Variations in Posture Among Average Sized Female Riders on a Touring Motorcycle
Report, 2025

Powered two- and three-wheelers (PTWs), such as motorcycles (MCs), are an increasingly popular mode of transportation, now accounting for 12% of the global motor vehicle fleet (WHO, 2023). However, PTW riders face a substantially higher risk of injury or fatality in crashes, making them the most vulnerable road user group worldwide (WHO, 2023).
Passive safety systems have shown promise in enhancing PTW rider safety (Ariffin et al., 2016; Capitani et al., 2010; Maier & Fehr, 2023). However, for these systems to be effective, the variability of PTW crashes must be addressed (Barbani et al., 2014; ISO 13232-6 2005; Rogers & Zellner, 2001).
An important factor contributing to this variability is rider posture, which has been shown to influence injury outcomes, particularly for the two most frequently injured (AIS2+) body regions— the head and chest (Langwieder, 1977; Schaper & Grandel, 1985; Sporner et al., 1990; Wisch et al.,
2019).
Despite its impact on injury risk, rider posture is often simplified in PTW safety research. Surrogates used in safety assessments, such as physical and virtual anthropometric test devices (ATDs) or finite element human body models (FE-HBMs), are typically positioned in a single rider posture (Capitani
et al., 2010; ISO 13232-6 2005; Maier et al., 2021; Maier et al., 2022; Prochowski & Pusty, 2013). This approach assumes that posture is primarily dictated by the ergonomic relationship between the handlebar, seat, and foot supports—the so-called “ergonomic triangle” (Arunachalam et al., 2019;
Sabbah & Bubb, 2008)—rather than individual rider preferences (Claflin, 2002; Lundin et al., 2024).
Although studies on rider posture have been conducted (Arunachalam et al., 2019; Chou & Hsiao, 2005; Robertson & Minter, 1996; Sabbah & Bubb, 2008), one of the main challenges in incorporating posture variability into PTW safety research is the lack of detailed data necessary for accurate
positioning of human surrogates. Existing studies, often focused on ergonomics, typically report only average postures, usually based on mean joint angles, with occasional inclusion of standard deviations or ranges for individual joints (Barone & Curcio, 2004; Chou & Hsiao, 2005; Sabbah &
Bubb, 2008; Smith et al., 2006; Van Auken et al., 2005). However, this segmented approach does not capture the full range of whole-body posture variability, which is particularly pronounced among female riders (Sabbah & Bubb, 2008).
In a previous study by Lundin et al. (2024), average and subpopulation posture variability data were compiled for 50th percentile male riders to support PTW safety system assessments. Building on these findings, the present study aims to take the first step in describing whole-body posture variability specific to 50th percentile female PTW riders. This study will provide ready-to-use posture information for positioning human surrogates in PTW crash analysis. Additionally, by comparing 50th percentile female and male postures on the same MC, this study will explore potential differences that may justify expanding future research to consider a broader range of anthropometries when assessing rider posture.

powered two wheeler

motorcycle

rider posture

human body model

female

posture

Author

Linus Lundin

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Maria Oikonomou

Aristotle University of Thessaloniki

Mats Svensson

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Johan Iraeus

Chalmers, Mechanics and Maritime Sciences (M2), Vehicle Safety

Motorcycle Rider Model For Injury Prediction

VINNOVA (2020-05153), 2021-06-01 -- 2024-05-31.

Areas of Advance

Transport

Health Engineering

Life Science Engineering (2010-2018)

Subject Categories (SSIF 2025)

Vehicle and Aerospace Engineering

Research report - Department of Mechanics and Maritime Sciences: 2025:01

Publisher

Chalmers

Related datasets

Quantifying rider posture variability in powered two- and three-wheelers for safety assessment [dataset]

DOI: 10.1080/15389588.2024.2351607

More information

Latest update

4/11/2025