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Title [sv]
ADOPTIVE – Automated Design & Optimisation of Vehicle Ergonomics
Title [en]
ADOPTIVE – Automated Design & Optimisation of Vehicle Ergonomics
Abstract [sv]
Syftet med projektet Automated Design and Optimisation of Vehicle Ergonomics (ADOPTIVE) är att studera användarens fysiska interaktion med fordonet och att utveckla metoder för avancerade fordonsergonomiska analyser som utförs i simuleringsverktyg. ADOPTIVE-projektet kommer att fokusera på bedömning och optimering av fordonets invändiga geometri och olika designlösningarnas anpassningsnivåer gällande användarna. Detta ska ske genom att möjliggöra snabba, objektiva och automatiserade simuleringar av virtuella provkörningsrutiner, som utförs av en familj av provdockor, samt genom påföljande ergonomiska utvärderingar. Forskningsprojekt har initierats och utformats i nära samarbete med fordonsergonomiska produktutvecklare inom industrin. Industrin behöver effektivare metoder och verktyg för att garantera en riktig ergonomi vid utformningen av framtidens fordon vilket gynnar produktkvalitetsaspekter såsom hänsyn till mångfald, användarupplevelse och aktiv säkerhet. Från akademisk synvinkel bidrar projektet till kunskapsutvecklingen inom effektivt beslutsstöd inom virtuell teknik för ergonomisk design, bland annat genom att tillräcklig hänsyn tas till mångfald bland användarna under designprocesserna. Forskningsrönen kommer att implementeras och testas i ett verktyg för digital human modellering (DHM), exempelvis det svenska DHM-verktyget IPS IMMA (Intelligently Moving Manikins). Konsortiet bakom ADOPTIVE är baserat på konsortierna för tidigare framgångsrika forskningsprojekt. De tidigare projekteten lade grunden för fordonsergonomiska simuleringar, och denna grund har gjort det möjligt för ADOPTIVE att ta sig an nya forskningsutmaningar för att få ett ännu större vetenskapligt och industriellt genomslag. Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC) kommer att vara en samarbetspartner i forskningen på konsultbasis. ADOPTIVE är ett associerat projekt till SAFER. SAFER är navet för trafiksäkerhetsforskning inom Sverige. SAFER består av 30 samarbetspartners som företräder intressenter inom bilindustrin, akademin och myndigheter. Finansiering och samverkan: KK-stiftelsen, CEVT, Scania, Volvo Cars (Volvo Personvagnar), Volvo Technology AB (VTEC)
Abstract [en]
The purpose of the project Automated Design and Optimisation of Vehicle Ergonomics (ADOPTIVE) is to study the physical vehicle user interaction and develop methodology for advanced vehicle ergonomics analyses within simulation tools. The ADOPTIVE project will focus on the assessment and optimisation of vehicle interior geometries and the user accommodation levels of alternative design solutions. This will be done by enabling fast, objective, and automated simulations of virtual driving test procedures performed by a family of manikins and through subsequent ergonomics evaluations. This research project has been initiated and designed in close collaboration with product developers working with vehicle ergonomics in the industry. The industrial need is to have more efficient methods and tools to ensure proper ergonomics in future designs of vehicles to benefit product quality aspects such as user diversity considerations, user experience, and active safety. From an academic point of view, the project contributes to developing knowledge in the area of efficient decision support in virtual engineering design for ergonomics, including successful consideration of user diversity in design processes. The research findings will be implemented and tested in a digital human modelling (DHM) tool, exemplified by the Swedish DHM tool IPS IMMA (Intelligently Moving Manikins). The consortium for ADOPTIVE is based on the consortia of previous successful research projects. The previous projects established the foundation for simulations of vehicle ergonomics, and this foundation allows ADOPTIVE to address new research challenges and advance scientific and industrial impacts. Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC) will be a research partner on a consultancy basis. ADOPTIVE is an associated project of SAFER. SAFER is the hub for traffic safety research in Sweden. SAFER consists of 30 partners representing stakeholders within the automotive industry, academia and government agencies. Funding and collaboration: The Knowledge Foundation, CEVT, Scania, Volvo Cars, Volvo Technology AB (VTEC)
Publications (6 of 6) Show all publications
Perez Luque, E., Brolin, E., Högberg, D. & Lamb, M. (2022). Challenges for the Consideration of Ergonomics in Product Development in the Swedish Automotive Industry – An Interview Study. In: DESIGN2022: . Paper presented at DESIGN2022, 17th International Design Conference, May, 23-26, 2022, Croatia (pp. 2165-2174). Cambridge University Press, 2
Open this publication in new window or tab >>Challenges for the Consideration of Ergonomics in Product Development in the Swedish Automotive Industry – An Interview Study
2022 (English)In: DESIGN2022, Cambridge University Press, 2022, Vol. 2, p. 2165-2174Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an interview study aiming to understand the state of the art of how ergonomics designers work in the vehicle development process within the Swedish automotive industry. Ten ergonomic designers from seven different companies participated in the interview study. Results report the ergonomics designers' objectives, workflow, tools, challenges, and ideal work performance tool. We identify four main gaps and research directions that can enhance the current challenges: human behavior predictions, simulation tool usability, ergonomics evaluations, and integration between systems.

