From Trolley to Autonomous Vehicle: Perceptions of Responsibility and Moral Norms in Traffic Accidents with Self-Driving Cars

2016-01-0164

04/05/2016

Event
SAE 2016 World Congress and Exhibition
Authors Abstract
Content
Autonomous vehicles represent a new class of transportation that may be qualitatively different from existing cars. Two online experiments assessed lay perceptions of moral norms and responsibility for traffic accidents involving autonomous vehicles. In Experiment 1, 120 US adults read a narrative describing a traffic incident between a pedestrian and a motorist. In different experimental conditions, the pedestrian, the motorist, or both parties were at fault. Participants assigned less responsibility to a self-driving car that was at fault than to a human driver who was at fault. Participants confronted with a self-driving car at fault allocated greater responsibility to the manufacturer and the government than participants who were confronted with a human driver at fault did. In Experiment 2, 120 US adults read a narrative describing a moral dilemma in which a human driver or a self-driving car must decide between either allowing five pedestrians to die or taking action to hit a single pedestrian in order to save the five. The “utilitarian” decision to hit the single pedestrian was considered the moral norm for both a self-driving and a human-driven car. Moreover, participants assigned the obligation of setting moral norms for self-driving cars to ethics researchers and to car manufacturers. This research reveals patterns of public perception of autonomous cars and may aid lawmakers and car manufacturers in designing such cars.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-0164
Pages
8
Citation
Li, J., Zhao, X., Cho, M., Ju, W. et al., "From Trolley to Autonomous Vehicle: Perceptions of Responsibility and Moral Norms in Traffic Accidents with Self-Driving Cars," SAE Technical Paper 2016-01-0164, 2016, https://doi.org/10.4271/2016-01-0164.
Additional Details
Publisher
Published
Apr 5, 2016
Product Code
2016-01-0164
Content Type
Technical Paper
Language
English