Driver arousal and workload under partial vehicle automation: A pilot study
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Summary
On-road pilot study (HFES Annual Meeting Proceedings, 2020) comparing driver cognitive arousal and workload between manual (Level-0) and partial automation (Level-2) driving in three production vehicles (Cadillac CT6, Tesla Model S, Volvo XC90). Twenty-eight participants drove a 44-mile section of I-80 in Utah at 75 mph in counterbalanced Level-0 and Level-2 conditions. Five outcome measures captured arousal and workload: heart rate (BPM), RMSSD heart-rate variability, parietal EEG alpha power, and DRT hit rate and reaction time. A linear mixed-effects model showed no significant effect of automation on any of the five measures. Bayes Factor analyses (BF range .030-.059) provided strong evidence in favor of the null hypothesis, indicating equivalent arousal and workload across Level-0 and Level-2 driving. Authors note participants were new to Level-2 automation; experienced users may differ.
Key finding
In drivers new to Level-2 automation, cognitive arousal and workload during partial automation are equivalent to manual driving. Bayes Factors of .030-.059 across heart rate, RMSSD, EEG alpha, DRT hit rate, and DRT reaction time provide strong evidence for the null, suggesting these drivers remained engaged with the driving task rather than becoming disengaged or overloaded.
Methodology
on_road
Sample size: N=28 (24% female; M_age=29.29, SD=4.27). Inclusion criteria: valid license, no at-fault crashes in past 2 years, >=10 hours/month driving, no neurological or heart conditions, no prior Level-2 experience.
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_sweep_intake on 2026-05-28 (4 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 3 | 2026-05-28 |
| archive | failed | pmc | — | — | 8 | 2026-06-04 |
| extract | skipped | empty | — | — | 8 | 2026-07-02 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-06 |
| promote | success | — | — | — | 2 | 2026-06-06 |
| summarize | success | llm | unknown | — | 1 | 2026-06-01 |
| tag | success | vector_similarity | — | — | 16 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-05-08 |
Summary generated by qwen3.6-35b-a3b-prismaquant on 2026-05-06; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- workload measurement
- situational awareness
- automation
- automation surprise
- mode awareness
- automation complacency bias
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
- Theoretical Contribution: theory or model, conceptual framework