Urban traffic is an increasingly urgent problem, especially during rush hours and special events, when traffic congestion becomes very common. Visualization and intelligent data analysis technology helps to efficiently interpret data, provide insight and insights, enhance the identification and resolution of congestion problems, and facilitate people's travel. This work uses multi-coordinated view, three-dimensional road network modeling technology and graph convolution neural algorithm to design and implement a set of road network traffic situation awareness visual analysis system. Firstly, multi-coordinated view is used to present multi-side information such as traffic network from multiple dimensions. At the same time, a road network health perception model is constructed according to the congestion period and the number of congested lanes, and suspicious traffic events are speculated. Furthermore, a three-dimensional dynamic twin model of lanes is constructed to increase or decrease the perception of traffic control personnel on hot sections. In terms of network prediction, through case analysis and algorithm comparison evaluation experiments, it is proved that the system provides effective technical support and decision-making basis for traffic situation awareness, congestion identification and analysis, and traffic situation prediction. The target users of this work are wide, including the public who are concerned about traffic congestion, the traffic management department of the municipal government, and the relevant researchers and scholars of traffic situation analysis. In addition, the visualization based on holographic road data enables the public to intuitively and directly feel the congestion situation of a certain road section at a certain time shown by the data, and at the same time intuitively shows the operation situation of each road network for relevant departments and governments, and provides auxiliary support for the effectiveness of relevant measures and improvement suggestions in combination with the operation situation of each road network. For relevant researchers and scholars, through the design of data processing ideas and visual views and interactions, new ideas for traffic situation analysis are provided.