Impact of Technology Readiness on User Satisfaction in Autonomous Driving Under Intelligent Automation

Autonomous driving technology is transitioning rapidly from laboratory research to large-scale commercialization. However, technological maturity alone does not ensure high user satisfaction. Guided by the Technology Readiness Level (TRL) model, this study extends TRL’s application into autonomous driving by developing a theoretical framework linking technology maturity to user satisfaction through key mediating factors: perceived ease of use, perceived safety, system reliability, and user experience. Using Apollo Go in Wuhan as a case, survey data from 1,077 valid respondents were analyzed through structural equation modeling (SEM). Results show that TRL has both a significant direct effect and notable indirect effects on user satisfaction via the mediating variables, with perceived safety playing the most influential mediating role. The findings validate TRL’s applicability in intelligent automation contexts and reveal multi-level pathways for enhancing satisfaction, offering theoretical and practical insights for technology optimization and user acceptance strategies in intelligent transportation.