Urban rail transit intelligent system based on BIM and GIS
By performing lightweight processing and LOD grading on BIM data, the adaptation problem of BIM models on GIS platforms was solved, enabling efficient cross-scale application of intelligent rail transit systems and improving the planning and engineering design efficiency of urban rail transit.
Patent Information
- Application Number
- CN202610175098.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-06
- Publication Date
- 2026-06-12
AI Technical Summary
The conversion of BIM models to GIS suffers from component-level refinement, resulting in large data volumes and long loading times. This makes it difficult to adapt to the macro-spatial analysis needs of GIS and integrate it into the GIS platform for rail transit engineering construction management.
By incorporating BIM acquisition, data splitting, geometric data conversion, non-geometric feature processing, lightweight processing, and verification modules, and combining them with the LOD grading method, lightweight processing of BIM data and adaptation to GIS platforms are achieved. Layered management and independent rendering channels are adopted, along with a custom rule engine that dynamically switches between different LOD standards.
It enables efficient planning and engineering design for rail transit applications across scales, meets different needs of macro-planning and engineering design, improves planning decision-making and analysis efficiency, and reduces resource consumption.
Smart Images
Figure CN122196060A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of rail transit project management technology, specifically to an intelligent urban rail transit system based on BIM and GIS. Background Technology
[0002] City-level GIS is a spatial information service platform that covers the entire lifecycle of urban planning, construction, management, and operation. It is a large-scale, intelligent, and integrated upgrade of traditional GIS. Its core features are covering the entire urban space, integrating multi-source heterogeneous data, and supporting cross-departmental business collaboration. It is the core spatial foundation of smart cities and city information models (CIM).
[0003] BIM stands for Building Information Modeling. It provides detailed 3D building models that can be used throughout the entire lifecycle of a building project, including planning, design, and construction, serving the fields of architecture, engineering, and construction management. Unlike BIM elements, which focus on the refined parameters and full lifecycle information of engineering components, GIS elements emphasize the location, distribution patterns, and macro-level correlation analysis of entities at the geographic spatial scale. With the development of urban GIS and the integration of project-level BIM resources, BIM models face problems in the conversion to GIS, such as "component-level detail and large data volume leading to long loading times and operational lag," making them unsuitable for the macro-level spatial analysis needs of GIS.
[0004] Therefore, the difficulty in integrating BIM models into GIS platforms for the construction and management of rail transit projects is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention
[0005] The purpose of this invention is to provide an intelligent urban rail transit system based on BIM and GIS.
[0006] To achieve the above objectives, the present invention provides the following technical solution: A smart urban rail transit system based on BIM and GIS includes: The BIM acquisition module acquires BIM data for a single project. The data splitting module splits the acquired project BIM data into geometric data and non-geometric data corresponding to each component in the geometric data, and deletes temporary construction components, auxiliary lines, and duplicate components. The geometric data conversion module converts the geometric data of the components obtained from the splitting process and performs coordinate system conversion. The non-geometric element processing module performs semantic and attribute mapping on the non-geometric data corresponding to the components. The lightweight processing module optimizes the surface of the components, merges duplicate surfaces, simplifies curves, controls the number of triangular surfaces, compresses textures, and performs parallel LOD classification according to the applicable scenario. The verification module verifies the conversion results.
[0007] As a further aspect of this invention: the method for classifying the LOD of the architecture involves encapsulating the two LOD systems into independent GIS layers, setting different display scale thresholds and detail loading rules, and the steps include: S1: Import the two sets of LOD models after BIM conversion (such as LOD200 engineering model + LOD2 city model); S2: Create two independent scene layers in ArcGIS / Cesium / SuperMap; S3: Configure unique LOD rules for each layer: Engineering layer: LOD400 is displayed for close distances (<500m), and LOD200 is displayed for distant distances (>2000m); City layer: LOD3 is displayed for close distances (<1000m), and LOD1 is displayed for distant distances (>5000m); S4: Enable layer visibility linkage to ensure that only the optimal LOD combination is loaded from the same viewpoint.
[0008] As a further aspect of this invention: the method for LOD hierarchical classification of the architecture is to bind multiple LOD meshes to the same model object using the instantiation technology of a 3D engine (such as Three.js, Unreal), and dynamically switch them according to different scene requirements. The steps include: S01: Create a LOD variant library for rail transit components (such as tunnel segments and rails) to store geometric representations at different levels of detail; S02: Develop a custom LOD selector to select the optimal LOD based on parameters such as view distance, analysis type, and user permissions; S03: Matched to digital twin rail transit systems, supporting real-time switching between engineering precision and visualization effects.