Place, publisher, year, edition, pages
Cambridge University Press, 2022
Series
Proceedings of the Design Society, E-ISSN 2732-527X ; Volume 2 - May 2022
Keywords
vehicle, ergonomics, human-centred design, simulation-based design, digital human modelling
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-22133 (URN)10.1017/pds.2022.219 (DOI)2-s2.0-85131373032 (Scopus ID)
Conference
DESIGN2022, 17th International Design Conference, May, 23-26, 2022, Croatia
Funder
Knowledge Foundation
Note

estela.perez.luque@his.se

This work has been made possible with the support from Knowledge Foundation in the project ADOPTIVE-Automated Design and Optimisation of Vehicle Ergonomics and participating organizations. This support is gratefully acknowledged.

Available from: 2022-12-16 Created: 2022-12-16 Last updated: 2023-01-17Bibliographically approved
Hanson, L., Högberg, D., Brolin, E., Billing, E., Iriondo Pascual, A. & Lamb, M. (2022). Current Trends in Research and Application of Digital Human Modeling. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June (pp. 358-366). Cham: Springer
Open this publication in new window or tab >>Current Trends in Research and Application of Digital Human Modeling
Show others...
2022 (English)In: Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches / [ed] Nancy L. Black; W. Patrick Neumann; Ian Noy, Cham: Springer, 2022, p. 358-366Conference paper, Published paper (Refereed)
Abstract [en]

The paper reports an investigation conducted during the DHM2020 Symposium regarding current trends in research and application of DHM in academia, software development, and industry. The results show that virtual reality (VR), augmented reality (AR), and digital twin are major current trends. Furthermore, results show that human diversity is considered in DHM using established methods. Results also show a shift from the assessment of static postures to assessment of sequences of actions, combined with a focus mainly on human well-being and only partly on system performance. Motion capture and motion algorithms are alternative technologies introduced to facilitate and improve DHM simulations. Results from the DHM simulations are mainly presented through pictures or animations.

Place, publisher, year, edition, pages
Cham: Springer, 2022
Series
Lecture Notes in Networks and Systems, ISSN 2367-3370, E-ISSN 2367-3389 ; 223
Keywords
Digital Human Modeling, Trends, Research, Development, Application
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Interaction Lab (ILAB); VF-KDO
Identifiers
urn:nbn:se:his:diva-19959 (URN)10.1007/978-3-030-74614-8_44 (DOI)2-s2.0-85111461730 (Scopus ID)978-3-030-74613-1 (ISBN)978-3-030-74614-8 (ISBN)
Conference
21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June
Funder
Knowledge Foundation, 20180167Vinnova, 2018-05026Knowledge Foundation, 20200003
Note

