Dynamics of Affective States During Takeover Requests in Conditionally Automated Driving Among Older Adults with and without Cognitive Impairment
DOI: 10.48550/arXiv.2505.18416
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Summary
This study investigates the dynamics of affective states during takeover requests (TORs) in conditionally automated vehicles (CAVs), focusing on older adults with and without cognitive impairment. As cognitive decline can compromise driving safety and lead to premature driving cessation, CAVs offer a potential assistive solution. However, their safety depends on the driver’s ability to re-engage effectively when automation reaches its limits. The research addresses a gap in understanding how emotional responses—specifically valence (emotional tone) and arousal (emotional intensity)—manifest in cognitively vulnerable populations during these critical transitions, aiming to inform the design of adaptive vehicle systems. The researchers conducted experiments using a high-fidelity driving simulator with a factorial design involving 18 cognitively healthy older adults and five individuals with mild cognitive impairment or very mild dementia. Participants underwent conditionally automated driving sessions featuring TORs across varying road geometries (straight vs. curved) and speeds (50 km/h vs. 100 km/h). Facial expressions were recorded via video and analyzed using deep learning models to extract continuous valence and arousal scores. Statistical analyses included Wilcoxon signed-rank tests for within-group changes and Mann–Whitney U tests for between-group comparisons. Results indicated significant within-group changes in both valence and arousal for both groups during TORs. Cognitively healthy participants exhibited adaptive responses, showing increased arousal under higher-demand conditions (curved roads or high speeds), suggesting heightened alertness. In contrast, individuals with cognitive impairment displayed blunted emotional activation, with reduced arousal even in moderately demanding scenarios and minimal change in the most complex conditions. Between-group comparisons revealed that cognitively impaired individuals consistently displayed lower arousal and higher valence than controls across most TOR conditions. This pattern suggests diminished situational awareness and a potential mismatch between emotional tone and task complexity, where impaired drivers may perceive less threat despite high objective risk. The findings highlight distinct affective profiles between cognitively healthy and impaired older adults during automated driving transitions. The blunted arousal and altered valence in cognitively impaired drivers suggest reduced engagement and potentially compromised readiness to resume control. These results underscore the need for adaptive CAV systems capable of detecting affective states to deliver tailored handover strategies, such as adjusted alert timing or additional support mechanisms, for cognitively vulnerable populations. The study acknowledges limitations regarding the small sample size of the impaired group and the reliance on facial expression data alone, recommending future multimodal approaches to enhance the reliability of driver state monitoring.
Key finding
Cognitively impaired older adults displayed lower arousal and higher valence than cognitively healthy controls during takeover requests, indicating blunted emotional activation and potentially reduced situational awareness.
Methodology
simulator
Sample size: 23
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via author_normalize on 2026-05-28.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | — | — | — | 1 | 2026-05-07 |
| archive | success | canonical_url | — | — | 1 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | normalization | — | — | 2 | 2026-05-28 |
| promote | success | — | — | — | 2 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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- Empirical Findings: behavioral performance data, physiological data
- Theoretical Contribution: conceptual framework