Highway space multi-modal visualization method, device and electronic equipment

Abstract

The present application relates to a kind of highway space multimode visualization method, device and electronic equipment, wherein the method comprises: highway space is divided into multiple basic space grid, and the structured space code including highway number, bid number, direction, start and end stake number and transverse partition is configured for each basic space grid;Two-dimensional engineering drawing, three-dimensional model, construction progress, structure state and bid management information are associated with corresponding basic space grid;The field of view grid is determined according to the field of view range of virtual camera;According to the range of view grid, each basic space grid and the range of view of virtual camera, according to LOD, rendering visualization picture is respectively based;Focus grid is determined according to the focus of virtual camera, and multiple conversion anchor points are extracted;Determine the coordinate system conversion parameter corresponding to focus grid;The visualization picture corresponding to focus grid is converted, and the visualization picture after coordinate conversion is re-rendered.Using the present application, the visualization effect of highway space is improved.

Description

Technical Field

[0001] This invention relates to the fields of digital management of highway engineering, BIM / GIS integration, construction process visualization and spatial information processing technology, and in particular to a method, device and electronic equipment for multimodal visualization of highway space for grid-based management of highway route chainage. Background Technology

[0002] Highway engineering is a long-distance linear project, characterized by long routes, numerous sections, complex cross-sectional composition, and dispersed structures. In actual management, engineering objects typically need to be located and managed according to units such as station intervals, sections, left and right lanes, lanes, roadbed and pavement structural layers, bridges and culverts, slopes, and drainage facilities, rather than simply viewing them using a single model or layer.

[0003] While existing BIM / GIS visualization platforms can overlay and display GIS base maps, 2D drawings, 3D models, and site data, their data organization methods are mostly based on layers, model files, or individual spatial objects, making it difficult to directly map them to the station intervals, lateral zones, and structural units commonly used in highway engineering. Construction progress, quality inspection, site location, and section responsibility information are often scattered across different systems, making it difficult to quickly aggregate and display drawings, models, site locations, and management status for the same highway spatial location.

[0004] In related technologies, global loading or layer overlay is typically used to render and display the spatial data of the entire highway, and the Level of Detail (LOD) of the 3D model is switched based on the viewpoint distance. However, when processing massive spatial data of highways spanning hundreds of kilometers, this method generates huge memory consumption, reducing rendering efficiency in the multimodal visualization process. Furthermore, for coordinate transformation between the geodetic coordinate system used by Geographic Information Systems (GIS) and the local engineering-independent coordinate system used for detailed engineering structures, existing technologies usually employ a single set of global transformation parameters covering the entire route. Due to the curvature of the Earth, these global transformation parameters produce significant length and angular projection distortions in the edge areas of the route, reducing the coordinate transformation accuracy in the multimodal visualization process and affecting the accuracy of multi-source spatial data overlay display.

[0005] Therefore, how to improve the rendering efficiency and coordinate transformation accuracy of highway multimodal visualization to enhance the effect of highway spatial multimodal visualization remains to be solved. Summary of the Invention

[0006] In view of this, it is necessary to provide a method, device and electronic equipment for multimodal visualization of highway space, in order to solve the technical problems in the existing technology that the two-dimensional drawings, three-dimensional models, GIS data, on-site positioning data, construction status data and section management information of highway engineering lack a unified spatial organization method, and it is difficult to aggregate and display and manage the project according to the chainage interval, lateral partition and structural unit. It also takes into account the problems of low data rendering efficiency of the entire highway and insufficient local coordinate alignment accuracy.

[0007] To address the aforementioned problems, in a first aspect, the present invention provides a method for multimodal visualization of highway space, comprising: The highway space is divided into multiple basic spatial grids, and the field of view grid is determined from the basic spatial grids according to the field of view of the virtual camera. Based on the viewing distance between each basic spatial grid in the view grid and the virtual camera, the corresponding level of detail is determined, and the visualization is rendered according to the level of detail. Based on the focus of the virtual camera, determine the focus grid from the field of view grid, and extract at least four conversion anchor points within the range of the focus grid; Based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database, the coordinate system transformation parameters corresponding to the focal grid are calculated. Based on the coordinate system transformation parameters, the visualization screen corresponding to the focal grid is transformed by coordinate transformation, and the two-dimensional engineering drawing, three-dimensional model, on-site positioning mark and engineering status information in the focal grid after coordinate transformation are fused and rendered.

[0008] In one possible implementation, after calculating the coordinate system transformation parameters corresponding to the focal mesh, the method further includes: Receive geodetic coordinate data streams collected by mobile terminals; Kalman filtering is applied to the geodetic coordinate data stream to obtain a smoothed coordinate data stream; The smoothed coordinate data stream is transformed using the coordinate system transformation parameters to obtain the transformed coordinates; Starting from the transformed coordinates, project onto the rendered 3D model surface within the focal mesh to obtain the projection intersection point; The location identifier of the mobile terminal is rendered at the projection intersection.

[0009] In one possible implementation, after re-rendering the visualization of the coordinate transformation, the following is also included: When it is detected that the focal mesh renders a two-dimensional engineering drawing and a three-dimensional model, the vector contour of the two-dimensional engineering drawing and the projection contour of the corresponding highway engineering object in the three-dimensional model are extracted. Perform polygon Boolean operations on the vector contour and the projected contour to calculate the area of ​​the non-overlapping region or the boundary Hausdorff distance between the vector contour and the projected contour. Based on the area of ​​the non-overlapping region or the boundary Hausdorff distance, the deviation status or review status of the corresponding highway engineering object within the focal grid is determined, and warning rendering is performed on the region that exceeds the preset tolerance.

[0010] In one possible implementation, determining the corresponding level of detail for each grid in the view grid and the virtual camera based on their viewing distance, and rendering the visualization according to the level of detail, includes: When the viewing distance is greater than the first preset threshold, the corresponding visualization screen is rendered by scheduling two-dimensional color or route color band. The visualization screen rendered by the two-dimensional color or route color band is used to display the route direction, section range or construction progress overview. When the viewing distance is between the first preset threshold and the second preset threshold, the lightweight three-dimensional contour model is scheduled to render the corresponding visualization screen. The visualization screen rendered by the lightweight three-dimensional contour model is used to display the outline of engineering objects such as roadbed, pavement, bridge, culvert, slope, drainage facilities or protective facilities. When the viewing distance is less than the second preset threshold, the high-precision component model and engineering detail construction drawing are scheduled to render the corresponding visualization screen. The visualization screen corresponding to the high-precision component model and engineering detail construction drawing is used to display the detailed structure, construction status, quality status or responsibility information within the corresponding basic spatial grid.

