Current Status and Future Prospects of Digital Twin Technology Applications in Intelligent Transportation Infrastructure Management

Abstract

Digital twin technology has emerged as a promising solution for the digital transformation of transportation infrastructure. This paper presents a comprehensive review of digital twin technology in the transportation industry, analyzing its relationship with key enabling technologies. By examining the development of digital twins across various transportation domains, we summarize the connotation, characteristics, and development trends of digital twins in transportation infrastructure. We propose a conceptual model and a digital system architecture for transportation infrastructure, along with a set of engineering application technical guidelines. Our findings reveal that current digital twin technology still faces challenges in driving the digital transformation of the transportation industry. From a theoretical perspective, the granularity of digital twin models is insufficient, lacking systematic support. In terms of application, the reconstruction of full-cycle digital processes primarily focuses on low-level applications. Future research should focus on theory innovation, data fusion, model integration, and professional applications to promote the development of digital twin technology in transportation infrastructure. Additionally, emphasis should be placed on collaborative design across disciplines and data standardization to build intelligent full-lifecycle management platforms, improve operation and maintenance efficiency, and provide new ideas and methods for sustainable development.