Digital twins (DTs) are emerging as a promising technology for effective infrastructure management by continuously capturing the dynamic and comprehensive state of physical systems. However, their adoption for managing road infrastructure during the operation and maintenance (O&M) phase remains limited, which is otherwise the most prolonged and critical phase of the asset life cycle. This study proposed a multitier DT framework specifically tailored for road O&M, which is designed to be flexible, modular, interoperable, and, importantly, trustworthy. A core component of this framework is a trustworthy AI-supported module that assists users in making informed decisions that align with their preferences and expectations, thereby fostering user trust and satisfaction in the road DT system. The framework was piloted on three major roads in the United Kingdom, demonstrating its effectiveness through the implementation of vegetation control. This study aims to actively promote the development and deployment of DT technologies and trustworthy AI within advanced road infrastructure management.