Digital Twin for the Whole Life Cycle of Transportation Infrastructure: Digital Characterization Technology and Database Construction

DOI: https://doi.org/10.62517/jike.202604125

Author(s)

Paiyong Zeng

Affiliation(s)

PowerChina Huadong Engineering Corporation Limited, Hangzhou, China

Abstract

Aiming at the core pain points in the whole life cycle management of transportation infrastructure, such as data silos, decision-making lag, and insufficient collaboration between models and data, this paper proposes a four-dimensional digital characterization system based on "form-state-property-trend". A standardized characterization data list and rule system covering multiple facility types including roads, bridges and tunnels, and running through the whole stages of planning, design, construction and operation & maintenance is constructed. The multi-source heterogeneous data collaborative interconnection technology and distributed characterization database platform are innovatively developed, which break through the limitations of traditional data management modes and realize a new paradigm of digital management featuring "digital-model linkage, spatio-temporal integration and full-cycle traceability". By assigning weights and quantifying the completeness of characterization with an index system, core evaluation criteria are put forward, including the description integrity of not less than 95% and the business process coverage of not less than 90%, providing technical support for the high-quality construction of the digital twin base of transportation infrastructure. This technical system can effectively eliminate information barriers, improve the refinement level and decision-making efficiency of whole life cycle management, and provide an underlying technical paradigm for the digital transformation of smart city transportation.

Keywords

Transportation Infrastructure; Digital Twin; Digital Characterization; Four-Dimensional Framework; Multi-Source Data Fusion; Characterization Database

References

[1] HUANG J X. Research on Road Traffic Digital Twin System Based on Multivariate Composite Mapping[J]. Journal of Information Technology in Civil Engineering and Architecture, 2024, 16(5): 76-84. DOI: 10.16670/j.cnki.cn11-5823/tu.2024.05.08. [2] WU C H, XU J D, FU Z Q, et al. Architecture, Key Technologies and Practical Cases of Highway Traffic Digital Twin System from the Perspective of Building a Powerful Transportation Country[J]. Journal of Transportation Research, 2023, 9(4): 1-16. DOI: 10.16503/j.cnki.2095-9931.2023.04.001. [3] YANG G L, JIANG S M. Research on Multi-source Heterogeneous Data Fusion Method Based on ETL Technology[J]. Journal of Qilu University of Technology, 2024, 38(4): 64-70, 78. DOI: 10.16442/j.cnki.qlgydxxb.2024.04.003. [4] LIANG H, FU D. Knowledge Graph Visual Fusion Method for Multi-source Heterogeneous Data[J]. Application of Electronic Technology, 2025, 51(1): 95-99. DOI: 10.16157/j.issn.0258-7998.233125. [5] HE G T. Multi-source Electrical and Mechanical State Management of Expressways from the Perspective of Data Association[J]. China Transportation Informatization, 2024(11): 142-145. DOI: 10.13612/j.cnki.cntp.2024.11.041. [6] LIAO Y T, TANG H, ZHU H. Design and Application of Integrated Intelligent Highway Management and Control Platform Based on Digital Twin[C]// Proceedings of the 17th China Intelligent Transportation Annual Conference. Beijing: Publishing House of Electronics Industry, 2022: 464-473.