Differences in drivers’ dependence on AR warning information in urban driving environments: the role of driving experience

Huo, Faren; Huo, Faren; Alla, Rubanka · 2025 · DOAJ

DOI: 10.3389/frvir.2025.1638823

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Summary

This study investigates how driving experience influences drivers' dependence on Augmented Reality Head-Up Display (AR HUD) warning messages in urban environments. While AR HUDs enhance situational awareness, excessive reliance on automation can lead to complacency and safety risks, particularly when systems fail. The research specifically examines whether experienced and novice drivers differ in their dependence on AR warnings under varying environmental loads (daytime vs. nighttime) and how this dependence manifests when the system malfunctions. The researchers employed a two-stage comparative experimental design using a driving simulator. Fifty-two participants, categorized as experienced (>50,000 km driven or >4 years licensed) or novice drivers, completed tasks involving a typical urban hazard: pedestrians suddenly running into the road. Experiment 1 compared hazard perception times between a control group (no AR warnings) and an AR group (with warnings) during both daytime and nighttime scenarios. Experiment 2 introduced a random AR warning failure to assess dependence; participants drove with AR warnings present for two hazards but experienced a system malfunction for one randomly selected hazard. Eye-tracking data and verbal hazard detection times were recorded to quantify objective dependence, while subjective perceptions of system intrusiveness and effectiveness were also analyzed. The results indicated that environmental load was the primary driver of dependence for both groups. Under high-load nighttime conditions, both experienced and novice drivers maintained high attention and exhibited minimal dependence on AR warnings. However, under lower-load daytime conditions, dependence varied significantly by experience. Experienced drivers remained self-reliant due to ingrained habits and situational awareness, whereas novice drivers showed increased relaxation and greater dependence on AR cues. Subjectively, drivers' perceived dependence correlated more strongly with the perceived intrusiveness of the AR system than with its actual effectiveness. The study found that novice drivers were more likely to rely on the system when it was present, making them more vulnerable to the absence of warnings during malfunctions. These findings suggest that dependence on AR HUD warnings is a complex interaction between environmental context, user experience, and perceived system intrusiveness. The study concludes that to mitigate automation complacency, AR HUD design strategies must be tailored to user experience levels and driving contexts. Specifically, warning systems should account for the higher susceptibility of novice drivers to over-reliance in low-load environments. This research provides practical insights for optimizing human-computer interaction in intelligent cockpits and highlights the need for adaptive trust calibration mechanisms to ensure safety across diverse driver populations.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-25; verification: verified.

Topics

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• hud ar windshield
• trust calibration
• automation surprise
• situational awareness
• automation complacency bias

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• Theoretical Contribution: theory or model