[0011] In one possible implementation, determining the focus grid from the view grid based on the focus of the virtual camera includes: In response to a user's trigger operation on any of the base spatial grids in the field of view, the focus of the virtual camera is moved to the base spatial grid targeted by the trigger operation, and the base spatial grid targeted by the trigger operation is determined as the focus grid; or, In response to the user's panning operation on the visual screen, when the focus of the virtual camera moves into another basic spatial grid in the field of view grid, the basic spatial grid into which the focus of the virtual camera moves is determined as the focus grid.

[0012] In one possible implementation, determining the field-of-view grid from the base spatial grid based on the field of view of the virtual camera includes: For each of the aforementioned basic spatial grids, a spatial bounding box is created, and a bounding box hierarchy tree is constructed; By performing intersection detection between the view frustum and the bounding box hierarchy tree, the basic spatial grid located within the view frustum is determined as the field of view grid.

[0013] In one possible implementation, the calculation of the coordinate system transformation parameters corresponding to the focal grid based on the first planar coordinates of the transformation anchor point in the geographic information system and the second planar coordinates in the engineering database includes: Based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database, a coordinate transformation equation containing a scale factor, rotation angle, and translation vector is constructed. With the goal of minimizing the sum of squared residuals at each of the transformation anchor points, the coordinate transformation equations are solved using the least squares method to obtain the coordinate system transformation parameters.

[0014] In one possible implementation, dividing the highway space into multiple basic spatial grids includes: Along the route direction of the highway space, the highway space is longitudinally segmented according to the station number, and laterally divided according to the lanes, guardrails or drainage ditches of the highway space to divide it into multiple basic spatial grids. After dividing the highway space into multiple basic spatial grids, the following is also included: Each of the basic spatial grids is configured with a structured spatial code, which includes highway number, section number, direction symbol, start and end station interval, and lateral partition identifier.

[0015] Secondly, the present invention also provides a highway spatial multimodal visualization device, comprising: The grid construction unit is used to longitudinally segment the highway route according to the station interval, and to divide it into multiple basic spatial grids according to the horizontal or vertical engineering zones of the highway, and to configure structured spatial coding for each basic spatial grid. The data association unit is used to associate at least one of GIS data, two-dimensional engineering drawings, three-dimensional models, on-site positioning data, construction status data, and section management information with the structured spatial code; A field-of-view determination unit is used to determine the field-of-view grid from the basic spatial grid based on the field of view of the virtual camera. The rendering unit is used to determine the corresponding level of detail for each basic spatial grid in the view grid and the virtual camera based on the viewing distance between each grid and the virtual camera, and to render the highway engineering objects and engineering status associated with the corresponding basic spatial grid according to the level of detail. A focus processing unit is used to determine a focus grid from the field of view grid based on the focus of the virtual camera, and extract at least four conversion anchor points within the range of the focus grid; The calculation unit is used to calculate the coordinate system transformation parameters corresponding to the focal grid based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database. The visualization unit is used to perform coordinate transformation on the visualization screen corresponding to the focal grid according to the coordinate system transformation parameters, and to perform fusion rendering on the two-dimensional engineering drawing, three-dimensional model, on-site positioning mark and engineering status information in the focal grid after coordinate transformation.

[0016] Thirdly, the present invention also provides an electronic device, including a communication interface, a memory, and a processor, wherein, The communication interface is used to collect highway space data corresponding to the highway space. The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the highway spatial multimodal visualization method described in any of the above implementations.

[0017] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program or instructions, which, when executed by a processor, can implement the steps in the highway spatial multimodal visualization method described in any of the above implementations.

[0018] The beneficial effects of this invention are: The multimodal visualization method for highway space provided by this invention divides the highway route longitudinally according to station intervals, and combines this with engineering objects such as left and right lanes, roadbed structure layers, pavement structure layers, bridges and culverts, slopes, drainage facilities or protective facilities to form multiple basic spatial grids. Each basic spatial grid is configured with a structured spatial code, which enables two-dimensional engineering drawings, three-dimensional models, GIS data, on-site positioning data, construction status data and section management information in highway engineering to be associated and displayed in a unified highway spatial unit. This makes it convenient for managers to quickly view the corresponding engineering objects, construction status and responsibility information according to station intervals, horizontal partitions or structure units.

[0019] Meanwhile, by determining the field of view grid based on the field of view of the virtual camera and performing detailed rendering of different basic spatial grids based on the viewing distance, the long-distance scene displays the route direction, section range and construction progress overview, the medium-distance scene displays the outline of the project object, and the close-distance scene displays high-precision models, two-dimensional drawings and project status information, thereby meeting the needs of highway engineering management and viewing while reducing the data loading and rendering pressure of the entire line.

[0020] Furthermore, by determining the basic spatial grid currently focused on by the virtual camera as the focal grid and calculating the local coordinate system transformation parameters based on the transformation anchor points within the focal grid, the overlay accuracy of GIS data, 2D engineering drawings, 3D models, and on-site positioning points within the local highway space can be improved. Combined with mobile terminal positioning mapping and 2D / 3D contour comparison, it can also assist in identifying the deviation status, pending verification status, or construction status of engineering objects within the corresponding grid, thereby improving the effectiveness of online monitoring and visual management of highway engineering. Attached Figure Description

[0021] Figure 1 A schematic flowchart of an embodiment of the highway spatial multimodal visualization method provided by the present invention; Figure 2 This is a schematic diagram illustrating the principle of dynamic spatial topology mapping for RTK terminals provided by the present invention. Figure 3 This is a schematic diagram of the structure of the highway spatial multimodal visualization device provided by the present invention. Detailed Implementation

[0022] 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 a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0023] In the description of the embodiments of the present invention, unless otherwise stated, "a plurality of" means two or more.

[0024] The terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a technical feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] This invention provides a method, device, and electronic device for multimodal visualization of highway space, which will be described below.

[0027] The execution entity of the highway spatial multimodal visualization method in this application embodiment can be the highway spatial multimodal visualization device provided in this application embodiment, or different types of electronic devices such as server equipment, physical host, or user equipment (UE) that integrate the highway spatial multimodal visualization device. The highway spatial multimodal visualization device can be implemented in hardware or software. The UE can be a terminal device such as a smartphone, tablet computer, laptop computer, handheld computer, desktop computer, or personal digital assistant (PDA).

[0028] The highway spatial multimodal visualization method of this application is applicable to construction monitoring and digital management scenarios of long-distance linear highway projects. It is especially suitable for smart construction sites, highway digital management and BIM and GIS integrated applications that require the integration and display of macro-geographic information systems and micro-building information models in the same view and real-time tracking of high-precision positioning of mobile terminals on site.

[0029] Figure 1 This is a schematic flowchart of an embodiment of the highway spatial multimodal visualization method provided by the present invention, as shown below. Figure 1 As shown, the multimodal visualization method for highway space includes: S101. Divide the highway space into multiple basic spatial grids, and determine the field-of-view grid from the basic spatial grids according to the field of view of the virtual camera.

