## 6 Current Applications of DTs in Transportation Infrastructure
### Case Studies  
Several cities and regions have begun adopting DT technology to address specific transportation challenges, demonstrating the versatility and efficacy of DIs in this domain. 1. Singapore: Singapore's comprehensive DT incorporates real-time data from its road networks, public transit systems, and environmental sensors. This system facilitates the simulation of various urban development scenarios, aiding decision-makingin road network configuration, public transit enhancements, and traffic congestion mitigation [103]. The successful implementation of this technology showcases its potential to foster more efficient, sustainable, and responsive urban environments. 2. London: In the UK, national-level DT strategies are supported by initiatives such as the National Digital Twin Programme [112], which aims to enable connected digital twins across different sectors, including transportation. DT technology is employed primarily in three areas: alleviating road congestion, managing motorway projects, and enhancing real-time traffic and travel information systems. As a leading city-level example, Transport for London (TfL) utilizes a DT to oversee traffic and public transport in real time. By integrating data from numerous sensors, cameras, and public transport networks, the DT facilitates dynamic traffic signal adjustments, congestion tracking, and incident management. This integrated approach has significantly decreased traffic delays and enhanced public transport reliability. London's case demonstrates how a city can pilot and refine DT solutions within a broader national policy context. 3. China: In China, DTs monitor the health of essential infrastructure such as bridges and tunnels. By employing sensor data and predictive analytics, these DTs detect structural issues early, enabling prompt maintenance and extending the assets' service life [117]. This proactive strategy has proven to be more cost-effective and safer than conventional maintenance methods. Leveraging technologies such as BIM, GIS, IoT, AI, and cloud computing, the East China Survey and Design Institute of CECC has developed a next-generation integrated management system for the entire lifecycle of BIM in rail transit engineering. This system enhances visibility and ensures the seamless flow of information across the design, construction, operation, and maintenance phases, alongside intelligent perception, analysis, and decision-making. The system's capabilities were demonstrated on Chengdu Metro Line 18, facilitating enhanced design, construction, operation, and maintenance coordination. 4. Germany: Germany's DT technology achieves exceptionally detailed simulation accuracy, extending to the real-time perception of car air conditioning and wheel wear. The German railway department has begun implementing a new DT train set. Rail transport logistics systems have developed a GIS for DTs, using a qualitative-explorative design to establish a validated strategy. This strategy emphasizes a socio-technical system focus, enabling user-oriented development and accounting for complex conditions [118]. The GIS and derived recommendations aim to facilitate the operational optimization and intelligent management of rail transport assets. 5. Australia: Curtin University in Australia has introduced a three-dimensional dynamic displacement measurement technique using a binocular camera system without targets, allowing for the full-field measurement of civil engineering structures' dynamic displacements. Additionally, the university has developed a deep-learning-based method for structural dynamic response noise reduction, deletion recovery, and reconstruction, achieving high-intensity signal denoising. It has also formulated several deep-learning-based structural damage identification methods, enhancing identification accuracy [119].