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Consistently estimating link speed using sparse GPS data with measured errors



Data sources using new technology such as the Geographical Positioning System are increasingly available. In many different applications, it is important to predict the average speed on all the links in a network. The purpose of this study is to estimate the link speed in a network using sparse GPS data set. Average speed is consistently estimated using Indirect Inference approach. In the end, the Monte Carlo evidence is provided to show that the results are consistent with parameter estimates.

Suggested Citation

  • Fadaei Oshyani, Masoud & Sundberg, Marcus & Karlström, Anders, 2013. "Consistently estimating link speed using sparse GPS data with measured errors," Working papers in Transport Economics 2013:12, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
  • Handle: RePEc:hhs:ctswps:2013_012
    Note: To be published in the proceedings of the 16th Euro Working Group on Transportation, Porto, Portugal, 4-6 September 2013. QS 2013

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    References listed on IDEAS

    1. Jenelius, Erik & Koutsopoulos, Haris N., 2013. "Travel time estimation for urban road networks using low frequency probe vehicle data," Transportation Research Part B: Methodological, Elsevier, vol. 53(C), pages 64-81.
    2. Frejinger, E. & Bierlaire, M., 2007. "Capturing correlation with subnetworks in route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 363-378, March.
    3. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 85-118, Suppl. De.
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    More about this item


    Travel time; Sparse GPS data; Indirect inference; Map matching; Route choice.;

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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