Joint Subjective and Objective Data Capture and Analytics for Automotive Applications
Paper in proceeding, 2018

In this paper we describe a novel technological framework for capture and analysis of both objective measurement data and subjective user experience data for automotive applications. We also investigate how the framework can be extended to address privacy issues by enforcing a rigorous privacy model called differential privacy. The system under development integrates a telematics system with a smartphone app service architecture and a data-driven analytics framework. The hypothesis is that the framework will improve the opportunities of conducting large scale user trials of automotive functions and services, while improving the quality of collected data. To achieve this, a number of challenges are addressed in the paper, including how to design the subjective data capture mechanisms to be both simple to use yet powerful, how to correlate subjective data with objective measurement data, and how to protect the privacy of users.


Mathias Johanson

Alkit Communications AB

Jonas Jalminger

Alkit Communications AB

Emmanuel Frécon

RISE Research Institutes of Sweden

Boel Nelson

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Tomas Olovsson

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Mats Gjertz

Volvo Cars

IEEE Vehicular Technology Conference

15502252 (ISSN)

2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)
Toronto, ON, Canada,

Areas of Advance

Information and Communication Technology


Subject Categories

Computer and Information Science



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