Ground identification line automatic association adjustment method based on block division

Abstract

The invention belongs to the field of image processing, particularly relates to an automatic association adjustment method for ground identification lines based on block division, and aims to solve the problems of long updating period, potential errors and omission, high resource consumption and low efficiency. The method comprises the following steps: analyzing airport AIP vector data to generate a structured data set; and constructing a topological sub-region in each functional region according to the connection relation of the marked line end points, subdividing the grid units when the marked line density exceeds a threshold value, and outputting a layered region map. And taking the area / grid unit as a detection unit, detecting new and old AIP change areas and position identifiers, and generating new version change area data. Recursively searching an N-degree correlation line by taking the change area as a starting point, and only updating the correlation line of geometric, type or topological connection change. Finally, the changed data and the unchanged data are spliced, and a complete airport model is generated through boundary adaptive extension cutting and global topology reconstruction. According to the method, efficient and accurate updating of the airport ground identifier is realized.

Description

Technical Field

[0001] The invention belongs to the technical field of image processing, and in particular relates to an automatic association adjustment method for ground marking lines based on block division. Background Art

[0002] With the rapid growth of civil aviation, airports around the world are constantly expanding and adapting to accommodate the growing demand for air traffic. These changes often involve runway extensions, additional taxiways, apron expansions, and terminal facility upgrades. To ensure flight safety, pilots must familiarize themselves with the operating procedures and environments of various airports through simulator training. Therefore, the airport models in simulator training systems must be consistent with the latest layouts of actual airports.

[0003] Currently, after physical changes are made to an airport, the airport model in the simulator training system must be updated accordingly. This process is typically performed by professional developers based on official change documentation and other relevant information provided by the airport. Specifically, this involves the following steps: Data collection: Developers need to obtain all relevant change documents from the airport management, including airport layout drawings, runway data, parking space configurations, taxi routes, etc.

[0004] Analysis and Planning: Conduct detailed analysis of all received change documents to determine which parts need to be modified in the simulator training system.

[0005] Manual adjustments: Based on the analysis results, developers need to manually modify the airport model in the simulator training system, which may involve adjusting the position, shape, and size of elements such as runways, taxiways, and parking spaces in the simulation environment.

[0006] Verification testing: After completing the model adjustments, a series of verification tests are required to ensure that the updated airport model can accurately reflect the actual situation without omissions or errors.

[0007] Although this manual method can update the airport model, it has the following significant problems: Long update cycles: Due to the need to collect and review a large amount of change documents, as well as to conduct detailed analysis and planning, the time interval between airport changes and simulator model updates is often long.

[0008] Potential errors and omissions: Even experienced developers can make mistakes when dealing with large amounts of change information, especially when large-scale changes are taking place at an airport.

[0009] High resource consumption: Each update requires a large amount of manpower and material resources, which not only increases operating costs but also may increase the pressure on resource allocation due to frequent changes.

[0010] Inefficiency: The manual update process is inefficient, especially when changes are made to multiple airports simultaneously. This can lead to update delays and affect the quality of pilot training.

[0011] Based on this, the present invention proposes a method for automatic association adjustment of ground marking lines based on block division. Summary of the Invention

[0012] In order to solve the above-mentioned problems in the prior art, namely, long update cycle, potential errors and omissions, high resource consumption and low efficiency, the present invention provides a method for automatic association adjustment of ground marking lines based on block division, which comprises: Parse the vector graphics data in the latest airport regulations AIP diagram, extract the geometric coordinates, line types and topological connection relationships of all ground marking lines, and generate a structured marking dataset; The airport is divided into multiple functional areas based on preset functional area types. Within each functional area, topological sub-areas are constructed based on the connection relationship between the marking endpoints. When the marking density of a sub-area exceeds a threshold, it is subdivided into grid unit areas with a dynamic grid size and output as a hierarchical regional map, recording the regional boundaries, hierarchical relationships, and the set of marking identifiers included. Using the sub-regions and / or grid unit areas in the hierarchical regional map as detection units, for each detection unit, detecting the changed areas between the new and old versions of the AIP and their location identifiers in the hierarchical regional map by comparing the marking coverage and matching the feature points, and generating new version marking data for the markings in the changed areas based on the structured marking dataset; Based on the topological connection relationship recorded in the hierarchical area map, recursively search for N-degree association lines starting from the changed area, and only update the association lines with changed geometric attributes or connection relationships; The changed area data is spliced ​​with the unchanged area data, and a complete airport model is generated through boundary consistency verification and global topology reconstruction.

[0013] Furthermore, in each functional area, a topological sub-area is constructed based on the connection relationship of the marked line endpoints. The method is as follows: When the Euclidean distance between the endpoints of two marking lines is less than the spatial tolerance threshold, it is determined that the endpoints coincide, and the two marking lines are classified into the same topological sub-region.

[0014] Furthermore, when the line density of the sub-area exceeds a threshold, the sub-area is subdivided into grid unit areas with a dynamic grid size, specifically including: When the total length of the marking lines per unit area in a sub-region exceeds a preset density threshold, the grid unit side length is adjusted according to the degree of spatial dispersion of the marking line endpoints within the sub-region; the more dispersed the endpoint distribution, the larger the grid size, and the more concentrated the distribution, the smaller the grid size; The sub-region is divided into equal-sized rectangular grid cell regions based on the calculated grid size.

[0015] Furthermore, the grid unit side length is adjusted according to the degree of spatial distribution dispersion of the marking line endpoints in the sub-region. The method is as follows: Identify the longest continuous marking line in the sub-area as a reference marking line, and use the length of the reference marking line as a grid reference size; If a group of mutually parallel marking lines exists within the sub-area, the grid cells are extended along the direction of the marking line group to form a rectangular grid with a long side parallel to the marking line direction and a length twice the grid reference size, and a short side equal to the grid reference size; wherein the mutually parallel marking line group is a group of marking lines with more than three marking lines and the angle between any two marking lines is less than a preset degree; If there is no dominant direction of the marking lines in the sub-area, a square grid with a side length equal to the grid reference size is generated.

