Jxie
10 Jan 2025
High-precision data parsing | Quickly building a digital traffic base based on Ili numeric road network data
NRT generates three-dimensional road twin models based on high-precision road network data (SHP) from Sichuan Eili Digital City Technology Co., Ltd., thereby rapidly building high-precision three-dimensional street network and associated structures, providing a new model for realizing large-scale digital traffic bases.
Introduction to shp
ESRI Shapefile, or simplyshapefile（shp)，It is an open format for spatial data developed by the American Institute of Environmental Systems (ESRI).The ability to interoperate data between ESRI products and those of other companies.SHP files are used to describe objects: points, polygons and polygons. You can store the geometrical locations of space objects such as wells, rivers, lakes, etc. You can also store the properties of these space objects, such as the name of a river, the temperature of a city, etc.
Shp is the most commonly used traffic data format. Our self-developed NRT Digital Twin supports the parsing of shp data, enabling the rapid construction of large-scale high-accuracy 3D traffic digital bases.
Showcase of large-scale 3D transportation digital plinth generation effects
In the NRT Digital Twin platform, based on road data, the model of flat crossings, road sections, traffic marking lines, barriers, non-motorway, road green belts, street lights and so on is built, and the resulting three-dimensional simulation scene is as follows:
（ Figure 1 : Road traffic markings , roadside assets ）
(Figure 2: road intersections)
（ Figure 3 : Panoramic view of the 3D traffic digital base ）
Dynamic presentation
From road network data to large-scale 3D digital bases, NRT Digital Twin can be completed in seconds, enabling fast, accurate and convenient modeling and simulation of real traffic scenarios.
In recent years, NRT has committed to technological innovation and industry application at the same time, generating road models based on road network data, providing a visual, operational and predictable digital base for digital transportation systems and traffic simulation system management, and contributing to the digital governance of urban transportation systems.