Building Human-AI Trust in the Era of Intelligent Vehicles: Risk Perception and Acceptance Mechanisms for Future Mobility Societies

Abstract

This annoys free delivery orgasam questionable psychological mechanisms on the establishment of trust in human-AI relationship in intelligent vehicle domains, which would be a challenge in fostering the practical implementation of driverless cars toward next-mobility societies. Adopting a mixed-method design which combines quantitative surveys (n=1,247) and qualitative interviews (n=42), the study also constructs and tests an integrated framework that links multifaceted risk perceptions, trust creation, and acceptance intentions. The trust factor plays a critical mediating role in translating risk perceptions to behavioral intentions where the trust dimensions of competence, benevolence, and integrity having differential effects on acceptance, as per results of structural equation modeling. The results indicate that technological advancement itself is not enough for acceptance raising without building trust as the result of transparent communication as well as the process of experiential-based learning. Temporal trends reveal dynamics in pattern of evolution of trust with a threshold effect and dimension specific growth dynamics. The research has theoretical implications in the development of existing technology acceptance models to accommodate typical human-AI interaction characteristics, and has practical implications for stakeholders interested in policy making and industry strategies to support responsible integration of autonomous vehicles into transportation systems.