[0016] Furthermore, for each detection unit, the changed areas between the new and old versions of the AIP and their location identification in the layered area map are detected by comparing the coverage of the markings and matching the feature points. The method is as follows: Calculate the absolute difference in the total length of the new and old versions of the marking line within the detection unit. If the difference exceeds the length tolerance threshold, mark it as a preliminary screening change area; Extract the endpoints and intersections of all marking lines in the initial screening change area as feature points; Perform bidirectional matching on the coordinates of the feature points of the new and old versions. If the proportion of unmatched feature points exceeds the feature point tolerance threshold, the area is output as the final changed area and its hierarchical position identifier in the hierarchical area map.

[0017] Furthermore, the two-way matching includes forward matching and reverse matching: The forward matching includes searching for the nearest neighbor feature point within a preset radius in the new version for each feature point in the old version; The reverse matching includes searching for the nearest neighbor feature point within a preset radius in the old version for each feature point in the new version; A match is considered successful only when the feature points are nearest neighbors to each other in both forward and reverse matching.

[0018] Furthermore, based on the topological connection relationship recorded in the hierarchical area map, recursively search for N-degree association lines starting from the changed area, and only update the association lines with changed geometric attributes or connection relationships. The method is as follows: Taking each marking line in the change area as the starting point, recursively search for all marking lines that are directly connected to it as 1-degree associated lines; Continue searching for lines that have direct endpoint connections with the 1st-degree correlation line as 2nd-degree correlation lines until the Nth-degree correlation line search is complete, where N is a preset recursive depth, which is pre-set based on the airport area type. A direct endpoint connection means that the endpoint coordinates of the two lines coincide within the spatial tolerance range, and their topological connection relationship is recorded in the layered area map. For each line in the associated line set, execute: Compare the geometric coordinate sequences, line types, and topological connection object identifiers between the new and old versions; If the geometric coordinate deviation exceeds the coordinate tolerance, the line type changes, or the topological connection object identifiers are inconsistent, data reconstruction is performed.

[0019] Furthermore, the data reconstruction includes: When the geometric coordinate deviation exceeds the coordinate tolerance, the old coordinates are overwritten with the new coordinates; When the line type changes, update the type identifier and record the change version number; When the topological connection object identifiers are inconsistent, the topological connection relationship is reconstructed and the boundary marking identifier set of the associated area is updated.

[0020] Furthermore, the changed area data is spliced ​​with the unchanged area data, and a complete airport model is generated through boundary consistency verification and global topology reconstruction. The method is as follows: The new version of the changed area data and the old version of the unchanged area data are spatially superimposed according to the geographic coordinate system, and the endpoints of the marking lines of the adjacent areas are aligned based on the boundary of the changed area; Detect markings that cross the boundary of the changed area. If the endpoint coordinates of the markings that cross the boundary of the changed area deviate from those in the adjacent area, automatically extend or crop the markings in the adjacent area to the matching coordinates based on the changed area data. The criteria for determining the endpoint coordinate deviation are: The Euclidean distance between the endpoints of the marking lines with the same identifier is greater than the coordinate matching threshold; Or there are unclosed endpoints of the marking line at the boundary of adjacent areas; A global topology connection table is generated based on the endpoint connection relationship of all markings, and it is verified that there are no isolated marking segments or unclosed areas in the topology connection table. The global topology connection table includes at least: a unique identifier for each marking, the coordinates of the starting and ending endpoints of the marking, a set of connected adjacent marking identifiers, and the functional area and sub-area codes to which they belong.

[0021] Furthermore, when the endpoint of the changed area marking line exceeds the boundary of the adjacent area, the adjacent area marking line is extended to the coordinates of the endpoint; When the adjacent area markings overlap with the changed area markings after extension, the overlapping parts are clipped and the topological connection is updated; Recalculate the geometric coordinate sequence for extended or cropped lines.

[0022] Beneficial effects of the present invention: This invention replaces manual data collection and analysis by directly parsing AIP vector graphics data and generating a structured marking dataset. It dynamically constructs gridded sub-areas based on functional area types and records topological relationships, providing a structured map for change detection. This eliminates the time bottleneck of manual document processing, enabling rapid response from airport changes to model updates, and ensuring real-time synchronization between the training system and the real scene.

[0023] Detection accuracy is improved by collaboratively verifying changed areas using line coverage comparison and feature point matching. A layered regional map clearly records the connections between line markings, preventing topological breaks during manual updates. This algorithm automatically identifies changed areas and associated lines, avoiding model deviations caused by human oversight and ensuring the geometric and topological integrity of the updated results.

[0024] This method recursively updates N-degree association lines based on topological connections, starting only from the changed area, avoiding full model reconstruction. A splicing mechanism preserves data in unchanged areas, reducing duplicate calculations. This significantly saves computing resources and manpower, making it particularly suitable for concurrent updates across multiple airports and significantly reducing long-term operation and maintenance costs.

[0025] This method automatically refines grid cells in areas with high-density markings, ensuring update accuracy in critical areas such as runway intersections. It also automatically verifies boundary continuity during splicing and repairs potential gaps. This approach is suitable for large-scale airport expansion scenarios (such as adding taxiways and aprons), ensuring model accuracy in highly complex areas.

[0026] After updating, this system automatically rebuilds the entire airport topology network and verifies the logical consistency of taxi routes. Automated processing based on authoritative AIP data eliminates manual transcription errors. This ensures the simulator environment is strictly consistent with the geometry, topology, and operating rules of the actual airport, providing pilots with a highly reliable training environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Other features, objects and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 It is a flow chart of a method for automatically adjusting the association of ground marking lines based on block division according to the present invention. DETAILED DESCRIPTION

[0028] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0029] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0030] The present invention provides a method for automatically adjusting the association of ground marking lines based on block division, the method comprising the following steps: Step S10: parsing the vector graphics data in the latest airport regulations AIP map, extracting the geometric coordinates, line types, and topological connection relationships of all ground marking lines, and generating a structured marking dataset; Step S20: Divide the airport into multiple functional areas based on preset functional area types. Within each functional area, construct topological sub-areas based on the connection relationship between the marking endpoints. When the marking density of a sub-area exceeds a threshold, subdivide it into grid unit areas with a dynamic grid size, and output a hierarchical regional map that records the regional boundaries, hierarchical relationships, and the set of marking identifiers contained therein. Step S30: Using the sub-regions and / or grid unit regions in the hierarchical regional map as detection units, for each detection unit, detecting the changed regions between the new and old versions of the AIP and their position identifications in the hierarchical regional map by comparing the coverage of the markings and matching the feature points, and generating new version marking data for the markings in the changed regions based on the structured marking dataset; Step S40, based on the topological connection relationship recorded in the hierarchical area map, recursively search for N-degree association lines starting from the changed area, and only update the association lines with changed geometric attributes or connection relationships; Step S50: splicing the changed area data with the unchanged area data, and generating a complete airport model through boundary consistency verification and global topology reconstruction.

