Dissociating eye movements and workload on lateral lane position variability
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Summary
This study investigates the theoretical underpinnings of the Detection Response Task (DRT), an International Standards Organization method for measuring cognitive workload in drivers. While the DRT correlates with driving outcomes, its basis in finite attention capacity remains poorly understood. The authors aimed to distinguish whether cognitive workload slows information processing rates or increases response caution using evidence-accumulation modeling. The researchers applied linear ballistic accumulation and Wald models to data from simple and choice DRT versions within a driving simulation. Participants performed driving tasks alongside a secondary cognitive load (counting backward by 3s). The models analyzed response times and omission rates to isolate parameters representing evidence accumulation rates, decision thresholds, and nondecision processes. Results indicated that secondary-task-induced workload reduced the rate of evidence accumulation, supporting limited-capacity attention theories. Additionally, participants exhibited a compensatory increase in the evidence required for responses and a slight speeding of nondecision processes. The ISO-standard DRT proved most sensitive to these workload effects. A Wald-distributed model augmented with an omission parameter provided the most parsimonious explanation of the data. These findings validate the DRT as a sensitive measure of dynamic fluctuations in limited-capacity attention. By linking workload to specific cognitive mechanisms, the study offers a framework for quantifying distraction risks. This supports future policy decisions regarding in-vehicle technologies and driver safety guidelines by clarifying how multitasking impairs information processing.
Key finding
Increased workload decreased lateral vehicle movement, but eye movement eccentricity affected lateral distance traveled only, suggesting the impact of eye movements on lateral control is smaller than previously hypothesized.
Methodology
simulator
Sample size: 27
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 | — | — | 8 | 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 | failed | — | — | — | 3 | 2026-07-02 |
| 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
- workload measurement
- peripheral attention
- cognitive capacity variation
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