Research on Digital Twin Model Construction Method for Smart Highway Southeast University

Format:

Book

Conference/Event

Author/Creator:

Zhang, Yawen, author.

Contributor:

Cai, Xianhua

Conference Name:

2024 International Conference on Smart Transportation Interdisciplinary Studies (2024-12-13 : Nanjing, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2025

Summary:

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

Notes:

Vendor supplied data

Publisher Number:

2025-01-7175

Access Restriction:

Restricted for use by site license