[0031] In order to more clearly illustrate the automatic correlation adjustment method of ground marking lines based on block division of the present invention, the following is combined with Figure 1 Each step in the embodiment of the present invention is described in detail.

[0032] A first embodiment of the present invention provides a method for automatically adjusting the association of ground marking lines based on block division, including steps S10 to S50, each of which is described in detail as follows: Step S10: parsing the vector graphics data in the latest airport regulations AIP map, extracting the geometric coordinates, line types, and topological connection relationships of all ground marking lines, and generating a structured marking dataset; In step S10 of this embodiment, when parsing the vector graphics data in the latest airport regulations AIP diagram, a processing method based on complete line segments is adopted to generate a structured line marking dataset.

[0033] The specific implementation process is as follows: first, use the GIS processing engine to read the vector graphics file in DXF or SHP format, and filter out all layer features representing ground identification lines; for these line features, process them as a whole according to the original line segment entities instead of splitting them into discrete points, retaining the complete geometric shape of each identification line.

[0034] When extracting geometric coordinates, the ordered vertex sequence of each line segment is directly obtained as a continuous coordinate string, and the corresponding line type attributes (such as runway edge, taxiway centerline, etc.) are recorded. Topological connectivity is established by automatically identifying the spatial proximity of line segment endpoints: when the distance between the endpoints of different line segments is less than a preset tolerance threshold (usually 0.1 meters), they are merged into the same topological node and each node is assigned a unique identifier; The result is a structured dataset consisting of three core components: a line feature set that records the complete geometric coordinates and types of all line segments, a topological node table that stores node locations and connectivity, and a connection mapping table that clearly defines the correspondence between the start and end nodes of each line segment. This entire process ensures that each ground-marking line is stored as a complete line entity, its geometric representation remains intact, and the topological connectivity between lines is explicitly maintained.

[0035] Step S20: Divide the airport into multiple functional areas based on preset functional area types. Within each functional area, construct topological sub-areas based on the connection relationship between the marking endpoints. When the marking density of a sub-area exceeds a threshold, subdivide it into grid unit areas with a dynamic grid size, and output a hierarchical regional map that records the regional boundaries, hierarchical relationships, and the set of marking identifiers contained therein. In this embodiment, in each functional area, a topological sub-area is constructed based on the connection relationship between the marked line endpoints, and the method is as follows: When the Euclidean distance between the endpoints of two marking lines is less than the spatial tolerance threshold, it is determined that the endpoints coincide, and the two marking lines are classified into the same topological sub-region.

[0036] Specifically, the airport is first divided into multiple functional zones based on the preset types of airport functional zones. Within each functional zone, topological sub-regions are constructed based on the endpoint connectivity of ground marking lines. When the Euclidean distance between the endpoints of two marking lines is less than a preset spatial tolerance threshold, the endpoints are considered to overlap and the two marking lines are assigned to the same topological sub-region, until all connected marking lines are divided into independent sub-regions.

[0037] In this embodiment, the preset airport functional area type is divided based on the standard airport planning practice of the International Civil Aviation Organization (ICAO) and the International Air Transport Association (IATA), and generally includes core functional areas such as the runway area (RWY), taxiway area (TWY), apron area (APN), stand area (STD), maintenance area (MTN), and vehicle service area (VSA). The system automatically divides the entire airport digitized vector graphic data into these different functional area categories according to the preset rules (such as geographic range and main functional features).

[0038] In each divided functional area, the system begins to construct topological sub-areas according to the connection relationship between the marking endpoints. The specific method of construction is as follows: the system calculates the Euclidean distance between the endpoints of any two ground marking lines in the functional area, and compares the distance with a preset spatial tolerance threshold. The tolerance threshold is usually set according to the drawing accuracy and actual engineering requirements, and a typical value is 0.1 meters or 0.3 feet. In this embodiment, the preferred value is 0.1 feet; When the distance between the endpoints of two marking lines is less than or equal to the threshold, the system determines that the two endpoints are coincident in spatial position, and the two marking lines are grouped into the same topological sub-area. The system gradually aggregates all marking lines that are spatially connected together based on the endpoint coincidence determination principle by traversing all marking lines and their endpoints in the functional area, and finally forms several topological sub-areas that are not overlapped in space and are topologically connected internally.

[0039] The dynamic grid size is subdivided into grid cell areas when the sub-area marking line density exceeds the threshold, which specifically includes: When the total length of marking lines per unit area in the sub-area exceeds the preset density threshold, the grid cell edge length is adjusted according to the spatial distribution dispersion degree of the marking line endpoints in the sub-area. The more dispersed the endpoint distribution, the larger the grid size, and the more concentrated the distribution, the smaller the grid size. The sub-area is divided into equal rectangular grid cell areas based on the calculated grid size.

[0040] In this embodiment, after completing the sub-area division, the system will evaluate the marking line density of each topological sub-area. The basis for evaluation is to calculate the total length of marking lines per unit area in the sub-area, for example, the total length of marking lines divided by the area of the sub-area, with units of meters per square meter or feet per square foot. The system compares the calculated density value with the preset density threshold. The density threshold is set according to the type of functional area and the actual scene, for example, in a taxiway waiting area with dense markings or a complex apron area, the typical threshold is set to 5 m2, while in an open runway area or maintenance area, it can be set to 3 m2; If the marking density of a certain sub-area exceeds the preset density threshold of its corresponding functional area, it indicates that the marking in this area is too dense, and more detailed grid division is needed to detect changes more accurately subsequently.

