Railway two-dimensional and three-dimensional integrated live-action enhancement visualization method and system

Abstract

The invention discloses a railway two-dimensional and three-dimensional integrated live-action enhancement visualization method and system. The method comprises the following steps: establishing two-dimensional and three-dimensional graphic data sets, performing coordinate alignment and layered superposition on two-dimensional and three-dimensional graphic data, and publishing two-dimensional and three-dimensional maps through cloud service; building a web container, and fusing the two-dimensional map and the three-dimensional map; packaging interfaces of a kilometer post algorithm and an elevation algorithm in the two-dimensional and three-dimensional integrated live-action enhancement graph; and a user accesses the uniform URL address through a web browser, checks the two-dimensional and three-dimensional integrated live-action enhancement graph, and interacts with the live-action enhancement graph. According to the method, the problems of cross-platform fusion display and layered display of railway professional multi-dimensional graphs which cannot be met by a general geographic information system are solved, and the method has rich interaction characteristics adapting to professional characteristics; meanwhile, based on enhancement of the live-action image, the display effect is improved, the cost is reduced, and popularization and application are facilitated.

Description

Technical Field

[0001] The present invention relates to a method for enhancing visualization of two-dimensional and three-dimensional integrated railway real scenes, and also relates to a system for implementing the method, belonging to the technical field of image processing. Background Art

[0002] Railways are critical national infrastructure and a primary means of public transportation. Their safe and efficient operation is crucial to national development and the lives of the people. With the continued expansion of the railway network and advancements in technology, the demand for railway visualization technology is also increasing. However, current railway visualization technology has many limitations and is unable to meet this growing demand.

[0003] Early railway visualization relied primarily on two-dimensional geographic information systems (GIS), based on meter-level resolution traffic and topographic maps. While this system provided a useful reference for macro-planning, it lacked elevation information, preventing three-dimensional visualization. This made two-dimensional GIS inadequate for scenarios requiring consideration of topographical undulations and spatial relationships, such as railway bridge construction planning and tunnel site selection. Furthermore, the low accuracy of meter-level resolution data made it difficult to meet the requirements for refined management of railway facilities.

[0004] While 3D Building Information Modeling (BIM) has significantly improved accuracy, it comes at a high cost. For example, the cost of modeling a single kilometer of railway line can exceed hundreds of thousands of yuan, a prohibitive expense for large-scale railway network construction and maintenance. Furthermore, BIM is primarily suitable for new railway projects and lacks compatibility with historical data from existing lines, making it difficult to integrate existing data and information into new models. This limits its application in the operation and maintenance of existing railways.

[0005] At the same time, the application of 3D maps has significantly increased the complexity of data collection. Collecting the longitude, latitude, and elevation coordinates of equipment on a 3D map is exponentially more labor-intensive than simply collecting the longitude and latitude coordinates on a 2D map. Furthermore, on 2D and 3D maps, when the current field of view is large or the elevation is low, it can be difficult to discern the current railway mileage location, hindering business analysis.

[0006] Chinese invention patent ZL 201110392006.4 proposes a railway information visualization method. This method uses a virtual three-dimensional map model linked to onboard camera footage to map multiple frames of video captured along the railway line to the mileage coordinates of the corresponding shooting locations. The video frames are then played back sequentially according to the mileage coordinates along the railway line. However, this method, based on a visualization system linking video footage with route diagrams, suffers from insufficient interactivity and scalability. It cannot implement arbitrary roaming, zooming, and rotation features supported by the map mode, nor does it facilitate the integration of business functions such as device search and personnel location. Summary of the Invention

[0007] The primary technical problem to be solved by the present invention is to provide a method for enhancing visualization of two-dimensional and three-dimensional integrated real scenes of railways.

[0008] Another technical problem to be solved by the present invention is to provide a system for enhancing the visualization of railway 2D and 3D integrated real scenes.

[0009] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0010] According to a first aspect of an embodiment of the present invention, a method for enhancing visualization of a two-dimensional and three-dimensional integrated railway scene is provided, comprising the following steps:

[0011] S1: Based on the national basic geographic data, national basic geographic data of cities and counties along the railway, orthophoto maps along the railway, and railway line shape files, a 2D graphic dataset is established. The coordinates of the 2D graphic data are aligned and layered, and the 2D map is published through cloud services.

[0012] S2: Create a 3D graphics dataset based on the railway section oblique camera survey map, railway station area oblique camera survey map, railway line vehicle-mounted laser radar survey map, railway professional traffic element 3D model map and DSM elevation file, coordinate align and layer the 3D graphics data, and publish the 3D map through cloud services;

[0013] S3: Build a web container to merge the 2D map published in step S1 with the 3D map published in step S2;

[0014] S4: Encapsulates the kilometer landmark algorithm and elevation algorithm interfaces in the 2D and 3D integrated augmented reality map, allowing users to call them in different business scenarios.

[0015] S5: The user accesses the unified URL address through a web browser to view the 2D and 3D integrated augmented reality image and interact with the augmented reality image.

[0016] Preferably, in step S3, a layer planning configurator is provided to support dynamic switching of multiple scales.

[0017] Preferably, in step S3, an element planning configurator is set up so that the data of the map and the business system can be synchronized in real time.

