The influence of Anthropomorphism, Interactivity, Perceived Green Value, and Social Influence on pedestrian acceptance of fully autonomous vehicles: The mediating effect of Perceived Risk and Perceived Safety.

Objective: Although Fully Autonomous Vehicles (FAVs) will bring significant benefits to road traffic, the replacement of human drivers by automated systems weakens pedestrians' ability to socially interact with road traffic and reduces their acceptance of FAVs. This study aims to explore factors influencing pedestrians' acceptance of FAVs.

Methods: This study proposes a novel FAVs Acceptance Model from the pedestrian perspective, integrating the Stimulus-Organism-Response (S-O-R) framework and Perceived Risk Theory. We examine four key antecedent variables Anthropomorphism, Interactivity, Perceived Green Value, and Social Influence and explore their influence on pedestrian acceptance through the mediating roles of Perceived Risk and Perceived Safety. Data were collected from 301 Chinese participants through an online survey, and Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to empirically analyze the model.

Results: The results reveal that Interactivity significantly enhances acceptance by reducing Perceived Risk and increasing Perceived Safety. Anthropomorphism influences acceptance primarily through reducing Perceived Risk, while its effect via Perceived Safety is not significant. Perceived Green Value improves Perceived Safety but has no significant impact on reducing Perceived Risk. Notably, Social Influence increases Perceived Risk and reduces Perceived Safety, leading to a negative indirect effect on Acceptance.

Conclusions: This study makes several contributions: (a) it expands the FAVs acceptance literature by shifting the focus to pedestrians, an underexplored stakeholder group; (b) it provides an integrated model combining psychological and design-related variables; (c) it offers actionable insights for policymakers and designers to improve human-FAVs interactions. These study findings offer a robust theoretical foundation and practical guidance for advancing safe and inclusive autonomous mobility.