Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

The blame game: double standards apply to autonomous vehicle accidents

Zhang, Qiyuan, Wallbridge, Christopher D. ORCID:, Jones, Dylan M. ORCID: and Morgan, Phil ORCID: 2021. The blame game: double standards apply to autonomous vehicle accidents. Presented at: AHFE 2021 Virtual Conference on Human Aspects of Transportation, Virtual, 25-29 July 2021. Advances in Human Aspects of Transportation. Lecture Notes in Networks and Systems Springer, Cham, pp. 308-314. 10.1007/978-3-030-80012-3_36

[thumbnail of Zhang. The Blame Game.pdf] PDF - Accepted Post-Print Version
Download (277kB)


Who is to blame when autonomous vehicles are involved in accidents? We report findings from an online study in which the attribution of blame and trust were measured from 206 participants who studied 18 hypothetical vignettes portraying traffic incidents under different driving environments. The focal vehicle involved in the incident was either controlled by a human driver or autonomous system. The accident severity also varied from near miss, minor accident to major accident. Participants applied double standards when assigning blame to humans and autonomous systems: an autonomous system was usually blamed more than a human driver for executing the same actions under the same circumstances with the same consequences. These findings not only have important implications to AI-related legislation, but also highlight the necessity to promote the design of robots and other automation systems which can help calibrate public perceptions and expectations of their characteristics and capabilities.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Psychology
Publisher: Springer, Cham
ISBN: 9783030800116
ISSN: 2367-3370
Date of First Compliant Deposit: 4 August 2021
Date of Acceptance: 3 May 2021
Last Modified: 10 Dec 2022 02:59

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics