###### Abstract  
The increasing urban traffic problems have made the transportation system require a large amount of data. Aiming at the current problems of data types redundancy and low coordination rate of intelligent transportation systems (ITS), this paper proposes an improved digital twin architecture applicable to ITS. Based on the improved digital twin architecture, a framework for dynamic and static data collaboration in ITS is constructed. For various collaboration methods, this paper specifically describes the collaboration methods and scopes, and designs the framework and interfaces for data mapping. Finally, the effectiveness of the framework is verified by case studies to mine the spatiotemporal distribution characteristics of data, capture human travel characteristics, and visualize intersections using digital twins. This paper provides a new data fusion idea for digital twin systems in ITS, and the framework covers all data types in digital twin systems for cross-integration analysis. intelligent transportation system; digital twin; multi-source data; data collaboration; spatiotemporal data +
Footnote †: journal: Applied Sciences  
account the users in the system. Based on the five-dimensional model, [PERSON] proposed a conceptual modelling method of digital twins, using the TRIZ function model to express the complex relationship between digital twins and their attributes [7]. Digital twin technology can help urban management and decision-making to coordinate and achieve intelligent, accurate and safe transportation [8]. In the ITS, the four elements of human-vehicle-road-environment are interrelated and coordinated. Due to its inherent structural characteristics, different data can be used to solve different problems. Compared with traditional data systems, digital twinning technology not only emphasizes information and physical data, but also emphasizes the integration and interconnection between data [9], and achieves interactive real-time information space and physical space through the relationship between data. In the study [10], [PERSON] et al. elaborated the evolution mechanism of the digital twin workshop and proposed the digital twin evolution model, which was combined with each stage of engineering application to give it application scenarios. [PERSON] et al. applied the digital twin technology to the industrial Internet and proposed the self-reinforced digital twin technology of intelligent in [11]. Because of the ability of digital twins to connect the information world and the physical world, they have been used by many researchers in information physics systems [12]. In [13], [PERSON] et al. applied the IoT solution to intelligent transportation systems, automated data collection and processing functions, and effectively improved efficiency through standardized processes. Many scholars have also applied digital twin technology to the field of architecture. [PERSON] et al. [14] proposed a future model to improve the energy consumption of buildings by using the combination of hierarchical process and building information modeling (BIM) model, and apply renewable technologies to buildings. [PERSON] et al. [15] proposed a BIM-based digital twin factory navigation framework to realize path searching of factory robots. Some scholars make a simple fusion of traffic spatiotemporal data for analysis. [PERSON] et al. [16] has chosen to use the GPS data of taxis and tweets collected on Weibo for three months to build a human detection system for traffic abnormalities, and identify deviations according to the taxi drivers' action routes. [PERSON] et al. have studied the data of floating cars and excavated the characteristics of the road network [17]. [PERSON] et al. used car floating data to study the travel dynamics of two different types of public transportation in a city [18]. [PERSON] et al. introduced an interactive platform that can detect the movement of a bus using large-scale GPS trajectories [19]. [PERSON] et al.