文献类型：期刊文献

英文题名：Vehicle multi-sensory user interaction design research based on MINDS methods

作者：Wu, Qianqian[1]; Zhang, Zhang[1]

机构：[1] East China University of Science and Technology, Shanghai, 200237, China

年份：2020

卷号：959

起止页码：442

外文期刊名：Advances in Intelligent Systems and Computing

收录：EI(收录号：20192507070058)

语种：英文

外文关键词：Artificial intelligence - Eye tracking - Audition - Speech recognition - Graphical user interfaces

摘要：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. ? Springer Nature Switzerland AG 2020.