Does the testing environment matter? Carsickness across on-road, test-track, and driving simulator conditions

Papaioannou, Georgios; Shyrokau, Barys · 2026 · Crossref

DOI: 10.54941/ahfe1007858

archive: archived pipeline: cataloged verified

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Summary

This study investigates the validity of driving simulators for assessing carsickness compared to on-road and test-track environments, addressing a critical gap in automated vehicle research. As automated vehicles increase passenger engagement in non-driving tasks, understanding and mitigating motion sickness is essential. However, the lack of standardization across testing environments complicates the comparison of results. While previous studies have compared pairs of environments, this research extends prior work by directly comparing subjective and objective motion sickness metrics across on-road, test-track, and motion-based driving simulator conditions. The primary objective was to determine if a simulator could accurately replicate the motion sickness exposure previously established in on-road and test-track settings. The experiment involved 28 participants who performed an eyes-off-road task (watching sports videos and counting unexpected events) while seated in the Delft Advanced Vehicle Simulator. The simulator reproduced longitudinal and lateral accelerations from a previously recorded on-road drive using an adaptive washout filter-based Motion Cueing Algorithm. Participants reported motion sickness levels every minute using the Misery Scale (MISC), with sessions terminating if scores reached 6 or higher. Post-experiment, participants completed the Motion Sickness Assessment Questionnaire. These results were compared against data from 47 participants in the corresponding on-road and test-track conditions. Objective motion sickness was quantified using the Motion Sickness Dose Value (MSDV) based on ISO-2631 standards. Statistical analysis included mixed-design ANOVA and Mann-Whitney U tests to assess differences over the 25-minute duration. The results revealed significant discrepancies between the simulator and real-world conditions. Objectively, the simulator’s MSDV was approximately 9 to 10 times lower than that of the on-road and test-track conditions. This reduction was attributed to the simulator’s limited workspace envelope, which prevented the reproduction of low-frequency motions (<0.5 Hz) known to be highly provocative for motion sickness. Subjectively, mean maximum MISC scores were significantly lower in the simulator (1.07) compared to on-road (2.74) and test-track (2.34) conditions, representing a reduction of roughly 54–61%. While no significant differences existed in the first 13 minutes, a significant Environment × Time interaction emerged, with divergence becoming statistically significant after the 14th minute. The simulator failed to replicate the cumulative sickness profile observed in real-world driving. The study concludes that current motion-based driving simulators are insufficient for fully replicating on-road carsickness exposure due to hardware limitations in reproducing low-frequency accelerations. The findings highlight that simulator-based research may underestimate motion sickness severity, particularly over longer durations. The authors suggest that future studies require advanced simulator architectures, such as 9-degree-of-freedom systems, to improve motion fidelity. This work underscores the necessity of considering testing environment constraints when validating motion sickness countermeasures for automated vehicles, as simulator data may not generalize to real-world scenarios.

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Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.

Topics

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• simulator sickness
• passenger motion sickness comfort
• simulator validity fidelity
• simulator training transfer

Information type

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• Methodological Resource: validation psychometrics, tool software