Stability of measurements of simulated driving: A comparison between a static and a dynamic motorcycle simulator with different degrees of fidelity
DOI: 10.1016/j.trf.2025.103468
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Summary
This study investigates the stability and coherence of simulated driving measurements across two motorcycle simulators with differing levels of fidelity, specifically examining their relationship with self-reported driving styles. The research addresses the need to validate whether low-fidelity simulators can reliably identify unsafe driving behaviors comparable to higher-fidelity systems, thereby broadening the tools available for road safety interventions. The authors aimed to verify the consistency of measurements from a static, low-fidelity Honda Riding Trainer (HRT) and a dynamic, medium-fidelity Lander simulator, while also assessing how well these simulated performances correlated with established self-report questionnaires: the Driver Behavior Questionnaire (DBQ) and the Dula Dangerous Driving Index (DDDI). The experimental design involved 76 Italian participants aged 19–32 who held valid driving licenses. Participants first completed online surveys using the DBQ and DDDI to assess their self-reported aberrant and risky driving behaviors. Subsequently, they underwent laboratory sessions where they performed driving tasks on both simulators. The HRT, a static simulator with a single monitor, was administered first to minimize motion sickness effects, followed by the Lander simulator, which featured a real moped chassis, a motion platform with three degrees of freedom, and a 180-degree field of view. Both tasks included training routes and experimental routes with predefined risky scenes, such as sudden vehicle appearances and traffic violations. Data analysis focused on correlating questionnaire scores with simulator-derived variables, including longitudinal and lateral speed control, harsh braking, and speed limit violations. The results demonstrated robust, positive correlations between the DBQ and DDDI scores, confirming their convergent validity in the Italian sample. Furthermore, moderate positive correlations were found between driving variables from the two simulators, indicating that both systems consistently identified unsafe driving behaviors despite differences in fidelity. Crucially, the study found that self-reported driving styles predicted specific simulated behaviors: the DDDI predicted longitudinal speed control and speed violations in both simulators, whereas the DBQ predicted longitudinal speed control in the HRT task and lateral speed control in the Lander task. Both simulators effectively discriminated between different driving styles regarding speed control and limit violations. The significance of these findings lies in the confirmation that low-fidelity simulators like the HRT can serve as valid tools for identifying risky driving behaviors, comparable to more expensive, high-fidelity systems. This suggests that cost-effective, portable simulators are suitable for preliminary studies, educational contexts, and safety training interventions. By establishing that multiple assessment tools yield coherent results, the study supports the development of diverse strategies for fostering road safety and preventing accidents, particularly for young drivers.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-18 |
| archive | success | openalex | — | — | 5 | 2026-06-25 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-18 |
| chunk | success | chunk | — | — | 1 | 2026-06-18 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-18 |
| promote | success | — | — | — | 1 | 2026-06-18 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-18 |
| verify | partial | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified_with_issues.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- simulator validity fidelity
- simulator training transfer
- dbq psychometrics
- simulator sickness
- motorcyclist skill
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).
- Methodological Resource: validation psychometrics, tool software
- Theoretical Contribution: computational model