CN115408410A - Method, device and equipment for matching electronic map data and map acquisition data - Google Patents

Abstract

The embodiment of the specification discloses a method, a device and equipment for matching electronic map data and map acquisition data. The scheme can comprise the following steps: acquiring map acquisition data acquired by map data acquisition equipment; determining a map element data set according to the relevant data of the first map element at the target road section in the map acquisition data and the relevant data of the second map element at the target road section in the electronic map data; constructing an undirected weighted graph according to the map element data set; and determining the first target complete sub-graph with the largest sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data. Therefore, the accuracy of the matching result of the map acquisition data and the electronic map data is improved, and the dependency of the accuracy of the matching result on the absolute accuracy acquired by the map data acquisition equipment is reduced.

Description

Method, device and equipment for matching electronic map data with map acquisition data

Technical Field

The application relates to the technical field of high-precision maps, in particular to a method, a device and equipment for matching electronic map data with map collected data.

Background

An Electronic map (digital map) is a map that is digitally stored and referred to using computer technology. The electronic map comprises a high-precision map, and the high-precision map provides important technical support for automatic driving. In order to ensure the real-time performance of the electronic map, the electronic map needs to be updated regularly.

At present, high-precision maps are updated according to high-precision crowd-sourced map data. In the process of updating the high-precision map by using the high-precision crowd-sourced map data, for each map element in the high-precision map, determining target map acquisition data corresponding to the map element in the map acquisition data acquired by the map data acquisition equipment, and updating the corresponding map element in the high-precision map according to the target map acquisition data.

However, in the related art, since the map data matching is performed only according to the absolute accuracy of the map data acquisition device, when the absolute accuracy of the map data acquisition device is low, the accuracy of the matching result of the map data acquired by the map data acquisition device and the electronic map data of the high-accuracy map is also low, thereby affecting the accuracy of the update result of the high-accuracy map. The absolute accuracy refers to the difference between the position data of a certain map element acquired by the map data acquisition device and the actual position data of the map element.

Disclosure of Invention

The embodiment of the specification provides a method, a device and equipment for matching electronic map data and map collected data, and aims to solve the technical problems that in the related art, the accuracy of the matching result of the map collected data and the electronic map data is low, and the accuracy of the matching result depends on the absolute accuracy of the map data collecting equipment.

In order to solve the above technical problem, the embodiments of the present specification are implemented as follows:

an embodiment of the present specification provides a method for matching electronic map data with map collection data, including:

acquiring map acquisition data acquired by map data acquisition equipment;

determining a map element data set according to the relevant data of a first map element at a target road section in the map acquisition data and the relevant data of a second map element at the target road section in the electronic map data;

constructing an undirected weighted graph according to the map element data set; the weight value of the vertex of the undirected weighted graph is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the connecting edge of the undirected weighted graph is used for reflecting that the difference degree between the map element position relations of the two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex;

and determining a first target complete subgraph with the maximum sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data.

An embodiment of the present specification provides a matching device for electronic map data and map acquisition data, including:

the map data acquisition module is used for acquiring map data acquired by the map data acquisition equipment;

the map element data set determining module is used for determining a map element data set according to the relevant data of the first map element at the target road section in the map acquisition data and the relevant data of the second map element at the target road section in the electronic map data;

the undirected weighted graph construction module is used for constructing an undirected weighted graph according to the map element data set; the weight value of the vertex of the undirected weighted graph is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the connecting edge of the undirected weighted graph is used for reflecting that the difference degree between the map element position relations of the two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex;

and the first target complete sub-graph determining module is used for determining a first target complete sub-graph with the largest sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data.

The matching device for electronic map data and map acquisition data provided by the embodiment of the specification comprises:

at least one processor; and the number of the first and second groups,

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to cause the at least one processor to:

acquiring map acquisition data acquired by map data acquisition equipment;

determining a map element data set according to the relevant data of the first map element at the target road section in the map acquisition data and the relevant data of the second map element at the target road section in the electronic map data;

constructing an undirected weighted graph according to the map element data set; the weight value of the vertex of the undirected weighted graph is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the connecting edge of the undirected weighted graph is used for reflecting that the difference degree between the map element position relations of the two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex;

and determining a first target complete subgraph with the maximum sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data.

