were used to develop, calibrate and compare three methods to identify trip start points in the data stream. The true start and end points of each trip were identified in advance in the GPS data stream using a supplemental trip log completed by the participants so that the accuracy of each automated trip division method could be measured and compared. A heuristic model, which combines heading change, dwell time and distance between the GPS points and the road network, performs best, correctly identifying 94% of trip ends.

Suggested Citation

  • Du, Jianhe & Aultman-Hall, Lisa, 2007. "Increasing the accuracy of trip rate information from passive multi-day GPS travel datasets: Automatic trip end identification issues," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(3), pages 220-232, March.
  • Handle: RePEc:eee:transa:v:41:y:2007:i:3:p:220-232

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

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


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Joubert, Johan W. & Meintjes, Sumarie, 2015. "Repeatability & reproducibility: Implications of using GPS data for freight activity chains," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 81-92.
    2. Chen, Cynthia & Gong, Hongmian & Lawson, Catherine & Bialostozky, Evan, 2010. "Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 830-840, December.
    3. repec:gam:jsusta:v:9:y:2017:i:6:p:949-:d:100527 is not listed on IDEAS
    4. Yijing Lu & Lei Zhang, 2015. "Imputing trip purposes for long-distance travel," Transportation, Springer, vol. 42(4), pages 581-595, July.

    More about this item


    Access and download statistics


    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:eee:transa:v:41:y:2007:i:3:p:220-232. 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: (Dana Niculescu). General contact details of provider: .

    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.