A method and apparatus for constructing a simulated sandbox data foundation

Abstract

The present application relates to the technical field of simulation sandbox, and particularly relates to a simulation sandbox data base construction method and device, wherein the method constructs compatible domain object models in the localization BIM forward design stage; according to unstructured drawings, localization BIM models and other data types, SHP data, geometric feature data and structured topology data are extracted or generated; simulation element data is obtained through field-level direct mapping, SHP data is converted twice and coordinates are unified, and then geometric feature completion, line segment merging and topology reconstruction are performed, object construction and labeling are completed based on the simulation element data, and simulation sandbox data base is obtained. The present application solves the problems of low construction efficiency, poor compatibility and insufficient geometric accuracy, realizes standardized data processing and efficient construction, can be directly loaded into a simulation sandbox, is suitable for airport and other scenes, and improves simulation accuracy and reliability.

Description

Technical Field

[0001] This invention relates to the field of simulation sandbox technology, specifically to a method and device for constructing a simulation sandbox data base. Background Technology

[0002] With the rapid development of simulation technology, simulation sandboxes are increasingly widely used in fields such as airports, architecture, and transportation. A high-quality simulation sandbox data base is the core foundation for ensuring the accuracy and reliability of simulations. Currently, the construction of simulation sandbox data bases mainly relies on the processing of unstructured drawing data or BIM model data, but existing technologies have many problems:

[0003] 1. Poor data compatibility: Existing methods do not build a domain object model compatible with the simulation sandbox during the BIM forward design phase, resulting in a mismatch between the BIM model or unstructured drawing data and the target format of the simulation sandbox. This requires a lot of format conversion and field adjustment, which is inefficient. 2. Insufficient data processing precision: The lack of clear precision standards and verification mechanisms in data format conversion, coordinate unification, line segment merging, etc., leads to problems such as geometric distortion and coordinate deviation in the generated data, which affects the simulation effect; 3. Incomplete topology: In the existing topology reconstruction process, the lack of standardized constraints on node merging and edge relationship construction leads to unclear business relationships in the final topology data, which cannot accurately reflect the spatial relationships and business logic of the actual infrastructure; 4. Insufficient process loop: There is a lack of effective correction mechanisms for data that fails verification in each step of data processing, which leads to a failure to guarantee data quality. Furthermore, the data connection between different steps is not smooth, affecting the overall construction efficiency.

[0004] Therefore, there is an urgent need for a method and equipment that can solve the above problems and achieve efficient, accurate and standardized construction of simulation sandbox data base. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method and device for constructing a simulation sandbox data base, so as to overcome the problems existing in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: On the one hand, this application provides a method for constructing a simulation sandbox data base, including: Step S1: Construct a domain object model compatible with the simulation sandbox data base during the domestic BIM forward design phase; wherein, the attribute fields of the domain objects in the domain object model and the target format of the simulation sandbox data base adopt the same naming convention. Step S2: Obtain the data to be processed. When the data to be processed is unstructured drawing data, perform data extraction and topology reconstruction on the unstructured drawing data according to the domain object model to obtain the corresponding SHP data, geometric feature data, and structured topology data. When the data to be processed is a domestic BIM forward design model, directly extract the standardized SHP data, geometric feature data, and structured topology data from the domestic BIM forward design model. Step S3: Based on the attribute specifications of the domain object model, perform field-level pass-through mapping on the structured topology data and convert it into simulation element data that conforms to the simulation sandbox data format; Step S4: Convert the SHP data obtained in step S2 to obtain first JSON data. After unifying the coordinates and geometrically regularizing the first JSON data, perform initial topology reconstruction to obtain the data format standard. Step S5: Based on the data format standard established in step S4, the SHP data obtained in step S2 is converted again to obtain the second JSON data, and the coordinates of the second JSON data are unified. Step S6: Based on the geometric feature data and structured topology data obtained in step S2, perform geometric feature completion and line segment merging on the second JSON data; Step S7: Perform final topology reconstruction on the data processed in step S6 to obtain the final topology data; Step S8: Based on the simulation element data obtained in step S3, the final topology data is constructed and labeled to obtain the simulation sandbox data base.

[0007] Furthermore, in the method described above, step S1 includes: In the domestic BIM forward design phase, the target format of the simulation sandbox data base is analyzed, all domain object types involved in the target format and the attribute fields corresponding to each domain object are extracted, the data type, business semantics, value range and unit specifications of each attribute field are clarified, and the relationship between each domain object is sorted out to form a standardized simulation sandbox interface specification. Based on the simulation sandbox interface specification and the engineering application requirements of domestic BIM forward design, a unified, hierarchical object system is constructed; wherein, the object system adopts a layered design, with the core layer remaining fixed and the business layer supporting dynamic expansion; Based on the object system, domain objects at each level are constructed, and the hierarchical level, inheritance relationship and unique identifier of each domain object in the object system are defined to ensure that each domain object is a legal leaf node or an extensible node in the object system. The structured data entity of the domain object is defined by dataclass, the core attribute fields and data format of the domain object are fixed, and the discrete attribute values ​​and state types of the domain object are strongly constrained by enumeration type, thus completing the standardized encapsulation of the domain object; Based on the object system, establish the association between the domain objects, construct the topological connections and hierarchical organization between the domain objects through the reference type or foreign key field in the dataclass, and integrate the encapsulated domain objects to form a domain object model compatible with the simulation sandbox data base.

[0008] Furthermore, in the method described above, step S2 includes: Obtain the data to be processed and determine the type of the data to be processed; if the data to be processed is unstructured drawing data, parse the file format of the unstructured drawing data, identify the geometric elements in the unstructured drawing data, and remove the annotations, fill patterns and text labels in the unstructured drawing data; Based on the object types defined in the domain object model, the identified geometric features are classified and separated with the goal of each target layer containing only a single type of geometric feature, thus distinguishing the target layers corresponding to different airport infrastructures and removing irrelevant graphs. Each geometric feature in the target layer is encapsulated according to the spatial data format specification of SHP file, and the basic attribute information of each geometric feature is associated to generate SHP data that corresponds one-to-one with each target layer. The geometric and basic attribute information in the SHP data are converted to generate JSON-Like intermediate format data; wherein, the JSON-Like intermediate format data retains the geometric and attribute association relationship of the SHP data, and the field names of the JSON-Like intermediate format data are consistent with the domain object model; Based on the topological association rules of the domain object model, the geometric elements in the JSON-Like intermediate format data are subjected to node generation, node merging, edge relationship construction, node degree calculation and connected component analysis to establish clear association relationships between nodes and edges, forming structured topological data; wherein, node merging adopts a preset tolerance, with a value range of 0.1 to 0.5 meters; Extract the geometric parameters from the JSON-Like intermediate format data to form geometric feature data, and output the SHP data, geometric feature data and structured topology data corresponding to the data to be processed; If the data to be processed is a domestically produced BIM forward design model, directly extract the SHP data, geometric feature data, and structured topology data that have been standardized according to the domain object model specification.