At least one embodiment provided in the present specification can achieve the following advantageous effects: after map acquisition data acquired by map data acquisition equipment is acquired, determining a map element data set according to relevant data of a first map element at a target road section in the map acquisition data and relevant data of a second map element at the target road section in electronic map data; constructing an undirected weighted graph according to the map element data set; the weight value of the vertex of the undirected weighted graph is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the connecting edge of the undirected weighted graph is used for reflecting that the difference degree between the map element position relations of the two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex; and determining a first target complete sub-graph with the largest sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data. Based on the method, the undirected weighted graph is constructed, and the process of determining the optimal matching result is converted into the process of determining the complete subgraph with the maximum sum of the weighted values, so that all the matching results are comprehensively considered, and the accuracy of the matching result of the map acquisition data and the electronic map data is improved; and because the connecting edge of the undirected weighted graph can be used for reflecting the difference between the map element position relations of the two vertexes corresponding to the connecting edge and is positioned in the preset difference range, the accuracy of the matching result can be ensured when the absolute precision of the map data acquisition equipment is lower, the dependency on the absolute precision acquired by the map data acquisition equipment is reduced, the accuracy of the matching result of the map acquisition data and the electronic map data can be improved when the absolute precision of the map data acquisition equipment is lower, and the accuracy of the matching result of the map acquisition data and the electronic map data can be further improved when the absolute precision of the map data acquisition equipment is higher.

Drawings

In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.

Fig. 1 is a schematic flowchart of a method for matching electronic map data with map collection data according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a vertex construction provided by an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a device for matching electronic map data and map collection data according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of a device for matching electronic map data and map collection data according to an embodiment of the present disclosure.

Detailed Description

To make the objects, technical solutions and advantages of one or more embodiments of the present disclosure more apparent, the technical solutions of one or more embodiments of the present disclosure will be clearly and completely described below with reference to specific embodiments of the present disclosure and the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments that can be derived by a person skilled in the art from the embodiments given herein without making any creative effort fall within the scope of protection of one or more embodiments of the present specification.

The technical solutions provided by the embodiments of the present description are described in detail below with reference to the accompanying drawings.

Fig. 1 is a schematic flowchart of a method for matching electronic map data and map collection data in an embodiment of the present specification. From the perspective of equipment, the executing body of the process may be a server, and from the perspective of a program, the executing body of the process may be an application program loaded in the server for matching the electronic map data with the map collecting data. As shown in fig. 1, the process may include the following steps:

step 101, acquiring map acquisition data acquired by map data acquisition equipment.

Specifically, the map acquisition data is vector semantic data generated based on map data acquired by the map data acquisition device, and includes position data and semantic data of map elements. The semantic data is used to reflect attributes of the map elements, such as element types of the map elements (e.g., a straight ground arrow or a left turn ground arrow), colors of the map elements, width values of the map elements, and the like.

In practical applications, the map data acquisition device is often mounted on a vehicle, the vehicle runs along a road to be acquired, and the map data acquisition device acquires data related to map elements passing by the vehicle during the running process of the vehicle.

Step 102, determining a map element data set according to the relevant data of the first map element at the target road section in the map acquisition data and the relevant data of the second map element at the target road section in the electronic map data.

In detail, the data volume of the collected data is often large due to the map collected each time. In order to improve the matching efficiency, the data related to the first map element at the target road section is selected from the map collected data, and the data related to the second map element at the target road section is selected from the electronic map data, so as to form a map element data set, and the electronic map data and the map collected data are matched based on the map element data set. The electronic map data may be related data of a high-precision map stored in a preset database.

103, constructing an undirected weighted graph according to the map element data set; for each vertex of the undirected weighted graph, the first map element corresponding to the vertex is matched with the second map element corresponding to the vertex, and the weight value of the vertex is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; for each connecting edge of the undirected weighted graph, the connecting edge is used for reflecting that the difference degree between the map element position relations of two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex.

In actual application, first, each vertex of the undirected weighted graph is constructed. The construction method of each vertex of the undirected weighted graph is the same, and the construction method of any vertex of the undirected weighted graph can be as follows:

for any one first map element, determining a target second map element with the same element type as that of the first map element from the second map elements; and if the distance value between the first map element and any one of the target second map elements is within a preset distance range, constructing a vertex in the undirected weighted graph by using the first map element and any one of the target second map elements.

The preset distance range represents the absolute accuracy requirement of the method for the map data acquisition device, for example, when the preset distance range is set to be 0-30 meters, the map acquisition data acquired by the map data acquisition device with the absolute accuracy within 0-30 meters can be used in the embodiment. Therefore, the number of vertexes of the undirected weighted graph is reduced, the matching efficiency is improved, and meanwhile, the accuracy of the matching result is ensured.

In a specific application process, after the map element data set is acquired, each first map element in the map element data set is traversed, and when any first map element (assumed as the first map element R1) is traversed, a target second map element (the number of the target second map elements is at least one) which is the same as the element type of the first map element R1 is determined in the map element data set. Then, a distance value between the first map element R1 and an arbitrary target second map element (assumed to be the second map element M1) is calculated from the position data of the map elements in the map element data set, and if the distance value is within a preset distance range, one vertex (R1, M1) in the undirected weighted graph is constructed using the first map element R1 and the second map element M1.

