Navigating artificial intelligence risk: Investigating intention to adopt driverless vehicles through an extended technology acceptance model

The growing development of driverless vehicles profoundly affects the future transportation landscape. The realization of their safety, environmental benefits, and economic efficiency hinges on practical implementation. Understanding the public’s perceived risks and psychological acceptance process of driverless vehicles is critical to predicting their widespread adoption. This research expands the technology acceptance model by incorporating perceived risk, affect-based trust, cognition-based trust, personal innovativeness, subjective norms, and cost to explain the adoption intention of driverless vehicles. The data utilized in this study were gathered through a questionnaire survey carried out in China. The findings indicate that perceived usefulness, perceived ease of use, attitude, and subjective norms exert positive influences on behavioral intention, whereas cost exhibits negative effects. Perceived risk demonstrates a dual-path influence: while it directly inhibits behavioral intention, it also exhibits significant indirect effects on behavioral intention through perceived usefulness and perceived ease of use. Personal innovativeness significantly enhances both perceived ease of use and perceived usefulness. Both cognition-based trust and affect-based trust enhance perceived usefulness and perceived ease of use. This study offers management insights for stakeholders to boost the public’s intention to adopt driverless vehicles.