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Improving Occupant Packaging Posture Prediction Through Integration of Simulation and Real Data
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (User Centred Product Design (UCPD))ORCID iD: 0000-0003-0746-9816
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (User Centred Product Design (UCPD))ORCID iD: 0000-0002-0125-0832
Ergonomics, Volvo Cars, Gothenburg, Sweden.
2025 (English)In: Proceedings of the 22nd Congress of the International Ergonomics Association, Volume 2: Better Life Ergonomics for Future Humans (IEA 2024) / [ed] Sangeun Jin; Jeong Ho Kim; Yong-Ku Kong; Jaehyun Park; Myung Hwan Yun, Singapore: Springer, 2025, p. 182-187Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a process for enhancing driver posture prediction in digital human modelling (DHM) tools by integrating real-world data from driver posture studies. The process leverages key data points such as seat position, steering wheel position, and eye point coordinates to position manikins and extract joint angles for ergonomic analysis. A test study involving 49 drivers was conducted, revealing significant variations in joint angles across different statures. These findings were used to develop stature-based strategies that demonstrated improved predictive accuracy for short and tall stature groups compared to the existing strategy in the DHM tool IPS IMMA. While the results highlight the potential benefits of this approach, limitations such as refined manikin body meshes, seat property considerations, and broader vehicle model validation are recommended. Overall, this method offers a promising solution for addressing incomplete datasets in occupant packaging studies, contributing to the development of more ergonomic and safer vehicle designs.

Place, publisher, year, edition, pages
Singapore: Springer, 2025. p. 182-187
Series
Springer Series in Design and Innovation, ISSN 2661-8184, E-ISSN 2661-8192 ; 40
Keywords [en]
dataset, digital human modelling, Occupant packaging, process, simulation
National Category
Production Engineering, Human Work Science and Ergonomics Vehicle and Aerospace Engineering
Research subject
User Centred Product Design
Identifiers
URN: urn:nbn:se:his:diva-25917DOI: 10.1007/978-981-96-8908-8_27ISI: 001594666700027Scopus ID: 2-s2.0-105018088099ISBN: 978-981-96-8907-1 (print)ISBN: 978-981-96-8910-1 (print)ISBN: 978-981-96-8908-8 (electronic)OAI: oai:DiVA.org:his-25917DiVA, id: diva2:2006745
Conference
22nd Triennial Congress of the International Ergonomics Association (IEA), Jeju, South Korea, August 25 to 29, 2024
Note

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025

Correspondence Address: E. Perez Luque; School of Engineering Science, University of Skövde, Skövde, Sweden; email: estela.perez.luque@his.se

Available from: 2025-10-16 Created: 2025-10-16 Last updated: 2026-05-22Bibliographically approved
In thesis
1. Human Posture and Motion Prediction for Automotive Ergonomics Design: Enhancing Functionality and Accuracy in Digital Human Modelling Tools
Open this publication in new window or tab >>Human Posture and Motion Prediction for Automotive Ergonomics Design: Enhancing Functionality and Accuracy in Digital Human Modelling Tools
2025 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Product development (PD) increasingly relies on digital tools to support the process of exploring, generating, and evaluating product design proposals. Ergonomics plays a critical role in ensuring that product designs align with human capabilities and needs. Digital human modelling (DHM) tools can simulate human-product interactions and assess ergonomics virtually, before physical prototypes exist. In vehicle design, DHM tools are frequently applied in occupant packaging activities, supporting the design of vehicle interiors that accommodate a diverse user population. Still, although commonly used in industry, DHM tools have various limitations. One challenge is their limited ability to predict human postures and motions with sufficient accuracy. This inaccuracy is the result of current simulation procedures and the prediction models used. To compensate for this, DHM tool users often require significant manual adjustments to produce realistic postures, making the process time-consuming, subjective, and difficult to reproduce. Moreover, the simulation procedures themselves can be complex and inefficient, reducing their accessibility and usefulness in iterative design work. These limitations often lead to costly and time-consuming validation activities involving real users.

