Map Matching of GPS Data with Bayesian Belief Networks
This paper proposes a map matching algorithm using Bayesian belief network for GPS traces to generate the spatial-temporal information of individuals. The algorithm incorporates the road network topology, distance from trace nodes to road segments, the angle between two lines, direction difference, accuracy of measured GPS log point, and position of roads. The GPS data collected in the Eindhoven region, The Netherlands, was used to examine the performance of this algorithm. Results based on a small sample show that the algorithm has a good performance in both processing efficiency and prediction accuracy of correctly identified instances. Even with a small sample, the overall prediction accuracy reaches 87.02%.
- Record URL:
- Summary URL:
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Authors:
- Feng, Tao
- TIMMERMANS, Harry J P
- Publication Date: 2013
Language
- English
- Japanese
Media Info
- Media Type: Digital/other
- Features: Figures; Maps; References; Tables;
- Pagination: pp 100-112
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Serial:
- Journal of the Eastern Asia Society for Transportation Studies
- Volume: 10
- Issue Number: 0
- Publisher: Eastern Asia Society for Transportation Studies
- EISSN: 1881-1124
- Serial URL: https://www.jstage.jst.go.jp/browse/easts/-char/en
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Bayes' theorem; Connectivity; Distance; Global Positioning System; Maps; Networks
- Geographic Terms: Eindhoven (Netherlands)
- Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01506015
- Record Type: Publication
- Source Agency: Japan Science and Technology Agency (JST)
- Files: TRIS, JSTAGE
- Created Date: Jan 29 2014 7:32AM