Examining pedestrians' trust in automated vehicles based on attributes of trust: A qualitative study

Pedestrians' trust in automated vehicles (AVs) needs to be analyzed and deconstructed to update it from its current broad concept into several lower-level attributes for assessment and measurement. In this study, we have employed virtual reality (VR) and scenario-based interviews to examine the trust of pedestrians toward AVs, based on the attributes of trust and trustworthiness. A hybrid approach of inductive and deductive thematic analysis of the responses of 36 participants was undertaken. Eight such attributes emerged from the analysis, including statistical reliability and dependability, competence, predictability, familiarity, authority/subversion, liberty/oppression, care/harm, and sanctity/degradation. The first four are objective attributes concerning automation trustworthiness and human trust in automation, while the remaining four are subjective attributes, analogous to properties of human morality. The findings of this study provide an empirical grounding for trust theories. Specifically, we have highlighted the importance of subjective qualities in constituting pedestrian-AV trust, including "automation morality" and "care/harm".