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.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Risks ; ISSN: 2227-9091 ; Volume: 7 ; Year: 2019 ; Issue: 1 ; Pages: 1-18 ; Basel: MDPI
- Klassifikation
-
Wirtschaft
- Thema
-
telematics car driving data
driving styles
pattern recognition
image recognition
convolutional neural networks
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Gao, Guangyuan
Wüthrich, Mario V.
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2019
- DOI
-
doi:10.3390/risks7010006
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Gao, Guangyuan
- Wüthrich, Mario V.
- MDPI
Entstanden
- 2019
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