Abstract
The work aims to conduct systematic review of literature on human-machine interface (HMI) of intelligent vehicles, summarize the objects, metrics, and methods for evaluation of user experience (UX) to develop a methodology for UX of HMI in intelligent vehicles. System literature review (SLR) was conducted and information was extracted from literature included in the systematic review to obtain basic data and conduct analysis. The effects of the development trend of intelligent vehicles on UX design and evaluation of vehicle HMI were analyzed and the research progress of UX was summarized from three aspects, which included evaluation objects, evaluation metrics and evaluation methods. It put forward two dimensions of evaluation objects:product types and product elements (including physical characteristics and virtual elements), and emphatically elaborated three types of evaluation metrics (namely safety, performance, and experience), based on the optimization layer of human-machine system. Three evaluation method dimensions were constructed based on the attributes of the evaluation methods, which included research objects, the method attributes, and the quality -efficiency, providing reference for the selection of evaluation methods. Besides, the application of evaluation tools in different studies was analyzed in detail. Finally, the objects, metrics and methods of evaluation were summarized. In the era of intelligent vehicles, the development of technology has increased the complexity of HMI. UX evaluation has been proved to be beneficial to provide feedback to help developers design and improve products and complete product iterations. This method can provide vehicle developers with theoretical knowledge and practical reference on how to conduct UX evaluation successfully.
Key words
intelligent vehicle; human-machine interaction; human-machine interface; user experience evaluation
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TAN Hao, TANG Shi-yan.
User Experience Evaluation Methodology of Interactive Interface in Intelligent Vehicle[J]. Packaging Engineering. 2023, 44(6): 12-24 https://doi.org/10.19554/j.cnki.1001-3563.2023.06.002
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