Evaluating the Effect of Google Glass on Driver Distraction

Fisher, Donald L.; Knodler, Michael A. · 2018 · ROSA P / New England University Transportation Center

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Summary

This study addresses the growing safety concerns associated with the increasing population of older drivers in the United States. With over 40 million drivers aged 65 or older, this demographic accounts for a disproportionate share of fatal and injury-causing traffic crashes, particularly at intersections. These incidents are often linked to age-related declines in sensory, perceptual, and cognitive performance, which impair hazard detection and right-of-way yielding. The research investigates whether customized visual and auditory alerts can effectively enhance hazard perception for drivers aged 60 and older without interfering with other driving tasks. The methodology employed a high-fidelity driving simulator and eye-tracking technology at the Arbella Insurance Human Performance Laboratory at the University of Massachusetts Amherst. Participants, all aged 60 or older, navigated eight mini-scenarios involving intersections and left-turn maneuvers. The study utilized a between-subjects design, assigning participants to either a control group or a collision warning alert group. The alert group received specific auditory instructions and visual cues—highlighted and flickering indicators on the simulator screen—regarding upcoming hazards. A Latin square method was used to counterbalance the sequence of drives. The primary dependent variables were latent hazard anticipation behavior, measured by glances toward target zones, and secondary task performance, measured by the proportion of correct secondary glances. The results, analyzed using univariate analysis of variance (ANOVA), indicated that visual and auditory alerts significantly improved hazard detection. Participants in the alert group exhibited statistically higher rates of anticipating latent vehicle hazards compared to the control group [F (1, 38) = 27.02, p=4.1]. However, the alerts did not significantly affect secondary glance behavior; there was no statistically significant difference between the two groups regarding the proportion of correct secondary glances [F (1, 38) = 0.014, p=4.1]. Additionally, the study noted a disparity in simulator sickness, with 50% of female participants experiencing motion sickness compared to only 17% of male participants. The findings conclude that appropriate visual and auditory alerts are effective tools for improving latent hazard detection among older drivers, supporting the hypothesis that such technology can mitigate unsafe behaviors at intersections. The lack of impact on secondary glances suggests that this specific behavior may be habitual and less responsive to immediate alerts, potentially requiring training rather than real-time warnings. These results imply that integrating alert systems into vehicle interfaces could enhance safety for elderly drivers by compensating for age-related perceptual declines, though considerations for simulator sickness and individual differences remain relevant for implementation.

Key finding

Older drivers who received visual and auditory collision-warning alerts before intersections anticipated significantly more latent hazards than an unalerted control group, while their secondary-glance performance was unaffected.

Methodology

simulator

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (7 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• visual
• hazard perception
• temporal
• looked but failed to see
• external distraction
• hud ar windshield

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: behavioral performance data
• Methodological Resource: tool software, measurement protocol