Vector navigation road data updating method and system based on spatial context relationship

Abstract

The invention relates to the technical field of navigation data updating, in particular to a vector navigation road data updating method and system based on a spatial context relation, a Voronoi diagram is constructed based on navigation elements, region segmentation is performed on a navigation road by using the Voronoi diagram, and a navigation road data updating unit is obtained. The navigation elements comprise point elements, line elements and surface elements in the navigation data; the same-name elements in the navigation road data updating unit are judged according to the similarity of the navigation elements, and the same-name elements serve as navigation elements to be updated; the navigation road data updating priority is determined according to the spatial context relation of the navigation elements to be updated, data updating is carried out on the navigation elements according to the priority, and the spatial context relation comprises the geometric features and the topological relation of the navigation elements. According to the method, the optimal data elements are analyzed, evaluated and selected by using the spatial context, so that the accuracy, real-time performance and reliability of the navigation data are ensured, and the updating efficiency and precision of the navigation data are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of navigation data updating, and in particular to a method and system for updating vector navigation road data based on spatial contextual relationship. Background Art

[0002] Road-level navigation enables the navigation system to restore lanes, lane lines, time-divided bus lanes and other real road details one-to-one, provide real-time and accurate navigation guidance, avoid continuous and multiple lane changes, ensure driving safety, and improve driving experience. At present, in the process of using multi-source data to update navigation data, there are problems such as poor consistency, data overlap, data conflict, unclear data update timeliness, different data accuracy and integrity, etc. from multiple data sources, which makes it difficult to judge the data priority during the navigation data update process, and it is difficult to finally determine the selection of navigation elements and data updates. Summary of the invention

[0003] To this end, the present invention provides a vector navigation road data updating method and system based on spatial context relationship, which solves the priority judgment and selection problems existing in the fusion of multi-source vector navigation data.

[0004] According to the design scheme provided by the present invention, on the one hand, a vector navigation road data updating method based on spatial context relationship is provided, comprising:

[0005] Constructing a Voronoi diagram based on navigation elements, and using the Voronoi diagram to perform regional segmentation on the navigation road, and obtaining a navigation road data update unit, wherein the navigation elements include point elements, line elements, and surface elements in the navigation data;

[0006] Using the similarity of navigation elements, determine the elements with the same name in the navigation road data update unit, and use the elements with the same name as the navigation elements to be updated;

[0007] The updating priority of the navigation road data is determined according to the spatial context relationship of the navigation elements to be updated, so as to update the data of the navigation elements according to the priority, wherein the spatial context relationship includes the geometric features and topological relationship of the navigation elements.

[0008] As a vector navigation road data updating method based on spatial context relationship of the present invention, further, a Voronoi diagram is constructed based on navigation elements, comprising:

[0009] Collecting the vector navigation data to be updated and the reference vector navigation data, wherein the vector navigation data to be updated and the reference vector navigation data both include road sections and points of interest;

[0010] The navigation line elements in both the vector navigation data to be updated and the reference vector navigation data are extracted, and a Voronoi diagram is constructed according to the navigation line elements.

[0011] As a vector navigation road data updating method based on spatial context relationship of the present invention, further, a Voronoi diagram is constructed according to navigation line elements, comprising:

[0012] Selecting seed points according to the road sections in the vector navigation data to be updated;

[0013] Extracting additional seed points from road segments in the reference vector navigation data;

[0014] Merging the selected seed points and the extracted additional seed points to form an initial seed point list;

[0015] Use the minimum distance threshold to screen various seed points in the initial seed point list to ensure that the distance between seed points is not less than the minimum distance threshold;

[0016] Construct the Voronoi diagram using the selected seed points.

[0017] As a vector navigation road data updating method based on spatial context relationship of the present invention, further, seed points are selected according to road sections in the vector navigation data to be updated, comprising:

[0018] If the length of the road segment is less than the threshold, the midpoint of the road segment is selected as the seed point. If the length of the road segment is greater than the threshold, multiple seed points are generated at specified intervals.

