Driver Identification via Brake Pedal Signals - A Replication and Advancement of Existing Techniques
Journal
IEEE International Conference on Intelligent Transportation Systems
Type
conference paper
Date Issued
2018-11
Author(s)
Abstract (De)
Driver identification is a growing topic which offers a streamlined user experience in the connected car, but potentially also highlights privacy issues of our interconnected lives. Recent studies have reported the ability for individuals to be reliably identified out of a group based on their driving behavior. In particular, the state-of-the-art study claims that, in a controlled setting, data collected on how a driver operated the brake pedal could separately identify each of the 15 drivers from the others. The paper at hand was not able to validate these strong scientific claims using naturalistic driving data. In line with the results of other studies using similar data, the replicated identification accuracy dropped to values between 40% and 70% by applying the outlined methods. Nevertheless, this paper further contributes to the field by presenting and evaluating an alternative feature collection technique in order to achieve identification results between 80% and 99.5% in this challenging setting, thus advancing the state-of-the-art. These findings demonstrate the real-world capabilities of data-enabled driver identification, which both facilitates new use-cases and potentially raises privacy questions. As such, important key features from the identification models are presented to assist both researchers and practitioners in this rapidly developing topic.
Funding(s)
Language
English
HSG Classification
contribution to scientific community
Book title
IEEE International Conference on Intelligent Transportation Systems
Publisher
IEEE
Volume
21
Pages
6
Event Title
IEEE International Conference on Intelligent Transportation Systems
Event Location
Maui, Hawaii, U.S.A.
Event Date
4.11-10.11.
Subject(s)
Contact Email Address
bernhard.gahr@unisg.ch
Eprints ID
255386
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Driver Identification via Brake Pedal Signals — A Replication and Advancement of Existing Techniques.pdf
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Format
Adobe PDF
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