[0041] For the over-dense sub-area that needs grid subdivision, the system adopts a dynamic grid size strategy for division. The actual size of the grid cell, i.e. the side length, is not fixed, but is dynamically determined by the spatial distribution dispersion of all marking endpoints in the sub-area (usually calculated based on the standard deviation of endpoint coordinates). The specific rule is: the more dispersed the endpoint distribution, i.e. the greater the spatial variability, the larger the grid cell size used; the more concentrated the endpoint distribution, i.e. the smaller the spatial variability, the smaller the grid cell size used. The dynamic adjustment formula can be designed as: grid size reference value = basic size + K x endpoint position standard deviation, where the basic size is the initial reference value, which is set to 1 meter in this embodiment, and K is a preset adjustment coefficient. This is done to use smaller grids in places where markings are dense and distributed concentratedly (such as complex intersections) to improve accuracy, and use slightly larger grids in places where markings are relatively sparse or distributed scatteredly to improve efficiency.

[0042] When calculating the grid cell side length, the system first identifies the longest continuous marking in the current over-dense sub-area, which is usually the longest taxiway centerline or guide line, and takes the actual length value of this reference marking as the basic grid reference size for grid division.

[0043] The grid cell side length is adjusted according to the spatial distribution dispersion of the marking endpoints in the sub-area, and the method is: Identify the longest continuous marking in the sub-area as the reference marking, and take the length of the reference marking as the grid reference size; If there are groups of parallel markings in the sub-area, extend the grid cell along the direction of the marking group to form a rectangular grid with the long side parallel to the marking direction and the length twice the grid reference size, and the short side equal to the grid reference size; wherein the group of parallel markings is a set of markings with more than three markings and the included angle between any two markings is less than a preset degree; If there is no dominant direction of the marking direction in the sub-area, generate a square grid with a side length equal to the grid reference size.

[0044] In this embodiment, the specific shape of the grid cell is determined according to the overall characteristics of the marking direction in the sub-area, including the following two cases: Case 1: Existence of a dominant parallel direction: The system analyzes whether there exists a group of three or more lines in the sub-region, and the angle between any two lines in the group is less than a preset parallel angle threshold, i.e., a dominant parallel line set, such as a row of parking stand guide lines or parallel taxiway boundary lines. If such a dominant parallel group exists, the system automatically determines the main direction of the group of lines. Then, the system extends the grid cells along this dominant direction. The generated grid cells are no longer square, but rectangular. The long side is strictly parallel to the direction of the dominant line group, and the length is set to twice the reference size; the short side remains equal to the reference size. This forms a long strip-shaped grid cell that is more consistent with the geometric characteristics of the taxiway or parking apron parallel line bundle.

[0045] In this embodiment, the parallel angle threshold is preferably 15 degrees.

[0046] Case 2: No dominant direction (direction is chaotic): If the direction of the lines in the sub-region is very chaotic and no group of lines can be found that meets the parallel determination condition, i.e., there is no dominant direction, then the system directly uses a square grid for division. Each grid cell generated is a square, and the side length is uniformly set to the value of the reference size.

[0047] In this embodiment, regardless of the shape (rectangular or square) used, the system ultimately uniformly divides the original over-dense topological sub-region into multiple grid cell regions of equal size based on the dynamically calculated grid size (long and short sides for rectangular, side length for square). All grid cells collectively cover the range of the original sub-region. The system constructs and outputs a hierarchical regional map containing information about these functional areas, topological sub-regions, and grid cells (if present). This map clearly records the geometric boundaries of the regions, the hierarchical inclusion relationship between the regions (such as a functional area containing multiple sub-regions, and a sub-region being subdivided into multiple grid cells), and the unique identifier set of ground marking lines contained within each region (functional area, sub-region, grid cell). This hierarchical structure is the basis for subsequent change detection, correlation adjustment, and model reconstruction.

[0048] The present embodiment also proposes a third case, i.e., when there are three or more line endpoints within a radius R of a certain endpoint, the corresponding endpoint is marked as a crosspoint core; a sub-grid cell with a side length of half the grid reference size is created centered on the crosspoint core; where the radius R is the minimum turning radius in the airport design specification; If two grid cells contain consecutive line segments of the same line, they are merged into a single grid cell; If the sub-grid cell overlaps with the main grid cell boundary, it is integrated into a continuous polygon detection area.

[0049] In this embodiment, if the system detects that there are three or more other marking endpoints within the circular neighborhood of a certain endpoint with radius R, i.e. the spatial density is high, it is determined that this endpoint is a critical geometric feature point, i.e. a crossing point core.

[0050] The value of radius R here is strictly determined by the minimum turning radius of the aircraft in the airport design specification; the specific value is selected according to the airport grade and the applicable aircraft type, for example, according to the ICAO specification, the minimum turning radius of the runway link for E-class aircraft such as B747 is usually 60 meters, and for C-class aircraft such as A320 it is 25 meters. The definition of this radius R ensures that the processing of the intersection area conforms to the actual requirements of the ground operation of the aircraft.

[0051] After identifying the crossing point core, the system immediately creates a higher-precision local grid in the surrounding area of the point. The creation rule is: taking the coordinate point of the crossing point core as the center, a new sub-grid unit is constructed. The shape of this sub-grid unit is a square, and its side length is explicitly specified as half of the grid reference size used in the atomic area grid division. The design of such a sub-grid can provide finer spatial division near high-density crossing points.

[0052] In the grid merging optimization link, the system analyzes the geometric relationship between the grid units and the markings: if it is found that two adjacent or neighboring grid units (whether main grid or sub-grid) jointly contain the continuous line segment of the same ground marking line (i.e. the marking passes through these two units without interruption), it is determined that this separation state may split the continuity of the marking. In order to maintain the topological integrity, the system will automatically merge these two grid units into a single larger grid unit. This merging operation ensures that a single continuous marking exists inside the detection unit, avoiding artificial segmentation caused by grid boundaries.

[0053] After generating all levels of grids (main grid and sub-grid), the system detects the spatial relationship between the boundaries of the grid units: if it is found that the physical boundaries of the sub-grid units created to process the crossing points overlap or are adjacent to the boundaries of the main grid units to which they belong (i.e. spatially connected or partially overlapping), the system will not retain multiple small units that are independent of each other. On the contrary, the system will integrate them into a single continuous polygonal area with coherent boundaries, which is a non-rectangular, complex polygonal area. This integrated area serves as a new, unified "detection area" unit participating in the subsequent change detection step, thereby eliminating unnecessary artificial boundaries between small grid units and ensuring the consistency and integrity of adjacent change area identification.

