To facilitate the construction of a robust transport infrastructure, it is
essential to implement a digital transformation of the current highway system.
The concept of digital twins, which are virtual replicas of physical assets,
offers a novel approach to enhancing the operational efficiency and predictive
maintenance capabilities of highway networks. The present study begins with an
exhaustive examination of the demand for the smart highway digital twin model,
underscoring the necessity for a comprehensive framework that addresses the
multifaceted aspects of digital transformation. The framework, as proposed, is
composed of six integral components: spatiotemporal data acquisition and
processing, multidimensional model development, model integration, application
layer construction, model iteration, and model governance. Each element is
critical in ensuring the fidelity and utility of the digital twin, which must
accurately reflect the dynamic nature of highway systems. The methodology for
constructing a smart highway digital twin model is explored through a systematic
approach that encompasses three pivotal stages. The first stage involves the
comprehensive perception of spatiotemporal data, the foundation for any digital
twin. The second stage pertains to entity modeling, where the physical assets of
the highway system are digitized, thus creating a virtual representation that
can be manipulated and analyzed. The final stage is real-time state modeling,
which enables the digital twin to simulate the current state of the highway
system, thereby providing real-time feedback and predictive analytics. This work
aims to contribute to the theoretical and technical discourse surrounding smart
highway digital twins, offering insights that can inform the development and
practical application of such models. By adhering to the proposed framework and
methodology, workers in the transportation sector can leverage the potential of
digital twins to enhance safety, efficiency, and sustainability within the
highway infrastructure ecosystem.