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Vehicle point of interest detection using in-car data
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Van Hinsbergh, James, Griffiths, Nathan, Taylor, Phillip M., Thomason, Alasdair, Xu, Zhou and Mouzakitis, Alexandros (2018) Vehicle point of interest detection using in-car data. In: 2nd International Workshop on AI for Geographic Knowledge Discovery, 2018, Seattle, WA, 6-9 Nov 2018. Published in: GeoAI'18 Proceedings of the 2nd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery pp. 1-4. ISBN 9781450360364. doi:10.1145/3281548.3281549
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WRAP-vehicle-point-interest-detection-car-data-2018.pdf - Accepted Version - Requires a PDF viewer. Download (1918Kb) | Preview |
Official URL: http://doi.org/10.1145/3281548.3281549
Abstract
Intelligent transportation systems often identify and make use of locations extracted from GPS trajectories to make informed decisions. However, many of the locations identified by existing systems are false positives, such as those in heavy traffic. Signals from the vehicle, such as speed and seatbelt status, can be used to identify these false positives. In this paper, we (i) demonstrate the utility of the Gradient-based Visit Extractor (GVE) in the automotive domain, (ii) propose a classification stage for removing false positives from the location extraction process, and (iii) evaluate the effectiveness of these techniques in a high resolution vehicular dataset.
Item Type: | Conference Item (Paper) | |||||||||
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Subjects: | G Geography. Anthropology. Recreation > G Geography (General) T Technology > TE Highway engineering. Roads and pavements |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | |||||||||
Library of Congress Subject Headings (LCSH): | Intelligent transportation systems, Global Positioning System | |||||||||
Journal or Publication Title: | GeoAI'18 Proceedings of the 2nd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery | |||||||||
Publisher: | ACM | |||||||||
ISBN: | 9781450360364 | |||||||||
Official Date: | 2018 | |||||||||
Dates: |
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Page Range: | pp. 1-4 | |||||||||
DOI: | 10.1145/3281548.3281549 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Reuse Statement (publisher, data, author rights): | © The Author's | ACM 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in GeoAI'18 Proceedings of the 2nd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, http://dx.doi.org/10.1145/3281548.3281549 | |||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||
Date of first compliant deposit: | 4 October 2018 | |||||||||
Date of first compliant Open Access: | 24 April 2019 | |||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | |||||||||
Title of Event: | 2nd International Workshop on AI for Geographic Knowledge Discovery, 2018 | |||||||||
Type of Event: | Conference | |||||||||
Location of Event: | Seattle, WA | |||||||||
Date(s) of Event: | 6-9 Nov 2018 | |||||||||
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