The impact of eye movements and cognitive workload on lateral position variability in driving
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Summary
This study investigates the paradoxical finding that increased cognitive workload often decreases lateral position variability in driving. Researchers sought to determine whether this effect is mediated by changes in eye movements (gaze concentration) or occurs independently of visual behavior. Using a fixed-base driving simulator, the authors conducted three experiments with undergraduate participants. They independently manipulated eye movements (via guided fixations on illuminated license plates) and cognitive workload (low, medium, and high secondary tasks). Dependent measures included standard deviation of lateral position, root mean squared error, and lane exceedance rates. Results indicated that cognitive workload substantially reduced lateral position variability across all conditions, whereas eye movements played only a modest role. Specifically, higher workload consistently led to lower variability regardless of whether gaze was static, dynamic, or eccentric. While dynamic eye movements interacted with workload to produce the lowest variability in Experiment 1, the primary driver of reduced variability was cognitive load, not gaze patterns. The findings suggest that increases in cognitive workload decrease lane position variability independently of eye movements. This supports hierarchical control theory, implying that high workload reduces residual attention allocated to the automatic inner loop of lane control, thereby stabilizing performance. These results challenge the gaze concentration hypothesis and indicate that lateral variability metrics may reflect cognitive state rather than visual attention alone.
Key finding
Eye movement eccentricity affected lateral distance traveled but not lane crossings or lateral position SD, while workload affected all measures, suggesting eye movements contribute less than previously hypothesized to lateral position variability.
Methodology
simulator
Sample size: 32
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 tag_papers on 2026-05-30 (4 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | — | — | — | 1 | 2026-05-06 |
| archive | failed | pmc | — | — | 12 | 2026-06-04 |
| extract | success | pdf_extracted | — | — | 2 | 2026-06-07 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | crossref | — | — | 1 | 2026-06-04 |
| promote | success | — | — | — | 2 | 2026-06-06 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-07 |
| tag | success | vector_similarity | — | — | 18 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-05-07 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-07; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- lane positioning
- eye movements scanning
- mental demand
- visual manual
- peripheral attention
- workload measurement
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: behavioral performance data, physiological data
- Theoretical Contribution: theory or model