This thesis addresses these challenges by developing and evaluating methods and models to enhance the functionality and accuracy of posture and motion predictions in DHM tools. The main contributions are: (1) identifying current practices and challenges in industry when applying DHM tools for ergonomics in PD, (2) developing methods that increase the functionality of DHM tools through improved simulations methods, and (3) developing and evaluating posture and motion prediction models that support more reliable and efficient virtual ergonomics assessments. Collectively, the findings support a more proactive, systematic, and human-centred approach to ergonomics in PD processes.

Abstract [sv]

Produktutveckling förlitar sig alltmer på digitala verktyg för att stödja processen med att utforska, generera och utvärdera produktdesignförslag. Ergonomi spelar en avgörande roll för att säkerställa att produktdesignen är anpassad till människans förmågor och behov. Digitala verktyg för mänsklig modellering (digital human modelling - DHM) kan simulera interaktioner mellan människa och produkt och bedöma ergonomin virtuellt, innan det finns fysiska prototyper. Inom fordonsdesign används DHM-verktyg ofta i aktiviteter som rör förar- och passagerarergonomi, för att stödja utformningen av fordonsinteriörer som passar en mångfald av användare. Dock, även om DHM-verktyg ofta används i industrin, så finns begränsningar av olika slag. En begränsning är DHM-verktygens förmåga att förutsäga mänskliga kroppsställningar och -rörelser med tillräcklig noggrannhet. Denna brist på noggrannhet beror på de nuvarande simuleringsförfarandena och de prediktionsmodeller som används. För att kompensera för detta behöver användare av DHM-verktyg ofta göra betydande manuella justeringar för att åstadkomma realistiska kroppsställningar, vilket gör processen tidskrävande, subjektiv och svår att reproducera. Dessutom kan simuleringsförfarandena i sig vara komplexa och ineffektiva, vilket minskar deras tillgänglighet och användbarhet i iterativt designarbete. Dessa begränsningar leder ofta till kostsamma och tidskrävande valideringsaktiviteter som involverar verkliga användare.

Avhandlingen behandlar dessa utmaningar genom att utveckla och utvärdera metoder och modeller för att förbättra funktionaliteten och noggrannheten av prediktioner av kroppsställningar och -rörelser i DHM-verktyg. De viktigaste bidragen är: (1) identifiering av rådande praktik och utmaningar i industrin vid användning av DHM-verktyg för ergonomi i produktutveckling, (2) utveckling av metoder som ökar funktionaliteten hos DHM-verktyg genom förbättrade simuleringsmetoder, och (3) utveckling och utvärdering av prediktionsmodeller för kroppsställningar och -rörelser som stöder mer tillförlitliga och effektiva virtuella ergonomiska bedömningar. Sammantaget stöder resultaten ett mer proaktivt, systematiskt och människocentrerat förhållningssätt för beaktande av ergonomi i produktutvecklingsprocesser.

Place, publisher, year, edition, pages
Skövde: University of Skövde, 2025. p. xi, 70 [196]
Series
Dissertation Series ; 65
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design
Identifiers
urn:nbn:se:his:diva-25793 (URN)978-91-989080-3-9 (ISBN)978-91-989080-4-6 (ISBN)
Public defence
2025-10-10, ASSAR Industrial Innovation Arena, Kavelbrovägen 2b, Skövde, 09:15 (English)
Opponent
Supervisors
Note

Paper D som submitted:

Perez Luque, E., Brolin, E., Nurbo, P., Lamb, M. & Högberg, D. (2025). Comparison of Driving Posture and Position Prediction Methods for Occupant Packaging Design. Journal Paper. Under Review Process in the International Journal of Human Factors and Ergonomics. [Titel som publicerat: A case study of digital human modelling assisted occupant packaging design: comparing driving posture and position prediction methods]

Available from: 2025-09-04 Created: 2025-09-03 Last updated: 2026-05-18Bibliographically approved

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