[0054] Step S30, taking the sub-regions and / or grid cell regions in the hierarchical regional map as detection units, detecting the changed regions between the new and old versions of AIP and their position identifiers in the hierarchical regional map by matching the feature points in the new and old versions of AIP through the line coverage ratio, and generating new version of the lines in the changed regions based on the structured line data set; In this embodiment, the changed regions between the new and old versions of AIP and their position identifiers in the hierarchical regional map are detected by matching the feature points in the new and old versions of AIP through the line coverage ratio, and the method is as follows: The absolute difference of the total length of the new and old version lines in the detection unit is calculated, and if the difference exceeds the length tolerance threshold, the detection unit is marked as a preliminary screening changed region; The endpoints and intersection points of all lines in the preliminary screening changed region are extracted as feature points; The new and old version feature point coordinates are bidirectionally matched, and if the proportion of unmatched feature points exceeds the feature point tolerance threshold, the region is output as a final changed region and its hierarchical position identifier in the hierarchical regional map.

[0055] In this embodiment, the system takes the topological sub-regions (when not too dense), the subdivided grid cell regions (after the over-dense sub-region division), or the continuous polygon detection regions for intersection points (after the sub-grid integration) recorded in the hierarchical regional map as the basic detection units. For each detection unit in the new and old versions of the airport specification (AIP) map, a two-step strict comparison is performed to identify the changed position.

[0056] First, the line coverage preliminary screening is performed: the absolute difference of the total length of all ground marking lines in the same detection unit in the new and old versions of AIP is calculated, the length unit is unified to meters or feet, and the difference is compared with the preset length tolerance threshold, which is determined according to the actual maintenance standard of the airport and the drawing accuracy of AIP, and is usually set to 1.5 to 2 times the design accuracy of the line, for example: 0.45 meters. If the absolute difference exceeds the threshold, it is determined that there is a significant line change in the detection unit, which is marked as a preliminary screening changed region. This step is used to quickly exclude a large number of unchanged regions and improve the efficiency of subsequent processing.

[0057] For each marked preliminary screening changed region, the system performs more detailed geometric feature matching analysis. The system extracts the endpoints (line start / end points) and intersection points (geometric points formed by intersecting lines) of all lines in the old version of AIP in the region as the old version feature point set. At the same time, the endpoints and intersection points of the new version of AIP in the corresponding position are extracted to form the new version feature point set. The type of feature points (endpoints / intersection points) and their unique coordinates in space are the key basis for matching.

[0058] The bidirectional matching includes forward matching and reverse matching: The forward matching includes searching for the nearest neighbor feature point within a preset radius in the new version for each feature point in the old version; The reverse matching includes searching for the nearest neighbor feature point within a preset radius in the old version for each feature point in the new version; Only when the feature points are the nearest neighbors of each other in the forward matching and the reverse matching, it is determined that the matching is successful.

[0059] In the embodiment, in the forward matching, each point in the old version feature point set is searched for the nearest neighbor feature point in the new version feature point set within a preset search radius (usually 0.15 meters) circular neighborhood with the coordinates as the center. If there is a unique nearest neighbor point and the distance is within the search radius, the point pair is recorded as a “forward candidate matching point pair”.

[0060] In the reverse matching, each point in the new version feature point set is searched for the nearest neighbor feature point in the old version feature point set within a preset search radius (0.15 meters) neighborhood with the coordinates as the center. If there is a unique nearest neighbor point and the distance is within the search radius, the point pair is recorded as a “reverse candidate matching point pair”.

[0061] The matching determination adopts the mutual reverse nearest neighbor principle: a point pair is only determined to be a successful matching when the following conditions are met: The point pair is identified as a candidate matching point pair in the forward matching (i.e., the old version point A points to the new version point B); And the point pair is also identified as a candidate matching point pair in the reverse matching (i.e., the new version point B points to the old version point A, and they are the unique nearest neighbors of each other).

[0062] After all the feature point matching operations are completed, the system calculates the proportion of the number of feature points in the preliminary screening changed region that fail to be successfully matched to the total number of feature points (the total number of feature points in the old and new versions). If the proportion exceeds a preset feature point tolerance threshold, which is usually set to 15% of the total number of feature points, the data quality can be adjusted according to the invention, which is not limited, it is determined that there is indeed a non-negligible geometric change in the preliminary screening changed region, and finally outputs the region as a “final changed region” and accurately records its position identifier in the hierarchical region map structure, including: the type of the functional area, the atomic region or the grid unit ID, its row and column index in the hierarchical map, etc.

[0063] For the final changed region confirmed to be changed, the system directly extracts all the marking information corresponding to the new version AIP vector data in the region based on the structured marking data set, including but not limited to geometric coordinates, line type, width, color, attribute, etc., to generate a new version marking data set corresponding to the region for subsequent associated updating. At the same time, the position identifier of the region will be written into the change record list.

[0064] Step S40, based on the topological connection relationship recorded in the hierarchical area map, recursively search for N-degree association lines starting from the changed area, and only update the association lines with changed geometric attributes or connection relationships; In this embodiment, based on the topological connection relationship recorded in the hierarchical area map, recursively search for N-degree association lines starting from the changed area, and only update the association lines with changed geometric attributes or connection relationships. The method is as follows: Taking each marking line in the change area as the starting point, recursively search for all marking lines that are directly connected to it as 1-degree associated lines; Continue searching for lines that have direct endpoint connections with the 1st-degree correlation line as 2nd-degree correlation lines until the Nth-degree correlation line search is complete, where N is a preset recursive depth, which is pre-set based on the airport area type. A direct endpoint connection means that the endpoint coordinates of the two lines coincide within the spatial tolerance range, and their topological connection relationship is recorded in the layered area map. For each line in the associated line set, execute: Compare the geometric coordinate sequences, line types, and topological connection object identifiers between the new and old versions; If the geometric coordinate deviation exceeds the coordinate tolerance, the line type changes, or the topological connection object identifiers are inconsistent, data reconstruction is performed.

[0065] In this embodiment, the system takes the final changed area identified in the hierarchical area map as the starting point, and starts the recursive search process of the N-degree association line based on the topological connection relationship of the marking lines recorded in the map, that is, the network relationship formed by the endpoint connection between the marking lines.

