Analysis of the Motion Sickness and the Lack of Comfort in Car Passengers

Asua, Estibaliz; Gutiérrez-Zaballa, Jon; Mata-Carballeira, Oscar; Ruiz, Jon Ander; del Campo, Inés · 2022 · Crossref

DOI: 10.3390/app12083717

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study investigates the factors influencing passenger comfort and motion sickness in vehicles, addressing a gap in research that has historically prioritized safety and efficiency over occupant well-being. With the rise of autonomous driving, where passengers are no longer controlling the vehicle, understanding ride comfort is critical for user acceptance. The research aims to quantify how driving style, vehicle dynamics, and road characteristics independently and collectively affect comfort metrics. The methodology involved an experimental campaign using a 26-kilometer route near Bilbao, Spain, divided into four distinct sections: an interurban road with altitude changes, a curvy interurban section, a flat highway, and an urban area. Data were collected using smartphone accelerometers (ZTE-Blade-A452 with Phyphox app) to record longitudinal, lateral, and vertical accelerations at up to 100 Hz. The route was traversed by three different drivers operating two different vehicles (a crossover and a sedan). To evaluate comfort, the authors applied ISO 2631 standards, calculating frequency-weighted root mean square accelerations for general discomfort ($a_v$) and Motion Sickness Dose Values (MSDV). Additionally, they employed Probability Density Statistical analysis and Power Spectral Density (PSD) analysis to examine the distribution and frequency content of the vibrations. Subjective feedback was gathered from four passengers who rated the drivers, vehicles, and road sections based on their experienced comfort and motion sickness. The results demonstrated that road type is the primary determinant of comfort evaluation variables, with significant variations observed across the different sections. However, driving style and vehicle dynamics were found to amplify or attenuate these baseline values. Specifically, the analysis revealed that longitudinal and lateral accelerations have a substantially greater impact on passenger discomfort and motion sickness than vertical accelerations. The statistical analysis showed that aggressive driving styles resulted in higher $a_v$ values and increased instances of acceleration exceeding discomfort thresholds (set at 2 m/s²). Furthermore, the study validated the use of Probability Density analysis as a complementary tool to traditional PSD methods for characterizing ride comfort. The subjective passenger feedback generally aligned with the quantitative data, confirming that drivers inducing higher lateral and longitudinal accelerations were perceived as less comfortable. The significance of this work lies in its comprehensive experimental framework that isolates and quantifies the effects of road, driver, and vehicle on passenger comfort. By establishing that horizontal accelerations are more critical than vertical ones for motion sickness and general discomfort, the findings provide specific targets for optimizing control algorithms in autonomous vehicles. The study concludes by proposing a new experimental campaign to further refine these insights, emphasizing that future vehicle design and ADAS development must integrate comfort-based strategies alongside safety protocols to ensure passenger acceptance of automated driving systems.

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.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• passenger motion sickness comfort
• simulator sickness