[0018] Preferably, the kilometer mark algorithm in step S4 includes the following steps:

[0019] S41: Filter the mileage points of the engineering profession in the railway line shape file and collect the coordinate points selected by the user;

[0020] S42: Find the corresponding vertical point in the railway line shape file according to the mileage pile point of the engineering professional, and split the railway line shape file into split files with a first preset length as a unit;

[0021] S43: Find the segmentation unit closest to the coordinate point selected by the user in the segmentation file;

[0022] S44: Find the corresponding vertical point in the segmentation unit according to the coordinate point selected by the user;

[0023] S45: Calculate the distance between the starting point of the segmentation unit and the corresponding vertical point in the segmentation unit along the direction of the segmentation unit;

[0024] S46: Add the kilometer mark of the starting point of the segmentation unit and the distance between the starting point of the segmentation unit and the corresponding vertical point in the segmentation unit to obtain the kilometer mark of the coordinate point selected by the user.

[0025] Preferably, the elevation algorithm in step S4 includes the following steps:

[0026] S401: Segmenting the DSM elevation file into DSM elevation segmentation files with a second preset length as a unit;

[0027] S402: According to the kilometer mark of the coordinate point selected by the user, the corresponding DSM elevation segmentation file is searched and obtained;

[0028] S403: Splitting the DSM elevation segmentation file into grid surfaces with a third preset length as the side length;

[0029] S406: Using the coordinate point selected by the user as a reference point, obtain straight lines intersecting with multiple grid surfaces, and count the number of intersections in each grid surface; if the number of intersections is an odd number, the grid surface contains the coordinate point selected by the user, and the elevation of the coordinate point selected by the user is returned; if the number of intersections is an even number, the grid surface does not contain the coordinate point selected by the user, and the grid surface is ignored.

[0030] Preferably, after step S403 and before step S406, the following steps are further included:

[0031] S404: Collect the longitude and latitude of the four points in each grid surface and obtain the minimum longitude value Min by comparison x 、Maximum longitude x 、Minimum latitude y and latitude maximum value Max y ;

[0032] S405: Collect the longitude A of the coordinate point selected by the user x and latitude A y , and according to the filtering rules, multiple grid surfaces next to the coordinate point selected by the user are obtained; the filtering rules are: Min x ≤A x ≤Max x And Min y ≤A y ≤Max y .

[0033] According to a second aspect of an embodiment of the present invention, a system for two-dimensional and three-dimensional integrated real-scene enhanced visualization of railways is provided, comprising a processor and a memory; wherein the memory is coupled to the processor and is used to store a computer program, and when the computer program is executed by the processor, the processor implements the above method.

[0034] Compared with existing technologies, this invention addresses the cross-platform integrated and layered display of multi-dimensional railway graphics, a challenge unmet by general geographic information systems. It offers rich interactive features tailored to specific needs. Furthermore, by enhancing real-world imagery, this invention improves display quality and reduces costs, facilitating widespread adoption and application. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a flow chart of a method for enhancing visualization of a two- and three-dimensional integrated railway scene in a first embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the effect of superimposing the national basic geographic data on the orthophoto map in the first embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the effects of the orthophoto map and basic data of points of interest in the first embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram of the effect of superimposing oblique camera imaging and laser radar measurement data in the first embodiment of the present invention;

[0039] Figure 5This is a schematic diagram of map storage and publishing in the first embodiment of the present invention;

[0040] Figure 6 This is a schematic diagram of a layer planning configurator in the first embodiment of the present invention;

[0041] Figure 7 This is a schematic diagram of the effect of augmented reality visualization in the first embodiment of the present invention;

[0042] Figure 8 This is a schematic diagram of the effects of automatic roaming line display and kilometer mark calculation in the first embodiment of the present invention;

[0043] Figure 9 This is a schematic diagram of a system for 2D and 3D integrated real-scene enhanced visualization of railways in the second embodiment of the present invention. DETAILED DESCRIPTION

[0044] The technical content of the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] First embodiment

[0046] A first embodiment of the present invention provides a method for enhancing visualization of a two-dimensional and three-dimensional integrated railway scene, comprising the following steps:

[0047] S1: Based on the national basic geographic data, national basic geographic data of cities and counties along the railway, orthophoto maps along the railway, and railway line shape files, a two-dimensional graphic dataset is established, the coordinates of the two-dimensional graphic data are aligned and layered, and the two-dimensional map is published through cloud services.

[0048] S2: Based on the railway section oblique camera survey map, railway station area oblique camera survey map, railway line vehicle-mounted laser radar survey map, railway professional traffic element 3D model map and DSM elevation file, a 3D graphic dataset is established. The 3D graphic data is aligned and layered, and the 3D map is published through cloud services.

[0049] S3: Build a web container, merge the two-dimensional map published in step S1 and the three-dimensional map published in step S2, and provide a unified URL address.

[0050] S4: Encapsulate the interfaces of the kilometer landmark algorithm and elevation algorithm in the 2D and 3D integrated real-scene augmented map so that users can call them in different business scenarios.

[0051] S5: Users access a unified URL address through a web browser to view and interact with the 2D and 3D integrated augmented reality image. Access control is performed on users based on their roles and permissions, and access services are provided to users through multiple interface types.

