Abstract
With the Development of Artificial Intelligence, there are different ways to interact with vehicles besides graphical user interface (GUI). Technology such as speech recognition, gesture recognition, facial expression recognition, and gaze tracking has gradually gained application in vehicle interaction. The advances in autonomous driving technology will also lead to the transformation of vehicle functions from transportation to multi-sensory space. Users can get a comprehensive experience based on sight, hearing, touch, taste and smell in future vehicles. Therefore, an exploration of the future vehicle interaction design combined with vehicle technology is needed. The objective of this paper is to deliver a vehicle multi-sensory user interaction design model based on the MINDS method [1]. This paper starts with the function analysis based on user requirement. On this basis, a connection between user and innovative services can be illustrated which enhances the user experience. Then an interaction sketch offered a detailed view of how users interact with vehicles and how technology impacts interaction. Finally, a new vehicle interaction model can be created by integrating the scenarios, technology, and users.
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Grenha Teixeira, J., Patrício, L., Huang, K.H., et al.: The MINDS method: integrating management and interaction design perspectives for service design. J. Serv. Res. 20(3), 195–197 (2017)
Stolovitch, H.D., Keep, E.J.: Telling ain’t training. American Society for Training and Development (2011)
Jinyan, T.: The interactive design in the era of big data. J. Packag. Eng. 36(8), 1–5 (2015)
Xiaoshan, Y., Liang, Y.: The development of the Internet of Things industry in 2018 and the outlook. J. China Autom. Ident. Technol. 6(8), 51–55 (2018)
SAE Standard J3016: Taxonomy and definitions for terms related to on-road motor vehicle automated driving systems, vol. 4, pp. 593–598 (2014)
Kuhnert, F., Stürmer, C., Koste, A.: Five Trends Transforming the Automotive Industry. PricewaterhouseCoopers, Frankfurt (2018)
Howard, D., Dai, D.: Public perceptions of self-driving cars: the case of Berkeley, California. In: Transportation Research Board 93rd Annual Meeting, vol. 14, no. 4502 (2014)
Schoettle, B., Sivak, M.: A survey of public opinion about autonomous and self-driving vehicles in the US, the UK, and Australia (2014)
Acknowledgments
We thank everyone who provided valuable suggestions and feedback during the writing of this paper, especially Dr. Zhang Zhang. Thanks to the supported by Shanghai Summit Discipline in Design - DA18304.
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Wu, Q., Zhang, Z. (2020). Vehicle Multi-sensory User Interaction Design Research Based on MINDS Methods. In: Nunes, I. (eds) Advances in Human Factors and Systems Interaction. AHFE 2019. Advances in Intelligent Systems and Computing, vol 959. Springer, Cham. https://doi.org/10.1007/978-3-030-20040-4_40
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DOI: https://doi.org/10.1007/978-3-030-20040-4_40
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