© 2022

Available from: 2021-06-22 Created: 2021-06-22 Last updated: 2023-08-16Bibliographically approved
Marshall, R., Brolin, E., Summerskill, S. & Högberg, D. (2022). Digital Human Modelling: Inclusive Design and the Ageing Population (1ed.). In: Sofia Scataglini; Silvia Imbesi; Gonçalo Marques (Ed.), Internet of Things for Human-Centered Design: Application to Elderly Healthcare (pp. 73-96). Singapore: Springer Nature
Open this publication in new window or tab >>Digital Human Modelling: Inclusive Design and the Ageing Population
2022 (English)In: Internet of Things for Human-Centered Design: Application to Elderly Healthcare / [ed] Sofia Scataglini; Silvia Imbesi; Gonçalo Marques, Singapore: Springer Nature, 2022, 1, p. 73-96Chapter in book (Refereed)
Abstract [en]

Digital human modelling (DHM) is a tool that allows humans to be modelled in three-dimensional CAD. An almost infinite variety of humans can be modelled and families of so-called manikins can be created to act as virtual user groups, evaluating the interactions between humans and products, workplaces and environments. This chapter introduces the concept of DHM, its use of, and reliance on, anthropometric data from national populations and showcases two exemplar tools in SAMMIE and IPS IMMA. Case studies are presented that highlight the advantages DHM can bring to understanding the requirements of designing for the ageing population; covering designing for the ageing workforce, the exploration of transport accessibility and how users can generate representative manikin families to properly represent the diversity of people. DHM is demonstrated to be a powerful tool for practitioners aiming to understand and design for people, including older people within society.

Place, publisher, year, edition, pages
Singapore: Springer Nature, 2022 Edition: 1
Series
Studies in Computational Intelligence, ISSN 1860-949X, E-ISSN 1860-9503 ; 1011
Keywords
Digital human modelling, Ageing, Anthropometry, SAMMIE, IPS IMMA
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; INF202 Virtual Ergonomics
Identifiers
urn:nbn:se:his:diva-20944 (URN)10.1007/978-981-16-8488-3_5 (DOI)2-s2.0-85126180378 (Scopus ID)978-981-16-8487-6 (ISBN)978-981-16-8488-3 (ISBN)978-981-16-8490-6 (ISBN)
Funder
Knowledge Foundation, 20180167Knowledge Foundation, 20200003
Note

First Online: 01 January 2022

Available from: 2022-02-28 Created: 2022-02-28 Last updated: 2022-04-25Bibliographically approved
Kolbeinsson, A., Brolin, E. & Lindblom, J. (2021). Data-Driven Personas: Expanding DHM for a Holistic Approach. In: Julia L. Wright; Daniel Barber; Sofia Scataglini; Sudhakar L. Rajulu (Ed.), Advances in Simulation and Digital Human Modeling: Proceedings of the AHFE 2021 Virtual Conferences on Human Factors and Simulation, and Digital Human Modeling and Applied Optimization, July 25-29, 2021, USA. Paper presented at International Conference on Applied Human Factors and Ergonomics (AHFE 2021), USA, July 25-29, 2021. (pp. 296-303). Springer, 264
Open this publication in new window or tab >>Data-Driven Personas: Expanding DHM for a Holistic Approach
2021 (English)In: Advances in Simulation and Digital Human Modeling: Proceedings of the AHFE 2021 Virtual Conferences on Human Factors and Simulation, and Digital Human Modeling and Applied Optimization, July 25-29, 2021, USA / [ed] Julia L. Wright; Daniel Barber; Sofia Scataglini; Sudhakar L. Rajulu, Springer, 2021, Vol. 264, p. 296-303Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we detail research and development of data-driven personas in the IPS-IMMA digital human modelling system. Semi-automatically generating personas for working with user experience (UX) aspects of the Operator 4.0 side of Industry 4.0 is suggested as a viable approach for contributing to operator well-being and diversity by supporting workstation designers to take these factors into account early in the workstation design process. These data-driven personas are being developed to be generated using anthropometric data from the manikin family generation module of IPS-IMMA. Specific design suggestions are presented, what should be taken into account and how that will be implemented, and the current state of development of the data-driven personas module is discussed. Prototypes are planned under the coming year.