[0052] like Figure 1 As shown, the specific implementation process of the above steps is described in detail below:

[0053] In step S1, the national basic geographic data is scaled at 1:1,000,000. This scale provides a macroscopic geographic framework, encompassing essential geographic information such as topography, landforms, and water systems across the country, providing a macroscopic reference for the overall planning and layout of railway lines. The data for cities and counties along the railway line is scaled at 1:5,000, which provides a detailed display of cities, towns, and roads along the railway line, and is crucial for the integration and coordination of the railway with its surrounding environment. The orthophoto images along the railway line have a resolution of 3cm, which accurately depicts the actual surface conditions along the railway line, including vegetation, buildings, and roads, providing an accurate foundation for the subsequent positioning and analysis of railway facilities.

[0054] At the same time, orthophotos along the railway line collect data within a 500-meter radius on either side of the railway line. This is because environmental factors within this radius have a significant impact on railway operations and safety. For example, natural disasters such as landslides and floods can damage the railway line, while surrounding buildings and roads can also affect railway construction and operations. By comprehensively collecting data within this radius, we can gain a more comprehensive understanding of the environmental conditions surrounding the railway, providing a more accurate basis for subsequent analysis and decision-making.

[0055] like Figure 2 As shown in the figure, after data collection is complete, the multi-source data is unified into the China Geodetic Coordinate System 2000 and layered to ensure data consistency and accuracy. Different data sources may use different coordinate systems, which can lead to spatial mismatches and errors in the data. Converting data from different coordinate systems into the unified China Geodetic Coordinate System 2000 ensures spatial consistency across all data, facilitating subsequent analysis and processing.

[0056] Among them, China Geodetic Coordinate System 2000 is a high-precision national geodetic coordinate system independently established by China. Its core goal is to provide a unified spatial reference for fields such as surveying and mapping, geographic information, and navigation and positioning. This coordinate system is based on the International Terrestrial Reference Frame (International Terres trialReference Frame). The coordinate frame is updated every year to ensure compatibility with the global geocentric coordinate system, and to cover China's land and sea areas, eliminating the regional inconsistency problem caused by local adjustment of traditional coordinate systems. As a conventional technique generally mastered by those skilled in the art, it will not be specifically described here.

[0057] like Figure 3 As shown, next, image recognition technology is used to annotate points of interest (POIs) and design POI icons. POIs include 28 types of infrastructure, including stations, machine rooms, bridges, tunnels, culverts, switches, turnouts, signals, track circuits, distribution stations, overhead lines, communication towers, and power towers. Image recognition technology leverages computer vision and machine learning algorithms to quickly and accurately identify infrastructure feature points in images. By combining equipment attributes with railway maintenance records, including name, model, jurisdiction, and maintenance records, detailed attribute information can be assigned to each POI, facilitating subsequent management and query.

[0058] Next, based on the basic data on the jurisdiction of specialized work areas, such as engineering, power supply, electrical, and communications, the boundaries of each specialized work area are automatically annotated. During the annotation process, an algorithm is used to optimize boundary smoothness and reduce jagged artifacts. The jurisdiction of specialized work areas is crucial for railway operations management. Generating segmented boundaries allows for a visual representation of each area's jurisdiction. Optimizing boundary smoothness improves visualization, making boundaries clearer and more aesthetically pleasing, making them easier for staff to review and analyze.

[0059] Finally, map publishing utilizes a spatial database and rendering engine, enabling GPU-accelerated rendering and supporting real-time loading and dynamic display of large-scale features. The spatial database efficiently stores and manages geospatial data, while the rendering engine is responsible for presenting this data visually to users. GPU-accelerated rendering leverages the powerful computing power of graphics processors to rapidly render maps, improving both display speed and quality. Supporting real-time loading and dynamic display of large-scale features satisfies users' demand for real-time data, enabling them to stay informed of the status and changes of railway facilities.

[0060] The present invention realizes the precise spatial positioning and cross-disciplinary collaborative management of railway infrastructure through multi-source data fusion and intelligent labeling technology. Multi-source data fusion integrates data of different types and different precisions, giving full play to their respective advantages and improving the accuracy and completeness of the data. Intelligent labeling technology improves the efficiency and accuracy of data processing through image recognition and clustering algorithms, providing a more reliable basis for the management of railway infrastructure. Coordinate calibration technology ensures the spatial consistency of different data sources, making the data spatially comparable and analyzable. The clustering algorithm effectively eliminates the problem of duplicate labeling and improves the quality and availability of data. The boundary optimization algorithm improves the visualization effect, making the map clearer and more beautiful, and convenient for staff to view and analyze.

[0061] In step S2, the resolution of the oblique camera survey map for railway sections is 2 cm, and the resolution of the oblique camera survey map for railway station areas is 1 cm. This resolution enables the acquisition of image information of ground objects from multiple angles, providing rich texture and detail. The resolution of the vehicle-mounted LiDAR survey map along the railway is 1 cm, which enables the highly accurate measurement of the 3D coordinates of ground objects, providing accurate geometric information for the construction of the 3D model.

[0062] Next, the multi-source 3D data are also unified into the China Geodetic Coordinate System 2000 and layered.

