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    GPS accuracy estimation using map matching techniques: Applied to vehicle positioning and odometer calibration


    Taylor, George and Brunsdon, Chris and Li, Jing and Olden, Andrew and Steup, Dorte and Winter, Marylin (2006) GPS accuracy estimation using map matching techniques: Applied to vehicle positioning and odometer calibration. Computers, Environment and Urban Systems, 30 (6). pp. 757-772. ISSN 0198-9715

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    Abstract

    A test-bed application, called Map Matched GPS (MMGPS) processes raw GPS output data, from RINEX files, or GPS derived coordinates. This developed method uses absolute GPS position- ing, map matched, to locate the vehicle on a road centre-line, when GPS is known to be sufficiently accurate. MMGPS software has now been adapted to incorporate positioning based on odometer derived distances (OMMGPS), when GPS positions are not available. Relative GPS positions are used to calibrate the odometer. If a GPS position is detected to be inaccurate, it is not used for posi- tioning, or for calibrating the odometer correction factor. In OMMGPS, GPS pseudorange obser- vations are combined with DTM height information and odometer positions to provide a vehicle position at ‘1 s’ epochs. The described experiment used GPS and odometer observations taken on a London bus on a predefined route in central of London. Therefore, map matching techniques are used to test GPS positioning accuracy, and to identify grossly inaccurate GPS positions. In total, over 15,000 vehicle positions were computed and tested using OMMGPS. In general, the position quality provided by GPS alone was extremely poor, due to multipath effects caused by the urban canyons of central London, so that odometer positioning was used much more often to position the vehicle than GPS. Typically, the ratio is 7:3 odometer positions to GPS positions. In the case of one particular trip, OMMGPS provides a mean error of position of 8.8 m compared with 53.7 m for raw GPS alone.

    Item Type: Article
    Keywords: GPS; Odometer calibration; Map matching;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 6150
    Identification Number: https://doi.org/10.1016/j.compenvurbsys.2006.02.006
    Depositing User: Prof. Chris Brunsdon
    Date Deposited: 26 May 2015 14:41
    Journal or Publication Title: Computers, Environment and Urban Systems
    Publisher: Elsevier
    Refereed: Yes
    URI:

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