[0019] As a vector navigation road data updating method based on spatial context relationship of the present invention, further, extracting additional seed points from road sections in the reference vector navigation data comprises:

[0020] If the road segment is a point feature, the road segment will be directly used as an additional seed point. If the road segment is a line feature, multiple additional seed points will be generated at specified intervals. If the road segment is a surface feature, additional seed points will be generated based on the centroid of the surface feature or the area of ​​the surface feature.

[0021] As a vector navigation road data updating method based on spatial contextual relationship of the present invention, further, using the similarity of navigation elements to judge the same-name elements in the navigation road data updating unit, it includes:

[0022] The geometric similarity between the source and target entities in the navigation element is calculated using the Fréchet distance;

[0023] The relative error is used to calculate the similarity of numerical type attributes, the Hamming distance is used to calculate the similarity of coding type attributes, and the edit distance is used to calculate the similarity of text type attributes. The attribute similarity between entities in the navigation elements is obtained by combining the similarities of various types of attributes.

[0024] If the geometric similarity and attribute similarity between two entities in the navigation element are both higher than the similarity threshold, the two entities are determined to be elements with the same name.

[0025] As a vector navigation road data updating method based on spatial context relationship of the present invention, further, determining the navigation road data updating priority according to the spatial context relationship of the navigation element to be updated comprises:

[0026] The number and distance of adjacent elements of the navigation element to be updated are obtained according to the proximity relationship between the navigation element to be updated and the surrounding elements, the number and type of connected elements of the navigation element to be updated are calculated according to the connectivity of the navigation element to be updated in the network, and the network centrality index of the navigation element to be updated is calculated according to the degree centrality, closeness centrality or betweenness centrality;

[0027] The priority score of each navigation element to be updated is calculated by comprehensively considering the adjacent elements, connection elements and network centrality indicators of the navigation elements to be updated and using the weighted average method.

[0028] In another aspect, the present invention further provides a vector navigation road data updating system based on spatial contextual relationship, comprising: an updating unit building module, an entity similarity judgment module and a navigation element updating module, wherein:

[0029] An update unit construction module is used to construct a Voronoi diagram based on navigation elements, and use the Voronoi diagram to perform regional segmentation on the navigation road to obtain a navigation road data update unit, wherein the navigation elements include point elements, line elements and surface elements in the navigation data;

[0030] An entity similarity judgment module, used to judge the elements with the same name in the navigation road data update unit by using the similarity of the navigation elements, and use the elements with the same name as the navigation elements to be updated;

[0031] The navigation element updating module is used to determine the updating priority of the navigation road data according to the spatial context relationship of the navigation element to be updated, so as to update the data of the navigation element according to the priority, wherein the spatial context relationship includes the geometric features and topological relationship of the navigation element.

[0032] Beneficial effects of the present invention:

[0033] 1. The present invention constructs a Voronoi diagram based on navigation elements to determine the update unit, uses the similarity of navigation elements in the navigation unit to determine the elements with the same name as the elements to be updated, determines the data priority of the spatial context relationship of the elements with the same name to update the data, and uses the spatial context analysis to evaluate and select the optimal data elements, thereby ensuring the accuracy, real-time and reliability of the navigation data and improving the efficiency and precision of the navigation data update.

[0034] 2. The present invention uses Voronoi diagram segmentation technology to adaptively determine data update units according to the spatial distribution of navigation elements. It has strong adaptability and can effectively determine reasonable update areas regardless of the size of the data and the complexity of the distribution. It also comprehensively evaluates the similarity of navigation elements through geometric similarity, attribute similarity, and topological similarity, accurately identifies the elements to be updated, avoids unnecessary update operations, and improves update efficiency; it determines the update priority by analyzing the spatial context relationship, and gives priority to updating high-priority elements that have a great impact on the network, ensuring the timeliness and accuracy of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The following is a schematic diagram of a vector navigation road data update process based on a spatial context relationship in an embodiment;

[0036] Figure 2 It is a schematic diagram of the principle architecture of updating navigation vector data taking into account spatial context information in an embodiment. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present invention clearer and more understandable, the present invention is further described in detail below in conjunction with the accompanying drawings and technical solutions.