[0009] Furthermore, in the method described above, step S3 includes: Based on the attribute specifications of the domain object model, the attribute correspondence between the structured topology data and the target format of the simulation sandbox data base is sorted out, and the mapping rules of each attribute field are clarified. Based on the mapping rules, the attribute fields of each domain object in the structured topology data are directly assigned and mapped to the corresponding fields in the target format of the simulation sandbox data base according to the correspondence of names and meanings; wherein, the geometry and topological association of the structured topology data are not changed during the mapping process, only the corresponding transfer of attribute fields is completed; The mapped data is format-validated, and invalid and abnormal data generated during the mapping process are removed. The validation includes consistency of attribute field names, data type matching, and compliance of value range. If the validation fails, the attribute correspondence is re-examined and the mapping operation is performed again until the validation passes. Based on the results of the format verification, the data that passes the verification is converted into simulation element data that conforms to the simulation sandbox data format.

[0010] Furthermore, in the method described above, step S4 includes: Based on the SHP data and the data specifications of the domain object model, a set of hierarchical SHP files to be processed is obtained, and the domain object type, geometric information and basic attributes corresponding to each hierarchical SHP file are determined. The geometric features and basic attribute information in each of the layered SHP files are completely converted into first JSON data; Using a coordinate system consistent with the simulation sandbox data base, all geometric coordinates in the first JSON data are uniformly transformed and calibrated; wherein the calibration error does not exceed 0.01 meters. The broken lines, discontinuous lines, and abnormal endpoints in the first JSON data are corrected to standardize the expression of geometric elements. Among them, line segments with a length of less than 0.3 meters and consistent with the direction of adjacent line segments are identified as broken lines, and isolated endpoints without associated edges are identified as abnormal endpoints. The correction method is to delete isolated endpoints and splice broken lines. Based on the topological association rules of the domain object model, an initial topological reconstruction operation is performed on the first JSON data through node generation, node merging, and edge relationship construction. The generated topological data is then formatted and converted to establish a unified data format standard. The data format standard includes data organization format, field name specification, coordinate system parameters, and topological storage structure.

[0011] Furthermore, in the method described above, step S5 includes: Based on the data format standard, the domain object type, geometric information and basic attributes corresponding to each layered SHP file in the layered SHP file set are confirmed. The geometric features and basic attribute information in each of the layered SHP files are completely converted into second JSON data, and the field name specifications and data organization format in the data format standard are strictly followed during the conversion process; Based on the coordinate system of the simulation sandbox data base, all geometric coordinates in the second JSON data are uniformly transformed and calibrated; The system checks whether the data organization format, field names, and coordinate parameters of the second JSON data fully conform to the data format standard. If the check fails, the hierarchical SHP is reconverted into the second JSON data, and the newly converted second JSON data is checked until it passes the check. Finally, the qualified second JSON data is output.

[0012] Furthermore, in the method described above, step S6 includes: By comparing the geometric parameters in the second JSON data with the geometric feature data, the missing geometric feature information in the second JSON data is identified; wherein, the missing geometric feature information includes at least: line segment type, arc parameters, and direction angle; Based on the missing geometric feature information, combined with the node connection relationships and connected component features in the structured topology data, and in accordance with the geometric expression specifications of the domain object model, the missing geometric parameters of the second JSON data are supplemented into the corresponding geometric elements; The distribution of line elements in the second JSON data after geometric feature completion is analyzed, and the edge relationships in the structured topology data are combined to identify broken lines, discontinuous lines and redundant segments drawn in segments for the same physical entity. The broken and discontinuous lines in the second JSON data with an interval of no more than 0.3 meters between the endpoints of adjacent line segments and a deviation of no more than 5° are spliced ​​together and integrated, and the expression form of geometric elements is standardized. Perform geometric verification on the merged line elements to confirm that the merged lines have no geometric distortion and that the core geometric parameters are preserved intact. Output the data that completes the geometric feature completion and line segment merging.

[0013] Furthermore, in the method described above, step S7 includes: Redundant and abnormal nodes are identified in the data where geometric feature completion and line segment merging have been completed, and node merging and calibration are performed according to the preset tolerance; wherein, the node position deviation after calibration does not exceed 0.01 meters; Based on the core logic of edge relationships in the structured topology data, the edge association relationships corresponding to the merged line elements are verified and corrected, missing edge attributes are supplemented, and the domain object type to which the edge belongs is clarified. Based on the requirements of the airport simulation scenario and the topological constraints of the domain object model, by analyzing the node connectivity degree, line element direction and spatial distribution characteristics in the data after edge association correction, data with a node connectivity degree of no more than 3 are identified as intersections, data with line element direction consistent with the connection between the airport runway and the aircraft stand and with a length of no more than 5 meters are identified as taxiways, and line elements that connect one end to the external area and the other end to the internal topological network of the airport are identified as entrances and exits, and the topological attributes and business meanings of the intersections, taxiways and entrances and exits are labeled. According to the topology storage structure in the data format standard, the nodes, edges and relationships of the data after the topology attributes and business meanings have been labeled are standardized and organized, and the final topology reconstruction is performed to generate the final topology data with complete business topology associations.

[0014] Furthermore, in the method described above, step S8 includes: Based on the naming convention of synonymy in the domain object model, the attribute information of each domain object in the simulation element data is accurately associated and matched with the topological units in the final topological data, and each topological unit is assigned a corresponding domain object identity to construct a structured simulation object that corresponds one-to-one with the airport infrastructure. Based on the geometric feature data and the structured topology data, the constructed structured simulation object is fully annotated with attributes, and geometric feature parameters and topological association information are added to the constructed structured simulation object; wherein, the annotation content of the full attribute annotation includes the type, unique number, geometric dimensions and running constraints of each simulation object; Based on the domain object association rules defined in the domain object model and the connectivity relationships in the structured topology data, hierarchical relationships and business association relationships between the structured simulation objects are constructed to form a complete object association network. Based on the data format standard and the target format of the simulation sandbox data base, the standardization of object construction, the accuracy of attribute labeling and the completeness of association relationships in the object association network are verified, abnormal data in the object association network are removed, and the format deviation in the object association network is corrected according to the verification results. The data format standard is integrated and encapsulated according to the target format of the simulation sandbox data base, and finally a simulation sandbox data base that can be directly loaded into the simulation sandbox and has complete geometric information, topological association and business attributes is generated.

[0015] On the other hand, this application provides a simulation sandbox data base construction device, including a processor and a memory, wherein the processor is connected to the memory: The processor is used to call and execute the program stored in the memory; The memory is used to store the program, which is used to execute at least any of the above-described simulation sandbox data base construction methods.

