Impact of Perceived Accident Risk on Automated Driving Technology Acceptance: Roles of Functional, Operational, and Human–Machine Collaboration Risks

As accidents involving automated vehicles occur with increasing frequency, the acceptance of automated driving technology (ADT) has shown a declining trend. However, the underlying mechanism through which accident risks influence ADT acceptance remains unclear, obstructing the development of ADT. To effectively quantify the impact of these risks on ADT acceptance, this study first quantified perceived accident risk into three dimensions—perceived functional risk (PFR), human operational risk (HOR), and human–machine collaboration risk (HMCR)—through the literature review and causal analysis of accident cases. Second, a theoretical model of ADT acceptance based on the perceived accident risk was constructed. Subsequently, structural equation modeling was applied to test the research hypotheses based on survey data from 1,642 drivers. The results indicate that PFR, HOR, and HMCR exert differential influence mechanisms on behavioral intention: PFR via attitude/subjective norm, and HOR/HMCR via perceived behavioral control (PBC). Moreover, compared to the mediating effect of PBC on HOR, its mediating effect on HMCR is relatively stronger, suggesting that individuals perceive weaker ability to manipulate and control HMCR. Thus, this study not only expands the theoretical framework of perceived risk influencing ADT acceptance, but also presents an empirical basis for formulating interventions to increase ADT acceptance.