Cognitive distraction impairs drivers' anticipatory glances: An on-road study

Biondi, F; Turrill, DM; Coleman, JR; Cooper, JM; Strayer, DL · 2015 · publications_jsonl

DOI: 10.17077/drivingassessment.1546

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Summary

This study investigates the impact of cognitive distraction on drivers’ anticipatory visual scanning behavior, specifically focusing on how secondary tasks affect hazard anticipation at road intersections. While manual and visual distractions are well-documented causes of accidents, cognitive distraction—diverting attentional resources to non-driving tasks—is more subtle and difficult to measure. The research was motivated by the growing adoption of voice-based technologies in vehicles, which are often marketed as safer alternatives because they minimize manual and visual demands. The authors sought to determine if these systems still impair driving performance by consuming cognitive resources, using an on-road study to validate findings previously observed in simulators. The experiment involved 25 undergraduate drivers operating an instrumented vehicle on a 2.75-mile loop in Salt Lake City, Utah. Participants completed eight conditions representing increasing levels of cognitive load: single-task driving, listening to the radio or an audiobook, conversing with a passenger, talking on a handheld or hands-free cell phone, interacting with a high-fidelity voice-based email/text system, and performing a demanding Operational Span (OSPAN) task. Visual scanning behavior was recorded via four high-definition cameras and coded frame-by-frame at 34 intersections, classified as high-priority (with crosswalks or stop signs) or low-priority. The coding system measured lateral glances, instrument glances, and head movements to assess how thoroughly drivers scanned for potential hazards. Results indicated that as cognitive demand increased, drivers significantly reduced their anticipatory glances. Compared to the single-task condition (74% complete scan probability), all tasks except radio listening significantly decreased lateral glance probability. Notably, there were no significant differences in glance reduction between hands-free phone use, speech-to-text interaction, and the high-demand OSPAN task, with all three conditions showing approximately 63–66% scan probabilities. At high-priority intersections, drivers were more likely to scan than at low-priority ones, but cognitive distraction still impaired this behavior. Specifically, interacting with the voice-based email system reduced the probability of a complete scan by 11% compared to the control condition and by 20% compared to single-task driving at stop-controlled intersections. Additionally, glances at instruments decreased significantly during speech-to-text and OSPAN tasks. The findings demonstrate that cognitive distraction impairs hazard anticipation even in familiar environments and when using voice-based technologies that require minimal visual or manual input. The study challenges the assumption that voice-based systems are risk-free, showing that the mental workload associated with these interactions diverts attention from the road, reducing the likelihood of detecting potential hazards. The authors conclude that manufacturers and policymakers should exercise caution in promoting voice-based technologies as safe solutions, as they still pose significant risks to road safety by degrading drivers’ situational awareness.

Key finding

Cognitive distraction reduces the frequency and quality of anticipatory glances, impairing drivers' ability to visually scan for upcoming road hazards even when eyes remain on the road.

Methodology

on_road

Sample size: 25

Provenance

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Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.

Topics

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• visual
• cognitive
• visual manual
• temporal
• external distraction
• auditory

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, observational prevalence
• Methodological Resource: measurement protocol