[0016] The beneficial effects of this invention are as follows: 1. Improve data compatibility: Build a compatible domain object model in the domestic BIM forward design phase, adopt the same name and synonym naming convention, realize seamless adaptation of BIM model, unstructured drawing data and simulation sandbox target format, reduce the workload of format conversion and improve construction efficiency; 2. Improve data processing accuracy: Clarify the accuracy standards for each step (such as coordinate calibration error, node merging tolerance, etc.), add multi-round verification and correction mechanisms to ensure high data geometric accuracy and no distortion, and improve simulation accuracy; 3. Improve topology relationships: Establish format standards through initial topology reconstruction, and improve business relationships through final topology reconstruction. Clarify the identification standards of topology features such as intersections, taxiways, and entrances / exits in scenarios such as airports, and ensure that the topology data is complete and meets actual business needs. 4. Achieve closed-loop process: Each data processing step is equipped with a verification and correction mechanism to reprocess unqualified data, ensuring data quality. At the same time, the steps are seamlessly connected to form a complete construction process. 5. Adaptable to multiple data sources: Supports differentiated processing of two data sources: unstructured drawing data and domestically produced BIM forward design models, broadening application scenarios and improving the versatility of the method. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a simulation sandbox data base construction method provided in an embodiment of the present invention; Figure 2 This is a general diagram of the domain object inheritance relationship of a simulation sandbox data base construction method provided in this embodiment of the invention; Figure 3 This is a general diagram of the domain object relationship of a simulation sandbox data base construction method provided in an embodiment of the present invention; Figure 4 This is a domain object inheritance relationship diagram of a simulation sandbox data base construction method provided in this embodiment of the invention; Figure 5 This is a diagram showing the association of runway markers in a simulation sandbox data base construction method provided in this embodiment of the invention. Figure 6 This is a diagram showing the association of slideway markers in a simulation sandbox data base construction method provided in this embodiment of the invention. Figure 7 This is a lane sign association diagram of a simulation sandbox data base construction method provided in an embodiment of the present invention; Figure 8 This is a diagram showing the association of apron markers in a simulation sandbox data base construction method provided in this embodiment of the invention. Figure 9 This is a diagram showing the association of other markers in a simulation sandbox data base construction method provided in this embodiment of the invention. Figure 10 This is a structural schematic diagram of a simulation sandbox data base construction device provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be described in detail below. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0020] Figure 1 This is a flowchart illustrating one embodiment of a method for constructing a simulation sandbox data base according to the present invention. Please refer to [link / reference]. Figure 1 The method in this embodiment may include the following steps: Step S1: Construct a domain object model compatible with the simulation sandbox data base during the domestic BIM forward design phase; wherein, the attribute fields of the domain objects in the domain object model and the target format of the simulation sandbox data base adopt the same naming convention. Step S2: Obtain the data to be processed. When the data to be processed is unstructured drawing data, perform data extraction and topology reconstruction on the unstructured drawing data according to the domain object model to obtain the corresponding SHP data, geometric feature data and structured topology data. When the data to be processed is a domestic BIM forward design model, directly extract the standardized SHP data, geometric feature data and structured topology data from the domestic BIM forward design model. Step S3: Based on the attribute specifications of the domain object model, perform field-level direct mapping on the structured topology data and convert it into simulation element data that conforms to the simulation sandbox data format; Step S4: Convert the SHP data obtained in step S2 to obtain the first JSON data. After unifying the coordinates and geometrically regularizing the first JSON data, perform initial topology reconstruction to obtain the data format standard. Step S5: Based on the data format standard established in step S4, the SHP data obtained in step S2 is converted again to obtain the second JSON data, and the coordinates of the second JSON data are unified. Step S6: Based on the geometric feature data and structured topology data obtained in step S2, perform geometric feature completion and line segment merging on the second JSON data; Step S7: Perform final topology reconstruction on the data processed in step S6 to obtain the final topology data; Step S8: Based on the simulation element data obtained in step S3, the final topology data is constructed and labeled to obtain the simulation sandbox data base.

[0021] Preferably, step S1 includes: In the domestic BIM forward design phase, the target format of the simulation sandbox data base is analyzed, all domain object types involved in the target format and the corresponding attribute fields of each domain object are extracted, the data type, business semantics, value range and unit specifications of each attribute field are clarified, and the relationship between each domain object is sorted out to form a standardized simulation sandbox interface specification. Based on the simulation sandbox interface specification and the engineering application requirements of domestic BIM forward design, a unified and hierarchical object system is constructed. The object system adopts a layered design, with the core layer remaining fixed and the business layer supporting dynamic expansion. Based on the object system, construct domain objects at each level, and clarify the ownership level, inheritance relationship and unique identifier of each domain object in the object system to ensure that each domain object is a legal leaf node or extensible node in the object system. By defining structured data entities for domain objects through dataclass, fixing the core attribute fields and data formats of domain objects, and using enumeration types to strongly constrain the discrete attribute values ​​and state types of domain objects, the standardized encapsulation of domain objects is completed. The association between domain objects is established based on the object system. The topological connections and hierarchical organization between domain objects are constructed through reference types or foreign key fields in the dataclass. The encapsulated domain objects are then integrated to form a domain object model compatible with the simulation sandbox data base.

[0022] Understandably, in domestically developed BIM forward design systems, domain objects are the core components of domain-driven design, referring to model elements with clearly defined responsibilities and boundaries within the business domain. To reduce backend conversion costs, domestically developed BIM platforms reference attribute families that correspond one-to-one with the simulation sandbox data base during object modeling. This allows subsequent mapping to only require field passthrough or enumeration translation, without the need for secondary expansion of the object model.

[0023] The constructed object system includes: a general layout system and a sign and marking system.

[0024] The site plan system derives composite objects such as runway centerline, taxiway baseline, and aircraft position template from the line base class, and supports strong / weak lifecycle associations.

[0025] In the master map system, the inheritance relationships of objects in each domain are as follows: Figure 2 As shown in the diagram. The base class for lines is used to implement the shape and basic attribute definitions, while subclasses implement domain-related business logic.

[0026] In the master map system, the relationships between objects in different domains are as follows: Figure 3 As shown in the diagram, the relationships between domain objects are divided into two categories based on their strength: objects with the same lifecycle establish a first relationship; objects with different lifecycles establish a second relationship. Domain objects are divided into four categories: composite objects, general objects, line objects, and data objects.

[0027] It should be noted that taxiway baselines are divided into curved taxiway baselines and other types of taxiway baselines. Figure 3 Taxiway baselines not specified in the text are other types of taxiway baselines. Figure 3 One curved taxiway baseline points to two taxiway baselines, which is only represented as a curved taxiway baseline to a taxiway baseline, and can be in a one-to-many form.

[0028] according to Figure 3 As shown, general areas, general lines, lane centerlines, and runway centerlines are independent geometric objects, unrelated to other domain objects. Curved taxiway baseline objects can establish a strong positive association with radius scheme objects and taxiway baseline objects through business tools, but their lifecycles differ; that is, radius schemes and taxiway baselines can exist independently of curved taxiway baselines. Aircraft stand templates are strongly positively associated with aircraft stand safety lines and aircraft stand stop lines throughout their entire lifecycle. When an aircraft stand template is deleted, its associated aircraft stand safety lines and aircraft stand stop lines are deleted simultaneously. Deleting either the aircraft stand safety line or the aircraft stand stop line does not affect the aircraft stand template. Apron objects are independent non-geometric domain objects; the apron itself is not bound to any geometric primitives. The apron area is only temporarily drawn into the view when viewing apron data in the apron manager.

[0029] In the sign and marking system, the inheritance relationships between objects in different domains are as follows: Figure 4 As shown. Among them, the mark and gradation base class is used to define the basic properties applicable to mark and gradation class objects; the mark and gradation base class is divided into gradation base class and mark base class, the gradation base class is used for defining linear marks and gradations, and the mark base class is used for defining marks of complex shapes.