[0063] After the layered overlay is completed, the 3D model is loaded and the basic data of the points of interest of the 2D graphic dataset is shared. This organically combines the 2D plane information with the 3D stereoscopic scene, providing a more comprehensive and intuitive perspective for the visual management of the railway.

[0064] To load 3D models, the present invention utilizes a specialized 3D model library for railway transportation elements. This library includes 3D models of various infrastructure along the railway, such as station buildings, bridges, tunnels, and signal towers. These models are precisely constructed using professional 3D modeling software based on the actual size, shape, and structure of railway facilities, ensuring high fidelity and accuracy. During the loading process, the corresponding 3D model image is selected from the library based on the user's needs and the current visualization scenario, and accurately placed at the geographic location corresponding to the 2D graphic data.

[0065] The 2D graphics dataset also includes basic data on points of interest (POIs) along the railway, such as station names, locations, and service facilities; bridge and tunnel numbers, lengths, and carrying capacities; and the installation locations and parameters of various equipment. By sharing this POI data, the 3D model seamlessly integrates with the 2D graphics data. When users view a specific railway facility in the 3D scene, they can quickly access the corresponding POI data, providing detailed information about the facility and enabling visual display and interactive querying.

[0066] like Figure 4 As shown, next, a vector diagram of linear elements such as lines, tracks, contact lines, and power lines is generated based on the lidar measurement and tilt camera measurement data.

[0067] LiDAR (LiDAR) measurement technology is a high-precision 3D measurement method that obtains the 3D coordinates of target objects by emitting a laser beam and measuring the time it takes for the reflected light to arrive. In railway surveying, LiDAR can quickly and accurately obtain 3D information about the terrain, landforms, and objects along the railway, including the route, slope, and curvature of the line. Oblique camera measurement captures ground images from multiple angles to obtain rich texture and geometric information, providing data support for generating high-precision 3D models.

[0068] After acquiring LiDAR and oblique camera data, preprocessing is performed. First, the LiDAR point cloud data is filtered and classified to remove noise and unnecessary ground features, extracting point cloud data related to railway linear features. For oblique camera data, image registration, feature extraction, and 3D reconstruction are performed to generate a high-precision 3D model.

[0069] Then, vector diagrams of linear elements such as lines, tracks, overhead wires, and power lines are generated based on the preprocessed data. For lines and tracks, vector curves are fitted based on the line centerline and track boundary information from the LiDAR measurement data. Furthermore, the vector curves are smoothed to better reflect the actual situation, taking into account the slope and curvature of the lines. For overhead wires and power lines, the centerlines of the wires are extracted based on the wire position information from the LiDAR point cloud data and the oblique camera measurement data, and the corresponding vector diagrams are generated. During the generation process, the tension and sag of the wires are taken into account, so that the vector diagrams more realistically reflect the actual shape of the wires.

[0070] The generated linear feature vector maps are highly precise and accurate. They not only accurately reflect the location and direction of railway linear features, but also provide detailed geometric information such as length, width, and height. These vector maps can be integrated with 2D graphic data and 3D models to form a complete railway visualization scene. During the planning and design phase of a railway, planners can use linear feature vector maps to assess the rationality and feasibility of the route. During the construction phase, construction personnel can use the vector maps for precise positioning and guidance. During the operational phase, operations and maintenance personnel can use the vector maps to monitor the status of linear features in real time, promptly identifying and addressing potential safety hazards.

[0071] Furthermore, linear feature vector maps can support intelligent railway management. Based on the information contained in the vector map, a database of railway facilities can be established, enabling information-based management of these facilities. Furthermore, by combining sensor technology with data analysis algorithms, the operating status of linear features can be monitored and analyzed in real time, ensuring safe railway operations.

[0072] Finally, publish the 3D map in the same way as publishing the 2D map.

[0073] This invention achieves efficient construction and smooth rendering of large-scale three-dimensional scenes through multi-sensor fusion and lightweight technology. Multi-sensor fusion integrates data from different types of sensors, fully leveraging their respective strengths and improving the accuracy and integrity of the three-dimensional scene. Lightweight technology significantly reduces the amount of data while maintaining model details, improving model loading speed and display efficiency. The registration algorithm ensures the spatial consistency of multi-source data, allowing point cloud data from different data sources to be accurately fused together. The centerline fitting algorithm improves the accuracy of line modeling, making the direction and position of the railway line more accurate.

[0074] like Figure 5 As shown, in step S3, web container technology can encapsulate the 2D and 3D rendering engines into independent containers for easy deployment and management. Integrating the 2D and 3D rendering engines allows users to view both 2D maps and 3D scenes simultaneously in the same interface, achieving seamless switching and integration of 2D and 3D maps.

[0075] Containerized deployment improves scalability and flexibility, quickly adapting to diverse business needs and user scale. Spatial index matching of 2D and 3D features can associate and match features in 2D maps with features in 3D scenes, enabling unified management and display of 2D and 3D data. Caching technology can store hotspot data in a cache, allowing users to retrieve it directly from the cache when they access it again, improving data access speed.