[0030] Among them, highway space refers to the three-dimensional geographical area occupied and affected by long-distance linear highway projects, including the spatial range of engineering entities such as topography, roadbed and pavement, bridges and tunnels, culverts and slopes and ancillary facilities along the route.

[0031] The basic spatial grid refers to the data organization unit with clear spatial boundaries obtained by discretizing the highway space according to preset rules.

[0032] The basic spatial grid serves not only as a rendering and scheduling unit but also as a highway construction management unit. Each basic spatial grid can be associated with engineering objects such as roadbed, pavement, bridges, culverts, slopes, drainage, and protection structures, and records the corresponding object's design drawings, BIM components, construction progress status, inspection data, section number, and responsible personnel. When a user clicks on any grid, the system displays the corresponding station interval, lateral partition, structure type, current construction stage, and management information. The construction progress status includes at least one of the following: not under construction, under construction, completed, pending review, or abnormal status. The construction progress status is associated with the structured spatial code of the basic spatial grid, allowing users to query the road construction progress or structure construction progress within the corresponding station interval based on the structured spatial code.

[0033] A virtual camera is a logical object that defines the user's observation position, orientation, and visible area in a 3D scene. The field of view is the spatial area that the virtual camera can currently observe.

[0034] Specifically, based on the highway spatial data corresponding to the highway space, the highway can be longitudinally segmented according to station numbers along the route, and laterally divided according to lanes, roadbed, pavement, slopes, bridges and culverts, drainage ditches, or protective facilities. This divides the entire highway into a series of spatially continuous and non-overlapping basic spatial grids. A structured spatial code is configured for each basic spatial grid, and two-dimensional engineering drawings, three-dimensional models, construction progress status, structure status, and section management information are associated with the structured spatial code. Then, the field of view, orientation, and coordinate parameters of the virtual camera are obtained to define the spatial boundary of the current field of view. Each basic spatial grid is then traversed, and its spatial position is compared with the field of view. Basic spatial grids that fall entirely or partially within the field of view are identified as the field of view grids.

[0035] In this embodiment, by discretizing a long-distance (e.g., hundreds of kilometers) continuous highway space into multiple independently managed basic spatial grid units, data organization and scheduling operations can be performed at the grid as the smallest granularity. The grids that fall within the field of view are selected for subsequent processing, so that the range of data to be processed in each frame is reduced from the entire highway to the currently visible local area. This avoids the invalid loading and rendering calculation of grid data outside the field of view and improves the utilization efficiency of rendering resources.

[0036] S102. Based on the viewing distance between each basic spatial grid in the view grid and the virtual camera, determine the corresponding level of detail for each grid, and render the visualization image according to the level of detail.

[0037] Among them, Level of Detail (LOD) refers to assigning different levels of rendering data with varying precision based on the importance of the underlying spatial grid in the current image.

[0038] View distance refers to the spatial distance between the virtual camera and the underlying spatial grid. In a 3D visualization scene, view distance determines the size of the grid's projection on the screen. The larger the view distance, the smaller the grid's proportion in the image, and the fewer details the human eye can discern; the smaller the view distance, the larger the grid's proportion in the image, and the higher the user's demand for detail precision.

[0039] Visualized images refer to the content displayed on the screen after each basic spatial grid in the field of view is rendered according to its corresponding level of detail. Basic spatial grids at different viewing distances can be combined to form the complete image currently seen by the user through different levels of precision, such as two-dimensional color blocks, lightweight three-dimensional contours, or high-precision component models.

[0040] Specifically, at least two distance thresholds can be preset to divide the level of detail into multiple levels, each corresponding to rendering data of different precision. When the viewing distance between the base space grid and the virtual camera falls within a certain threshold range, the corresponding Level of Detail (LOD) is determined for that base space grid, and visualization data matching that level of detail is scheduled from the data source for rendering. By performing hierarchical scheduling at the grid level, different precision rendering data is matched to grids at different viewing distances, allowing distant grids to be presented with low-precision data without consuming high-precision model resources, while nearby grids receive high-precision detail rendering. This minimizes the rendering load while ensuring a good visual experience, improving the rendering frame rate and interactive smoothness in long-distance highway scenes.

[0041] S103. Based on the focus of the virtual camera, determine the focus grid from the field of view grid, and extract at least four conversion anchor points within the range of the focus grid.

[0042] The focus of a virtual camera refers to the central position that the virtual camera is facing or that the user is currently focusing on within its field of view. The focus grid is the basic spatial grid in which the focus of the virtual camera is currently located.

[0043] Transformation anchor points are geometric feature points selected within the focal grid that simultaneously possess known coordinates in both the geographic information system (GIS) coordinate system and the local independent coordinate system of the engineering database. They are used to establish transformation relationships between the two coordinate systems. For example, transformation anchor points can be physical boundary points or known geometric feature points within the focal grid, such as highway centerlines, station control points, bridge and culvert corner points, intersections of roadbed edges, drainage facility endpoints, or survey control points.

[0044] Specifically, the position coordinates of the virtual camera's focus point within the highway space can be obtained. These coordinates are then matched one by one with the spatial range of each basic spatial grid in the field of view grid, and the basic spatial grid containing these coordinates is determined as the focus grid. Subsequently, at least four transformation anchor points are extracted within the focus grid. Transformation anchor points are geometric feature points within the focus grid that have known coordinates in both the geographic information system coordinate system and the local independent coordinate system of the engineering database. Transformation anchor points can be selected from the physical boundary corners of the focus grid or known engineering survey control points. To create redundant observation conditions to adjust measurement errors and improve the accuracy and robustness of the solution results, the number of transformation anchor points is no less than four. By locking the focus grid from the field of view grid and extracting transformation anchor points within this focus grid, the calculation range of subsequent coordinate transformations is limited to the smallest spatial unit currently of interest to the user. This avoids the cumulative errors caused by performing coordinate transformations across the entire line, ensuring the spatial specificity of the anchor point extraction and the accuracy of the transformation.

[0045] S104. Based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database, the coordinate system transformation parameters corresponding to the focal grid are calculated.

[0046] The first plane coordinate represents the planar position of the transformation anchor point in the coordinate system used by the GIS. The second plane coordinate represents the planar position of the same transformation anchor point in the local independent coordinate system used by the engineering database.

[0047] Coordinate system transformation parameters refer to a set of parameters that are calculated based on the known coordinates of the transformation anchor points within the focal grid in two coordinate systems. These parameters are used to describe the spatial transformation relationship between the coordinate system used by the geographic information system and the local independent coordinate system used by the engineering database. This set of parameters is used to transform engineering primitives and model data within the current focal grid from one coordinate system to another.

