User Experience Evaluation Indicators for Automotive Autonomous Driving Takeover System

Automotive automation technology reduces the burden on humans, it also introduces new human factors and difficulties such as low or excessive cognitive load, lack of attention, and so on. However, the user experience review of the automotive autonomous driving takeover system has yet to establish a consistent standard. In this study, we use user research to better understand users’ real needs, behavioral habits, and experience feelings, to clarify current problems in the user experience of the automotive autonomous driving takeover system, and to obtain and analyze user experience indexes to build a more comprehensive evaluation system with practical significance. In this study, we initially obtain the indicator dimensions through qualitative research methods and analyze and categorize them accordingly, apply the user experience evaluation method and model construction method, use the grounded theory to interpret the semi-structured interview materials in a bottom-up progressive description, refine the concepts and cluster categories, and construct the relevant evaluation indicator system by analyzing the logical relationship. This study systematically constructed user experience evaluation indicators for autonomous driving takeover systems in automobiles, which has corresponding guiding significance for relevant researchers.