Data Driven Design Framework for Adaptive Mixed Reality User Interfaces for Road Cycling and Beyond

Road cycling presents a more challenging use case for Mixed Reality interface design. Smart glasses can facilitate decision making by placing information in context, yet prototyping in-situ is challenging. While low-fidelity studies offer observational insights, positional guidelines for interface design are sorely needed. Building on previous high-fidelity analysis, this paper presents an extension – a data driven design framework consisting of a methodology and browser-based supportive tooling. It enables designers to prototype user interfaces for cycling and other dynamic environments, based on data from prior user sessions. Adhering to values of Optimisation, Steerability, Legibility, and Continuity, it is a marked improvement in translating insights into practical designs. The designer is supported in optimising and customising the positioning of an MR user interface, with interface elements transparently and continuously negotiating visual real-estate during prototyping. The designer arrives at actionable interface layouts for evaluation without compromising safety.

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Publication Details

Published
2025-11-03
DOI
https://doi.org/10.1145/3749385.3749414
Citations
1
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
1.28
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article

Data Driven Design Framework for Adaptive Mixed Reality User Interfaces for Road Cycling and Beyond

Frances M.T. Brazier, Peter J. Beek, Radoslaw Dukalski
1 citations
Augmented Reality Applications
1.28
article

Data Driven Design Framework for Adaptive Mixed Reality User Interfaces for Road Cycling and Beyond

Frances M.T. Brazier, Peter J. Beek, Radoslaw Dukalski
article en
1 citations

Abstract

Road cycling presents a more challenging use case for Mixed Reality interface design. Smart glasses can facilitate decision making by placing information in context, yet prototyping in-situ is challenging. While low-fidelity studies offer observational insights, positional guidelines for interface design are sorely needed. Building on previous high-fidelity analysis, this paper presents an extension – a data driven design framework consisting of a methodology and browser-based supportive tooling. It enables designers to prototype user interfaces for cycling and other dynamic environments, based on data from prior user sessions. Adhering to values of Optimisation, Steerability, Legibility, and Continuity, it is a marked improvement in translating insights into practical designs. The designer is supported in optimising and customising the positioning of an MR user interface, with interface elements transparently and continuously negotiating visual real-estate during prototyping. The designer arrives at actionable interface layouts for evaluation without compromising safety.

Vrije Universiteit Amsterdam (NL), Delft University of Technology (NL)
Openalex Percentile: Top 15%
Augmented Reality Applications
1.28
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