The power and sensitivity of four core driver workload measures for benchmarking the distraction potential of new driver vehicle interfaces
DOI: 10.1016/j.trf.2021.09.019
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Summary
Secondary analysis of a multi-vehicle on-road dataset (173 participants, 40 vehicles, 50 in-vehicle infotainment systems including 5 with both Android Auto and Apple CarPlay) evaluating the power and sensitivity of four core driver workload measures for benchmarking HMI distraction potential. Measures compared: DRT Reaction Time (vibrotactile stimulus, cognitive demand), DRT Miss Rate (LED stimulus, visual demand), NASA-TLX (subjective demand), and Task Interaction Time (temporal demand). Variance partitioning and power analyses quantified each measure's ability to discriminate between vehicles during text messaging, navigation, audio entertainment, and calling/dialing tasks. Authors argue Task Interaction Time paired with a visual demand metric (DRT Miss Rate, eye glance coding, or visual occlusion) provides the most efficient basis for distraction-potential evaluation that could be incorporated into NCAP testing.
Key finding
Task Interaction Time was the most sensitive measure of between-vehicle workload differences, followed by DRT Miss Rate, NASA-TLX, and finally DRT Reaction Time. DRT Miss Rate variance attributable to vehicle ranged from 10% (collapsed) to 20% (navigation), with 80%-power sample size requirements of 10-17 per task. DRT Reaction Time accounted for only ~5% of variance overall (n~89 needed), suggesting cognitive load operated in an on-off fashion at a similar elevated level across vehicles, tasks, and modalities. Correlations between the four measures were weak, indicating each captures a partially unique aspect of workload; Task Interaction Time was largely independent of the other three.
Methodology
Secondary analysis of pooled on-road data from prior AAA Foundation projects (Strayer et al. 2018; Cooper et al. 2020). Participants drove 40 production vehicles on public roads while completing four secondary task categories (text messaging, navigation, audio entertainment, calling/dialing) across voice, touchscreen, and mixed modalities. A remote DRT (ISO 17488) provided LED Miss Rate and vibrotactile Reaction Time; NASA-TLX captured subjective workload; Task Interaction Time measured task duration. Mixed-effects models partitioned variance (marginal R^2, eta-squared) by Vehicle, Task, and Modality. Power analyses estimated sample sizes needed to detect Vehicle effects at 0.8 power.
Sample size: N=173 drivers across 40 vehicles and 50 IVIS configurations
Quality score: 5 / 5