[0066] First, for each changed line within the changed area, the system considers it as the initial search node. The first-degree connection line search rule is to recursively search for all other lines that have direct endpoint connections to the line in question, i.e., lines connected by endpoints with overlapping coordinates. The specific connection determination follows the criteria from step S20: if the Euclidean distance between the endpoints of two lines is ≤ the preset spatial tolerance threshold (standard value 0.1 meter) and their topological relationship is annotated in the layered map, then the connection is considered direct.

[0067] After completing the 1st degree associated line search, the system continues to perform the Kth degree (K=2 to N) associated line search: the associated lines found in the previous order (K-1 degree) are used as the new starting point, and all other markings that have direct endpoint connections with these lines are recursively searched, and the marked lines are excluded. This process is executed in a loop until the preset recursive depth N is reached. The value of the recursive depth parameter N is dynamically determined by the type of airport functional area. For example, in this embodiment, the taxiway area (TWY) with high complexity requires deep detection, and N=3 is set; the relatively simple runway area (RWY) or apron (APN) is set to N=2; and the open area can be N=1. The system finally outputs a set of associated lines consisting of the lines in the changed area and all their N-degree associated lines. The set contains all K=1 to N-order associated lines.

[0068] After obtaining a complete set of associated lines, the system performs a comparative analysis of the old and new versions of each associated line in the set, and only updates the lines that have actually changed. The specific comparison dimensions include: Geometric coordinate sequence: Compare the node coordinate sequence of the marking line in the new version with that in the old version. If the coordinate displacement deviation between any corresponding nodes exceeds the geometric coordinate tolerance threshold (this threshold is stricter than the spatial tolerance and is usually set to 0.05 meters), it is considered a geometric change. Line type: Check whether the type attributes of the marking lines in the new and old versions (such as taxiway center line, parking stand guide line, runway edge line, etc.) are consistent; Topological connection object identifiers: Verify whether the set of adjacent line IDs connected by the line in the old version completely matches the new version (that is, the connected line objects are not added, deleted, or replaced).

[0069] The data reconstruction includes: When the geometric coordinate deviation exceeds the coordinate tolerance, the old coordinates are overwritten with the new coordinates; When the line type changes, update the type identifier and record the change version number; When the topological connection object identifiers are inconsistent, the topological connection relationship is reconstructed and the boundary marking identifier set of the associated area is updated.

[0070] Specifically, if the geometric coordinate deviation exceeds the standard: the system directly overwrites the old version coordinate data with the precise coordinate sequence in the new version AIP data, retaining the historical version number mark; If the line type changes: the system updates the type identifier attribute of the line marking and records the change version number and timestamp in the metadata (e.g., TYPE_UPDATE:AIP_2025); If the topological connection object identifiers are inconsistent (e.g., the connection point disappears, a new branch is added, or reconnection occurs): the system reconstructs the topological connection relationship of the marking line and the associated marking line (e.g., deletes the old connection relationship, establishes a new connection edge), and synchronously updates the boundary marking line identifier set (e.g., the boundary line ID list associated with the grid unit) of all affected areas in the hierarchical area map, to ensure that the area boundary description is consistent with the actual geometry.

[0071] The present application only performs update operations on the associated marking lines of the three types of attributes mentioned above that have changed, and the associated lines that have not detected changes (i.e., the geometry / type / connection are consistent) remain unchanged, thereby minimizing unnecessary processing. The reconstructed marking line data and topological relationship will be passed to the subsequent stitching process.

[0072] In step S50, the changed area data and the unchanged area data are stitched to generate a complete airport model through boundary consistency verification and global topological reconstruction.

[0073] In this embodiment, the changed area data and the unchanged area data are stitched to generate a complete airport model through boundary consistency verification and global topological reconstruction, and the method is as follows: The new version of the changed area data and the old version of the unchanged area data are spatially overlapped according to the geographic coordinate system, and the marking line endpoints of the adjacent areas are aligned according to the changed area boundary as the reference; The marking lines that cross the changed area boundary are detected, and if the endpoint coordinates of the marking lines that cross the changed area boundary have deviations in the adjacent areas, the marking lines of the adjacent areas are automatically extended or trimmed to match the coordinates according to the changed area data as the reference. The determination condition of the endpoint coordinate deviation is: The Euclidean distance between the endpoints of the marking lines with the same identifier is greater than the coordinate matching threshold; Or there are unclosed marking line endpoints at the boundary of the adjacent areas; A global topological connection table is generated based on the endpoint connection relationship of all marking lines to verify that there are no isolated marking line segments or unclosed areas in the topological connection table. The global topological connection table at least includes: the unique identifier of each marking line, the start and end endpoint coordinates of the marking line, the set of adjacent marking line identifiers connected, the functional area and sub-area code to which it belongs.

[0074] In this embodiment, the new version of the changed area data (including the updated marking line geometry and topological properties) output in step S40 and the old version of the data of other unchanged areas of the airport are spatially overlapped according to a unified geographic coordinate system (e.g., WGS-84 UTM). In this process, the system takes the polygon boundary of the changed area as the reference line to calibrate the coordinates of the marking lines on the boundary of the adjacent unchanged areas. The specific method is to identify all the cross-boundary marking lines (i.e., the same marking line is distributed in the changed area and the adjacent area), and forcibly align the endpoint coordinates of the marking lines on the side of the adjacent area to the endpoint coordinates on the side of the changed area.

[0075] The system then checks for boundary consistency conflicts. For each line that crosses the boundary of a changed area (i.e., partly within the changed area and partly within the adjacent unchanged area), if any of the following conditions are detected, it is considered a boundary mismatch and triggers adaptive processing: Coordinate tolerance exceeded: The Euclidean distance between the endpoint coordinates of the same line identifier on both sides of the boundary is greater than the coordinate matching threshold (this threshold is looser than the geometric tolerance and is usually set to 0.2 meters to tolerate stitching errors); Unclosed endpoints: There are unconnected objects at the endpoints of the marking lines at the region boundary (for example, the marking line that should be connected to the endpoint of the changed region is missing on the adjacent region side), resulting in holes or discontinuities in the boundary.