[0076] Token-based tenant-level permission control supports fine-grained permission configuration and hides the server-side architecture through URL rewriting. Tenant-level permission control allows access to functions and data based on different user roles and permissions, ensuring system security and data confidentiality. Fine-grained permission configuration allows for more detailed division of user permissions to meet the needs of different users. URL rewriting hides the server-side architecture, improving system security by preventing external users from directly accessing server-side resources through URLs.

[0077] like Figure 6 As shown, at the same time, a layer planning configurator and an element planning configurator are provided. The layer planning configurator supports dynamic switching of multiple scales from 1:1,000,000 to 1:10, supports users to extract one or more layers separately, and adopts technology to reduce rendering load and provide professional color schemes. Dynamic switching of multiple scales can dynamically adjust the scale of the map according to user needs and the display range of the map, providing clearer and more accurate map information. The use of technology to reduce rendering load can improve the display speed and performance of the map and reduce the requirements for system resources. Professional color schemes can provide appropriate map colors according to the characteristics and needs of the railway industry to improve the visualization of the map.

[0078] The feature planning configurator sets loading thresholds, employs algorithms for intelligent icon avoidance, and supports real-time integration with business system data. Setting loading thresholds allows for dynamic loading of map features based on the map's display range and scale, reducing unnecessary data loading and improving map display speed. The intelligent icon avoidance algorithm prevents overlapping icons on the map, improving map readability. Support for real-time integration with business system data allows for real-time synchronization of maps with business system data, allowing users to access relevant business information while viewing the map.

[0079] The interface service provides multiple interface types, ensuring timely response times and supporting high-concurrency query requests. This variety of interface types meets the needs of different users and systems, facilitating integration and docking with other systems. Meeting the required response times ensures timely responses when using the system, improving the user experience. Supporting high-concurrency query requests meets the needs of large-scale users and ensures stability and reliability in high-concurrency scenarios.

[0080] This invention achieves efficient data management and rapid functional expansion in multi-tenant scenarios through an intelligent configurator and cloud architecture design. The intelligent configurator can flexibly configure system functions and display content based on different business needs and user roles. The cloud architecture design can offload computing and storage tasks to cloud servers, reducing the computing pressure on terminal devices and achieving efficient data management and functional expansion. Rendering optimization technology effectively improves performance, the icon avoidance algorithm ensures the clarity of annotations, and the interface design facilitates third-party system integration.

[0081] In one embodiment of the present invention, the kilometer marker algorithm in step S4 includes the following steps:

[0082] S41: Filter the mileage points of the engineering profession in the railway line shape file and collect the coordinate points selected by the user.

[0083] S42: According to the mileage pile points of the engineering professional, the corresponding vertical points in the railway line shape file are found, and the railway line shape file is divided into segmented files with a first preset length as a unit.

[0084] S43: Find the segmentation unit closest to the coordinate point selected by the user in the segmentation file.

[0085] S44: Find the corresponding vertical point in the segmentation unit according to the coordinate point selected by the user.

[0086] S45: Calculate the distance between the starting point of the segmentation unit and the corresponding vertical point in the segmentation unit along the direction of the segmentation unit.

[0087] S46: Add the kilometer mark of the starting point of the segmentation unit and the distance between the starting point of the segmentation unit and the corresponding vertical point in the segmentation unit to obtain the kilometer mark of the coordinate point selected by the user.

[0088] In the real-world management and maintenance of railway projects, the workload of collecting longitude, latitude, and elevation coordinates for 3D maps is far greater than simply collecting longitude and latitude on 2D maps. Furthermore, when the current scale is too large or the elevation display is too low, it is difficult to discern the specific mileage of a railway line on both 2D and 3D maps, hindering operational analysis. A series of interlocking technical steps have effectively addressed these challenges, providing critical support for precise positioning and efficient management.

[0089] First, the railway line shapefile is used to select mileage points of interest to the engineering profession. These points serve as key coordinate anchor points on the railway line, providing a precise location reference for subsequent measurement and maintenance operations. Simultaneously, coordinate points selected by users on the map based on practical needs (such as troubleshooting and project planning) are collected and converted into a processable data format, avoiding the interference of massive amounts of irrelevant data. This provides a clear target and raw data foundation for the subsequent calculation of the railway mileage corresponding to these coordinate points. It should be noted that shapefiles are a simple, publicly available geospatial vector data format developed by ESRI (Environmental Systems Research Institute) for storing spatial data of geometric elements such as points, lines, and surfaces, as well as their associated attribute information. They consist of three main files: a .shp file (which stores the shape of the geometric elements), a .shx file (which stores the index of the geometric elements), and a .dbf file (which stores the attribute data corresponding to the geometric elements, organized in dBASE tables).

[0090] Next, a spatial geometry algorithm is used to determine the vertical points of the milepost locations within the railway line shapefile, establishing a precise vertical correspondence between the starting point and the line direction. This operation acts as a "scale line" for line division. Subsequently, long lines are segmented into multiple independent unit files according to preset reasonable lengths, converting complex spatial data into clearly structured, easy-to-process segments. This not only facilitates maintenance personnel's targeted management of different line segments, but also establishes standardized basic units for subsequent calculations, effectively reducing data processing complexity and calculation errors, and enabling refined management of railway lines.