[0048] Specifically, using the known coordinate values ​​of each transformation anchor point within the focal grid in both the GIS coordinate system and the engineering database, the coordinate system transformation parameters corresponding to the focal grid are calculated. These parameters characterize the spatial transformation relationship between the two coordinate systems. By utilizing the known coordinates of the transformation anchor points within the focal grid in both coordinate systems, the corresponding coordinate system transformation parameters are independently calculated for each focal grid. Since the scale of a single grid is small, the curvature deformation of the Earth within that grid is negligible. Therefore, the coordinate transformation accuracy within the focal grid can be improved, ensuring the consistency of spatial alignment throughout the entire long-distance linear engineering project.

[0049] S105. Based on the coordinate system transformation parameters, perform coordinate transformation on the visualization screen corresponding to the focal grid, and perform fusion rendering on the two-dimensional engineering drawing, three-dimensional model, on-site positioning mark and engineering status information within the focal grid after coordinate transformation.

[0050] The visualization corresponding to the focus grid is the corresponding partial display area rendered by the focus grid in the visualization, which is a subset of the visualization obtained in step S102 and is the specific object of the coordinate transformation operation.

[0051] Specifically, the original coordinates of the engineering elements and model data corresponding to the rendered visualization within the focal grid are obtained. Using the calculated coordinate system transformation parameters, the original coordinates are transformed one by one to obtain the corrected position of each element and model in the local engineering independent coordinate system. Based on the corrected position, the rendering process is re-executed, refreshing the visualization corresponding to the focal grid. By actually applying the coordinate system transformation parameters to the engineering elements and model data of the focal grid, and re-rendering after coordinate transformation, the 2D engineering drawings, 3D building information models, and geographic information base maps displayed within the focal grid are strictly aligned in spatial position. This eliminates element misalignment and geometric drift caused by coordinate system differences when switching between macro-geographic information views and micro-engineering views, ensuring the spatial consistency of multimodal data in highway space within the focal grid. This improves the rendering efficiency and spatial alignment accuracy of multimodal visualization of highway space, thereby enhancing the visualization effect of highway space.

[0052] In summary, the highway spatial multimodal visualization method provided by this invention divides the highway space into multiple basic spatial grids and performs view filtering and layered rendering at the grid granularity. This ensures that each frame only processes currently visible data with corresponding precision, improving the rendering frame rate and interaction smoothness in long-distance highway scenes. By locking the focal grid from the view grid and independently calculating the exclusive coordinate system transformation parameters within the focal grid, the coordinate transformation accuracy within the focal grid is improved. By applying the exclusive transformation parameters to the visualization of the focal grid and redrawing it, the spatial consistency of multimodal data within the focal grid is ensured, improving the rendering efficiency and spatial alignment accuracy of highway spatial multimodal visualization, thereby enhancing the visualization effect of the highway space.

[0053] In some embodiments of the present invention, after step S104, the method further includes: receiving a geodetic coordinate data stream collected by a mobile terminal; performing Kalman filtering on the geodetic coordinate data stream to obtain a smoothed coordinate data stream; using the coordinate system transformation parameters to transform the smoothed coordinate data stream to obtain transformed coordinates; using the transformed coordinates as the starting point, projecting onto the rendered 3D model surface within the focal grid to obtain a projection intersection point; and rendering the positioning identifier of the mobile terminal at the projection intersection point.

[0054] Among them, the mobile terminal refers to a portable device equipped with a high-precision positioning module. This high-precision positioning module can output geodetic coordinate data streams with centimeter-level accuracy. The data streams contain timestamps and geodetic coordinate information, and the output frequency of the data streams can be pre-configured.

[0055] Kalman filtering is used to predict the current state based on the speed and position of the mobile terminal at the previous moment, and to fuse it with the current observation to output a smooth and non-jumping optimal estimated coordinate curve, so as to filter out the instantaneous drift and jump points caused by occlusion in complex construction site environments.

[0056] Ray casting refers to a technique that involves projecting a virtual ray from a point in space along a specified direction and calculating the coordinates of the intersection point between the ray and a triangular facet in a 3D model. The Möller-Trumbore intersection algorithm can be used to obtain the projection intersection point.

[0057] Specifically, after the coordinate system transformation parameters corresponding to the focal grid are calculated, a long data connection is established with the mobile terminal to receive the timestamped geodetic coordinate data stream output by the mobile terminal in real time. This geodetic coordinate data stream is then smoothed using a Kalman filter to obtain a smoothed coordinate data stream. Using the calculated coordinate system transformation parameters, coordinate transformation is performed on each coordinate point in the smoothed coordinate data stream, converting the coordinates in the geodetic coordinate system to the transformed coordinates in the local engineering coordinate system corresponding to the focal grid. Starting from the projection point of the transformed coordinates on the horizontal plane, a spatial ray is emitted vertically downwards. The intersection point of this spatial ray with the rendered 3D model triangular facet within the focal grid is calculated and used as the projection intersection point. The mobile terminal's location marker is rendered at this projection intersection point, ensuring that the location marker is aligned with the 3D model surface.

[0058] In one specific implementation, such as Figure 2 The diagram shown illustrates the principle of dynamic spatial topology mapping for RTK terminals. It demonstrates the complete process of projecting a smoothed version of the mobile terminal's location point from its original geodetic coordinates onto the surface of a rendered 3D model, and then capturing the intersection point.

[0059] Figure 2The image shows the original positioning trajectory, represented by a dashed line, which exhibits jitter and offset; the smoothed coordinate curve obtained after Kalman filtering; the projection position of the smoothed coordinate point on the horizontal plane; a virtual space ray emitted vertically downwards from this projection position; triangular facets on the 3D model surface; and the intersection of the virtual ray and the triangular facets, i.e., the rendering position of the positioning marker. The working principle is as follows: The system receives a timestamped geodetic coordinate data stream from the mobile terminal. After Kalman filtering to eliminate instantaneous drift and jumps, smoothed coordinates are obtained. The horizontal projection point of the smoothed coordinates is used as the starting point of the ray, and a virtual space ray is emitted vertically downwards. The intersection point of this ray with the rendered 3D model triangular facets within the focal mesh is calculated using a cross-intersection algorithm. The mobile terminal's positioning marker is rendered at this intersection point, thus achieving precise alignment between the positioning marker and the 3D model surface.

[0060] Understandably, this embodiment eliminates instantaneous drift and jumps in mobile terminal positioning data through Kalman filtering, then uses the dedicated coordinate system transformation parameters of the focal grid to transform the smoothed coordinates to the local engineering coordinate system, and precisely attaches the positioning mark to the surface of the three-dimensional model through ray projection. This solves the problem that the mobile terminal positioning point is suspended in mid-air or buried under the ground in the three-dimensional scene, and realizes high-precision dynamic mapping between the mobile terminal positioning point and the surface of the engineering structure.

