Convolutional Neural Network Classification of Telematics Car Driving Data

18 Pages Posted: 1 Nov 2018

See all articles by Guangyuan Gao

Guangyuan Gao

Renmin University of China - School of Statistics

Mario V. Wuthrich

RiskLab, ETH Zurich

Date Written: October 18, 2018

Abstract

The aim of this project is to analyse high-frequency GPS location data (second per second) of individual car drivers (and trips). We extract feature information about speeds, acceleration, braking 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.

Keywords: telematics car driving data, driving styles, pattern recognition, image recognition, convolutional neural networks

JEL Classification: G22, C02, C45

Suggested Citation

Gao, Guangyuan and Wuthrich, Mario V., Convolutional Neural Network Classification of Telematics Car Driving Data (October 18, 2018). Available at SSRN: https://ssrn.com/abstract=3269283 or http://dx.doi.org/10.2139/ssrn.3269283

Guangyuan Gao

Renmin University of China - School of Statistics ( email )

No.59 Zhongguancun Street, Renmin University
Beijing, 100872
China

Mario V. Wuthrich (Contact Author)

RiskLab, ETH Zurich ( email )

Department of Mathematics
Ramistrasse 101
Zurich, 8092
Switzerland

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