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MOBILITY BOX: A DESIGN RESEARCH METHODOLOGY TO EXAMINE PEOPLE'S NEEDS IN RELATION TO AUTONOMOUS VEHICLE DESIGNS AND MOBILITY BUSINESS MODEL
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Design Methods
Published online by Cambridge University Press: 11 June 2020
Abstract
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The future focus of research in the automotive sector will be on automation and data-driven technologies. These technologies provide new services and values to customers, owners and other stakeholders in mobility. We propose a wizard-of-oz like method to evaluate future user needs and redesign the current approach of vehicle development. The mobility box provides a modular and extendable framework to merge user centred design with vehicle data acquisition. This enables the design of services and properties for unknown mobility concepts.
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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
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References
Achleiter, A. et al. (2016), “Formen und neue Konzepte”, In: Pischinger, S. and Seiffert, U. (Eds.), Vieweg Handbuch Kraftfahrzeugtechnik, ATZ/MTZ-Fachbuch, Springer Fachmedien, Wiesbaden, pp. 131–251.CrossRefGoogle Scholar
Becker, T. et al. (2018), Enabling the Value of Time: Implikationen für die Innenraumgestaltung autonomer Fahrzeuge, Fraunhofer IAO, Stuttgart.Google Scholar
Bellem, H. et al. (2018), “Comfort in automated driving. An analysis of preferences for different automated driving styles and their dependence on personality traits”, Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 55, pp. 90–100.CrossRefGoogle Scholar
Buchenau, M. and Suri, J.F. (2000), “Experience prototyping”, In: Designing interactive systems: Processes, practices, methods, and techniques, ACM, New York City, pp. 424–433.CrossRefGoogle Scholar
Cohen, B. and Kietzmann, J. (2014), “Ride On! Mobility Business Models for the Sharing Economy”, Organization & Environment, Vol. 27 No. 3, pp. 279–296.CrossRefGoogle Scholar
Festner, M., Eicher, A. and Schramm, D. (2017), “Beeinflussung der Komfort- und Sicherheitswahrnehmung beim hochautomatisierten Fahren durch fahrfremde Tätigkeiten und Spurwechseldynamik”, 11. Workshop Fahrerassistenzsysteme und automatisertes Fahren, pp. 63–73.Google Scholar
Fuchs, J. and Lienkamp, M. (2013), “Technologie und Architektur für Elektrifizierte Fahrzeuge”, ATZ - Automobiltechnische Zeitschrift, Vol. 115 No. 3, pp. 164–170.CrossRefGoogle Scholar
Gomez, R., Popovic, V. and Bucolo, S. (2006), “Emotional driving experiences: An opportunity for future technology”, Proceedings from the 5th Conference on Design and Emotion.Google Scholar
Gunn, W., Otto, T. and Smith, R.C. (2014), Design anthropology: Theory and practice, Bloomsbury, London.Google Scholar
Hartwich, F., Beggiato, M. and Krems, J.F. (2018), “Driving comfort, enjoyment and acceptance of automated driving - effects of drivers’ age and driving style familiarity”, Ergonomics, Vol. 61 No. 8, pp. 1017–1032.CrossRefGoogle ScholarPubMed
Heißing, B. and Brandl, H.J. (2002), Subjektive Beurteilung des Fahrverhaltens, Vogel, Würzburg.Google Scholar
Helm, S., Günter, B. and Eggert, A. (2017), Kundenwert: Grundlagen - Innovative Konzepte - Praktische Umsetzungen, Springer Fachmedien, Wiesbaden.CrossRefGoogle Scholar
Martelaro, N. and Ju, W. (2017a), “The Needfinding Machine”, Companion of the 2017 ACM/IEEE International Conference on Human Robot Interaction, Vienna, Association for Computing Machinery, pp. 355–356.CrossRefGoogle Scholar
Martelaro, N. and Ju, W. (2017b), “WoZ Way”, Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, Portland, ACM, pp. 21–24.CrossRefGoogle Scholar
McKim, R. (2016), “Designing for the Whole Man”, In: Arnold, J.E. (Ed.), Creative engineering, pp. 198–217.Google Scholar
Mok, B. and Ju, W. (2014), “The Push vs Pull of Information between Autonomous Cars and Human Drivers”, 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications – Automotive UI, Seattle, ACM Press, pp. 1–5.CrossRefGoogle Scholar
Risto, M. et al. (2017), “Human-Vehicle Interfaces: The Power of Vehicle Movement Gestures in Human Road User Coordination”, 9th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design: driving assessment, Manchester Village, University of Iowa, pp. 186–192.CrossRefGoogle Scholar
Rothenbücher, D. et al. (2015), “Ghost driver”, 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Nottingham, Association for Computing Machinery, pp. 44–49.CrossRefGoogle Scholar
SAE (2018), SAE J3016:2018, Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles, SAE International, Warrendale.Google Scholar
Schloßmacher, J. (2017), Concept Car Audi Aicon – autonom auf Zukunftskurs. Available at: https://www.audi-mediacenter.com/de/pressemitteilungen/concept-car-audi-aicon-autonom-auf-zukunftskurs-9332 (accessed 25 November 2019).Google Scholar
Tzivanopoulos, T. et al. (2014), “Analysis of new freedoms in future vehicle interiors”, 14. Internationales Stuttgarter Symposium: Automobil- und Motorentechnik, Springer Vieweg, pp. 1475–1488.CrossRefGoogle Scholar
Volkswagen, A.G. (2018), SEDRIC: Das Auto der Zukunft zum Anfassen. available at: https://www.volkswagenag.com/de/news/stories/2018/02/sedric-the-future.html (accessed 25 November 2019).Google Scholar
Weber, C. (2007), “Looking at ‘DFX’ and ‘Product Maturity’ from the Perspective of a New Approach of Modelling Product and Product Development Processes”, 17th CIRP Design Conference, Nantes, Springer, pp. 85–104.CrossRefGoogle Scholar
Wiedemann, E., Meurle, J. and Lienkamp, M. (2012), “Optimization of Electric Vehicle Concepts Based on Customer-Relevant Characteristics”, SAE 2012 World Congress and Exhibition, Detroit, SAE.CrossRefGoogle Scholar
Winner, H. and Wachenfeld, W. (2015), “Auswirkungen des autonomen Fahrens auf das Fahrzeugkonzept”, In: Maurer, M. (Ed.), Autonomes Fahren: Technische rechtliche und gesellschaftliche Aspekte, Springer Vieweg, Berlin, pp. 265–285.CrossRefGoogle Scholar
Wittmann, M. et al. (2017), “A holistic framework for acquisition, processing and evaluation of vehicle fleet test data”, 20th International Conference on Intelligent Transportation Systems, Yokohama, IEEE, pp. 1–7.CrossRefGoogle Scholar
Woopen, T. et al. (2018), “UNICARagil - Disruptive modulare Architektur für agile, automatisierte Fahrzeugkonzepte”, Aachener Kolloquium, Vol. 27, Aachen, RWTH Aachen University.Google Scholar
Ziemann, A. (2007), Zielsystemmanagement für die Produktentstehung von PKW, [ PhD thesis], Technical University of Munich.Google Scholar
Zott, C. and Amit, R. (2010), “Business Model Design: An Activity System Perspective”, Long Range Planning, Vol. 43 No. 2-3, pp. 216–226.CrossRefGoogle Scholar
Zott, C., Amit, R. and Massa, L. (2011), “The Business Model: Recent Developments and Future Research”, Journal of Management, Vol. 37 No. 4, pp. 1019–1042.CrossRefGoogle Scholar
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