[0061] In some embodiments of the present invention, after step S105, the method further includes: when it is detected that the focal mesh renders a two-dimensional engineering drawing and a three-dimensional model, extracting the vector contour of the two-dimensional engineering drawing and the projection contour of the corresponding highway engineering object in the three-dimensional model; performing polygon Boolean operations on the vector contour and the projection contour to calculate the area of ​​the non-overlapping region or the boundary Hausdorff distance between the vector contour and the projection contour; determining the deviation state or the state to be reviewed of the corresponding highway engineering object in the focal mesh based on the area of ​​the non-overlapping region or the boundary Hausdorff distance, and performing early warning rendering on the region that exceeds the preset tolerance.

[0062] Among them, vector contour refers to a set of closed polygons or line segments composed of vertex arrays extracted from two-dimensional engineering drawings, used to represent geometric information such as the boundaries and axes of structures.

[0063] Projected profile refers to the two-dimensional polygon obtained by performing parallel orthographic projection on a three-dimensional model component along the vertical direction.

[0064] Polygon Boolean operations refer to computational geometry algorithms that perform logical union, intersection, or difference operations on two sets of polygons. The Weiler-Atherton algorithm can be used as an example. The Hausdorff distance is a measure of the maximum deviation between two sets of points; the larger the value, the more significant the geometric difference between the two sets of contours.

[0065] Warning rendering refers to the visual processing of primitives that have been detected to have spatial deviations, which is different from normal rendering. For example, highlighting or breathing flashing may be used.

[0066] Specifically, after the visualization of the focal grid is re-rendered, it is detected whether a 2D engineering drawing and a 3D model are simultaneously rendered within the focal grid. When both are detected, the vector data in the 2D engineering drawing is parsed, and the closed polygons or line segments corresponding to the structural boundaries and axes are extracted as vector contours. Parallel orthographic projection is performed on the 3D model components along the vertical direction to obtain the 2D polygons of the outer contours of each component as projection contours. The polygon Boolean operation algorithm is called to perform an XOR intersection operation on the vector contours and projection contours to calculate the area of ​​the non-overlapping region or the boundary Hausdorff distance between them. When the area of ​​the non-overlapping region exceeds the preset area tolerance, or the boundary Hausdorff distance exceeds the preset distance tolerance, it is determined that there is a spatial mismatch between the design drawing and the 3D model within the focal grid, and a warning rendering is performed on the elements with deviations.

[0067] Understandably, this embodiment automatically extracts the vector contours of the two-dimensional engineering drawings and the projected contours of the corresponding highway engineering objects in the three-dimensional model at the focal grid level and performs geometric comparison, and performs early warning rendering for deviation areas that exceed the preset tolerance, thereby realizing the automated inspection of spatial consistency between the design drawings and the three-dimensional model.

[0068] In some embodiments of the present invention, step S102 includes: when the viewing distance is greater than a first preset threshold, scheduling a two-dimensional color or route color strip to render the corresponding visualization screen, the visualization screen rendered by the two-dimensional color or route color strip is used to display the route direction, section range, or construction progress overview; when the viewing distance is between the first preset threshold and a second preset threshold, scheduling a lightweight three-dimensional contour model to render the corresponding visualization screen, the visualization screen rendered by the lightweight three-dimensional contour model is used to display the outline of engineering objects such as roadbed, pavement, bridges and culverts, slopes, drainage facilities, or protective facilities; when the viewing distance is less than the second preset threshold, scheduling a high-precision component model and engineering detail construction drawing to render the corresponding visualization screen, the visualization screen rendered by the high-precision component model and engineering detail construction drawing is used to display the detailed structure, construction status, quality status, or responsibility information within the corresponding basic spatial grid.

[0069] Two-dimensional color blocks refer to road zone strip color blocks represented in the form of planar polygons, used to characterize the spatial orientation and extent of highways from a distance, such as route orientation, section scope, and construction progress.

[0070] Lightweight 3D contour models refer to the shell of a 3D model that has its internal structural details removed and only the outer surface geometry retained, such as the contours of engineering objects like roadbeds, pavements, bridges, culverts, slopes, and drainage facilities.

[0071] High-precision component models refer to three-dimensional component-level models that contain complete internal structural details, while engineering detailed construction drawings refer to two-dimensional planar construction drawings in CAD format, such as high-precision BIM models and two-dimensional design drawings, along with some construction status and responsibility information of the structures.

[0072] Specifically, a first preset threshold D1 and a second preset threshold D2 are pre-set. When the viewing distance between the basic spatial grid and the virtual camera is greater than D1, the grid's projected area on the screen is small, and the corresponding visualization is rendered using two-dimensional color or route color bands. The visualization is used to display the route direction, section range, or construction progress overview. When the viewing distance is between D1 and D2, the grid begins to have a recognizable shape, and a lightweight three-dimensional contour model is rendered. When the viewing distance is less than D2, the grid becomes the visual focus, and a high-precision component model and detailed engineering construction drawings are rendered.

[0073] Understandably, this embodiment divides the mesh into three levels of detail based on distance and schedules data of corresponding precision for rendering, so that distant meshes only occupy very little video memory and bandwidth resources, and only loads full-precision model data for nearby focal meshes. This reduces the amount of rendering data per frame from tens of GB to tens of MB, which is the total amount of data loaded at full precision across the entire line, thereby improving the rendering frame rate and smoothness of interaction in long-distance highway scenes.

[0074] In some embodiments of the present invention, step S103 includes: in response to a user's trigger operation on any of the basic spatial grids in the field of view grid, moving the focus of the virtual camera to the basic spatial grid targeted by the trigger operation, and determining the basic spatial grid targeted by the trigger operation as the focus grid; or, in response to a user's panning operation on the visual image, when the focus of the virtual camera moves into another basic spatial grid in the field of view grid, determining the basic spatial grid into which the focus of the virtual camera moves as the focus grid.

[0075] Among them, the trigger operation refers to the interactive action performed by the user on the visual screen to select the target basic spatial grid.

[0076] Panning refers to the interactive action of users dragging the visual image to change the field of view of the virtual camera.

[0077] Specifically, there are two methods for determining the focus grid. First, detect user actions on any base space grid within the view grid, move the virtual camera's focus to the base space grid targeted by the action, and designate that base space grid as the focus grid. Second, detect user panning actions on the visual image; when the virtual camera's focus moves into another base space grid within the view grid during the pan, designate the newly moved base space grid as the focus grid.

[0078] Understandably, this embodiment determines the focus grid through both triggering and translation operations, enabling the determination of the focus grid to support both user-initiated selection of the target grid and automatic switching during continuous roaming along the route, thereby improving the flexibility of interactive operations.

