Public acceptance of autonomous flying cars in urban air mobility: The mediating role of trust

The widespread deployment of autonomous flying cars relies heavily on artificial intelligence, making public trust in AI a prerequisite for willingness to fly. However, how AI-related attributes shape this trust and adoption willingness remains underexplored. Based on the integrative model of trust, this study investigates how negative AI attitudes and AI literacy shape public willingness to adopt autonomous flying cars, with trust playing a key mediating role and AI self-efficacy acting as a moderator. Based on survey data collected from 420 respondents, mediation analysis demonstrates that trust plays a predominant mediating role in the relationship between AI attitudes and willingness to fly. AI literacy is examined along various dimensions, such as technical understanding and critical appraisal, which yield divergent effects on trust. While technical understanding is positively associated with trust, critical appraisal shows no significant effect. This suggests that in early-stage adoption, trust is driven more by prior knowledge than by cognitive evaluation. Moreover, an Artificial Neural Network coupled with explainable machine learning is further employed for nonlinear insights, revealing significant nonlinear relationships between these factors and willingness to fly, particularly the opposing effects of critical appraisal. These findings provide theoretical and empirical support for UAM policymaking and sustainable urban mobility.