Artikel
Convolutional neural network classification of telematics car driving data
The aim of this project is to analyze high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, deceleration, and changes of direction from this high-frequency GPS location data. Time series of this feature information allow us to appropriately allocate individual car driving trips to selected drivers using convolutional neural networks.
- Language
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Englisch
- Bibliographic citation
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Journal: Risks ; ISSN: 2227-9091 ; Volume: 7 ; Year: 2019 ; Issue: 1 ; Pages: 1-18 ; Basel: MDPI
- Classification
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Wirtschaft
- Subject
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telematics car driving data
driving styles
pattern recognition
image recognition
convolutional neural networks
- Event
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Geistige Schöpfung
- (who)
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Gao, Guangyuan
Wüthrich, Mario V.
- Event
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Veröffentlichung
- (who)
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MDPI
- (where)
-
Basel
- (when)
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2019
- DOI
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doi:10.3390/risks7010006
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Gao, Guangyuan
- Wüthrich, Mario V.
- MDPI
Time of origin
- 2019
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