[0030] In a sign and marking system, the relationships between various domain objects are as follows: Figures 5 to 9 As shown. Relationships are divided into two types: strong relationships (dependencies throughout the entire lifecycle, where the dependent object is deleted when the dependent object is deleted); and weak relationships (dependencies at creation time, where the dependency only occurs at creation time). Relationships are further divided into cross-project (cross-disciplinary) dependencies and current-project dependencies.

[0031] exist Figure 5 In this system, all signs and markings depend on the runway centerline of the overall layout system; runway edgeline signs are created based on the runway edgeline objects of the pavement system; aiming point signs are strongly dependent on the touchdown zone signs; runway number signs are created based on the runway threshold signs; runway centerline signs are created based on the runway number signs; and runway centerline signs are strongly dependent on the runway inward movement signs.

[0032] exist Figure 6 In the system, the intermediate holding position, taxiway centerline marking, runway number marking, mandatory instructions, and runway holding position are strongly dependent on the taxiway baseline object of the master plan system; mandatory instructions and runway holding position are in turn dependent on the runway centerline object of the master plan system; runway number and enhanced runway centerline marking depend on the runway holding position when created; taxiway edge marking is strongly dependent on the taxiway edge object of the pavement system; and taxiway centerline marking is strongly dependent on the curved taxiway baseline object of the master plan system.

[0033] exist Figure 7 In the map, directional arrow signs, speed limit signs, stop signs, and yield signs are strongly dependent on the lane centerline signs of the master plan system; service lane edge signs, wingtip clearance lines, service lane signs crossing taxiways, and lane centerline signs are strongly dependent on the lane edge objects of the pavement system; among them, lane centerline signs are strongly dependent on the lane centerline objects of the master plan system; service lane edge signs crossing taxiways are strongly dependent on the taxiway baseline objects of the master plan system; service lane edge signs crossing taxiways; wingtip clearance lines depend on service lane edge signs when created; and guide line signs have no dependency.

[0034] exist Figure 8In this system, the safety line, code mark, and stop point mark of the aircraft position are strongly dependent on the safety line mark of the aircraft position in the general layout system; the code mark and stop point mark are in turn strongly dependent on the lead-in line mark of the aircraft position; the stop line of the aircraft position and the aircraft type code table are strongly dependent on the stop line object of the aircraft position in the general layout system; the activity range of the corridor bridge, the operation protection area, and the push-out line have no dependency relationship.

[0035] exist Figure 9 In China, pavement markings are heavily reliant on the taxiway edge lines, runway edge lines, lane edge lines, and shoulder edge lines of the pavement system; general feature markings are not reliant on them.

[0036] In this embodiment, the domain object is encapsulated using a dataclass and an enumeration type, which supports serialization / deserialization and facilitates version management and inter-system exchange.

[0037] Preferably, step S2 includes: Acquire the data to be processed and determine its type. If the data to be processed is unstructured drawing data, parse the file format of the unstructured drawing data, identify the geometric elements in the unstructured drawing data, and remove annotations, fill patterns, and text labels from the unstructured drawing data. Based on the object types defined in the domain object model, the identified geometric features are classified and separated with the goal of each target layer containing only a single type of geometric feature. This distinguishes the target layers corresponding to different airport infrastructures and removes irrelevant graphs. The geometric features in each target layer are encapsulated according to the spatial data format specification of SHP files, and the basic attribute information of each geometric feature is associated to generate SHP data that corresponds one-to-one with each target layer. The geometric and basic attribute information in the SHP data is converted to generate JSON-Like intermediate format data. The JSON-Like intermediate format data retains the geometric and attribute relationships of the SHP data, and the field names of the JSON-Like intermediate format data are consistent with the domain object model. Based on the domain object model, the topological association rules perform node generation, node merging, edge relationship construction, node degree calculation, and connected component analysis on the geometric elements in the JSON-Like intermediate format data, establishing clear associations between nodes and edges to form structured topological data; among them, node merging adopts a preset tolerance, with a value range of 0.1 to 0.5 meters; Extract geometric parameters from JSON-Like intermediate format data to form geometric feature data, and output the SHP data, geometric feature data and structured topology data corresponding to the data to be processed; If the data to be processed is a domestically produced BIM forward design model, directly extract the SHP data, geometric feature data, and structured topology data that have been standardized according to the domain object model specification.

[0038] Understandably, the data to be processed includes domestically produced BIM forward design models and unstructured CAD and PDF drawings.

[0039] For domestically produced BIM forward design models, structured objects can be directly exported, namely SHP data, geometric feature data, and structured topology data.

[0040] For unstructured CAD and PDF drawings, to ensure a unified, lightweight, and language-independent input for subsequent topology construction algorithms, this embodiment of the domestic BIM forward design system first exports the CAD drawings as SHP files by layer, then converts them to a JSON-like intermediate format, and finally constructs the airport network topology. After extracting key information, the drawing information is standardized into a JSON array format. The common fields of the JSON-like intermediate format are shown in Table 1.

[0041] Table 1 General Fields Table

[0042] After converting the SHP file to a JSON-Like intermediate format, the JSON-Like intermediate format data is geometrically normalized. Specifically, for straight line segments, the data is sorted by projection along the principal direction; for arc segments, the data is estimated by center and then sorted by polar angle; and for complex polylines, the nearest neighbor algorithm is used to prevent self-intersection.

[0043] In topology reconstruction, nodes are merged based on spatial tolerance (1–3 meters) and R-Tree is used to accelerate nearest neighbor search; connectors are automatically identified as special edge types (such as level crossing arc transition sections); nodes are classified, including free endpoints, intersections, and regular nodes.

[0044] Preferably, step S3 includes: Based on the attribute specifications of the domain object model, the attribute correspondence between structured topology data and the target format of the simulation sandbox data base is sorted out, and the mapping rules of each attribute field are clarified. Based on the mapping rules, the attribute fields of objects in each domain in the structured topology data are directly assigned and mapped to the corresponding fields in the target format of the simulation sandbox data base according to the correspondence of names and meanings; in the mapping process, the geometry and topological relationship of the structured topology data are not changed, only the corresponding transfer of attribute fields is completed. The mapped data is format-validated, and invalid and abnormal data generated during the mapping process are removed. The validation includes consistency of attribute field names, data type matching, and compliance of value range. If the validation fails, the attribute correspondence is re-examined and the mapping operation is performed again until the validation passes. Based on the format verification results, the verified data is converted into simulation element data that conforms to the simulation sandbox data format.

[0045] Understandably, in this embodiment, based on the constructed airport network topology, the system automatically infers the physical scope of business objects through semantic rules and geometric features (such as endpoint degrees, line segment naming keywords, and connection patterns). For example, a gate access line typically appears as a free endpoint (degree=1) and its name contains 'gate', thereby triggering the auto_detect_stands() process. Simultaneously, it utilizes attribute families pre-embedded during the design phase to achieve field-level passthrough or enumeration translation.

[0046] Because BIM object attributes correspond one-to-one with the simulation base standard, the conversion process does not require adding new model fields; only format encapsulation is needed. The original dataset is output in .shp, .udb, or GeoJSON format. AIRAC changes output a complete dataset plus a difference list. Non-AIRAC changes only output incremental XML, and geometric additions and deletions are prohibited. Each type of feature (runway, aircraft stand, taxiway, signage, etc.) carries a geometry, attribute, and topology triplet to ensure that the simulation system can directly parse and use it.

