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Understanding Driver Expectations and Preferences Around Data Transparency in Vehicular Digital Twins

Research output: Chapter in Book/Report/Conference proceeding/Legal commentaryConference contributionpeer-review

Abstract

While vehicles become more data-intensive, hardly any studies have systematically examined how drivers of such vehicles perceive the various privacy aspects related to the potential data usage. To address this gap, we present preliminary findings from an online survey of 30 drivers that investigates their expectations and preferences around data transparency in the context of vehicular digital twins (VDTs). We found that privacy aspects related to data access and control are important for potential VDT users, although they expressed uncertainty about their understanding of how the data is collected and used. Nevertheless, participants also showed some tolerance towards data collection and usage if it would potentially have a direct personal benefit. To inform future design of user-centered and privacy-aware VDT interfaces, we conclude that it is relevant to include and further discuss how the expectation of personal benefits might alter or even compromise privacy concerns.

Original languageEnglish
Title of host publication Adjunct Proceedings of the 17th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '25 Adjunct)
PublisherACM
Pages227-232
Number of pages6
ISBN (Electronic)9798400720147
ISBN (Print)979-8-4007-2014-7
DOIs
Publication statusPublished - Oct 2025
Event 17th International ACM Conference on Automotive User Interfaces
and Interactive Vehicular Applications
- Queensland University of Technology (QUT), Brisbane, Australia
Duration: 22 Sept 202525 Sept 2025
Conference number: 17
https://www.auto-ui.org/25/

Conference

Conference 17th International ACM Conference on Automotive User Interfaces
and Interactive Vehicular Applications
Abbreviated titleAutoUI ’25
Country/TerritoryAustralia
CityBrisbane
Period22/09/2525/09/25
Internet address

Keywords

  • Data Transparency
  • Driver-Vehicle Interaction
  • User Study
  • Vehicular Digital Twins

Fields of Science and Technology Classification 2012

  • 102 Computer Sciences

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