Place, publisher, year, edition, pages
Springer, 2021
Series
Lecture Notes in Networks and Systems, ISSN 2367-3370, E-ISSN 2367-3389 ; 264
Keywords
Digital human modelling, DHM, Personas, Data-driven personas, Industry 4.0, Operator 4.0, Social sustainability
National Category
Human Computer Interaction Production Engineering, Human Work Science and Ergonomics
Research subject
INF202 Virtual Ergonomics; Interaction Lab (ILAB); User Centred Product Design
Identifiers
urn:nbn:se:his:diva-20250 (URN)10.1007/978-3-030-79763-8_36 (DOI)2-s2.0-85111990978 (Scopus ID)978-3-030-79762-1 (ISBN)978-3-030-79763-8 (ISBN)
Conference
International Conference on Applied Human Factors and Ergonomics (AHFE 2021), USA, July 25-29, 2021.
Funder
Knowledge Foundation, 20180167Knowledge Foundation, 20200003
Note

This work has been realized by the Knowledge Foundation and the INFINIT research environment (KKS Dnr. 20180167) who have financially supported the Synergy Virtual Ergonomics project (SVE), as well as partner organizations.

Available from: 2021-07-27 Created: 2021-07-27 Last updated: 2022-04-19Bibliographically approved
Brolin, E., Högberg, D. & Hanson, L. (2020). Skewed Boundary Confidence Ellipses for Anthropometric Data. In: Lars Hanson, Dan Högberg, Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020. Paper presented at 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020, Skövde, Sweden (pp. 18-27). Amsterdam: IOS Press
Open this publication in new window or tab >>Skewed Boundary Confidence Ellipses for Anthropometric Data
2020 (English)In: DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020 / [ed] Lars Hanson, Dan Högberg, Erik Brolin, Amsterdam: IOS Press, 2020, p. 18-27Conference paper, Published paper (Refereed)
Abstract [en]

Some anthropometric measurements, such as body weight often show a positively skewed distribution. Different types of transformations can be applied when handling skewed data in order to make the data more normally distributed. This paper presents and visualises how square root, log normal and, multiplicative inverse transformations can affect the data when creating boundary confidence ellipses. The paper also shows the difference of created manikin families, i.e. groups of manikin cases, when using transformed distributions or not, for three populations with different skewness. The results from the study show that transforming skewed distributions when generating confidence ellipses and boundary cases is appropriate to more accurately consider this type of diversity and correctly describe the shape of the actual skewed distribution. Transforming the data to create accurate boundary confidence regions is thought to be advantageous, as this would create digital manikins with enhanced accuracy that would produce more realistic and accurate simulations and evaluations when using DHM tools for the design of products and workplaces.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2020
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 11
Keywords
Anthropometry, Skewness, Boundary Cases, Confidence Ellipses
National Category
Production Engineering, Human Work Science and Ergonomics Probability Theory and Statistics
Research subject
User Centred Product Design
Identifiers
urn:nbn:se:his:diva-19120 (URN)10.3233/ATDE200005 (DOI)000680825700003 ()2-s2.0-85091204037 (Scopus ID)978-1-64368-104-7 (ISBN)978-1-64368-105-4 (ISBN)
Conference
6th International Digital Human Modeling Symposium, August 31 – September 2, 2020, Skövde, Sweden
Funder
Knowledge Foundation, 20180167
Note

CC BY-NC 4.0

Funder: Knowledge Foundation and the INFINIT research environment (KKS Dnr. 20180167). This work has been made possible with support from the Knowledge Foundation and the associated INFINIT research environment at the University of Skövde (projects: Synergy Virtual Ergonomics and ADOPTIVE), and with support from Vinnova in the VIVA project, and SAFER - Vehicle and Traffic Safety Centre at Chalmers, Sweden, and by the participating organizations. This support is gratefully acknowledged.

