The thesis proposes an open and scalable technical pipeline. This pipeline has several dimensions including 3D representation (such as three-dimensional visualization ofbuildings and networks), 4D infrastructure dynamics (such as noise changes), and 5D simulation capabilities (such as traffic flow, land planning, and prediction). Thepipeline is applied to create a complete urban traffic digital twin (DT) system to help simulate, analyze, and optimize transportation and infrastructure in the physicalworld. Simulation of Urban MObility (SUMO) is used to simulate traffic flow. Subsequently, the simulation results are combined with the Cesium 3D WebGISplatform to achieve dynamic visualization of traffic flow and road infrastructure.

In addition, the thesis further explores the potential application of this technical pipeline in urban traffic prediction, planning, and management when obtaining morerealistic data, including Backcasting, Nowcasting, and Forecasting functions. This method not only improves the visualization of traffic simulation results, but alsoprovides powerful analysis and optimization tools for traffic decision-makers. The research results show that the platform has the advantages of lightweight, opennessand interactivity, and can be widely used in urban traffic management and future intelligent transportation system research.

The thesis finally discusses the limitations of the system, including the limitationsof data sources and the challenges of matching actual traffic networks with threedimensional scenes, and puts forward further optimization suggestions for futureresearch directions.