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Consistently estimating link speed using sparse GPS data with measured errors

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    Abstract

    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.

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    File URL: http://www.transportportal.se/swopec/CTS2013-12.pdf
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    Bibliographic Info

    Paper provided by CTS - Centre for Transport Studies Stockholm (KTH and VTI) in its series Working papers in Transport Economics with number 2013:12.

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    Length: 23 pages
    Date of creation: 16 Sep 2013
    Date of revision:
    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
    Contact details of provider:
    Postal: Centrum för Transportstudier (CTS), Teknikringen 10, 100 44 Stockholm, Sweden
    Web page: http://www.kth.se/abe/om_skolan/organisation/centra/cts

    Related research

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

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    1. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
    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. 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.
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