How to Indicate Multiple Potential Hazards to Cyclists on Smart Glasses? Findings from a Focus Group Discussion with Research Experts and UX Students
Cyclists are exposed to numerous potential hazards in traffic, often due to interactions with motorized vehicles. Early notifications about these hazards could help cyclists react more consciously and proactively before a hazard materializes. Future technologies, such as connected traffic systems, could provide real-time hazard information via smart glasses. Similar to head-up displays in vehicles, relevant information is presented in the cyclist’s direct line of sight. A crucial aspect for usability is how visual information is presented to support cyclists, ensuring quick comprehension of notifications without causing additional distraction. Our study involved focus group discussions with two groups: cycling HCI researchers (NR=3) and user experience design master’s students (NU=4). We explored key aspects of delivering information through smart glasses for cyclists. Furthermore, we asked participants to generate visual notification concepts they deemed suitable for providing hazard information. Many of these concepts involve integrating augmented reality overlays with real-world objects, posing a specific challenge in overlay placement due to the HUD moving with the cyclist’s head. Additionally, it is essential to identify which hazards are relevant for notification to not overload cyclists with excessive information by indicating every potential hazard.
Authors
- Tamara von Sawitzky (ORCID: https://orcid.org/0000-0003-0001-3170)
- Thomas Grauschopf (ORCID: https://orcid.org/0000-0002-0005-9841)
- Philipp Wintersberger (ORCID: https://orcid.org/0000-0001-9287-3770)
- Andreas Riener (ORCID: https://orcid.org/0000-0002-9174-8895)
Institutions
- Johannes Kepler University of Linz (AT)
- TU Wien (AT)
- Technische Hochschule Ingolstadt (DE)
- University of Applied Sciences Upper Austria (AT)
Publication Details
- Published
- 2024-09-17
- DOI
- https://doi.org/10.1145/3641308.3685044
- Citations
- 1
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.64