[0076] When the endpoint of the changed area marking line exceeds the boundary of the adjacent area, the adjacent area marking line is extended to the coordinates of the endpoint; When the adjacent area markings overlap with the changed area markings after extension, the overlapping parts are clipped and the topological connection is updated; Recalculate the geometric coordinate sequence for extended or clipped lines.

[0077] Specifically, during the extension operation, if the coordinates of the endpoint of a side marking in the changed area exceed the boundary of an adjacent unchanged area (i.e., the point is within the adjacent area), the system will automatically extend the nearest associated marking in the adjacent area to extend its geometric path to the coordinates of the endpoint of the changed area. This extension uses a linear interpolation algorithm to generate new nodes to ensure a smooth path.

[0078] Trimming: If the extended adjacent area's markings partially overlap with the modified area's markings (overlap distance > tolerance), the system trims the overlapping segments (usually retaining the modified area data) and generates new endpoints at the trimming points. After trimming, the geometric coordinate sequence for the markings is recalculated to remove redundant nodes.

[0079] Topology update: For markings that are geometrically deformed after extension or cropping, the system synchronously updates their topological connection relationships: delete or add connections with adjacent markings, and write the changes to the boundary marking identifier set of the area to which the marking belongs in the layered area map (such as adding a newly generated extension line segment ID to the boundary of the taxiway sub-area).

[0080] After completing all boundary consistency processing, the system initiates global topology reconstruction: scanning the endpoint coordinates of all markings in the entire airport model (including changed and unchanged areas), reconstructing the topological connection network based on a unified spatial tolerance threshold (0.1 meters), and generating a complete global topological connection table. The core fields of this table include: Field describe Line_ID Unique marking identifier Start_Point <origin coordinates (x1, y1)> End_Point endpoint coordinates (x2, y2) Connected_Lines The ID set of adjacent marking lines connected directly to the endpoints Function_Zone Functional area code (such as RWY_01) Sub_Region_ID Sub-region or grid cell code Perform a topology integrity check on this table to ensure: No isolated marking: Each marking set contains at least one adjacent ID (except for special end points such as runway threshold markings); No unclosed area: Functional area boundary markings must form a closed polygon (e.g. the apron area boundary must be completely closed); Full network connectivity: There is a marking connection path between any two points in the taxiway system.

[0081] If the verification fails (such as finding a broken point or an island), the system automatically marks the topological conflict position and alarms. After verification, the airport ground marking full feature model with complete spatial coordinates, attributes, and topological relationships is output.

[0082] Although the steps in the above embodiments are described in the above order, those skilled in the art can understand that, in order to achieve the effect of the embodiments, the different steps do not have to be executed in such an order, and they can be executed simultaneously (in parallel) or in a reversed order, and these simple changes are within the protection scope of the present application.

[0083] The second embodiment of the application is a ground marking line automatic association adjustment system based on block division, which is based on the first embodiment of the ground marking line automatic association adjustment method based on block division. The system comprises: A structured marking data set analysis module configured to analyze the vector graphic data in the latest airport regulation AIP map, extract the geometric coordinates, line type and topological connection relationship of all ground marking lines, and generate a structured marking data set; The airport is divided into multiple functional areas based on the preset functional area type. In each functional area, a topological sub-area is constructed according to the marking endpoint connection relationship. When the sub-area marking density exceeds the threshold, the sub-area is subdivided into grid cell areas with dynamic grid size, and a hierarchical area map is output, recording the area boundary, hierarchical relationship and contained marking identifier set; The sub-area and / or grid cell area in the hierarchical area map are taken as detection units. For each detection unit, the changed area between the new and old versions of AIP and its position identifier in the hierarchical area map are detected by matching the feature points through marking coverage comparison, and the marking in the changed area is based on the structured marking data set to generate a new version of marking data; Based on the topological connection relationship recorded in the hierarchical area map, the N-degree associated line is recursively searched from the changed area as the starting point, and only the associated line with changed geometric attributes or connection relationship is updated; The data for the changed areas is spliced ​​with the data for the unchanged areas, and a complete airport model is generated through boundary consistency verification and global topology reconstruction. Those skilled in the art will clearly understand that for ease and brevity of description, the specific operating process and related descriptions of the system described above can be referred to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0084] It should be noted that the above embodiment provides an automatic association adjustment system for ground marking lines based on block division, which is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be decomposed or combined. For example, the modules in the above embodiment can be combined into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps and are not regarded as improper limitations on the present invention.

[0085] An electronic device according to a third embodiment of the present invention includes: at least one processor; and a memory communicatively connected to at least one of the processors; wherein, The memory stores instructions that can be executed by the processor, and the instructions are used to be executed by the processor to implement the above-mentioned method for automatic association adjustment of ground marking lines based on block division.

[0086] A fourth embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to be executed by the computer to implement the above-mentioned method for automatic association adjustment of ground marking lines based on block division.

[0087] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes and related instructions of the storage device and processing device described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0088] Those skilled in the art should be able to appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two, and the programs corresponding to the software modules and method steps can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the art. In order to clearly illustrate the interchangeability of electronic hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0089] The terms "first", "second", etc. are used to distinguish similar objects, rather than to describe or indicate a particular order or sequence.

[0090] The term "comprise" or any other similar term is intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0091] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A method for automatically adjusting the association of ground marking lines based on block division, characterized in that: The method includes: Parse the vector graphics data in the latest airport regulations AIP diagram, extract the geometric coordinates, line types and topological connection relationships of all ground marking lines, and generate a structured marking dataset; The airport is divided into multiple functional areas based on preset functional area types. Within each functional area, topological sub-areas are constructed based on the connection relationship between the marking endpoints. When the marking density of a sub-area exceeds a threshold, it is subdivided into grid unit areas with a dynamic grid size and output as a hierarchical regional map, recording the regional boundaries, hierarchical relationships, and the set of marking identifiers included. Using the sub-regions and / or grid unit areas in the hierarchical regional map as detection units, for each detection unit, detecting the changed areas between the new and old versions of the AIP and their location identifiers in the hierarchical regional map by comparing the marking coverage and matching the feature points, and generating new version marking data for the markings in the changed areas based on the structured marking dataset; Based on the topological connection relationship recorded in the hierarchical area map, recursively search for N-degree association lines starting from the changed area, and only update the association lines with changed geometric attributes or connection relationships; The changed area data is spliced ​​with the unchanged area data, and a complete airport model is generated through boundary consistency verification and global topology reconstruction.

