Supplementary data for the paper 'Augmented reality for supporting the interaction between pedestrians and automated vehicles: An experimental outdoor study'

doi: 10.4121/a1f9f15c-1213-4657-8e4d-a154a725d747.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/a1f9f15c-1213-4657-8e4d-a154a725d747
Datacite citation style:
Aleva, Thomas; Wilbert Tabone; Dodou, Dimitra; de Winter, Joost (2024): Supplementary data for the paper 'Augmented reality for supporting the interaction between pedestrians and automated vehicles: An experimental outdoor study'. Version 1. 4TU.ResearchData. dataset.
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Communication from automated vehicles (AVs) to pedestrians using augmented reality (AR) could positively contribute to traffic safety. However, previous AR research for pedestrians was mainly conducted through online questionnaires or experiments in virtual environments instead of real ones. In this study, 28 participants conducted trials outdoors with an approaching AV and were supported by four different AR interfaces. The AR experience was created by having participants wear a Varjo XR-3 headset with see-through functionality, with the AV and AR elements virtually overlaid onto the real environment. The AR interfaces were vehicle-locked (Planes on vehicle), world-locked (Fixed pedestrian lights, Virtual fence), or head-locked (Pedestrian lights HUD). Participants had to hold down a button when they felt it was safe to cross, and their opinions were obtained through rating scales, interviews, and a questionnaire. The results showed that participants had a subjective preference for AR interfaces over no AR interface. Furthermore, the Pedestrian Lights HUD was more effective than no AR interface in a statistically significant manner, as it led to participants more frequently keeping the button pressed. The Fixed pedestrian lights scored lower than the other interfaces, presumably due to low saliency and the fact that participants had to visually identify both this AR interface and the AV. In conclusion, while users favour AR in AV-pedestrian interactions over no AR, its effectiveness depends on design factors like location, visibility, and visual attention demands. In conclusion, this work provides important insights into the use of AR outdoors. The findings illustrate that, in these circumstances, a clear and easily interpretable AR interface is of key importance.

  • 2024-01-08 first online, published, posted
script/m; data/mat; data/csv; data/xlsx; videos/mp4; images/png; images/docx; instructions/pdf; questionnaires/pdf; Unity files (various formats)
TU Delft, Faculty of Mechanical Engineering, Department of Cognitive Robotics


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