Journal article
Who is to blame for crashes involving autonomous vehicles? Exploring blame attribution across the road transport system
Ergonomics, Vol.63(5), pp.525-537
2020
Abstract
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 in regard to vehicle type. However, the government received more blame in high severity crashes. The findings have implications for policy and legislation surrounding crash liability.
Details
- Title
- Who is to blame for crashes involving autonomous vehicles? Exploring blame attribution across the road transport system
- Authors
- Elin Pollanen (Author) - University of the Sunshine Coast - School of Social SciencesGemma J M Read (Author) - University of the Sunshine CoastBen R Lane (Author) - University of the Sunshine CoastJason Thompson (Author) - University of MelbournePaul M Salmon (Author) - University of the Sunshine Coast
- Publication details
- Ergonomics, Vol.63(5), pp.525-537
- Publisher
- Taylor & Francis Ltd.
- DOI
- 10.1080/00140139.2020.1744064
- ISSN
- 0014-0139
- Organisation Unit
- University of the Sunshine Coast, Queensland; Centre for Human Factors and Sociotechnical Systems; School of Law and Society; School of Health - Psychology
- Language
- English
- Record Identifier
- 99451329602621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Engineering, Industrial
- Ergonomics
- Psychology
- Psychology, Applied
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