To illustrate the above in more detail, the following is exemplified. Fig. 2 is a schematic diagram of vertex construction provided in an embodiment of the present specification. As shown in fig. 2, a solid line in the figure represents a ground mark line collected by the map data collecting device, a dotted line represents a ground mark line in the electronic map data, and the distance value between the two ground mark lines is calculated to be within a preset distance range, so that a vertex in the undirected weighted graph can be constructed by using the two ground mark lines.

Then, the connected edges of the undirected weighted graph are constructed. The construction method of each connecting edge of the undirected weighted graph is the same, and the construction method of any connecting edge of the undirected weighted graph can be as follows:

for each vertex in the undirected weighted graph, if a first map element corresponding to the vertex is a point element, determining a transverse directional distance and a longitudinal directional distance between the first map element corresponding to the vertex and the second map element corresponding to the vertex according to the related data of the first map element corresponding to the vertex and the related data of the second map element corresponding to the vertex; and if the first map element corresponding to the vertex is a line element, determining the transverse directional distance between the first map element corresponding to the vertex and the second map element corresponding to the vertex according to the relevant data of the first map element corresponding to the vertex and the relevant data of the second map element corresponding to the vertex.

Then, for any two vertexes in the undirected weighted graph, if a first map element corresponding to at least one vertex in the any two vertexes is a line element, whether the difference degree between the transverse directed distances corresponding to the any two vertexes is within a first preset difference degree range is judged, and if the difference degree between the transverse directed distances corresponding to the any two vertexes is within the first preset difference degree range, one connecting edge is constructed between the any two vertexes. And if the first map elements corresponding to any two vertexes are point elements, judging whether the difference degree between the transverse directed distances corresponding to any two vertexes is located in a first preset difference degree range, judging whether the difference degree between the longitudinal directed distances corresponding to any two vertexes is located in a second preset difference degree range, and if the difference degree between the transverse directed distances corresponding to any two vertexes is located in the first preset difference degree range, constructing a connecting edge between any two vertexes if the difference degree between the longitudinal directed distances corresponding to any two vertexes is located in the second preset difference degree range.

To illustrate the above in more detail, the following is exemplified. It is assumed that vertices V1 (R1, M1) and vertices V2 (R2, M2) are arbitrary two vertices of the undirected weighted graph, and that R1 and R2 both belong to a first map element whose element type is a point element, and that M1 and M2 both belong to a second map element whose element type is a point element. In constructing a connecting edge of the undirected weighted graph using vertex V1 (R1, M1) and vertex V2 (R2, M2), it can be: the transverse directional distance of the vertex V1 (R1, M1) is calculated first, and specifically, the transverse coordinate of the second map element M1 is subtracted from the transverse coordinate of the first map element R1 to obtain the transverse directional distance D1. Next, the lateral directional distance of the vertex V2 (R2, M2) is calculated, and specifically, the lateral coordinate of the second map element M2 is subtracted from the lateral coordinate of the first map element R2 to obtain the lateral directional distance D2. Then, the absolute value of the difference between the lateral directed distance D1 and the lateral directed distance D2, i.e., | D1-D2| is calculated. Meanwhile, the longitudinal directional distance of the vertex V1 (R1, M1) is calculated, specifically, the longitudinal coordinate of the second map element M1 is subtracted from the longitudinal coordinate of the first map element R1 to obtain a longitudinal directional distance d1. Next, the longitudinal directional distance of the vertex V2 (R2, M2) is calculated, specifically, the longitudinal coordinate of the second map element M2 is subtracted from the longitudinal coordinate of the first map element R2 to obtain the longitudinal directional distance d2. Then, the absolute value of the difference between the longitudinal directed distance d1 and the longitudinal directed distance d2, i.e., | d1-d2| is calculated. Finally, if the absolute value | D1-D2| is within the first preset difference range and the absolute value | D1-D2| is within the second preset difference range, a connecting edge of the undirected weighted graph is constructed between the vertex V1 (R1, M1) and the vertex V2 (R2, M2).

The lateral direction is a direction perpendicular to the road traveling direction, and the longitudinal direction is a direction parallel to the road traveling direction.

In addition, after each vertex of the undirected weighted graph is constructed, the weight value of each vertex can also be determined. The determination method of the weight value of each top point of the undirected weighted graph is the same, and the determination method of the weight value of any top point can be as follows:

calculating map element attribute similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex aiming at any vertex in the undirected weighted graph; then, according to the at least one of the category and the length of the second map element corresponding to the vertex, calculating the importance degree value of the vertex; and finally, calculating the product of the map element attribute similarity and the importance degree value to obtain the weight value of the vertex.