[0079] In some embodiments of the present invention, step S101 includes: establishing a spatial bounding box for each of the basic spatial grids and constructing a bounding box hierarchy tree; performing intersection detection between the view frustum and the bounding box hierarchy tree, and determining the basic spatial grid located within the view frustum as the view grid.

[0080] Among them, the spatial bounding box refers to the smallest geometry that completely encloses the basic spatial mesh, and can be either an axial-aligned bounding box (AABB) or an oriented bounding box (OBB).

[0081] Bounding Volume Hierarchy (BVH) is a tree-like acceleration structure that organizes multiple spatial bounding boxes in a hierarchical manner, used to quickly eliminate non-intersecting spatial objects.

[0082] The view frustum is the visible space region defined by the field of view, near and far clipping planes, and orientation of the virtual camera.

[0083] Specifically, for each base spatial grid obtained, its minimum bounding cube or oriented bounding volume is calculated as the spatial bounding box. The spatial bounding boxes of all base spatial grids are organized layer by layer according to spatial proximity to construct the BVH. The field of view, orientation, and coordinate parameters of the virtual camera are obtained to generate the view frustum of the current frame. Starting from the root node of the BVH, the spatial relationship between the bounding box of each node and the six clipping planes of the view frustum is checked layer by layer. Subtrees of nodes completely outside the view frustum are removed, and the base spatial grids corresponding to the leaf nodes that are completely or partially inside the view frustum are determined as the view grid.

[0084] Understandably, this embodiment improves the screening efficiency of the field of view grid by establishing BVH and combining it with view cone intersection detection to quickly eliminate a large number of basic spatial grids outside the field of view.

[0085] In some embodiments of the present invention, step S104 includes: constructing a coordinate transformation equation containing a scale factor, a rotation angle, and a translation vector based on the first plane coordinates of the transformation anchor points in the geographic information system and the second plane coordinates in the engineering database; and solving the coordinate transformation equation using the least squares method with the goal of minimizing the sum of squared residuals of each transformation anchor point to obtain the coordinate system transformation parameters.

[0086] The coordinate transformation equation is a mathematical model that describes the spatial transformation relationship between two planar coordinate systems. It includes four parameters to be determined: the scale factor λ, the rotation angle θ, and the translation vectors ΔX and ΔY.

[0087] The residual sum of squares refers to the cumulative square of the deviations between the fitted coordinates calculated by the coordinate transformation equation for each transformation anchor point and the actual known coordinates. It is used to measure the overall fitting accuracy of the coordinate transformation equation.

[0088] The Least Squares Method is used to find the optimal solution for each unknown parameter in the coordinate transformation equation.

[0089] Specifically, coordinate pairs are formed by combining the first plane coordinates (x_i, y_i) of each transformation anchor point within the focal grid in the geographic information system and the second plane coordinates (X_i, Y_i) in the engineering database. Based on these coordinate pairs, a Helmert Transformation model is constructed as the coordinate transformation equation. The mathematical form of the Helmert Transformation model is: ; in,( , ) represents the first plane coordinates of the i-th transformation anchor point, ( , Let θ be the second plane coordinate of the i-th transformation anchor point, λ be the scale factor, θ be the rotation angle, and ΔX and ΔY be the translation vectors. , Let be the residuals of the i-th transformation anchor point in the X and Y directions.

[0090] The error equation V = AX - L is constructed using the least squares method, where A is the coefficient matrix, X is the vector of parameters to be solved, L is the vector of observed values, and V is the residual vector. By solving the normal equation, the sum of squared residuals at all transformation anchor points is equal to the sum of squared residuals at all transformation anchor points Σ( 2 + 2With minimization as the optimization objective, the optimal values ​​of λ, θ, ΔX, and ΔY are calculated in milliseconds by constructing error equations and solving normal equations, thus obtaining the coordinate system transformation parameters corresponding to the focal grid.

[0091] Understandably, this embodiment describes the transformation relationship between two coordinate systems using the Helmert transformation model, and solves each parameter by least squares with the goal of minimizing the sum of squared residuals at the transformation anchor points. This improves the accuracy and stability of the coordinate system transformation parameters and ensures the accuracy of coordinate transformation within the focal grid.

[0092] In some embodiments of the present invention, step S101 includes: longitudinally segmenting the highway space according to the station number along the route direction of the highway space, and laterally dividing the highway space according to the lanes, guardrails or drainage ditches, to divide multiple basic spatial grids; after dividing the highway space into multiple basic spatial grids, it further includes: configuring a structured spatial code for each basic spatial grid, wherein the structured spatial code includes highway number, section number, direction symbol, start and end station number interval and lateral partition identifier.

[0093] Among them, longitudinal segmentation refers to dividing the highway into continuous longitudinal sections along the extension direction of the highway route, based on the mileage of the station number, according to a preset length.

[0094] Lateral zoning refers to further dividing each longitudinal section into different lateral sub-regions along the cross-section of the road, based on the spatial distribution of different functional areas such as lanes, guardrails, and drainage ditches.

[0095] Structured spatial coding refers to a string identifier containing spatial attribute information of an engineering project, generated according to preset field rules. This structured spatial code includes the highway number, section number, direction indicator, start and end station range, and lateral partition identifier. For example, a structured spatial code can be represented as G25-S3-N-K103+150~200-L, where G25 represents the highway number, S3 represents the section number, N represents the direction indicator, K103+150~200 represents the start and end station range, and L represents the lateral partition identifier.

[0096] Specifically, the highway is longitudinally segmented at preset station intervals, with the length of each segment adjustable according to engineering precision requirements. Within each longitudinal segment, lateral partitions are created based on the spatial boundaries of functional areas such as lanes, guardrails, and drainage ditches, thus discretizing the entire highway into multiple rectangular or irregularly shaped basic spatial grids. Each basic spatial grid's spatial boundary is defined by both the longitudinal segment range and the lateral partition range. After grid division, a structured spatial code is configured for each basic spatial grid. The highway number, section number, direction symbol, start and end station intervals, and lateral partition identifier are combined according to a preset format to form a unique identifier for that grid, and the structured spatial code is associated with and stored in relation to the grid's spatial boundary coordinates.

[0097] Understandably, this embodiment discretizes the entire highway into a set of structured basic spatial grids by longitudinally segmenting it according to station numbers and laterally partitioning it according to functional areas. Each grid is configured with a structured spatial code that includes the highway number, section number, direction symbol, start and end station number interval, and lateral partition identifier. This improves the spatial positioning accuracy and data indexing efficiency of the grids and ensures that subsequent LOD scheduling, focus grid determination, and anchor point extraction operations can be performed at the granularity of clear engineering spatial units.