[0038] Embodiments of the present invention, see Figure 1 As shown, a method for updating vector navigation road data based on spatial context relationship is provided, comprising:

[0039] S101, constructing a Voronoi diagram based on navigation elements, and using the Voronoi diagram to segment navigation roads into regions, and obtaining a navigation road data update unit, wherein the navigation elements include point elements, line elements, and surface elements in the navigation data.

[0040] The point, line and surface elements in the navigation data represent different geographic information elements. For example, point elements usually represent single location markers, such as connection points, road signs, traffic lights, traffic signs, and road marking lights. These elements are displayed separately as points on the map. Line elements represent geographic entities with a certain length, such as roads, ferry elements, regional boundaries, and road marking lights. They are displayed as lines on the map to indicate the direction and path of the geographic entity. Surface elements represent areas with a certain area, such as regions and land cover lights. They are stored as discrete point strings and displayed as closed graphics when rendered to indicate the scope and area of ​​the geographic entity.

[0041] Specifically, the Voronoi diagram is constructed based on the navigation elements and can be designed to include:

[0042] Collecting the vector navigation data to be updated and the reference vector navigation data, wherein the vector navigation data to be updated and the reference vector navigation data both include road sections and points of interest;

[0043] The navigation line elements in both the vector navigation data to be updated and the reference vector navigation data are extracted, and a Voronoi diagram is constructed according to the navigation line elements.

[0044] Among them, the Voronoi diagram is constructed according to the navigation line features, including:

[0045] A seed point is selected according to the road section in the vector navigation data to be updated; if the length of the road section is less than a threshold, the midpoint of the road section is selected as the seed point; if the length of the road section is greater than the threshold, multiple seed points are generated at a specified interval.

[0046] Additional seed points are extracted from the road segments in the reference vector navigation data; if the road segment is a point feature, the road segment is directly used as the additional seed point; if the road segment is a line feature, multiple additional seed points are generated at specified intervals; if the road segment is a surface feature, additional seed points are generated based on the centroid of the surface feature or the area of ​​the surface feature.

[0047] Merging the selected seed points and the extracted additional seed points to form an initial seed point list;

[0048] Use the minimum distance threshold to screen various seed points in the initial seed point list to ensure that the distance between seed points is not less than the minimum distance threshold;

[0049] The Voronoi diagram is constructed using the screened seed points to generate Voronoi polygons and segment the data with navigation features by determining the boundaries of each Voronoi cell.

[0050] S102: using the similarity of navigation elements, determine the elements with the same name in the navigation road data update unit, and use the elements with the same name as navigation elements to be updated.

[0051] Specifically, determining the elements with the same name in the navigation road data update unit by using the similarity of the navigation elements may include:

[0052] The geometric similarity between the source and target entities in the navigation element is calculated using the Fréchet distance;

[0053] The relative error is used to calculate the similarity of numerical type attributes, the Hamming distance is used to calculate the similarity of coding type attributes, and the edit distance is used to calculate the similarity of text type attributes. The attribute similarity between entities in the navigation elements is obtained by combining the similarities of various types of attributes.

[0054] If the geometric similarity and attribute similarity between two entities in the navigation element are both higher than the similarity threshold, the two entities are determined to be elements with the same name.

[0055] Among them, when combining the similarities of various types of attributes, the following formula can be used to obtain the attribute similarity between entities in the navigation elements:

[0056] Attribute similarity = (numeric similarity + encoding similarity + text similarity) / 3

[0057] S103, determining the navigation road data update priority according to the spatial context relationship of the navigation element to be updated, so as to update the navigation element data according to the priority, wherein the spatial context relationship includes the navigation element geometric features and topological relationship.

