Ageing drivers’ mental workload in real-time driving tasks based on subjective and objective measures
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Summary
This study investigates the mental workload of ageing drivers during real-time driving tasks, aiming to determine how situation complexity affects their cognitive load and to compare these metrics against a younger control group. Motivated by the rapidly increasing global population of older adults and the associated risks of degenerative processes affecting driving performance, the research seeks to provide evidence-based guidelines for designers, manufacturers, and policymakers to improve driving environments for this demographic. The study employs a dual-measurement approach, combining subjective self-reports with objective physiological data to capture a comprehensive view of mental workload. The methodology involved 30 healthy drivers, comprising 20 ageing participants (mean age ~58 years) and 10 young drivers serving as a control group. Participants completed on-the-road experimental driving tasks across three distinct environments representing varying levels of complexity: a simple highway situation, a moderately complex rural road, and a very complex city road. Subjective workload was assessed using the NASA-Task Load Index (NASA-TLX), which measures dimensions such as mental, physical, and temporal demand. Objective physiological data were collected via electroencephalogram (EEG) recordings, specifically analyzing the relative power of theta (RPθ) and alpha (RPα) frequency bands at frontal (FZPZ) and occipital (O1O2) channel locations. Data were processed to remove artifacts and normalized to estimate power spectral density. The results indicated that situation complexity significantly influenced the mental workload of ageing drivers. Subjectively, ageing drivers reported the highest physical demand scores in moderately complex and very complex situations, with scores more than doubling as complexity increased from highway to city driving. The overall weighted workload was highest in city environments. Physiologically, EEG analysis revealed significant effects of situation complexity on RPθ and RPα bands. Specifically, theta and alpha power were lower in city driving compared to rural roads, suggesting higher attentional demands and reduced sleepiness in complex environments. Gender differences were observed in EEG signals, with males showing significantly higher theta power than females, but no significant gender differences were found in subjective NASA-TLX ratings. When comparing age groups, a significant difference in weighted workload was found only in the simple highway situation, where young drivers reported higher workload than ageing drivers, likely due to less experience. No significant differences were found between age groups in EEG metrics. The study concludes that driving environment complexity significantly impacts the mental workload of ageing drivers, particularly increasing physical demand and altering brain activity patterns associated with attention and information processing. The findings highlight that while ageing drivers may perceive lower subjective workload in simple tasks compared to inexperienced young drivers, complex urban environments impose substantial cognitive and physical loads. These insights are critical for developing adaptive driving systems and infrastructure that accommodate the specific needs of older drivers, thereby enhancing road safety and mobility for an ageing population.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | unpaywall | — | — | 2 | 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 | success | semantic_scholar | — | — | 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
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- mental demand
- workload measurement
- stress driving
- cognitive capacity variation
- road complexity
- older drivers
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, self report data
- Theoretical Contribution: theory or model