[0091] After completing route segmentation, a distance metric algorithm quickly selects the segmentation unit closest to the user-selected coordinate point. This process is like accurately locating the target area in a "data maze," avoiding a meaningless, comprehensive search across the entire route data and significantly improving data processing efficiency. Furthermore, subsequent calculations are limited to the minimum effective range, significantly enhancing positioning accuracy and providing reliable scope definition for precise analysis.

[0092] After locking onto the nearest segmented unit, the vertical position of the user's coordinate point within that unit is further calculated. Through precise spatial geometry calculations, the coordinate point is refined from a general regional range to a specific vertical corresponding point on the line. This operation acts as a microscopic "anchor" for the coordinate point's precise location, providing millimeter-level precision data support for practical tasks such as line defect location and new facility site selection, ensuring the consistency and high precision of the entire calculation process.

[0093] Then, along the route of each segmented unit, specialized geographic information system technology is used to precisely measure the distance from the unit's starting point to the vertical point, converting the vertical point's spatial location into quantifiable mileage data. This distance data is not only a key parameter for calculating the final kilometer mark, but also provides an intuitive quantitative basis for line condition assessment and maintenance resource allocation, shifting railway maintenance from an experience-driven to a data-driven approach.

[0094] Finally, the kilometer mark at the starting point of the segmented unit is integrated with the aforementioned distance parameters to generate the railway kilometer mark corresponding to the user-selected coordinate point. As a unified location language in railway engineering, kilometer marks clearly present the precise location of the coordinate point along the entire line in an intuitive numerical form, greatly facilitating tasks such as line setting during construction, troubleshooting during operations, and data statistics during routine maintenance. This technical method of converting spatial coordinates into mileage marks not only solves the positioning problem of 2D / 3D maps under specific conditions, but also establishes an efficient data processing system suitable for complex railway engineering environments. This provides solid technical support for the digital management and intelligent operation and maintenance of railway lines, significantly improving the overall efficiency and safety of railway engineering management.

[0095] This series of closely linked technical steps, from data screening to precise positioning, from spatial analysis to mileage quantification, systematically overcomes core problems in railway projects such as cumbersome coordinate collection and ambiguous mileage positioning, providing a replicable solution for the railway industry's refined management in complex scenarios. While improving operational efficiency and reducing labor costs, it also fundamentally enhances the safety and reliability of railway operations.

[0096] The elevation algorithm in step S4 includes at least the following steps:

[0097] S401: Segment the DSM elevation file into DSM elevation segmentation files with a second preset length as a unit.

[0098] S402: According to the kilometer mark of the coordinate point selected by the user, the corresponding DSM elevation segmentation file is searched and obtained.

[0099] S403: Split the DSM elevation segmentation file into a plurality of grid surfaces with a third preset length as the side length.

[0100] S404: Collect the longitude and latitude of the four points in each grid surface and obtain the minimum longitude value Min by comparison x 、Maximum longitude x 、Minimum latitude y and latitude maximum value Max y .

[0101] S405: Collect the longitude A of the coordinate point selected by the user xand latitude A y , and according to the filtering rules, multiple grid surfaces next to the coordinate point selected by the user are obtained; the filtering rules are: Min x ≤A x ≤Max x And Min y ≤A y ≤Max y .

[0102] S406: Using the coordinate point selected by the user as a reference point, obtain straight lines intersecting with multiple grid surfaces, and count the number of intersections in each grid surface; if the number of intersections is an odd number, the grid surface contains the coordinate point selected by the user, and the elevation of the coordinate point selected by the user is returned; if the number of intersections is an even number, the grid surface does not contain the coordinate point selected by the user, and the grid surface is ignored.

[0103] In railway engineering management and maintenance, three-dimensional maps require the collection of equipment's longitude, latitude, and elevation coordinates. This significantly increases operational complexity compared to two-dimensional maps, which only collect longitude and latitude. Furthermore, when the scale of a two-dimensional or three-dimensional map is too large or the elevation display is too low, it is difficult to locally resolve railway line mileage positions and accurately obtain elevation information, seriously affecting business analysis efficiency. This invention systematically resolves these challenges through layered processing and precise analysis of DSM elevation files, providing an efficient solution for three-dimensional coordinate collection and mileage position analysis in complex scenarios.

[0104] First, the DSM elevation file is split into multiple DSM elevation segmentation files according to the second preset length. This operation is like breaking down the huge three-dimensional data into small pieces, effectively reducing the complexity of the original data. DSM elevation files usually contain elevation information of a large range of terrain. The data volume is huge and the structure is complex, and direct processing is inefficient. By reasonably setting the second preset length for segmentation, it can not only ensure that the elevation file in each segmentation file corresponds to the mileage section of the railway line, but also greatly reduce the amount of data processed at a single time, laying the foundation for subsequent rapid retrieval and analysis, and significantly reducing the data processing pressure in three-dimensional coordinate collection.

[0105] Then, based on the kilometer mark of the coordinate point selected by the user (this kilometer mark can be obtained through the previous steps such as line segmentation and vertical point calculation), the corresponding DSM elevation segmentation file is accurately searched, realizing the rapid association between the mileage position and the elevation file. In a two-dimensional or three-dimensional map, when the field of view scale is large, directly locating the elevation area corresponding to a specific mileage is like "finding a needle in a haystack". However, the kilometer mark, a unified location identifier in railway projects, can quickly lock the elevation file of the target area like an "index", avoiding blind searches in the entire range of data, greatly improving data retrieval efficiency, and ensuring that users can quickly locate the elevation file of the required mileage position under complex field of view conditions.

