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A Vehicle Telematics Service for Driving Style Detection: Implementation and Privacy Challenges

Topics: Big Data and Vehicle Analytics; Connected Services; Driver Behavior Analysis; Information Systems and Technologies; Mobility and the Internet of Vehicles; Security and Safety; Traffic and Vehicle Data Collection and Processing; Vehicle Information Systems; Vehicle Telematics; Vehicular Cloud Computing

Authors: Christian Kaiser 1 ; Alexander Stocker 1 ; Andreas Festl 1 ; Marija Djokic Petrovic 1 ; Efi Papatheocharous 2 ; Anders Wallberg 2 ; Gonzalo Ezquerro 3 ; Jordi Ortigosa Orbe 3 ; Tom Szilagyi 4 and Michael Fellmann 4

Affiliations: 1 Virtual Vehicle Research GmbH, Graz, Austria ; 2 RISE (Research Institutes of Sweden), Kista, Sweden ; 3 JIG, Logroño, Spain ; 4 University of Rostock, Rostock, Germany

Keyword(s): Automotive, Connected Vehicles, Data-driven Services, Vehicle Telematics Service, Privacy, Trust, Cloud Computing, Mobile Driver Application, Quantified Vehicles.

Abstract: Connected mobility is not only a future market, but also holds great innovation potential. The analysis of vehicle telematics data in the cloud enables novel data-driven services for several stakeholders, e.g. a mobile application for the driver to obtain his driving style. This inevitably leads to privacy concerns and the question why and when are users willing to share driving telematic data, which we addressed in an empirical study. The paper presents an implementation of a data-driven service based on vehicle telematics data and discusses how privacy issues can be tackled. For the data-driven service, the most interesting steps along the vehicle data value chain are described in detail, firstly (i) vehicle telematics data collection, secondly, (ii) the wireless data transfer to a cloud platform, and thirdly, (iii) pre-processing and data analysis to evaluate the drivers’ driving style and analyse the driving risk. Finally, (iv) a smartphone application for drivers presents drivin g style and driving risk data on the smartphone in an interactive way, so that the driver can work on improving both, which has a positive effect on driving and road safety. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Kaiser, C.; Stocker, A.; Festl, A.; Petrovic, M.; Papatheocharous, E.; Wallberg, A.; Ezquerro, G.; Orbe, J.; Szilagyi, T. and Fellmann, M. (2020). A Vehicle Telematics Service for Driving Style Detection: Implementation and Privacy Challenges. In Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-419-0; ISSN 2184-495X, SciTePress, pages 29-36. DOI: 10.5220/0009329400290036

@conference{vehits20,
author={Christian Kaiser. and Alexander Stocker. and Andreas Festl. and Marija Djokic Petrovic. and Efi Papatheocharous. and Anders Wallberg. and Gonzalo Ezquerro. and Jordi Ortigosa Orbe. and Tom Szilagyi. and Michael Fellmann.},
title={A Vehicle Telematics Service for Driving Style Detection: Implementation and Privacy Challenges},
booktitle={Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2020},
pages={29-36},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009329400290036},
isbn={978-989-758-419-0},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - A Vehicle Telematics Service for Driving Style Detection: Implementation and Privacy Challenges
SN - 978-989-758-419-0
IS - 2184-495X
AU - Kaiser, C.
AU - Stocker, A.
AU - Festl, A.
AU - Petrovic, M.
AU - Papatheocharous, E.
AU - Wallberg, A.
AU - Ezquerro, G.
AU - Orbe, J.
AU - Szilagyi, T.
AU - Fellmann, M.
PY - 2020
SP - 29
EP - 36
DO - 10.5220/0009329400290036
PB - SciTePress