Predicting driver distraction using computed occlusion task times : estimation of task element times and distributions.

Elwart, Tessa; Green, Paul; Lin, Brian · 2015 · ROSA P / Center for Advancing Transportation Leadership and Safety (ATLAS Center)

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Summary

This research addresses the challenge of predicting driver distraction caused by in-vehicle interfaces, specifically aiming to provide an alternative to costly and time-consuming user testing. The National Highway Traffic Safety Administration (NHTSA) recommends visual-occlusion testing to ensure interfaces meet distraction guidelines, but this method requires a fully functional prototype and significant resources. To facilitate earlier design-stage evaluation, the authors sought to refine Pettitt’s method, a computational approach that estimates total occlusion task times by summing individual task element times and adjusting for periods when vision is blocked. The study aimed to generate experimentally based estimates for these task elements and their distributions to improve the accuracy of such predictions. The researchers conducted an occlusion experiment using a next-generation Hyundai navigation radio. Participants wore Plato goggles that opened and closed in alternating 1.5-second intervals, simulating the visual constraints of driving. The study included subjects aged 25–35 and 45–55. Data were collected via frame-by-frame video analysis of subjects performing various tasks, such as tuning the radio, dialing phone numbers, and entering navigation addresses. This analysis allowed the authors to isolate and time specific task elements, including flicks, button presses, knob turns, reaches, searches, and system wait times. The resulting database comprised 22,922 element times, which were analyzed to determine mean durations and statistical distributions for each action. The results provided specific mean times for 15 distinct task elements. For example, a "flick" averaged 0.50 seconds, "press button" 0.64 seconds, "reach for center console" 0.75 seconds, and "wait-loading" 0.90 seconds. Most element time distributions followed a lognormal pattern. A key finding was that while the mean element time for middle-aged subjects was only 16% longer than that of young subjects, the total mean task time was 44% greater. This discrepancy was attributed to middle-aged subjects requiring 32% more element occurrences to complete the same tasks. Additionally, the study revealed that 45% of all element occurrences happened while the goggles were closed or during transition periods. This finding challenges the core assumption of Pettitt’s method, which posits that visual tasks progress only when the goggles are open, suggesting that the current computational model may require revision to account for non-visual or preparatory actions occurring during occlusion. The significance of this work lies in providing a robust, empirically derived dataset for predicting driver distraction without the need for full-scale user testing. By establishing precise times and distributions for task elements, the report supports the refinement of SAE J2365 and Pettitt’s method, enabling engineers to assess interface usability earlier in the development process. The findings highlight the importance of accounting for age-related differences in task complexity rather than just speed, and they identify limitations in current occlusion prediction models regarding the timing of element execution relative to visual availability. This contributes to the broader field of human factors and ergonomics by offering a more nuanced understanding of how drivers interact with in-vehicle systems under constrained visual conditions.

Key finding

Middle-aged subjects completed individual task elements 16% slower than young subjects, but total task times were 44% greater due to 32% more element occurrences, and 45% of all element occurrences happened while occlusion goggles were closed.

Methodology

lab_experiment

Provenance

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

Topics

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• temporal
• visual
• visual manual
• manual
• attention allocation
• visual occlusion

Information type

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• Empirical Findings: behavioral performance data, observational prevalence
• Methodological Resource: measurement protocol