Convolutional neural network classification of telematics car driving data

Guangyuan Gao and Mario V. Wüthrich

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.

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Year of publication:	2019
Authors:	Gao, Guangyuan ; Wüthrich, Mario V.
Subject:	telematics car driving data \| driving styles \| pattern recognition \| image recognition \| convolutional neural networks \| Neuronale Netze \| Neural networks \| Kraftfahrzeug \| Motor vehicle \| Kfz-Industrie \| Automotive industry \| Telekommunikation \| Telecommunications \| Straßenverkehr \| Road transport

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Type of publication:	Article
Type of publication (narrower categories):	Aufsatz in Zeitschrift ; Article in journal
Language:	English
Other identifiers:	10.3390/risks7010006 [DOI] hdl:10419/257844 [Handle]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012018697