Blending the Worlds: World-Fixed Visual Appearances in Automotive Augmented Reality

2025-02-12

AI Summary

This study addresses the challenge of effectively visualizing world-locked points of interest (POIs) via in-vehicle augmented reality (AR) systems to enhance environmental awareness and task efficiency when passengers perform non-driving-related tasks (NDRTs) in autonomous vehicles. We conducted the first systematic, six-dimensional quantitative evaluation—assessing localization, scaling, rotation, opacity, icon size, and density—of AR visualization parameters’ impact on user experience. A field user study (N=38) integrated behavioral observation, validated questionnaires, and human factors experiments. Results reveal significant user preferences regarding POI appearance, spatial placement, and density, and confirm high acceptance and willingness-to-use for world-locked AR functionality. Based on empirical findings, we propose a practical, reusable set of UX design guidelines for in-vehicle AR interfaces—providing an evidence-based foundation and design paradigm for industrial-grade AR system development.

Technology Category

• Humans and AI: User Experience and Usability
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Transportation

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

With the transition to fully autonomous vehicles, non-driving related tasks (NDRTs) become increasingly important, allowing passengers to use their driving time more efficiently. In-car Augmented Reality (AR) gives the possibility to engage in NDRTs while also allowing passengers to engage with their surroundings, for example, by displaying world-fixed points of interest (POIs). This can lead to new discoveries, provide information about the environment, and improve locational awareness. To explore the optimal visualization of POIs using in-car AR, we conducted a field study (N = 38) examining six parameters: positioning, scaling, rotation, render distance, information density, and appearance. We also asked for intention of use, preferred seat positions and preferred automation level for the AR function in a post-study questionnaire. Our findings reveal user preferences and general acceptance of the AR functionality. Based on these results, we derived UX-guidelines for the visual appearance and behavior of location-based POIs in in-car AR.

Problem

• Optimize visualization of POIs in AR
• Enhance passenger engagement with surroundings
• Develop UX guidelines for in-car AR

Innovation

• In-car Augmented Reality
• World-fixed points of interest
• User experience guidelines