[0058] Specifically, determining the update priority of the navigation road data according to the spatial context relationship of the navigation elements to be updated may include:

[0059] The number and distance of adjacent elements of the navigation element to be updated are obtained according to the proximity relationship between the navigation element to be updated and the surrounding elements, the number and type of connected elements of the navigation element to be updated are calculated according to the connectivity of the navigation element to be updated in the network, and the network centrality index of the navigation element to be updated is calculated according to the degree centrality, closeness centrality or betweenness centrality;

[0060] The priority score of each navigation element to be updated is calculated by comprehensively considering the adjacent elements, connection elements and network centrality indicators of the navigation elements to be updated and using the weighted average method.

[0061] By analyzing the proximity relationship between the elements to be updated and the surrounding elements, the number and distance of adjacent elements are calculated. Elements with a large number of adjacent elements and close distances usually have higher importance in the network. By analyzing the connectivity of the elements to be updated in the network, the number and type of connected elements (such as intersections, bridges, etc.) are calculated. Elements with strong connectivity usually have higher importance in the network. Calculate the network centrality indicators of the elements to be updated, such as degree centrality, closeness centrality, and betweenness centrality. Elements with high centrality usually have higher importance in the network.

[0062] Taking into account factors such as proximity, connectivity, and network centrality, a weighted average method is used to combine the influence of various factors and assign a priority score to each feature to be updated, so that navigation features are updated according to the priority scores of features with the same name.

[0063] Furthermore, based on the above method, an embodiment of the present invention also provides a vector navigation road data updating system based on spatial context relationship, comprising: an updating unit construction module, an entity similarity judgment module and a navigation element updating module, wherein:

[0064] An update unit construction module is used to construct a Voronoi diagram based on navigation elements, and use the Voronoi diagram to perform regional segmentation on the navigation road to obtain a navigation road data update unit, wherein the navigation elements include point elements, line elements and surface elements in the navigation data;

[0065] An entity similarity judgment module, used to judge the elements with the same name in the navigation road data update unit by using the similarity of the navigation elements, and use the elements with the same name as the navigation elements to be updated;

[0066] The navigation element updating module is used to determine the updating priority of the navigation road data according to the spatial context relationship of the navigation element to be updated, so as to update the data of the navigation element according to the priority, wherein the spatial context relationship includes the geometric features and topological relationship of the navigation element.

[0067] See also Figure 2 As shown, it includes three parts. The first is to generate initial seed points according to the navigation line elements, use the Voronoi diagram to perform regional segmentation, and determine the data update unit; the second is to calculate the geometric similarity, attribute similarity and topological similarity of the navigation elements, obtain a comprehensive similarity index, and identify the navigation elements to be updated; the third is to analyze the spatial context relationship of the elements to be updated, including proximity, connectivity and network centrality, etc. to determine the update priority, give priority to updating high-priority elements, and update the navigation data.

[0068] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present invention.

[0069] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0070] The units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person of ordinary skill in the art may use different methods to implement the described functions for each specific application, but such implementation is not considered to be beyond the scope of the present invention.

[0071] Those skilled in the art will appreciate that all or part of the steps in the above method can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, such as a read-only memory, a disk or an optical disk. Optionally, all or part of the steps in the above embodiment can also be implemented using one or more integrated circuits, and accordingly, each module / unit in the above embodiment can be implemented in the form of hardware or in the form of software function modules. The present invention is not limited to any specific form of combination of hardware and software.

[0072] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for updating vector navigation road data based on spatial context, characterized in that: Include: Constructing a Voronoi diagram based on navigation elements, and using the Voronoi diagram to perform regional segmentation on the navigation road, and obtaining a navigation road data update unit, wherein the navigation elements include point elements, line elements, and surface elements in the navigation data; Using the similarity of navigation elements, determine the elements with the same name in the navigation road data update unit, and use the elements with the same name as the navigation elements to be updated; The updating priority of the navigation road data is determined according to the spatial context relationship of the navigation elements to be updated, so as to update the data of the navigation elements according to the priority, wherein the spatial context relationship includes the geometric features and topological relationship of the navigation elements.

