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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, marco.bertoni@bth.se

Abstract

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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

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