Understanding Drivers’ Trust After Software Malfunctions and Cyber Intrusions of Digital Displays in Automated Cars

William Payre, Jaume Perello March, Giedre Sabaliauskaite, Hesamaldin Jadidbonab, Siraj Shaikh, Hoang Nga Nguyen, Stewart Birrell

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

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Abstract

The aim of this paper is to examine the effect of explicit (i.e., ransomware) and silent (i.e., no turn signals) failures on drivers’ reported levels of trust and perception of risk. In a driving simulator study, 38 participants rode in a conditionally automated vehicle in built-up areas and motorways. They all experienced both failures. Not only levels of trust decreased after experiencing the failures, especially after the explicit one, but also some of the scores were low. This could mean cyber-attacks lead to distrust in automated driving, rather than merely decreasing levels of trust. Participants also seemed to differentiate connected driving from automated driving in terms of perception of risk. These results are discussed in the context of cyber intrusions as well as long- and
short-term trust.
Original languageEnglish
Title of host publicationHuman Factors in Transportation
Subtitle of host publicationAccelerating Open Access Science in Human Factors Engineering and Human-Centered Computing
EditorsKatie Plant, Gesa Praetorius
PublisherAHFE Conference
Pages320-328
Number of pages9
Volume60
ISBN (Print)9781958651360
DOIs
Publication statusPublished - 2022
Event13th International Conference on Applied Human Factors and Ergonomics - , United States
Duration: 24 Jul 202228 Jul 2022
https://2022.ahfe.org/

Conference

Conference13th International Conference on Applied Human Factors and Ergonomics
Abbreviated titleAHFE 2022
Country/TerritoryUnited States
Period24/07/2228/07/22
Internet address

Bibliographical note

© 2022. Published by AHFE Open Access. All rights reserved.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited..

Keywords

  • Trust
  • Automation
  • Automotive
  • Cyber security
  • Driving
  • Digital display
  • Perception of risk

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