[0047] Preferably, step S4 includes: Based on SHP data and combined with the data specifications of the domain object model, a set of hierarchical SHP files to be processed is obtained, and the domain object type, geometric information and basic attributes corresponding to each hierarchical SHP file are identified. The geometric features and basic attribute information of each layer of SHP file are completely converted into the first JSON data; Using a coordinate system consistent with the simulation sandbox data base, all geometric coordinates in the first JSON data are uniformly transformed and calibrated; the calibration error does not exceed 0.01 meters. The broken lines, discontinuous lines, and abnormal endpoints in the first JSON data are corrected to standardize the expression of geometric elements. Specifically, line segments with a length of less than 0.3 meters and consistent with the direction of adjacent line segments are identified as broken lines, and isolated endpoints without connected edges are identified as abnormal endpoints. The correction method is to delete isolated endpoints and splice broken lines. Based on the domain object model, the topology association rules perform initial topology reconstruction on the first JSON data through node generation, node merging, and edge relationship construction. The generated topology data is then formatted and converted to establish a unified data format standard. The data format standard includes data organization format, field name specification, coordinate system parameters, and topology storage structure.

[0048] Understandably, this embodiment first converts the geometric data and attribute information in the shapefile into a JSON intermediate format, extracts key information such as line segment coordinate point sequence, name and type, and then uniformly converts the local coordinates of each layer into the WGS-84 geographic coordinate system to ensure that the data is processed under a unified coordinate system. Then, geometric normalization is performed, and after the geometric normalization is completed, initial topology reconstruction is performed, and the data after topology reconstruction is converted into a format and output.

[0049] In some optional embodiments, the geometric normalization process specifically includes: sorting the points of a straight line segment according to the projection direction; sorting the points of a circular arc segment according to the polar angle, estimating the center of the circle and determining the correct traversal direction; and sorting complex polylines using nearest neighbor instances to avoid self-intersections.

[0050] In the initial topology reconstruction, similar nodes are merged based on spatial tolerance (default 1-3 meters), then continuous line segments with the same name are identified and merged, preserving complete geometric information, identifying arc connectors at level crossings, distinguishing transition sections connecting different pavements, and classifying nodes to identify intersections, free endpoints, and regular nodes.

[0051] The output data formats include: Structured JSON, Simplified JSON, and GeoJSON. Structured JSON contains complete topological information (nodes, edges, connectors), metadata, and statistics. Simplified JSON is a lightweight format that is easy for programs to load and use quickly. GeoJSON is used for viewing and further processing in GIS software.

[0052] Preferably, step S5 includes: Based on data format standards, the domain object type, geometric information and basic attributes corresponding to each layered SHP file in the layered SHP file collection are identified. The geometric features and basic attribute information in each layer of SHP files are completely converted into second JSON data, and the field name specifications and data organization format in the data format standard are strictly followed during the conversion process; Based on the coordinate system of the simulation sandbox data base, all geometric coordinates in the second JSON data are uniformly transformed and calibrated; The system checks whether the data organization format, field names, and coordinate parameters of the second JSON data fully conform to the data format standard. If the check fails, the hierarchical SHP is reconverted into the second JSON data, and the newly converted second JSON data is checked until it passes the check. Finally, the qualified second JSON data is output.

[0053] Preferably, step S6 includes: By comparing the geometric parameters and geometric feature data in the second JSON data, the missing geometric feature information in the second JSON data is identified; among them, the missing geometric feature information includes at least: line segment type, arc parameters and direction angle; Based on the missing geometric feature information, combined with the node connection relationships and connected component features in the structured topology data, and in accordance with the geometric expression specifications of the domain object model, the missing geometric parameters of the second JSON data are supplemented into the corresponding geometric elements. By analyzing the distribution of line elements in the second JSON data after completing the geometric features, and combining the edge relationships in the structured topology data, we can identify broken lines, discontinuous lines, and redundant segments that are drawn in segments for the same physical entity. The broken and discontinuous lines in the second JSON data with a distance of no more than 0.3 meters between the endpoints of adjacent line segments and a deviation of no more than 5° are spliced ​​and integrated, and the expression form of geometric elements is standardized. Perform geometric verification on the merged line elements to confirm that the merged lines have no geometric distortion and that the core geometric parameters are preserved intact. Output the data that completes the geometric feature completion and line segment merging.

[0054] Understandably, the process involves first using tools like GeoPandas or Fiona to read the geometric and attribute data from the SHP file, then converting the projected coordinates or local coordinates in the SHP file to the WGS-84 geographic coordinate system, extracting the geometric and attribute information of line segments and converting it to a JSON array format, and finally performing geometric feature completion and line segment merging on the JSON array format.

[0055] In practical engineering applications, unstructured CAD drawings often face challenges such as inconsistent layer definitions, missing feature names, or misaligned attributes, particularly regarding geometric feature completion and line segment merging. To ensure the robustness of the simulation base construction, this embodiment constructs a semantic completion mechanism that automatically infers the business type of a feature based on its geometric attributes and topological associations when metadata is missing.

[0056] A multi-dimensional determination is made by analyzing the endpoint degrees, curvature, length characteristics, and relationships of line segments. Specifically: For the aircraft stand introduction line, its geometric characteristics present a typical "tree-like end". One end connects to the taxiway baseline, and the other end is a suspended free endpoint (degree D=1). When completing the aircraft stand introduction line, even if the layer name is not "Aircraft Stand", if a line segment with a length between 15 and 50 meters and a unique endpoint connected to the taxiway network is detected, it will be automatically marked as a StandData object, and its node with $D=1$ will be used as the stop point stop_node.

[0057] For taxiway connectors, the line segment type of the taxiway connector is "arc", and each end connects to two straight line segments with different names or directions. When completing the taxiway connector, if road_segment_name is empty, the tangent direction of the arc segment is calculated. If it smoothly connects two main paths, its semantics are automatically completed to connector type, and a cross-path topology jump index is established.

[0058] For the runway centerline, which has a very long straight section (usually >1500 meters) and is usually accompanied by a large number of intersection nodes (connecting crossings) with an angle of 3 or 4 on both sides, when completing the runway centerline, the "longest simple path" in the network is searched, and combined with the feature that the nodes at both ends have D=1, it is deduced to be the runway centerline, and the path that cuts perpendicularly is automatically identified as potential runway entry.

[0059] To address the geometric overlap issue caused by layer misalignment, spatial clustering and deduplication logic is introduced, specifically including: Overlapping line segments are merged by using R-Tree to retrieve parallel line segments with the same orientation within a spatial tolerance of 1–3 meters. If multiple line segments have overlapping geometry but different layers, a "voting mechanism" is used, or line segments with max_speed or width attributes are prioritized and redundant geometry is discarded.

[0060] Automatic breakpoint stitching: For broken lines generated during CAD export, it identifies endpoints that are in the same direction and have a spacing smaller than the tolerance, and performs an automatic merge_continuous_segments operation to restore the complete physical edge structure.

