Abstract
The future urban environment may consist of mixed traffic in which pedestrians interact with automated vehicles (AVs). However, it is still unclear how AVs should communicate their intentions to pedestrians. Augmented reality (AR) technology could transform the future of interactions between pedestrians and AVs by offering targeted and individualized communication. This paper presents nine prototypes of AR concepts for pedestrian-AV interaction that are implemented and demonstrated in a real crossing environment. Each concept was based on expert perspectives and designed using theoretically-informed brainstorming sessions. Prototypes were implemented in Unity MARS and subsequently tested on an unmarked road using a standalone iPad Pro with LiDAR functionality. Despite the limitations of the technology, this paper offers an indication of how future AR systems may support future pedestrian-AV interactions.
Original language | English |
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Title of host publication | Proceedings of the 13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021 |
Publisher | Association for Computing Machinery (ACM) |
Pages | 209-218 |
ISBN (Electronic) | 978-1-4503-8063-8 |
DOIs | |
Publication status | Published - 2021 |
Event | 13th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021 - Virtual, Online, United Kingdom Duration: 9 Sept 2021 → 14 Sept 2021 |
Conference
Conference | 13th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2021 |
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Country/Territory | United Kingdom |
City | Virtual, Online |
Period | 9/09/21 → 14/09/21 |
Keywords
- Augmented reality
- Implemented prototypes
- Pedestrian-automated vehicle interaction
- Road crossing
- Theoretically-informed design
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Supplementary materials for the article: Towards future pedestrian-vehicle interactions: Introducing theoretically-supported AR prototypes
Tabone, W. (Creator), Lee, Y. M. (Creator), Merat, N. (Creator), Happee, R. (Creator) & de Winter, J. C. F. (Creator), TU Delft - 4TU.ResearchData, 15 Jul 2021
DOI: 10.4121/14933082
Dataset/Software: Software