biostudies-literatureLiao WSichuan Province Science and Technology Support ProgramXihua UniversityState Key Laboratory of Vehicle NVH and Safety Technologye0331911https://www.ebi.ac.uk/biostudies/studies/S-EPMC12425220biostudies-literatureUnknown20(9)This study explains Chinese public acceptance of autonomous driving (n = 412) through subjective norms, personal norms, and psychological empowerment (cognitive, emotional, behavioral). Using covariance-based SEM with bootstrapped mediation, we find behavioral empowerment has the strongest direct effect on acceptance (≈2 × cognitive; ≈ 3.2 × emotional). All three empowerment dimensions partially mediate both subjective- and personal-norm paths, with behavioral mediation (≈46-50%) dominating. Importance-Performance Analysis highlights behavioral empowerment as high-importance/high-performance, while cognitive empowerment shows headroom for improvement. A Bayesian network confirms predictive validity with low overall error. Findings suggest design and policy should primarily strengthen usersPloS oneTop-down norms and psychological empowerment: Explaining Chinese public acceptance of autonomous driving.PMC12425220S202410623072S202410623061Z231015IVSTSKL-202424Liu XJiang KYang JChen JLiao WfalseTop-down norms and psychological empowerment: Explaining Chinese public acceptance of autonomous driving.This study explains Chinese public acceptance of autonomous driving (n = 412) through subjective norms, personal norms, and psychological empowerment (cognitive, emotional, behavioral). Using covariance-based SEM with bootstrapped mediation, we find behavioral empowerment has the strongest direct effect on acceptance (≈2 × cognitive; ≈ 3.2 × emotional). All three empowerment dimensions partially mediate both subjective- and personal-norm paths, with behavioral mediation (≈46-50%) dominating. Importance-Performance Analysis highlights behavioral empowerment as high-importance/high-performance, while cognitive empowerment shows headroom for improvement. A Bayesian network confirms predictive validity with low overall error. Findings suggest design and policy should primarily strengthen users2025-01-01T00:00:00Z20252026-04-23T03:20:16.074Z2026-04-23T03:10:23.679ZS-EPMC124252204093417310.1371/journal.pone.0331911