Scenario Parameters for Fatigue Induction in Truck-Driving Simulators: A Systematic Review of Experimental Designs
DOI: 10.3390/app16063057
archive: archived pipeline: cataloged verified
Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)
Summary
This systematic review addresses the lack of reproducibility and cross-study comparability in fatigue-induction protocols for truck-driving simulators. While simulators provide a safe environment to study the multidimensional psychophysiological state of fatigue, significant variation in scenario design and incomplete reporting hinder the identification of effective experimental patterns. The study aims to consolidate evidence on scenario parameters used to induce fatigue-related reductions in alertness, identify recurring protocol designs associated with interpretable outcomes, and highlight methodological gaps. The authors conducted a systematic search in February 2026 across five databases (Scopus, Web of Science, IEEE Xplore, PubMed, and ScienceDirect) following PRISMA 2020 guidelines and a prospectively registered PROSPERO protocol. Eligibility criteria required peer-reviewed English studies involving truck drivers, using driving simulators, reporting fatigue-relevant scenario parameters, and measuring at least one fatigue outcome. After screening 172 records, 23 studies comprising 419 participants were included. Data were extracted using a structured form covering study characteristics, simulator specifications, scenario parameters, and fatigue measures. Risk of bias was assessed using an adapted 11-item checklist based on NHLBI tools, focusing on simulator-specific features such as counterbalancing, familiarization, and simulator sickness assessment. The review found that fatigue-related changes were most consistently reported in protocols combining sustained time-on-task with low-variability driving demands, typically implemented through monotonous road environments and reduced traffic complexity. Interpretable effects were more evident when sessions were scheduled at night or after work shifts and when outcomes were assessed repeatedly during the drive. However, the evidence base is limited by substantial methodological heterogeneity and reporting deficiencies. Key limitations included incomplete control or reporting of baseline sleep pressure, stimulant intake, counterbalancing, familiarization procedures, simulator sickness, and outlier handling. These gaps limit causal interpretation and confidence in cross-study comparisons. The included studies predominantly used static simulators with inconsistent reporting of field of view and cabin realism, and samples were often small and male-dominated. The significance of this review lies in its identification of recurring design patterns rather than a single optimal protocol for fatigue induction. It highlights the critical need for standardized scenario descriptions and minimum reporting requirements to improve reproducibility in truck-driving simulator research. By clarifying which parameter combinations yield interpretable fatigue-related changes, the findings inform the development of more robust experimental designs for evaluating fatigue countermeasures and monitoring technologies. The study underscores that current methodological inconsistencies hinder the field's ability to draw definitive conclusions about fatigue induction, necessitating stricter adherence to reporting standards in future research.
Key finding
Fatigue-related changes in truck-driving simulators are most consistently induced by protocols combining sustained time on task with low-variability driving demands, particularly when scheduled at night or after work shifts.
Methodology
review
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_sweep_intake on 2026-05-28.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 2 | 2026-05-28 |
| archive | success | openalex | — | — | 20 | 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 | — | — | — | 1 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-06-03 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 3 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- truck driver fatigue
- simulator sickness
- time on task
- simulator validity fidelity
- simulator training transfer
- sleep deprivation
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
- Methodological Resource: validation psychometrics, tool software