[0061] This embodiment significantly reduces the dependence of the data base construction on the quality of the original drawings. Even in extreme cases (such as when the drawings have only one layer and no text annotations), most of the key navigation elements of the airport can still be reconstructed through the topology, greatly reducing the workload of manual secondary annotation.

[0062] Preferably, step S7 includes: Redundant and abnormal nodes in the data after geometric feature completion and line segment merging are identified, and node merging and calibration are performed according to a preset tolerance; wherein the node position deviation after calibration does not exceed 0.01 meters; Based on the core logic of edge relationships in structured topological data, the edge relationships corresponding to the merged line elements are verified and corrected, missing edge attributes are supplemented, and the type of the domain object to which the edge belongs is clarified. Combining the requirements of airport simulation scenarios and the topological constraints of domain object models, by analyzing the node connectivity degree, line element direction and spatial distribution characteristics in the data after edge association correction, data with a node connectivity degree of no more than 3 are identified as intersections, data with line element direction consistent with the connection between airport runways and aircraft stands and with a length of no more than 5 meters are identified as taxiways, and line elements connecting one end to the external area and the other end to the internal topological network of the airport are identified as entrances and exits, and the topological attributes and business meanings of intersections, taxiways and entrances and exits are marked. According to the topology storage structure in the data format standard, the nodes, edges and relationships of the data after the topology attributes and business meanings have been labeled are standardized and organized, and the final topology reconstruction is performed to generate the final topology data with complete business topology associations.

[0063] Understandably, the data that has undergone geometric feature completion and line segment merging is normalized and sorted. For straight lines in the data, points are sorted according to the principal direction projection to ensure that the point sequence reflects the actual direction of the line segment. For arcs in the data, the center position is estimated, and the point sequence is sorted according to the polar angle to verify the rationality of the sorting result. For complex polylines in the data, the nearest neighbor method is used to sort unordered points to avoid path self-intersection. Then, the line segment type is automatically identified based on road_segment_name, which includes runways, taxiways, and aircraft stand access lines.

[0064] After normalization and point sorting are completed, continuous line segments are identified by finding line segments with the same name that are connected by the first and last points. Then, continuous line segments are merged into a single side, and all geometric detail points are retained for line segment merging. The arc connectors at the level crossing are identified, and the transition segments connecting different track surfaces are distinguished for connector identification. Finally, the original line segment IDs before merging are recorded for easy traceability and debugging, thus completing the merging and preprocessing of line segments.

[0065] During topology reconstruction, nodes are first created and merged, then edges are constructed and connections are determined, connectors are identified, and finally the topology structure is output.

[0066] 1. The node creation and merging phase includes: Based on spatial tolerance (default 1-3 meters), find similar points and merge them into the same node; Use R-Tree spatial indexing to accelerate node lookup; The node type is determined by the number of connecting edges. Node types include: intersection (≥3 edges), free endpoint (1 edge and is the runway / aircraft stand lead-in line), and regular node (2 edges).

[0067] 2. The phase of constructing and determining connection relationships includes: Create an edge object for each line segment and associate it with the start and end nodes; Record the edge type (taxiway, runway, camera access line, connector), name, and geometric point sequence; Maintain the edge connection list of the nodes and establish bidirectional associations.

[0068] 3. The connector identification stage includes: Identify the arc connectors at the level crossing: the first and last points connect to different lane surfaces; Connectors are used to represent transitions between pavements and are treated as a special edge type in the topology network.

[0069] 4. The topology output stage includes: A node dictionary containing node ID, coordinates, type, and a list of connected edges; The edge dictionary contains edge ID, name, type, start / end node, geometric point sequence, and original ID list; The connector dictionary records connector edge information separately, including information about the connected edges; Statistical information, including node type distribution, edge type distribution, connectivity analysis, and pavement name statistics.

[0070] Preferably, step S8 includes: Based on the naming convention of synonymy in the domain object model, the attribute information of each domain object in the simulation element data is accurately associated and matched with the topological units in the final topological data, and each topological unit is assigned a corresponding domain object identity to construct a structured simulation object that corresponds one-to-one with the airport infrastructure. Based on geometric feature data and structured topology data, comprehensive attribute annotation is performed on the constructed structured simulation objects, and geometric feature parameters and topological association information are added to the constructed structured simulation objects. Among them, the annotation content of comprehensive attribute annotation includes the type, unique number, geometric dimensions and running constraints of each simulation object. Based on the domain object association rules defined in the domain object model and the connectivity relationships in the structured topology data, the hierarchical relationships and business association relationships between various structured simulation objects are constructed to form a complete object association network. Based on the target format of the data format standard and the simulation sandbox data base, the standardization of object construction, the accuracy of attribute labeling and the completeness of association relationships in the object association network are verified, abnormal data in the object association network are removed, and the format deviation in the object association network is corrected according to the verification results. The data format standards are integrated and encapsulated according to the target format of the simulation sandbox data base, and finally a simulation sandbox data base that can be directly loaded into the simulation sandbox and has complete geometric information, topological associations and business attributes is generated.

[0071] Understandably, after the topology is built, the Managers module performs semantic annotation and object construction on airport resources, mapping the abstract topology network to specific business objects (runways, aircraft stands, taxiways, etc.).

[0072] Specifically, after topology reconstruction, a geometric network with semantic potential is obtained, where nodes are explicitly classified as 'free_end', 'intersection', or 'regular'. Based on this, and combining line segment naming rules and topological characteristics (such as free_ends typically corresponding to aircraft parking positions, runway entrances, and other business entities), runtime semantics are injected through Managers to transform the abstract topology into concrete airport resource objects.

[0073] 1. Targeting the runway The data loading is completed by deserializing the JSON dictionary data using RunwayData.from_dict(data_dict) to construct the runway object; Then RunwayData(name) creates a new runway object, requiring only the runway name (e.g., "01L / 19R").

[0074] After creating the runway object, pick the runway segments (add them to the edges collection), and mark the entry nodes (set entries), midpoint nodes (add them to midpoints), and waiting point nodes (add them to holds) to complete the labeling.

[0075] The object properties of a runway object include: name, the runway name (string); edges, which constitute the set of physical edge IDs of the runway (Set[str]), are selected through a pick operation; entries, a dictionary of runway entry nodes (Dict[str,str]), where the key is the node ID and the value is the entry name (e.g., "01L"); midpoints, a set of IDs of midpoints / must-pass points on the runway (Set[str]); holds, a set of runway waiting point node IDs (Set[str]).

[0076] 2. For camera positions The data loading is completed by deserializing the JSON dictionary data using StandData.from_dict(data_dict) to construct the stand object; Then, a new standby object is created using StandData(name,stop_node,entry_edge,related_edges,is_valid,stand_type); Finally, the auto_detect_stands() function automatically identifies the stand segments based on keywords and determines the physical endpoints based on the node degree (Degree=1) to complete the construction of the stand object.

[0077] For the constructed camera position object, first set the stop point node, then add related line segments (related_edges) and set the entry line (entry_edge), and finally configure the camera position type (top push / self slide) to generate camera position mutual exclusion relationships (auto_generate_conflicts) to complete the annotation of the camera position object.