[0106] Subsequently, the DSM elevation segmentation file is further split into raster surfaces with a third preset length as the side length, which is a refined processing of the elevation file. The raster surface has a regular grid structure, and each raster surface corresponds to a specific geographical range. The third preset length of the side length is usually set according to the accuracy requirements of the business analysis. For example, a smaller side length can be set in key railway sections (such as bridges and tunnels) that require local resolution to improve the resolution of the local elevation file. This rasterization process converts continuous elevation surfaces into discrete grid units, which is not only convenient for rapid computer processing and storage, but more importantly, it provides a structured data foundation for the subsequent accurate judgment of the elevation area where the coordinate point is located, effectively solving the problem of blurred local details at low elevation displays or large scales.

[0107] Finally, based on the geometric inclusion relationship between the midpoint and the surface of the grid surface, the grid surface containing the coordinate point selected by the user is calculated and its elevation is returned, realizing the precise mapping from the coordinate position to the specific elevation value. The geometric algorithm is used to determine whether the coordinate point is located within a certain grid surface. This process is like finding the precise "belonging unit" for the coordinate point in the "data grid". Even when the three-dimensional map field of view is complex or the elevation display is unclear, the elevation file corresponding to the coordinate point can be quickly determined through the precise division of the grid surface. This method avoids the tedious operation of manually identifying the elevation in traditional three-dimensional coordinate acquisition, greatly reduces the workload, and at the same time improves the accuracy and efficiency of obtaining elevation files, providing high-precision elevation information support for railway line three-dimensional modeling, disease analysis, engineering design and other businesses.

[0108] In summary, this series of steps, through layered segmentation, mileage association, rasterization, and geometric analysis of DSM elevation files, establishes an efficient processing chain from complex 3D data to precise elevation information. This not only addresses the daunting task of collecting 3D map coordinates, but also, through refined data processing, ensures that railway line mileage locations and corresponding elevation files can be quickly and accurately located even under extreme viewing conditions on 2D or 3D maps. This provides powerful data support for terrain analysis, line design, and maintenance decision-making within railway engineering management, significantly improving work efficiency and analytical accuracy in complex scenarios.

[0109] like Figure 7 As shown, in step S5, the user accesses the URL address through a web browser to realize the display and interaction of a two-dimensional and three-dimensional integrated real scene enhancement picture.

[0110] Basic interactive functions include but are not limited to roaming, zooming, rotating, searching, and locating. Users can conveniently view and browse the map by dragging the mouse to roam, using the scroll wheel to zoom, and rotating in 3D. Dragging the mouse to roam allows users to freely move the map display area, using the scroll wheel to zoom adjusts the map scale, and rotating in 3D allows users to view the 3D scene from different angles, providing more comprehensive and intuitive map information.

[0111] like Figure 8 As shown, the search function includes fuzzy matching based on point of interest keywords, searching based on line kilometer marker values, and searching based on the names of located dynamic objects (personnel, rolling stock, mobile control balls). Fuzzy matching allows users to find related map features by entering partial keywords, improving search efficiency and accuracy. Kilometer marker jump allows users to directly locate a specified kilometer marker location, facilitating precise positioning and viewing of railway lines. Dynamic object tracking can track dynamic objects on the railway, such as trains and inspection vehicles, in real time, allowing users to promptly understand their location and status.

[0112] Advanced interactive features include, but are not limited to, navigation, measurement, and simulation. Advanced interaction integrates intelligent measurement tools, supporting distance and volume measurement. Simulation analysis modules include flood inundation simulation and catenary drift simulation. Intelligent measurement tools allow users to measure distances and volumes directly on a map, providing accurate measurement data for railway planning, design, and construction. Flood inundation simulation can predict the scope and extent of flood impacts on railway lines, providing a basis for decision-making in disaster prevention and mitigation. Catenary drift simulation simulates catenary drift under different operating conditions, providing a reference for catenary maintenance and repair.

[0113] Furthermore, augmented reality features include dynamic kilometer marker display and multi-device compatibility. Dynamic kilometer marker display dynamically displays kilometer marker information based on the user's viewing angle and the map's display range, improving readability and usability. Multi-device compatibility allows users to use the system on a variety of devices, such as computers, mobile phones, and tablets, enhancing system usability and convenience.

[0114] By combining operational information with real-world imagery, this system provides users with more authentic and intuitive operational support. The application of specialized algorithms in measurement and simulation improves the accuracy and reliability of the system. The 3D rotation algorithm ensures smooth operation, allowing users to experience a seamless 3D rotation experience. The measurement algorithm also improves precision, resulting in more accurate and reliable measurement results.

[0115] Second embodiment

[0116] Based on the above method, the second embodiment of the present invention provides a system for enhancing the visualization of railway 2D and 3D integrated real scenes. Figure 9 As shown, the system includes one or more processors and a memory. The memory is used to store one or more programs. When the programs are executed by the processors, the methods in the above embodiments are implemented.

