Impact of Cognitive Workload on Physiological Arousal and Performance in Younger and Older Drivers
DOI: 10.17077/drivingassessment.1382
archive: archived pipeline: cataloged verified
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Summary
This study investigates the validity of using physiological measures to assess cognitive workload in drivers, specifically examining whether these metrics can reliably differentiate between varying levels of mental demand in both younger and older adults. The research was motivated by contradictory prior findings regarding the sensitivity of physiological indices in driving environments and the need to validate simulator-based data against on-road conditions. The primary objective was to determine if heart rate and skin conductance could accurately rank-order cognitive workload induced by an auditory secondary task and to assess if age influenced these physiological responses. The experiment involved 30 male participants divided into two age groups: 15 younger drivers (aged 25–35) and 15 older drivers (aged 60–69). All participants were in good health and drove regularly. The study was conducted in a fixed-base driving simulator using STISIM Drive™ software. Participants drove a simulated highway while performing an auditory delayed digit recall task (n-back) at three difficulty levels: 0-back, 1-back, and 2-back. The task difficulty was randomized across participants to prevent order effects. Physiological data, including heart rate and skin conductance level, were collected continuously. Driving performance was measured via average forward velocity and the standard deviation of lateral lane position. Statistical analysis employed repeated measures general linear models to assess the effects of age and workload level. The results demonstrated that both heart rate and skin conductance increased significantly with each increment in cognitive workload. Heart rate showed a statistically significant linear increase from baseline through the 0-back, 1-back, and 2-back conditions. Skin conductance also increased significantly from baseline to 0-back and from 0-back to 1-back, though the difference between 1-back and 2-back was not statistically significant. Crucially, these physiological patterns were consistent across both age groups, with no statistically significant effect of age on heart rate or skin conductance reactivity. In contrast, driving performance measures were less sensitive; while speed decreased during dual-task conditions, the changes were nonlinear and did not effectively differentiate between specific workload levels. Older drivers exhibited significantly higher error rates on the secondary task, particularly at the highest difficulty level, compared to younger drivers. The findings confirm that heart rate and skin conductance are sensitive, valid indicators of incremental cognitive workload in a simulated driving environment. The consistency of these physiological responses across age groups suggests that these metrics can be reliably used to model workload differences in healthy older adults, similar to younger drivers. Furthermore, the study validates the use of simulators for assessing physiological reactivity, as the results replicated patterns observed in previous on-road studies. This supports the utility of physiological measures in user interface design and evaluation, offering a more precise tool for detecting mental workload than traditional driving performance metrics, which often fail to capture subtle changes in cognitive demand.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | cached | — | — | 3 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| enrich | failed | — | — | — | 1 | 2026-08-09 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 10 | 2026-08-11 |
| verify | success | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- workload measurement
- mental demand
- stress driving
- cognitive capacity variation
- stress arousal performance
- neuro workload indices
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: physiological data, behavioral performance data
- Theoretical Contribution: theory or model