Available from: 2020-09-29 Created: 2020-09-29 Last updated: 2022-04-19Bibliographically approved
Brolin, E., Högberg, D. & Nurbo, P. (2020). Statistical Posture Prediction of Vehicle Occupants in Digital Human Modelling Tools. In: Vincent G. Duffy (Ed.), Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Posture, Motion and Health: 11th International Conference, DHM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part I. Paper presented at 11th International Conference, DHM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020 (pp. 3-17). Cham: Springer
Open this publication in new window or tab >>Statistical Posture Prediction of Vehicle Occupants in Digital Human Modelling Tools
2020 (English)In: Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Posture, Motion and Health: 11th International Conference, DHM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part I / [ed] Vincent G. Duffy, Cham: Springer, 2020, p. 3-17Conference paper, Published paper (Refereed)
Abstract [en]

When considering vehicle interior ergonomics in the automotive design and development process, it is important to be able to realistically predict the initial, more static, seated body postures of the vehicle occupants. This paper demonstrates how published statistical posture prediction models can be implemented into a digital human modelling (DHM) tool to evaluate and improve the overall posture prediction functionality in the tool. The posture prediction functionality uses two different posture prediction models in a sequence, in addition to the DHM tool´s functionality to optimize postures. The developed posture prediction functionality is demonstrated and visualized with a group of 30 digital human models, so called manikins, by using accurate car geometry in two different use case scenarios where the sizes of the adjustment ranges for the steering wheel and seat are altered. The results illustrate that it is possible to implement previously published posture prediction models in a DHM tool. The results also indicate that, depending on how the implemented functionality is used, different results will be obtained. Having access to a digital tool that can predict and visualize likely future vehicle occupants’ postures, for a family of manikins, enables designers and developers to consider and evaluate the human-product interaction and fit, in a consistent and transparent manner. © 2020, Springer Nature Switzerland AG.

Place, publisher, year, edition, pages
Cham: Springer, 2020
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 12198
Keywords
Digital human modelling, Posture prediction, Vehicle ergonomics, Automobile manufacture, Digital devices, Ergonomics, Forecasting, Health, Health risks, Human computer interaction, Risk management, Safety engineering, Vehicles, Automotive designs, Digital human models, Product interaction, Steering wheel, Use case scenario, Vehicle occupants, Predictive analytics
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design
Identifiers
urn:nbn:se:his:diva-18893 (URN)10.1007/978-3-030-49904-4_1 (DOI)2-s2.0-85088750749 (Scopus ID)978-3-030-49903-7 (ISBN)978-3-030-49904-4 (ISBN)
Conference
11th International Conference, DHM 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020
Projects
Virtual Driver Ergonomics
Funder
Knowledge Foundation
Note

This work has been made possible with the support from The Knowledge Foundation and the associated INFINIT research environment at the University of Skövde (projects: Virtual Driver Ergonomics, Synergy Virtual Ergonomics and ADOPTIVE), in Sweden, and SAFER - Vehicle and Traffic Safety Centre at Chalmers, Sweden, and by the participating organizations. This support is gratefully acknowledged.

Available from: 2020-08-11 Created: 2020-08-11 Last updated: 2022-04-19Bibliographically approved
Principal InvestigatorBrolin, Erik
Co-InvestigatorBrolin, Erik
Co-InvestigatorHögberg, Dan
Co-InvestigatorLamb, Maurice
Co-InvestigatorPerez Luque, Estela
Co-InvestigatorBandaru, Sunith
Coordinating organisation
University of Skövde
Funder
Period
2021-03-01 - 2024-02-29
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
DiVA, id: project:2616Project, id: 20200003

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ADOPTIVE