From Driver to Supervisor: Comparing Cognitive Load and EEG-Based Attentional Resource Allocation Across Automation Levels
DOI: 10.1016/j.ijhcs.2023.103169
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Summary
This study investigates how increasing vehicle automation affects drivers’ cognitive load and attentional resource allocation as their role shifts from active operator to passive supervisor. The research addresses a critical gap in human-computer interaction literature, which has largely relied on driving simulators and subjective self-reports, often yielding contradictory results regarding cognitive states in automated driving. To provide ecologically valid evidence, the authors conducted a real-world experiment comparing manual driving, SAE Level 2 (L2) partial automation, and SAE Level 3 (L3) conditional automation. The study aimed to determine if objective neural measures of attention align with subjective perceptions of workload across these automation levels. The experimental design involved 30 participants driving a prototype automated vehicle on a realistic test track. While driving, participants underwent a passive auditory oddball task, where they were exposed to standard tones and rare novel sounds without being instructed to respond. Electroencephalogram (EEG) data were recorded to measure the amplitude of the P3a event-related potential, an objective neural index of involuntary attention switching and resource allocation to environmental stimuli. Subjective cognitive load was assessed using the NASA Task Load Index (NASA-TLX). This mixed-methods approach allowed for a direct comparison of neural activity and self-reported workload across the three driving conditions. The results revealed distinct patterns in subjective and objective measures. Subjective cognitive load, as measured by NASA-TLX, showed no significant difference between manual and L2 driving, but significantly decreased during L3 driving. In contrast, the P3a amplitude was highest during manual driving, indicating greater attentional resource allocation to environmental sounds compared to both L2 and L3 conditions. This suggests that while drivers perceive lower workload in higher automation levels, their brains allocate fewer resources to processing external auditory cues. The authors note that this reduction in P3a amplitude may stem from top-down attentional withdrawal rather than merely bottom-up resource competition, as driving is a low-to-moderate load task. These findings highlight a discrepancy between perceived and actual cognitive engagement in automated driving. The study provides novel empirical evidence that drivers in automated vehicles may disengage attentionally from the environment, potentially compromising situational awareness despite feeling less burdened. The authors conclude that understanding these neural mechanisms is crucial for designing user-centered interfaces and safety systems that effectively manage driver attention and mitigate risks associated with passive supervision roles in future automated vehicles.
Key finding
Drivers allocate fewer attentional resources to environmental stimuli and report lower subjective cognitive load during SAE Level 3 automated driving compared to manual driving, as evidenced by reduced P3a amplitude and NASA-TLX scores.
Methodology
on_road
Sample size: 30
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 openalex_abstract on 2026-05-08 (5 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | — | — | — | 1 | 2026-05-07 |
| archive | success | canonical_url | — | — | 7 | 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 | semantic_scholar | — | — | 5 | 2026-05-08 |
| promote | success | — | — | — | 1 | 2026-05-07 |
| 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: physiological data
- Theoretical Contribution: theory or model, conceptual framework