[0078] The object properties of a station object include: name, the gate name (string, such as "101" or "A12"); stop_node, the ID (string) of the stop point node; entry_edge, the camera position imports the edge ID (string); related_edges is a set of physical edge IDs associated with the machine position (Set[str]). Conflicts, a set of mutually exclusive gate names (Set[str]), used to identify gates that cannot be used simultaneously; is_valid, a boolean value indicating the validity of the workstation. stand_type, stand type (enumeration); The specific types of camera positions (enumeration) include: -StandType.PUSHBACK, top ejection (requires towing); -StandType.SELF_MANEUVER, self-sliding in / out (through / diagonal).

[0079] 3. For taxiway targets First, the taxiway object is constructed by deserializing the JSON dictionary data using TaxilaneData.from_dict(data_dict); Then, the taxiway object is constructed by creating a new taxiway object using TaxilaneData(id, name), providing the ID and name (such as "TL_N1").

[0080] For the constructed taxiway object, first pick the taxiway line segment (add it to the edges set), then set the entrance node (entrances dictionary), bind the associated stand (related_stands set), and finally automatically associate the stand (auto_associate_stands) to determine the computer stand connection relationship (based on the entrance and stand type), thus completing the annotation of the taxiway object.

[0081] The object properties of the taxiway object include: id, a unique identifier for the taxiway (a string, such as "TL_001"); name, the name of the zipline (string); edges, which constitute the set of line segment IDs (Set[str]) of the slide, are selected through a pick operation; related_stands is a set of associated stand IDs (Set[str]), which are bound to the stands on this taxiway; `entrances` is a dictionary of entry nodes (Dict[str,str]), where the key is the node ID and the value is the entry name (e.g., "E1", "E2"). Multiple entry nodes are supported. ordered_nodes is an ordered list of nodes (List[str]), a sequence of nodes generated based on topological sorting. `stand_connections` is a dictionary of stand connection relationships (Dict[str, List[Dict]]), with the structure {Entry node ID: [List of stand connection information]}. node_mileage, a node mileage dictionary (Dict[str,float]), records the mileage position of each node on the taxiway; total_length, the total length of the taxiway (float, meters).

[0082] The calculation of the connection relationship between the machine positions is specifically carried out by generating a node sequence (ordered_nodes) based on BFS traversal, and then calculating the access point of the machine position.

[0083] For pushback positions, select the node that is farthest from the entrance (maximum index) to leave room for the trailer to operate; For self-masting positions, select the node closest to the entrance (with the smallest index) to facilitate direct turning into the entrance.

[0084] The present invention also provides a simulation sandbox data base construction device for implementing the above method embodiments. Figure 10 This is a schematic diagram of a structure provided in one embodiment of a simulation sandbox data base construction device of the present invention. Figure 10 As shown, the simulation sandbox data base construction device of this embodiment includes a processor 21 and a memory 22, with the processor 21 connected to the memory 22. The processor 21 is used to call and execute a program stored in the memory 22; the memory 22 is used to store the program, which is at least used to execute the simulation sandbox data base construction method in the above embodiments.

[0085] The specific implementation scheme of the simulation sandbox data base construction device provided in this application embodiment can refer to the implementation scheme of the simulation sandbox data base construction method in any of the above embodiments, and will not be repeated here.

[0086] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0087] It should be noted that in the description of this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means at least two.

[0088] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0089] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0090] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it includes one or a combination of the steps of the method embodiments.

[0091] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0092] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0093] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0094] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for constructing a simulation sandbox data base, characterized in that, include: Step S1: Construct a domain object model compatible with the simulation sandbox data base during the domestic BIM forward design phase; wherein, the attribute fields of the domain objects in the domain object model and the target format of the simulation sandbox data base adopt the same naming convention. Step S2: Obtain the data to be processed. When the data to be processed is unstructured drawing data, perform data extraction and topology reconstruction on the unstructured drawing data according to the domain object model to obtain the corresponding SHP data, geometric feature data, and structured topology data. When the data to be processed is a domestic BIM forward design model, directly extract the standardized SHP data, geometric feature data, and structured topology data from the domestic BIM forward design model. Step S3: Based on the attribute specifications of the domain object model, perform field-level pass-through mapping on the structured topology data and convert it into simulation element data that conforms to the simulation sandbox data format; Step S4: Convert the SHP data obtained in step S2 to obtain first JSON data. After unifying the coordinates and geometrically regularizing the first JSON data, perform initial topology reconstruction to obtain the data format standard. Step S5: Based on the data format standard established in step S4, the SHP data obtained in step S2 is converted again to obtain the second JSON data, and the coordinates of the second JSON data are unified. Step S6: Based on the geometric feature data and structured topology data obtained in step S2, perform geometric feature completion and line segment merging on the second JSON data; Step S7: Perform final topology reconstruction on the data processed in step S6 to obtain the final topology data; Step S8: Based on the simulation element data obtained in step S3, the final topology data is constructed and labeled to obtain the simulation sandbox data base.

2. The method according to claim 1, characterized in that, Step S1 includes: In the domestic BIM forward design phase, the target format of the simulation sandbox data base is analyzed, all domain object types involved in the target format and the attribute fields corresponding to each domain object are extracted, the data type, business semantics, value range and unit specifications of each attribute field are clarified, and the relationship between each domain object is sorted out to form a standardized simulation sandbox interface specification. Based on the simulation sandbox interface specification and the engineering application requirements of domestic BIM forward design, a unified, hierarchical object system is constructed; wherein, the object system adopts a layered design, with the core layer remaining fixed and the business layer supporting dynamic expansion; Based on the object system, domain objects at each level are constructed, and the hierarchical level, inheritance relationship and unique identifier of each domain object in the object system are defined to ensure that each domain object is a legal leaf node or an extensible node in the object system. The structured data entity of the domain object is defined by dataclass, the core attribute fields and data format of the domain object are fixed, and the discrete attribute values ​​and state types of the domain object are strongly constrained by enumeration type, thus completing the standardized encapsulation of the domain object; Based on the object system, establish the association between the domain objects, construct the topological connections and hierarchical organization between the domain objects through the reference type or foreign key field in the dataclass, and integrate the encapsulated domain objects to form a domain object model compatible with the simulation sandbox data base.

3. The method according to claim 2, characterized in that, Step S2 includes: Obtain the data to be processed and determine the type of the data to be processed; if the data to be processed is unstructured drawing data, parse the file format of the unstructured drawing data, identify the geometric elements in the unstructured drawing data, and remove the annotations, fill patterns and text labels in the unstructured drawing data; Based on the object types defined in the domain object model, the identified geometric features are classified and separated with the goal of each target layer containing only a single type of geometric feature, thus distinguishing the target layers corresponding to different airport infrastructures and removing irrelevant graphs. Each geometric feature in the target layer is encapsulated according to the spatial data format specification of SHP file, and the basic attribute information of each geometric feature is associated to generate SHP data that corresponds one-to-one with each target layer. The geometric and basic attribute information in the SHP data are converted to generate JSON-Like intermediate format data; wherein, the JSON-Like intermediate format data retains the geometric and attribute association relationship of the SHP data, and the field names of the JSON-Like intermediate format data are consistent with the domain object model; Based on the topological association rules of the domain object model, the geometric elements in the JSON-Like intermediate format data are subjected to node generation, node merging, edge relationship construction, node degree calculation and connected component analysis to establish clear association relationships between nodes and edges, forming structured topological data; wherein, node merging adopts a preset tolerance, with a value range of 0.1 to 0.5 meters; Extract the geometric parameters from the JSON-Like intermediate format data to form geometric feature data, and output the SHP data, geometric feature data and structured topology data corresponding to the data to be processed; If the data to be processed is a domestically produced BIM forward design model, directly extract the SHP data, geometric feature data, and structured topology data that have been standardized according to the domain object model specification.

