Development and Validation of a Driving Simulator for Comfort Assessment
DOI: 10.1007/s13177-024-00427-y
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Summary
This study addresses the critical need for comprehensive ride comfort assessment in the context of autonomous vehicles, where passenger well-being is paramount. The research aims to bridge the gap between objective vibration metrics and subjective passenger perception, a combination rarely explored in existing literature. To achieve this, the authors developed and validated a driving simulator capable of replicating real-world driving conditions, allowing for controlled experiments that correlate objective signal analysis with subjective comfort questionnaires. The methodology involved two primary platforms: a sensorized third-generation Toyota Prius for data acquisition and a six-degree-of-freedom Stewart platform driving simulator for replication. A diverse route in the Basque Country, divided into six distinct zones varying in road type and roughness, was driven to collect data. Variables including accelerations, vehicle speed, and driver inputs were recorded via the car’s CAN bus and seat-mounted accelerometers. This data was used to build a virtual scenario in the simulator using IPG-Carmaker and Matlab-Simulink, ensuring accurate reproduction of road dimensions and roughness. Subjective data was gathered using a custom three-part questionnaire administered to passengers before, during, and after the simulation, assessing motion sickness susceptibility, symptom severity, and the perceived impact of specific driving factors like braking and steering. The validation results demonstrated that the simulator accurately replicated the longitudinal and lateral acceleration trends of the real vehicle, particularly regarding driver-controlled variables. However, the study identified a significant limitation: the simulator’s seat-mounted accelerometer failed to capture linear acceleration values comparable to the real car, as the platform’s mechanical rotation emulated sensation rather than actual linear movement. Consequently, simulator seat accelerations were deemed unsuitable for objective comfort metrics. In contrast, the simulator’s internal model accelerations correlated strongly with real-world data. The subjective questionnaires successfully captured passenger perceptions, allowing for a comparison between self-reported comfort levels and the objective ISO-2631 Motion Sickness Dose Value (MSDV) metrics derived from the validated signals. The significance of this work lies in establishing a foundational framework for combined subjective and objective comfort analysis. By validating a simulator that can reliably reproduce driving dynamics while capturing subjective passenger feedback, the study provides a robust tool for future research. This approach allows for the isolation of specific driving factors affecting comfort without the confounding variables of real-world testing, such as weather or traffic. The resulting database and methodology offer a pathway to optimize autonomous vehicle control strategies for enhanced passenger comfort and reduced motion sickness, addressing a key barrier to the widespread adoption of self-driving technology.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-25 |
| archive | success | canonical_url | — | — | 1 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-25 |
| chunk | success | chunk | — | — | 1 | 2026-06-25 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-25 |
| promote | success | — | — | — | 1 | 2026-06-25 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-25 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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- Empirical Findings: self report data
- Methodological Resource: validation psychometrics, tool software