[0117] The processor is used to control the overall operation of the system to complete all or part of the steps of the above method. The processor can be a central processing unit (CPU), a graphics processing unit (GPU), a field programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a digital signal processing (DSP) chip, etc. The memory is used to store various types of data to support operations in the system. These data may include, for example, instructions for any application or method operating on the system, as well as application-related data. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, etc.

[0118] In an exemplary embodiment, the system can be implemented by a computer chip or entity, or by a product having certain functions, for executing the above method and achieving the same technical effect as the above method. A typical embodiment is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, an in-vehicle human-computer interaction device, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0119] In another exemplary embodiment, the present invention further provides a computer-readable storage medium including program instructions, which, when executed by a processor, implement the steps of the method described in any of the above embodiments. For example, the computer-readable storage medium may be the aforementioned memory including the program instructions, which may be executed by a processor to perform the above method and achieve the same technical effects as the above method.

[0120] It should be noted that the above embodiments are merely examples, and the technical solutions of the various embodiments may be combined and are all within the scope of protection of the present invention.

[0121] The above describes in detail the method and system for 2D and 3D integrated railway scene enhancement visualization provided by the present invention. For those skilled in the art, any obvious modification to the present invention without departing from its essence will constitute an infringement of the present invention's patent rights and will result in corresponding legal liability.

Claims

1. A method for enhancing the visualization of railway 2D and 3D integrated real scenes, characterized in that The following steps are involved: S1: Based on the national basic geographic data, national basic geographic data of cities and counties along the railway, orthophoto maps along the railway, and railway line shape files, a 2D graphic dataset is established. The coordinates of the 2D graphic data are aligned and layered, and the 2D map is published through cloud services. S2: Create a 3D graphics dataset based on the railway section oblique camera survey map, railway station area oblique camera survey map, railway line vehicle-mounted laser radar survey map, railway professional traffic element 3D model map and DSM elevation file, coordinate align and layer the 3D graphics data, and publish the 3D map through cloud services; S3: Build a web container to merge the 2D map published in step S1 with the 3D map published in step S2; S4: Encapsulates the kilometer landmark algorithm and elevation algorithm interfaces in the 2D and 3D integrated augmented reality map, allowing users to call them in different business scenarios. S5: The user accesses the unified URL address through a web browser to view the 2D and 3D integrated augmented reality image and interact with the augmented reality image.

2. The method according to claim 1, wherein In step S3, a layer planning configurator is set to support dynamic switching of multiple scales.

3. The method according to claim 1, wherein In step S3, an element planning configurator is set up so that the data of the map and the business system can be synchronized in real time.

4. The method according to claim 1, wherein The kilometer mark algorithm in step S4 includes the following steps: S41: Filter the mileage points of the engineering profession in the railway line shape file and collect the coordinate points selected by the user; S42: Find the corresponding vertical point in the railway line shape file according to the mileage pile point of the engineering professional, and split the railway line shape file into split files with a first preset length as a unit; S43: Find the segmentation unit closest to the coordinate point selected by the user in the segmentation file; S44: Find the corresponding vertical point in the segmentation unit according to the coordinate point selected by the user; S45: Calculate the distance between the starting point of the segmentation unit and the corresponding vertical point in the segmentation unit along the direction of the segmentation unit; S46: Add the kilometer mark of the starting point of the segmentation unit and the distance between the starting point of the segmentation unit and the corresponding vertical point in the segmentation unit to obtain the kilometer mark of the coordinate point selected by the user.

5. The method according to claim 1, wherein The elevation algorithm in step S4 comprises the following steps: S401: Segmenting the DSM elevation file into DSM elevation segmentation files with a second preset length as a unit; S402: According to the kilometer mark of the coordinate point selected by the user, the corresponding DSM elevation segmentation file is searched and obtained; S403: Splitting the DSM elevation segmentation file into grid surfaces with a third preset length as the side length; S406: Using the coordinate point selected by the user as a reference point, obtain straight lines intersecting with multiple grid surfaces, and count the number of intersections in each grid surface; if the number of intersections is an odd number, the grid surface contains the coordinate point selected by the user, and the elevation of the coordinate point selected by the user is returned; if the number of intersections is an even number, the grid surface does not contain the coordinate point selected by the user, and the grid surface is ignored.

6. The method according to claim 5, wherein After step S403 and before step S406, the following steps are further included: S404: Collect the longitude and latitude of the four points in each grid surface and obtain the minimum longitude value Min by comparison x 、Maximum longitude x 、Minimum latitude y and latitude maximum value Max y ; S405: Collect the longitude A of the coordinate point selected by the user x and latitude A y , and according to the filtering rules, multiple grid surfaces next to the coordinate point selected by the user are obtained; the filtering rules are: Min x ≤A x ≤Max x And Min y ≤A y ≤Max y .

7. The method according to claim 1, wherein The step S5 further includes: Access control is performed on users based on their roles and permissions, and access services are provided to users through various interface types.

8. A railway 2D and 3D integrated real-scene enhanced visualization system, characterized by The method comprises a processor and a memory; wherein the memory is coupled to the processor and is used to store a computer program, and when the computer program is executed by the processor, the processor implements the method according to any one of claims 1 to 7.

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