[0009] As a further aspect of this invention, the method for classifying LODs in the architecture involves constructing an LOD transformation rule base using ETL tools such as FME, automatically generating multiple sets of LODs for the model, and registering them with the rule engine of the GIS platform. Beneficial effects
[0010] This invention achieves coexistence of different LOD standards through hierarchical management, independent rendering channels, and a custom rule engine. It is particularly suitable for cross-scale application scenarios such as rail transit. In macro-planning scenarios, it calls GIS to adapt to low-LOD scenarios, supporting collaborative planning of urban rail networks, urban road networks, and underground spaces. It can quickly complete line comparison and station coverage analysis without loading massive amounts of detailed components, thus improving the efficiency of planning decisions. In engineering design / construction scenarios, it calls BIM's native high-LOD scenarios to meet the high-precision requirements of collision detection between disciplines, construction simulation, and prefabricated component processing, ensuring the compliance of engineering design and construction. It loads on demand, reducing resource consumption, and performs hierarchical calculations to improve analysis efficiency. Attached Figure Description
[0011] Figure 1 This is a schematic block diagram of a smart urban rail transit system based on BIM and GIS according to the present invention. Detailed Implementation
[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention. like Figure 1 As shown; This embodiment provides an intelligent urban rail transit system based on BIM and GIS, including: The BIM acquisition module acquires BIM data for a single project. The data splitting module splits the acquired project BIM data into geometric data and non-geometric data corresponding to each component within the geometric data. The model is split according to civil engineering (stations, tunnels), track (rails, turnouts), electromechanical (power supply, signaling), and ancillary facilities (platform screen doors, ventilation shafts), deleting temporary construction components, auxiliary lines, and duplicate components. Unified export format: Prioritize exporting in IFC4 format (compatible with extended attributes of rail transit); for professional software models (such as Bentley OpenRail), export the OpenRail Model and then convert it to IFC to ensure that key information such as mileage station numbers and component attributes are not lost; Geometric integrity verification: Repair non-manifold edges and overlapping surfaces of the BIM model to ensure the correct topological relationships of components and avoid model damage after conversion; The geometric data conversion module converts the geometric data of the components obtained from the splitting process and performs coordinate system transformation. The coordinate system is determined by defining the urban benchmark coordinate system (such as CGCS2000 / EPSG:4490), obtaining the transformation parameters (seven parameters / four parameters + elevation fitting) from the independent coordinate system of the rail transit line to the urban coordinate system, and constraining the coordinate registration accuracy of the underground tunnel through the ground CPIII control points. The non-geometric element processing module performs semantic and attribute mapping on the non-geometric data corresponding to the components. Following the urban GIS element classification standard, it maps rail transit BIM components into GIS-recognizable geographic entities and synchronizes the operation and maintenance attributes (maintenance cycle, responsible person) and safety attributes (fire protection level) in BIM to the GIS attribute table to support urban-level rail transit safety management and control. The lightweight processing module optimizes the surface of the components, merges duplicate surfaces, simplifies curves, controls the number of triangular surfaces, compresses textures, and performs parallel LOD classification according to the applicable scenario. Geometric simplification reduces the number of model patches and data volume while preserving core spatial features and semantic information, thus adapting to the performance requirements of large-scale visualization and analysis in city-level GIS.
[0013] Texture compression is used, with above-ground components (such as the station facade) using the KTX2 lightweight texture format and underground untextured areas filled with solid colors to reduce memory usage.
[0014] The model is divided into blocks according to mileage intervals, sections, and specialties, generating a hierarchical tile structure of 3DTiles, enabling on-demand loading on the GIS platform (e.g., loading only the model of a certain interval when viewing a station). The verification module verifies the conversion results; Completeness verification involves checking the number of components (such as the number of stations and tunnel mileage) and attribute fields (such as mileage station number and structural parameters) before and after the conversion to ensure that nothing is missing.
[0015] Accuracy verification involves randomly checking the urban coordinates of key locations (station center point, tunnel entrance / exit) to verify whether the conversion error meets the requirements.
[0016] Performance testing simulated concurrent access by multiple users to ensure that the model loading time in a city-level GIS scenario is ≤8 seconds.
