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

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 driving 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.