Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-26T03:44:35.404Z Has data issue: false hasContentIssue false
  • English
  • Français

A VALUE-DRIVEN DESIGN APPROACH FOR THE VIRTUAL VERIFICATION AND VALIDATION OF AUTONOMOUS VEHICLE SOLUTIONS

Published online by Cambridge University Press:  19 June 2023

Marco Bertoni  and
Stefan Thorn
Marco Bertoni*
Affiliation:
Blekinge Institute of Technology;
Stefan Thorn
Affiliation:
Volvo Autonomous Solutions
*
Bertoni, Marco, Blekinge Institute of Technology, Sweden, [email protected]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Autonomous vehicle solutions (AVS) are regarded as a major enabling technology to support the realization of 'total site solutions' in the construction equipment industry. Their full-scale deployment is hindered today by the need to test autonomous driving capabilities against the varying conditions an AVS is expected to be exposed to during its lifetime. Therefore, using virtual simulation environments is common to overcome the cost and time limitations of physical testing. A caveat in this virtual verification and validation (V&V) work is how to trade off the ‘realism’ of the V&V output (using high-fidelity models across many scenarios) against computational time. This research investigates expectations and needs for value-driven decision support in the virtual V&V process, proposing an approach and a tool to raise awareness among decision-makers about the value associated with using selected simulation models/components in the virtual verification and validation task for AVS. Verification activities performed on the initial prototype show that its main benefit lies in facilitating cross-domain negotiations and knowledge sharing when negotiating the desired features of the virtual simulation environment.

Keywords

Value-Driven DesignCase studySystems Engineering (SE)Virtual Engineering (VE)Digital / Digitised engineering value chains
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 435 - 444
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Argyris, C. and Schön, D.A. (1989), “Participatory action research and action science compared: A commentary”, American behavioral scientist, Vol. 32, No. 5, pp. 612–623. https://doi.org/10.1177/0002764289032005008CrossRefGoogle Scholar
Bertoni, M., Bertoni, A. and Isaksson, O. (2018), EVOKE: “A Value-Driven Concept Selection Method for Early System Design”, Journal of Systems Science and Systems Engineering, Vol. 27, No. 1, pp. 46–77. https://doi.org/10.1007/s11518-016-5324-2CrossRefGoogle Scholar
Blessing, L.T. and Chakrabarti, A. (2009), DRM: A Design Research Methodology, Springer, London, UK. https://doi.org/10.1007/978-1-84882-587-1_2CrossRefGoogle Scholar
Bobbe, T., Opeskin, L., Lüneburg, L. M., Wanta, H., Pohlmann, J., & Krzywinski, J. (2023). “Design for communication: how do demonstrators demonstrate technology?”. Design Science, Vol. 9, e3.CrossRefGoogle Scholar
Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R. and Schiele, B. (2016), “The cityscapes dataset for semantic urban scene understanding”, IEEE Conference on computer vision and pattern recognition, pp. 3213–3223.CrossRefGoogle Scholar
Donà, R. and Ciuffo, B. (2022), “Virtual testing of Automated Driving Systems. A survey on Validation Methods”, IEEE Access. Vol. 10, pp. 24349–24367. https://doi.org/10.1109/ACCESS.2022.3153722CrossRefGoogle Scholar
Eres, M.H., Bertoni, M., Kossmann, M. and Scanlan, J. (2014). “Mapping customer needs to engineering characteristics: an aerospace perspective for conceptual design”, Journal of Engineering Design, Vol. 25, No. (1-3), pp. 64–87. https://doi.org/10.1080/09544828.2014.903387CrossRefGoogle Scholar
Frank, M., Ruvald, R., Johansson, C., Larsson, T., & Larsson, A. (2019). Towards autonomous construction equipment-supporting on-site collaboration between automatons and humans. International Journal of Product Development, 23(4), 292–308.CrossRefGoogle Scholar
Hospach, D., Mueller, S., Rosenstiel, W. and Bringmann, O. (2016), “Simulation of falling rain for robustness testing of video-based surround sensing systems”, IEEE Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 233–236.CrossRefGoogle Scholar
Isaksson, O., Kossmann, M., Bertoni, M., Eres, H., Monceaux, A., Bertoni, A., Wiseall, S. and Zhang, X. (2013), “Value-Driven Design–A methodology to Link Expectations to Technical Requirements in the Extended Enterprise”, INCOSE International Symposium, Vol. 23, No. 1, pp. 803–819. https://doi.org/10.1002/j.2334-5837.2013.tb03055.xCrossRefGoogle Scholar
Johansson, C., Wall, J. and Panarotto, M. (2017), “Maturity of models in a multi-model decision support system”, In DS 87-6 Proceedings of the 21st International Conference on Engineering Design (ICED 17) Vol 6: Design Information and Knowledge, Vancouver, Canada, pp. 237–246.Google Scholar
Koopman, P. and Wagner, M. (2016). ”Challenges in autonomous vehicle testing and validation”, International Journal of Transportation Safety, Vol. 4, No. 1, pp. 15–24. https://doi.org/10.4271-2016-01-0128CrossRefGoogle Scholar
Leminen, S., Rajahonka, M., Wendelin, R., Westerlund, M. and Nyström, A.G. (2022), “Autonomous vehicle solutions and their digital servitization business models”. Technological Forecasting and Social Change, Vol. 185, 122070. https://doi.org/10.1016/j.techfore.2022.122070CrossRefGoogle Scholar
Monceaux, A. and Kossmann, M. (2012), “Towards a Value-Driven Design Methodology–Enhancing Traditional Requirements Management Within the Extended Enterprise”, INCOSE International Symposium. Vol. 22, No. 1, pp. 910–925. https://doi.org/10.1002/j.2334-5837.2012.tb01379.xCrossRefGoogle Scholar
Rezaei, A. and Caulfield, B. (2021), “Safety of autonomous vehicles: what are the insights from experienced industry professionals?”. Transportation research part F: traffic psychology and behaviour. Vol. 81, pp. 472–489. https://doi.org/10.1016/j.trf.2021.07.005CrossRefGoogle Scholar
Riedmaier, S., Danquah, B., Schick, B. and Diermeyer, F. (2021), “Unified framework and survey for model verification, validation and uncertainty quantification”, Archives of Computational Methods in Engineering, 28(4), 2655–2688. https://doi.org/10.1007/s11831-020-09473-7CrossRefGoogle Scholar
Schlager, B., Muckenhuber, S., Schmidt, S., Holzer, H., Rott, R., Maier, F. M., et al. (2020), “State-of-the-art sensor models for virtual testing of advanced driver assistance systems/autonomous driving functions”, SAE International Journal of Connected and Automated Vehicles, Vol. 3, pp. 233–261. https://doi.org/10.4271/12-03-03-0018CrossRefGoogle Scholar
Schramm, D., Hiller, M. and Bardini, R. (2016), Vehicle Dynamics: Modeling and Simulation, Springer Berlin, Heidelberg.Google Scholar
Struwe, S., & Slepniov, D. (2023). Unlocking digital servitization: A conceptualization of value co-creation capabilities. Journal of Business Research, 160, 113825.CrossRefGoogle Scholar
von Bernuth, A., Volk, G. and Bringmann, O. (2019), Simulating photo-realistic snow and fog on existing images for enhanced CNN training and evaluation, IEEE Intelligent Transportation Systems Conference (ITSC), pp. 41–46. https://doi.org/10.1109/ITSC.2019.8917367CrossRefGoogle Scholar
Yin, R.K., Case study research: Design and methods, Sage publications Ltd, London, UK.Google Scholar