[0017] Spatial conflict detection involves overlaying urban underground pipe network data to detect spatial conflicts between rail transit models and other facilities.
[0018] The method for LOD grading of the architecture involves encapsulating the two LOD systems into independent GIS layers, setting different display scale thresholds and detail loading rules, and the steps include: S1: Import the two sets of LOD models after BIM conversion (such as LOD200 engineering model + LOD2 city model); S2: Create two independent scene layers in ArcGIS / Cesium / SuperMap; S3: Configure unique LOD rules for each layer: Engineering layer: LOD400 is displayed for close distances (<500m), and LOD200 is displayed for distant distances (>2000m); City layer: LOD3 is displayed for close distances (<1000m), and LOD1 is displayed for distant distances (>5000m); S4: Enable layer visibility linkage to ensure that only the optimal LOD combination is loaded from the same viewpoint.
[0019] The method for hierarchical LOD of the architecture involves using the instantiation technology of a 3D engine (such as Three.js or Unreal Engine) to bind multiple LOD meshes to the same model object and dynamically switch between them according to different scene requirements. The steps include: S01: Create a LOD variant library for rail transit components (such as tunnel segments and rails) to store geometric representations at different levels of detail; S02: Develop a custom LOD selector to select the optimal LOD based on parameters such as view distance, analysis type, and user permissions; S03: Matched to digital twin rail transit systems, supporting real-time switching between engineering precision and visualization effects.
[0020] The method for LOD (Level of Detail) classification of the architecture involves building an LOD transformation rule base using ETL tools such as FME, automatically generating multiple sets of LODs for the model, and registering them with the rule engine of the GIS platform, such as: IF Scene Type = "Engineering Analysis" THEN Apply BIM_LOD_300 rule IF Scene Type = "Urban Planning" THEN Apply GIS_LOD_2 Rules If element type = "tunnel" AND burial depth > 50m THEN, automatically upgrade the LOD level (preserving more structural details).
[0021] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.
Claims
1. An intelligent urban rail transit system based on BIM and GIS, characterized in that, include: The BIM acquisition module acquires BIM data for a single project. The data splitting module splits the acquired project BIM data into geometric data and non-geometric data corresponding to each component in the geometric data, and deletes temporary construction components, auxiliary lines, and duplicate components. The geometric data conversion module converts the geometric data of the components obtained from the splitting process and performs coordinate system conversion. The non-geometric element processing module performs semantic and attribute mapping on the non-geometric data corresponding to the components. The lightweight processing module optimizes the surface of the components, merges duplicate surfaces, simplifies curves, controls the number of triangular surfaces, compresses textures, and performs parallel LOD classification according to the applicable scenario. The verification module verifies the conversion results.
2. The intelligent urban rail transit system based on BIM and GIS according to claim 1, characterized in that: The method for classifying the LOD (Level of Detail) hierarchy of the architecture involves encapsulating the two LOD systems into independent GIS layers, setting different display scale thresholds and detail loading rules. The steps include: S1: Import the two sets of LOD models after BIM conversion (such as LOD200 engineering model + LOD2 city model); S2: Create two independent scene layers in ArcGIS / Cesium / SuperMap; S3: Configure unique LOD rules for each layer: Engineering layer: LOD400 is displayed for close distances (<500m), and LOD200 is displayed for distant distances (>2000m); City layer: LOD3 is displayed for close distances (<1000m), and LOD1 is displayed for distant distances (>5000m); S4: Enable layer visibility linkage to ensure that only the optimal LOD combination is loaded from the same viewpoint.
3. The intelligent urban rail transit system based on BIM and GIS according to claim 1, characterized in that: The method for hierarchical LOD of the architecture involves using the instantiation technology of a 3D engine (such as Three.js or Unreal Engine) to bind multiple LOD meshes to the same model object, dynamically switching between them according to different scene requirements. The steps include: S01: Create a LOD variant library for rail transit components (such as tunnel segments and rails) to store geometric representations at different levels of detail; S02: Develop a custom LOD selector to select the optimal LOD based on parameters such as view distance, analysis type, and user permissions; S03: Matched to digital twin rail transit systems, supporting real-time switching between engineering precision and visualization effects.
4. A smart urban rail transit system based on BIM and GIS according to claim 1, characterized in that: The method for classifying LODs in the architecture involves building an LOD transformation rule base using ETL tools such as FME, automatically generating multiple sets of LODs for the model, and registering them with the rule engine of the GIS platform.