2. The method for automatically adjusting the ground marking lines based on block division according to claim 1 is characterized in that: In each functional area, a topological sub-area is constructed based on the connection relationship of the marked line endpoints. The method is as follows: When the Euclidean distance between the endpoints of two marking lines is less than the spatial tolerance threshold, it is determined that the endpoints coincide, and the two marking lines are classified into the same topological sub-region.

3. The method for automatically adjusting the ground marking lines based on block division according to claim 1 is characterized in that: When the line density of the sub-area exceeds a threshold, the sub-area is subdivided into grid unit areas with a dynamic grid size, specifically including: When the total length of the marking lines per unit area in a sub-region exceeds a preset density threshold, the grid unit side length is adjusted according to the degree of spatial dispersion of the marking line endpoints within the sub-region; the more dispersed the endpoint distribution, the larger the grid size, and the more concentrated the distribution, the smaller the grid size; The sub-region is divided into equal-sized rectangular grid cell regions based on the calculated grid size.

4. The method for automatically adjusting the association of ground marking lines based on block division according to claim 3 is characterized in that: The length of the grid cell side is adjusted according to the degree of spatial distribution discreteness of the endpoints of the marking line in the sub-region. The method is: Identify the longest continuous marking line in the sub-area as a reference marking line, and use the length of the reference marking line as a grid reference size; If a group of mutually parallel marking lines exists within the sub-area, the grid cells are extended along the direction of the marking line group to form a rectangular grid with a long side parallel to the marking line direction and a length twice the grid reference size, and a short side equal to the grid reference size; wherein the mutually parallel marking line group is a group of marking lines with more than three marking lines and the angle between any two marking lines is less than a preset degree; If there is no dominant direction of the marking lines in the sub-area, a square grid with a side length equal to the grid reference size is generated.

5. The method for automatically adjusting the ground marking lines based on block division according to claim 1 is characterized in that: For each detection unit, the changed areas between the new and old versions of the AIP are detected and their location identification in the layered area map is detected by comparing the coverage of the markings and matching the feature points. The method is as follows: Calculate the absolute difference in the total length of the new and old versions of the marking line within the detection unit. If the difference exceeds the length tolerance threshold, mark it as a preliminary screening change area; Extract the endpoints and intersections of all marking lines in the initial screening change area as feature points; Perform bidirectional matching on the coordinates of the feature points of the new and old versions. If the proportion of unmatched feature points exceeds the feature point tolerance threshold, the area is output as the final changed area and its hierarchical position identifier in the hierarchical area map.

6. The method for automatically adjusting the association of ground marking lines based on block division according to claim 5 is characterized in that: The two-way matching includes forward matching and reverse matching: The forward matching includes searching for the nearest neighbor feature point within a preset radius in the new version for each feature point in the old version; The reverse matching includes searching for the nearest neighbor feature point within a preset radius in the old version for each feature point in the new version; A match is considered successful only when the feature points are nearest neighbors to each other in both forward and reverse matching.

7. The method for automatically adjusting the ground marking lines based on block division according to claim 1 is characterized in that: Based on the topological connection relationship recorded in the hierarchical area map, recursively search for N-degree association lines starting from the changed area, and only update the association lines with changed geometric attributes or connection relationships. The method is as follows: Taking each marking line in the change area as the starting point, recursively search for all marking lines that are directly connected to it as 1-degree associated lines; Continue searching for lines that have direct endpoint connections with the 1st-degree correlation line as 2nd-degree correlation lines until the Nth-degree correlation line search is complete, where N is a preset recursive depth, which is pre-set based on the airport area type. A direct endpoint connection means that the endpoint coordinates of the two lines coincide within the spatial tolerance range, and their topological connection relationship is recorded in the layered area map. For each line in the associated line set, execute: Compare the geometric coordinate sequences, line types, and topological connection object identifiers between the new and old versions; If the geometric coordinate deviation exceeds the coordinate tolerance, the line type changes, or the topological connection object identifiers are inconsistent, data reconstruction is performed.

8. The method for automatically adjusting the association of ground marking lines based on block division according to claim 7 is characterized in that: The data reconstruction includes: When the geometric coordinate deviation exceeds the coordinate tolerance, the old coordinates are overwritten with the new coordinates; When the line type changes, update the type identifier and record the change version number; When the topological connection object identifiers are inconsistent, the topological connection relationship is reconstructed and the boundary marking identifier set of the associated area is updated.

9. The method for automatically adjusting the association of ground marking lines based on block division according to claim 1, characterized in that: The changed area data is spliced ​​with the unchanged area data, and a complete airport model is generated through boundary consistency verification and global topology reconstruction. The method is as follows: The new version of the changed area data and the old version of the unchanged area data are spatially superimposed according to the geographic coordinate system, and the endpoints of the marking lines of the adjacent areas are aligned based on the boundary of the changed area; Detect markings that cross the boundary of the changed area. If the endpoint coordinates of the markings that cross the boundary of the changed area deviate from those in the adjacent area, automatically extend or crop the markings in the adjacent area to the matching coordinates based on the changed area data. The criteria for determining the endpoint coordinate deviation are: The Euclidean distance between the endpoints of the marking lines with the same identifier is greater than the coordinate matching threshold; Or there are unclosed endpoints of the marking line at the boundary of adjacent areas; A global topology connection table is generated based on the endpoint connection relationship of all markings, and it is verified that there are no isolated marking segments or unclosed areas in the topology connection table. The global topology connection table includes at least: a unique identifier for each marking, the coordinates of the starting and ending endpoints of the marking, a set of connected adjacent marking identifiers, and the functional area and sub-area codes to which they belong.

10. The method for automatically adjusting the association of ground marking lines based on block division according to claim 9, characterized in that: When the endpoint of the changed area marking exceeds the boundary of the adjacent area, the adjacent area marking is extended to the coordinates of the endpoint; When the adjacent area markings overlap with the changed area markings after extension, the overlapping parts are clipped and the topological connection is updated; Recalculate the geometric coordinate sequence for extended or cropped lines.

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