Data for the study: "Mind the responsibility gap: the control ability of automated car drivers does not impact their perceived responsibility"

doi: 10.4121/16652056.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/16652056
Datacite citation style:
Beckers, Niek; Cavalcante Siebert, Luciano; Bruijnes, Merijn; C.M. (Catholijn) Jonker; Abbink, D.A. (David) (2021): Data for the study: "Mind the responsibility gap: the control ability of automated car drivers does not impact their perceived responsibility". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/16652056.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
This dataset contains the data and analysis scripts (R) for the study "Mind the responsibility gap: the control ability of automated car drivers does not impact their perceived responsibility"
The research objective was to gauge the general public's perception on the extent of responsibility for a human driver, an automated vehicle, and the vehicle's manufacturer in case the vehicle crashes. We measured the perceived responsibility to each of the three actors (human, vehicle, manufacturer), the perceived ability of the human driver to intervene and avoid the accident, and the situational awareness of the driver.
The data were gathered through an online questionnaire; participants were recruited through an online crowd-sourcing platform Prolific. Each participant was assigned to one of the five experiment conditions.
All data are quantitative data, with the responses on a 0-100 point scale for responsibility, ability, and awareness.
The analysis scripts execute the statistical analysis (moderated mediation) through a bootstrap confidence interval analysis.
history
  • 2021-09-22 first online, published, posted
publisher
4TU.ResearchData
format
.Rmd .Rda .csv .md .ipynb
organizations
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering, Department of Human-Robot Interaction.
TU Delft, Faculty of Electrical Engineering, Mathematics & Computer Science, Department of Interactive Intelligence.

DATA

files (5)