2. The method for updating vector navigation road data based on spatial context relationship according to claim 1, characterized in that: Construct a Voronoi diagram based on navigation features, including: Collecting the vector navigation data to be updated and the reference vector navigation data, wherein the vector navigation data to be updated and the reference vector navigation data both include road sections and points of interest; The navigation line elements in both the vector navigation data to be updated and the reference vector navigation data are extracted, and a Voronoi diagram is constructed according to the navigation line elements.

3. The method for updating vector navigation road data based on spatial context relationship according to claim 2, characterized in that: Construct a Voronoi diagram based on the navigation line features, including: Selecting seed points according to the road sections in the vector navigation data to be updated; Extracting additional seed points from road segments in the reference vector navigation data; Merging the selected seed points and the extracted additional seed points to form an initial seed point list; The various seed points in the initial seed point list are screened using the minimum distance threshold to ensure that the distance between seed points is not less than the minimum distance threshold; Construct the Voronoi diagram using the selected seed points.

4. The method for updating vector navigation road data based on spatial context relationship according to claim 3, characterized in that: Selecting seed points according to the road sections in the vector navigation data to be updated includes: If the length of the road segment is less than the threshold, the midpoint of the road segment is selected as the seed point. If the length of the road segment is greater than the threshold, multiple seed points are generated at specified intervals.

5. The method for updating vector navigation road data based on spatial context relationship according to claim 3, characterized in that: Extract additional seed points from the road segments in the reference vector navigation data, including: If the road segment is a point feature, the road segment will be directly used as an additional seed point. If the road segment is a line feature, multiple additional seed points will be generated at specified intervals. If the road segment is a surface feature, additional seed points will be generated based on the centroid of the surface feature or the area of ​​the surface feature.

6. The method for updating vector navigation road data based on spatial context relationship according to claim 1, characterized in that: Using the similarity of navigation elements to determine the elements with the same name in the navigation road data update unit, including: The geometric similarity between the source and target entities in the navigation element is calculated using the Fréchet distance; The relative error is used to calculate the similarity of numerical type attributes, the Hamming distance is used to calculate the similarity of coding type attributes, and the edit distance is used to calculate the similarity of text type attributes. The attribute similarity between entities in the navigation elements is obtained by combining the similarities of various types of attributes. If the geometric similarity and attribute similarity between two entities in the navigation element are both higher than the similarity threshold, the two entities are determined to be elements with the same name.

7. The method for updating vector navigation road data based on spatial context relationship according to claim 1, characterized in that: The update priority of navigation road data is determined according to the spatial context relationship of the navigation elements to be updated, including: The number and distance of adjacent elements of the navigation element to be updated are obtained according to the proximity relationship between the navigation element to be updated and the surrounding elements, the number and type of connected elements of the navigation element to be updated are calculated according to the connectivity of the navigation element to be updated in the network, and the network centrality index of the navigation element to be updated is calculated according to the degree centrality, closeness centrality or betweenness centrality; The priority score of each navigation element to be updated is calculated by comprehensively considering the adjacent elements, connection elements and network centrality indicators of the navigation elements to be updated and using the weighted average method.

8. A vector navigation road data updating system based on spatial context relationship, characterized in that: It includes: update unit construction module, entity similarity judgment module and navigation element update module, among which, An update unit construction module is used to construct a Voronoi diagram based on navigation elements, and use the Voronoi diagram to perform regional segmentation on the navigation road to obtain a navigation road data update unit, wherein the navigation elements include point elements, line elements and surface elements in the navigation data; An entity similarity judgment module, used to judge the elements with the same name in the navigation road data update unit by using the similarity of the navigation elements, and use the elements with the same name as the navigation elements to be updated; The navigation element updating module is used to determine the updating priority of the navigation road data according to the spatial context relationship of the navigation element to be updated, so as to update the data of the navigation element according to the priority, wherein the spatial context relationship includes the geometric features and topological relationship of the navigation element.

9. An electronic device, characterized in that: include: at least one processor, and a memory coupled to the at least one processor; The memory stores a computer program, and the computer program can be executed by the at least one processor to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the method according to any one of claims 1 to 7 can be implemented.

Images