4. The method according to claim 3, characterized in that, Step S3 includes: Based on the attribute specifications of the domain object model, the attribute correspondence between the structured topology data and the target format of the simulation sandbox data base is sorted out, and the mapping rules of each attribute field are clarified. Based on the mapping rules, the attribute fields of each domain object in the structured topology data are directly assigned and mapped to the corresponding fields in the target format of the simulation sandbox data base according to the correspondence of names and meanings; wherein, the geometry and topological association of the structured topology data are not changed during the mapping process, only the corresponding transfer of attribute fields is completed; The mapped data is format-validated, and invalid and abnormal data generated during the mapping process are removed. The validation includes consistency of attribute field names, data type matching, and compliance of value range. If the validation fails, the attribute correspondence is re-examined and the mapping operation is performed again until the validation passes. Based on the results of the format verification, the data that passes the verification is converted into simulation element data that conforms to the simulation sandbox data format.

5. The method according to claim 4, characterized in that, Step S4 includes: Based on the SHP data and the data specifications of the domain object model, a set of hierarchical SHP files to be processed is obtained, and the domain object type, geometric information and basic attributes corresponding to each hierarchical SHP file are determined. The geometric features and basic attribute information in each of the layered SHP files are completely converted into first JSON data; Using a coordinate system consistent with the simulation sandbox data base, all geometric coordinates in the first JSON data are uniformly transformed and calibrated; wherein the calibration error does not exceed 0.01 meters. The broken lines, discontinuous lines, and abnormal endpoints in the first JSON data are corrected to standardize the expression of geometric elements. Among them, line segments with a length of less than 0.3 meters and consistent with the direction of adjacent line segments are identified as broken lines, and isolated endpoints without associated edges are identified as abnormal endpoints. The correction method is to delete isolated endpoints and splice broken lines. Based on the topological association rules of the domain object model, an initial topological reconstruction operation is performed on the first JSON data through node generation, node merging, and edge relationship construction. The generated topological data is then formatted and converted to establish a unified data format standard. The data format standard includes data organization format, field name specification, coordinate system parameters, and topological storage structure.

6. The method according to claim 5, characterized in that, Step S5 includes: Based on the data format standard, the domain object type, geometric information and basic attributes corresponding to each layered SHP file in the layered SHP file set are confirmed. The geometric features and basic attribute information in each of the layered SHP files are completely converted into second JSON data, and the field name specifications and data organization format in the data format standard are strictly followed during the conversion process; Based on the coordinate system of the simulation sandbox data base, all geometric coordinates in the second JSON data are uniformly transformed and calibrated; The system checks whether the data organization format, field names, and coordinate parameters of the second JSON data fully conform to the data format standard. If the check fails, the hierarchical SHP is reconverted into the second JSON data, and the newly converted second JSON data is checked until it passes the check. Finally, the qualified second JSON data is output.

7. The method according to claim 6, characterized in that, Step S6 includes: By comparing the geometric parameters in the second JSON data with the geometric feature data, the missing geometric feature information in the second JSON data is identified; wherein, the missing geometric feature information includes at least: line segment type, arc parameters, and direction angle; Based on the missing geometric feature information, combined with the node connection relationships and connected component features in the structured topology data, and in accordance with the geometric expression specifications of the domain object model, the missing geometric parameters of the second JSON data are supplemented into the corresponding geometric elements; The distribution of line elements in the second JSON data after geometric feature completion is analyzed, and the edge relationships in the structured topology data are combined to identify broken lines, discontinuous lines and redundant segments drawn in segments for the same physical entity. The broken and discontinuous lines in the second JSON data with an interval of no more than 0.3 meters between the endpoints of adjacent line segments and a deviation of no more than 5° are spliced ​​together and integrated, and the expression form of geometric elements is standardized. Perform geometric verification on the merged line elements to confirm that the merged lines have no geometric distortion and that the core geometric parameters are preserved intact. Output the data that completes the geometric feature completion and line segment merging.

8. The method according to claim 7, characterized in that, Step S7 includes: Redundant and abnormal nodes are identified in the data where geometric feature completion and line segment merging have been completed, and node merging and calibration are performed according to the preset tolerance; wherein, the node position deviation after calibration does not exceed 0.01 meters; Based on the core logic of edge relationships in the structured topology data, the edge association relationships corresponding to the merged line elements are verified and corrected, missing edge attributes are supplemented, and the domain object type to which the edge belongs is clarified. Based on the requirements of the airport simulation scenario and the topological constraints of the domain object model, by analyzing the node connectivity degree, line element direction and spatial distribution characteristics in the data after edge association correction, data with a node connectivity degree of no more than 3 are identified as intersections, data with line element direction consistent with the connection between the airport runway and the aircraft stand and with a length of no more than 5 meters are identified as taxiways, and line elements that connect one end to the external area and the other end to the internal topological network of the airport are identified as entrances and exits, and the topological attributes and business meanings of the intersections, taxiways and entrances and exits are labeled. According to the topology storage structure in the data format standard, the nodes, edges and relationships of the data after the topology attributes and business meanings have been labeled are standardized and organized, and the final topology reconstruction is performed to generate the final topology data with complete business topology associations.

9. The method according to claim 8, characterized in that, Step S8 includes: Based on the naming convention of synonymy in the domain object model, the attribute information of each domain object in the simulation element data is accurately associated and matched with the topological units in the final topological data, and each topological unit is assigned a corresponding domain object identity to construct a structured simulation object that corresponds one-to-one with the airport infrastructure. Based on the geometric feature data and the structured topology data, the constructed structured simulation object is fully annotated with attributes, and geometric feature parameters and topological association information are added to the constructed structured simulation object; wherein, the annotation content of the full attribute annotation includes the type, unique number, geometric dimensions and running constraints of each simulation object; Based on the domain object association rules defined in the domain object model and the connectivity relationships in the structured topology data, hierarchical relationships and business association relationships between the structured simulation objects are constructed to form a complete object association network. Based on the data format standard and the target format of the simulation sandbox data base, the standardization of object construction, the accuracy of attribute labeling and the completeness of association relationships in the object association network are verified, abnormal data in the object association network are removed, and the format deviation in the object association network is corrected according to the verification results. The data format standard is integrated and encapsulated according to the target format of the simulation sandbox data base, and finally a simulation sandbox data base that can be directly loaded into the simulation sandbox and has complete geometric information, topological association and business attributes is generated.

10. A simulation sandbox data base construction device, characterized in that, It includes a processor and a memory, wherein the processor is connected to the memory: The processor is used to call and execute the program stored in the memory; The memory is used to store the program, which is at least used to execute the simulation sandbox data base construction method according to any one of claims 1-9.

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