Building trust in autonomous driving: a conceptual model and design insights

In the automotive industry, the introduction of advanced AI technologies such as L3 autonomous driving is generally expected to significantly enhance traffic safety. However, the widespread adoption of these technologies in the actual market has encountered notable obstacles, with the core difficulty lying in successfully establishing user trust. To construct a trustworthy human-machine co-driving interaction system, we have conducted an in-depth analysis of existing research findings in the field of automation trust, considering them as important experiences and lessons learned from the application of AI technologies in autonomous vehicles. Based on these research findings in automation trust, we systematically defined the key attributes of autonomous driving trust and its primary influencing factors, and further constructed a conceptual model to comprehensively elucidate the underlying logic of the trust mechanism. On this foundation, we proposed a series of design suggestions aimed at enhancing trust in autonomous vehicles. Finally, we briefly introduced several design practice cases by automotive companies. This paper aims to provide invaluable references and guidance for researchers and designers of autonomous vehicles, helping them better address the critical challenge of trust establishment, and thereby facilitating the market penetration and industry development of autonomous driving technologies.