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Tytuł pozycji:

Who is to blame for crashes involving autonomous vehicles? Exploring blame attribution across the road transport system.

Tytuł:
Who is to blame for crashes involving autonomous vehicles? Exploring blame attribution across the road transport system.
Autorzy:
Pöllänen E; School of Social Sciences, University of the Sunshine Coast, Maroochydore, Australia.
Read GJM; Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore, Australia.
Lane BR; Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore, Australia.
Thompson J; Faculty of Architecture, Building and Planning, Melbourne School of Design, Transport, Health and Urban Design (THUD) Research Hub, University of Melbourne, Melbourne, Australia.
Salmon PM; Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore, Australia.
Źródło:
Ergonomics [Ergonomics] 2020 May; Vol. 63 (5), pp. 525-537. Date of Electronic Publication: 2020 Apr 03.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Publication: London : Informa Healthcare
Original Publication: London, Taylor & Francis.
MeSH Terms:
Accidents, Traffic*
Automation*
Automobile Driving*
Liability, Legal*
Safety*
Adolescent ; Adult ; Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Surveys and Questionnaires ; Young Adult
Contributed Indexing:
Keywords: Road crashes; autonomous vehicles; blame attribution; liability; self-driving cars
Entry Date(s):
Date Created: 20200318 Date Completed: 20200825 Latest Revision: 20200825
Update Code:
20240105
DOI:
10.1080/00140139.2020.1744064
PMID:
32180531
Czasopismo naukowe
The introduction of fully autonomous vehicles is approaching. This warrants a re-consideration of road crash liability, given drivers will have diminished control. This study, underpinned by attribution theory, investigated blame attribution to different road transport system actors following crashes involving manually driven, semi-autonomous and fully autonomous vehicles. It also examined whether outcome severity alters blame ratings. 396 participants attributed blame to five actors (vehicle driver/user, pedestrian, vehicle, manufacturer, government) in vehicle-pedestrian crash scenarios. Different and unique patterns of blame were found across actors, according to the three vehicle types. In crashes involving fully autonomous vehicles, vehicle users received low blame, while vehicle manufacturers and government were highly blamed. There was no difference in the level of blame attributed between high and low severity crashes regarding vehicle type. However, the government received more blame in high severity crashes. The findings have implications for policy and legislation surrounding crash liability. Practitioner summary: Public views relating to blame and liability in transport accidents is a vital consideration for the introduction of new technologies such as autonomous vehicles. This study demonstrates how a systems ergonomics framework can assist to identify the implications of changing public opinion on blame for future road transport systems. Abbreviation: ANOVA: analysis of variance; DAT: defensive attribution theory; IV: independent variable.

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