[0098] It is worth noting that, in order to maintain the spatial alignment accuracy within each grid during the entire roaming process, after the coordinate transformation and re-rendering of the visualization of the focus grid, the process also includes: responding to the virtual camera's focus moving out of the current focus grid, releasing the coordinate system transformation parameters corresponding to the current focus grid; determining the base space grid into which the virtual camera's focus falls as the new focus grid, re-extracting the transformation anchor point and solving the new coordinate system transformation parameters.

[0099] Among them, releasing refers to destroying the coordinate system transformation parameters and geometry cache corresponding to the current focus mesh from memory in order to reclaim video memory and computing resources.

[0100] Specifically, during the user's continuous panning along the highway route, the real-time position of the virtual camera's focus is monitored. When the virtual camera's focus is detected to leave the spatial range of the current focus grid and enter an adjacent base spatial grid, the coordinate system transformation parameters and geometric cache corresponding to the current focus grid are destroyed. The newly entered base spatial grid is then designated as the new focus grid. At least four transformation anchor points are extracted from the new focus grid's range. The first plane coordinates of each transformation anchor point in the geographic information system and the second plane coordinates in the engineering database are obtained. The coordinate system transformation parameters corresponding to the new focus grid are calculated, and the visualization corresponding to the new focus grid is re-rendered after coordinate transformation using the new coordinate system transformation parameters. By releasing the old parameters and recalculating the new parameters when the focus grid switches, it is ensured that all grids along the entire route always use the local transformation parameters of the current grid during the roaming process. This avoids projection distortion caused by the cumulative curvature of the earth in long-distance linear engineering and ensures the consistency of spatial alignment throughout the entire route.

[0101] In some embodiments of the present invention, after configuring structured spatial coding for each of the basic spatial grids, the method includes: associating the basic spatial grids with corresponding highway engineering objects, wherein the highway engineering objects include at least one of roadbed, pavement, bridge, culvert, slope, drainage ditch, and protective facilities; configuring a construction progress status for the highway engineering objects; and performing differentiated rendering of the corresponding basic spatial grids or highway engineering objects in the visualization screen according to the construction progress status.

[0102] Among them, highway engineering objects refer to structures or functional areas within the highway space that have independent engineering attributes and management significance. According to the type of structure, they can be divided into categories such as roadbed, pavement, bridge, culvert, slope, drainage ditch, and protective facilities.

[0103] Construction progress status refers to the stage of construction of a highway project at the current time point, including statuses such as not started, under construction, and completed.

[0104] Differentiated rendering refers to using different visual styles to draw grids or engineering objects at different construction progress stages in order to intuitively distinguish their current state.

[0105] Specifically, after completing the basic spatial grid division and structured spatial coding configuration, each basic spatial grid is traversed, and the spatial range of the grid is matched with the spatial location of various engineering objects in the highway design data to establish an association between the grid and the corresponding highway engineering object. A construction progress status identifier is configured for each highway engineering object, which can be derived from the progress reporting data in the engineering construction management database. When rendering the visual grid, the grid color blocks or engineering object models are rendered differently based on the construction progress status of the highway engineering objects associated with each basic spatial grid, using corresponding colors, transparency, or textures. For example, areas not yet started are presented as gray semi-transparent color blocks, areas under construction are presented as yellow highlighted color blocks, and completed areas are presented as green normal color blocks.

[0106] Understandably, this embodiment associates the basic spatial grid with highway engineering objects and configures the construction progress status, and renders them differently according to the construction progress in the visualization screen. This allows managers to intuitively grasp the construction progress of each section and structure of the entire highway from a macro perspective, thereby improving the engineering information carrying capacity of the visualization screen and the efficiency of construction management decision-making.

[0107] In some embodiments of the present invention, after configuring a structured spatial code for each of the basic spatial grids, the method further includes: associating the structured spatial code with the corresponding section management information, wherein the section management information includes at least one of construction section, construction unit, supervision unit, responsible personnel, planned construction time and actual construction time; and displaying the section management information corresponding to the basic spatial grid in a visualization screen in response to a user's triggering operation on any basic spatial grid.

[0108] Among them, the section management information refers to attribute data related to highway engineering construction management, which is used to describe the management entity, time plan and execution status of a specific section or spatial unit.

[0109] Triggered actions refer to interactive actions performed by users on the basic spatial grid on the visual screen, including but not limited to clicking, double-clicking, hovering, or selecting.

[0110] Specifically, after configuring the structured spatial coding, the structured spatial code of each basic spatial grid is associated with the management information of the corresponding construction section, construction unit, supervision unit, responsible personnel, planned construction time, and actual construction time, and stored in the database. When a user performs a click or hover operation on any basic spatial grid in the visualization screen, the associated section management information is queried based on the structured spatial code of that grid, and the query results are displayed in the visualization screen in the form of an information panel or a floating prompt box.

[0111] Understandably, this embodiment improves the linkage efficiency of spatial positioning and management information retrieval in long-distance highway engineering management by associating structured spatial coding with section management information and displaying it on demand in response to user interaction. This ensures that managers can directly obtain section management information corresponding to any spatial location in a three-dimensional visualization scene.

[0112] To better implement the highway spatial multimodal visualization method in this embodiment of the invention, based on the highway spatial multimodal visualization method, correspondingly, as follows: Figure 3 As shown, this embodiment of the invention also provides a highway spatial multimodal visualization device, the highway spatial multimodal visualization device 300 comprising: The first determining unit 301 is used to divide the highway space into multiple basic spatial grids and determine the field of view grid from the basic spatial grids according to the field of view of the virtual camera. The rendering unit 302 is used to determine the corresponding level of detail for each basic spatial grid in the view grid and the virtual camera based on the viewing distance between each grid and the virtual camera, and to render the visualization image according to the level of detail. The second determining unit 303 is used to determine the focus grid from the field of view grid based on the focus of the virtual camera, and extract at least four conversion anchor points within the range of the focus grid; The calculation unit 304 is used to calculate the coordinate system transformation parameters corresponding to the focal grid based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database. The visualization unit 305 is used to perform coordinate transformation on the visualization screen corresponding to the focal grid according to the coordinate system transformation parameters, and to perform fusion rendering on the two-dimensional engineering drawing, three-dimensional model, on-site positioning mark and engineering status information in the focal grid after coordinate transformation.

[0113] The highway spatial multimodal visualization device 300 provided in the above embodiments can realize the technical solutions described in the above highway spatial multimodal visualization method embodiments. The specific implementation principles of each module or unit can be found in the corresponding content in the above highway spatial multimodal visualization method embodiments, and will not be repeated here.

[0114] Accordingly, this application also provides an electronic device. This electronic device includes a processor, a memory, a display, and a communication interface.

[0115] In some embodiments, the processor may be a central processing unit (CPU), a microprocessor, or other data processing chip, used to run program code stored in memory or process data, such as the highway spatial multimodal visualization method of the present invention.

