Convolutional Neural Network Classification of Telematics Car Driving Data

Guangyuan Gao and Mario V. Wüthrich
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Guangyuan Gao: Center for Applied Statistics and School of Statistics, Renmin University of China, Beijing 100872, China
Mario V. Wüthrich: RiskLab, Department of Mathematics, ETH Zurich, 8092 Zürich, Switzerland

Risks, 2019, vol. 7, issue 1, 1-18

Abstract: 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.

Keywords: telematics car driving data; driving styles; pattern recognition; image recognition; convolutional neural networks (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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