## 5 DT Technology in the Lifecycle of Transportation Infrastructure
### Planning and Design Phase  
During the planning and design phase, transportation infrastructure design must consider complex factors, including traffic flow, topography, environmental conditions, and socio-economic aspects. Traditional methods, which rely heavily on historical data and experience [34], often fail to accurately predict future usage scenarios, presenting several challenges: (a) the lack of comprehensive, sufficient, and effective lifecycle data support hampers the creation of a useful database for design decisions; (b) the complexity of design models and the difficulty in integrating interdisciplinary models; (c) the absence of precise simulation methods makes design validation challenging and time-consuming. To address these challenges, the adoption of dynamic and flexible DT technology facilitates extensive twin data support for establishing a knowledge database and assisting with modeling tasks. Using high-precision DT modeling technology and model fusion theory, the planning and design of urban transportation projects are transformed from traditional two-dimensional drawings and static analyses into dynamic simulation processes based on three-dimensional virtual environments. Additionally, the realistic simulation environment provided by DTs enhances design verification capabilities, accelerates the design process, and improves design accuracy, offering planners an unprecedented intuitive understanding and optimization of design plans. DT technology spans from preliminary to detailed design, providing services like virtual facility simulation, multi-dimensional visualization, scenario evaluation and optimization, multi-objective trade-offs, decision support, and collaborative design. By constructing highly realistic virtual models, planners can simulate urban transportation infrastructure operations under various conditions. These models integrate historical and real-time data, encompassing geometric and structural details of physical facilities, as well as traffic flow, weather, 24 h lighting, and volumetric clouds. This method allows for testing different design schemes within a virtual setting, providing an intuitive observation and assessment of their potential performance. For example, DTs simulate traffic flow distribution for various road layouts, helping planners identify congestion points and traffic bottlenecks [65; 66]. By combining dynamic population data with traffic flow information, DTs can evaluate the impact of road designs on traffic efficiency and capacity, offering quantitative results [67]. Ref. [68] suggested DTs for scenario generation in large-scale planning across multiple cities, enhancing decision-making. Their study in Alesund, Norway, demonstrated the benefits of DTs in urban mobility planning. Visualization features in these models include zooming, orbiting, bird's-eye views, panning, roaming, flying, and querying. They support visual scenarios under various conditions, merge real geographic environmental data, and facilitate the integration and interaction of business data related to urban transport in a DT environment. Compared to Building Information Models (BIM),DTs provide a multi-dimensional view by integrating operational data, environmental impacts, and structural behaviors, along with detailed geometric information. Scenario optimization is a crucial application of DT technology during the planning phase. It allows planners to balance multiple objectives, such as traffic flow efficiency, pedestrian safety, and environmental impact. Through multiple simulations and feedback from DTs, the optimal design can be determined. [PERSON]. [69] introduced an enhanced framework for ITS that uses DTs for spatiotemporal data mining, capturing human travel patterns, and visualizing intersections. DTs employ AI and machine learning to explore the best solutions through extensive simulations and data analysis.