[0116] Accordingly, this application also provides a computer-readable storage medium for storing a computer-readable program or instruction. When the program or instruction is executed by a processor, it can implement the steps or functions of the highway spatial multimodal visualization method provided in the above-described method embodiments.

[0117] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware (such as a processor, controller, etc.), and the computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0118] The above provides a detailed description of the highway spatial multimodal visualization method, device, and electronic equipment provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for multimodal visualization of highway space, characterized in that, include: The highway space is divided into multiple basic spatial grids, and the field of view grid is determined from the basic spatial grids according to the field of view of the virtual camera. Based on the viewing distance between each basic spatial grid in the view grid and the virtual camera, the corresponding level of detail is determined, and the visualization is rendered according to the level of detail. Based on the focus of the virtual camera, determine the focus grid from the field of view grid, and extract at least four conversion anchor points within the range of the focus grid; Based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database, the coordinate system transformation parameters corresponding to the focal grid are calculated. Based on the coordinate system transformation parameters, the visualization screen corresponding to the focal grid is transformed by coordinate transformation, and the two-dimensional engineering drawing, three-dimensional model, on-site positioning mark and engineering status information in the focal grid after coordinate transformation are fused and rendered.

2. The highway spatial multimodal visualization method according to claim 1, characterized in that, After obtaining the coordinate system transformation parameters corresponding to the focal mesh through calculation, the method further includes: Receive geodetic coordinate data streams collected by mobile terminals; Kalman filtering is applied to the geodetic coordinate data stream to obtain a smoothed coordinate data stream; The smoothed coordinate data stream is transformed using the coordinate system transformation parameters to obtain the transformed coordinates; Starting from the transformed coordinates, project onto the rendered 3D model surface within the focal mesh to obtain the projection intersection point; The location identifier of the mobile terminal is rendered at the projection intersection.

3. The highway spatial multimodal visualization method according to claim 1, characterized in that, After re-rendering the visualization after coordinate transformation, the process also includes: When it is detected that the focal mesh renders a two-dimensional engineering drawing and a three-dimensional model, the vector contour of the two-dimensional engineering drawing and the projection contour of the corresponding highway engineering object in the three-dimensional model are extracted. Perform polygon Boolean operations on the vector contour and the projected contour to calculate the area of ​​the non-overlapping region or the boundary Hausdorff distance between the vector contour and the projected contour. Based on the area of ​​the non-overlapping region or the boundary Hausdorff distance, the deviation status or review status of the corresponding highway engineering object within the focal grid is determined, and warning rendering is performed on the region that exceeds the preset tolerance.

4. The highway spatial multimodal visualization method according to claim 1, characterized in that, The step of determining the corresponding level of detail for each grid in the view grid and the virtual camera based on their viewing distance, and rendering the visualization according to the level of detail, includes: When the viewing distance is greater than the first preset threshold, the corresponding visualization screen is rendered by scheduling two-dimensional color or route color band. The visualization screen rendered by the two-dimensional color or route color band is used to display the route direction, section range or construction progress overview. When the viewing distance is between the first preset threshold and the second preset threshold, the lightweight three-dimensional contour model is scheduled to render the corresponding visualization screen. The visualization screen rendered by the lightweight three-dimensional contour model is used to display the outline of engineering objects such as roadbed, pavement, bridge, culvert, slope, drainage facilities or protective facilities. When the viewing distance is less than the second preset threshold, the high-precision component model and engineering detail construction drawing are scheduled to render the corresponding visualization screen. The visualization screen corresponding to the high-precision component model and engineering detail construction drawing is used to display the detailed structure, construction status, quality status or responsibility information within the corresponding basic spatial grid.

5. The highway spatial multimodal visualization method according to claim 1, characterized in that, Determining the focus grid from the view grid based on the focus of the virtual camera includes: In response to a user's trigger operation on any of the base spatial grids in the field of view, the focus of the virtual camera is moved to the base spatial grid targeted by the trigger operation, and the base spatial grid targeted by the trigger operation is determined as the focus grid; or, In response to the user's panning operation on the visual screen, when the focus of the virtual camera moves into another basic spatial grid in the field of view grid, the basic spatial grid into which the focus of the virtual camera moves is determined as the focus grid.

6. The highway spatial multimodal visualization method according to claim 1, characterized in that, The step of determining the field-of-view grid from the basic spatial grid based on the field of view of the virtual camera includes: For each of the aforementioned basic spatial grids, a spatial bounding box is created, and a bounding box hierarchy tree is constructed; By performing intersection detection between the view frustum and the bounding box hierarchy tree, the basic spatial grid located within the view frustum is determined as the field of view grid.

7. The highway spatial multimodal visualization method according to claim 1, characterized in that, The coordinate system transformation parameters corresponding to the focal grid are calculated based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database, including: Based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database, a coordinate transformation equation containing a scale factor, rotation angle, and translation vector is constructed. With the goal of minimizing the sum of squared residuals at each of the transformation anchor points, the coordinate transformation equations are solved using the least squares method to obtain the coordinate system transformation parameters.

8. The highway spatial multimodal visualization method according to claim 1, characterized in that, The division of highway space into multiple basic spatial grids includes: Along the route direction of the highway space, the highway space is longitudinally segmented according to the station number, and laterally divided according to the lanes, guardrails or drainage ditches of the highway space to divide it into multiple basic spatial grids. After dividing the highway space into multiple basic spatial grids, the following is also included: Each of the basic spatial grids is configured with a structured spatial code, which includes highway number, section number, direction symbol, start and end station interval, and lateral partition identifier.

9. A multimodal visualization device for highway space, characterized in that, include: The first determining unit is used to divide the highway space into multiple basic spatial grids and determine the field-of-view grid from the basic spatial grids according to the field of view of the virtual camera. The rendering unit is used to determine the corresponding level of detail for each basic spatial grid in the view grid and the virtual camera based on their viewing distance, and to render the visualization image according to the level of detail. The second determining unit is used to determine the focus grid from the field of view grid based on the focus of the virtual camera, and extract at least four conversion anchor points within the range of the focus grid; The calculation unit is used to calculate the coordinate system transformation parameters corresponding to the focal grid based on the first plane coordinates of the transformation anchor point in the geographic information system and the second plane coordinates in the engineering database. The visualization unit is used to perform coordinate transformation on the visualization screen corresponding to the focal grid according to the coordinate system transformation parameters, and to perform fusion rendering on the two-dimensional engineering drawing, three-dimensional model, on-site positioning mark and engineering status information in the focal grid after coordinate transformation.

10. An electronic device, characterized in that, Includes communication interfaces, memory, and processors, among which, The communication interface is used to collect highway space data corresponding to the highway space. The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the highway spatial multimodal visualization method according to any one of claims 1 to 8.

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