Preferably, the calculating of the map element attribute similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex may specifically include:

determining a target attribute of the first map element corresponding to the vertex; then, aiming at each target attribute, adopting a preset attribute similarity calculation rule corresponding to the type of the target attribute to calculate the target attribute similarity of the target attribute; and finally, calculating the average value of the target attribute similarity of the target attribute to obtain the map element attribute similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex.

Preferably, the calculating the target attribute similarity of the target attribute by using a preset attribute similarity calculation rule corresponding to the type of the target attribute specifically includes:

if the type of the target attribute is a continuous attribute, determining the first target attribute similarity of the target attribute according to the map element similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the map element similarity is positively correlated with the first target attribute similarity.

If the type of the target attribute is a discrete attribute, determining second target attribute similarity of the target attribute according to the element type of the first map element corresponding to the vertex and the element type of the second map element corresponding to the vertex; when the similarity of the second target attribute is a first preset value, the element type of the first map element corresponding to the vertex is the same as the element type of the second map element corresponding to the vertex; and when the similarity of the second target attribute is a second preset value, the element type of the first map element corresponding to the vertex is different from the element type of the second map element corresponding to the vertex.

In an actual application process, if the type of the target attribute is a continuous attribute, the target attribute similarity corresponding to the target attribute may be calculated according to the following calculation formula:

wherein R is _i As a first map element, M _i Is a second map element; similarity _(Continuous) (R _i ，M _i ) Attribute value (R) for target attribute similarity _i ) Is an attribute value of the first map element; attribute (M) _i ) Is the attribute value of the second map element.

In order to explain the above calculation formula in more detail, the following is exemplified. For example, the first map element and the second map element corresponding to a vertex are both ground level lines. For the ground reticle, the attribute of the ground reticle comprises the width, and the method for calculating the similarity of the target attribute corresponding to the width attribute for the vertex is as follows:

wherein S is _{Width of} The target attribute similarity corresponding to the width attribute of the first map element.

Secondly, if the type of the target attribute is a discrete attribute, calculating the target attribute similarity of the target attribute according to the following calculation formula:

in the above example, the attributes of the ground reticle may also include color and reticle type. The similarity of the target attributes corresponding to the color attributes is as follows:

wherein S is _Colour(s) The target attribute similarity corresponding to the color attribute of the first map element.

The similarity of the target attributes corresponding to the reticle types is as follows:

wherein S is _{Type (B)} The target attribute similarity corresponding to the reticle-type attribute of the first map element.

Finally, after determining the target attribute similarity corresponding to each attribute of the ground marked line, calculating S _{Width of} 、S _Colour(s) And S _{Types of} Average value of (2)(i.e., (S) _{Width of} +S _Colour(s) +S _{Type (B)} ) And/3) obtaining the attribute similarity of the map elements of the vertex.

Preferably, the calculating the importance degree value of the vertex according to at least one of the category and the length of the second map element corresponding to the vertex specifically includes:

judging whether the first map element corresponding to the vertex is a point element or not; if the first map element corresponding to the vertex is a point element, determining that the importance degree value of the vertex is a third preset value; if the first map element corresponding to the vertex is not a point element, determining an importance degree value aiming at the vertex according to the element length of the second map element corresponding to the vertex; the element length of the second map element corresponding to the vertex is positively correlated with the importance degree value of the vertex.

In a specific application process, the importance value of the vertex can be calculated according to the following calculation formula:

wherein, length (R) _i ，M _i ) Is the importance degree value of the vertex; the UNIT is a preset constant, and specifically can be set to 100, 200, 300 and the like, and the UNIT is meter.

And 104, determining a first target complete sub-graph with the largest sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data.

Specifically, each complete subgraph of the undirected weighted graph is a matching result, and the greater the sum of the weight values of the complete subgraphs is, the higher the accuracy of the matching result corresponding to the complete subgraph is. After the complete subgraph with the largest sum of the weight values is determined, the matching result corresponding to the complete subgraph with the largest sum of the weight values can be determined according to each vertex included in the complete subgraph with the largest sum of the weight values.

In this embodiment, with the above technical solution, after map acquisition data acquired by the map data acquisition device is acquired, a map element data set is determined according to data related to a first map element at a target road segment in the map acquisition data and data related to a second map element at the target road segment in the electronic map data; constructing an undirected weighted graph according to the map element data set; aiming at each vertex of the undirected weighted graph, matching a first map element corresponding to the vertex with a second map element corresponding to the vertex, wherein the weight value of the vertex is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; aiming at each connecting edge of the undirected weighted graph, the connecting edge is used for reflecting that the difference between the map element position relations of two vertexes corresponding to the connecting edge is within a preset difference range; the map element position relation is the position relation of a first map element corresponding to any vertex relative to a second map element corresponding to any vertex; and determining a first target complete sub-graph with the largest sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data. Based on the method, the process of determining the optimal matching result is converted into the process of determining the complete subgraph with the maximum sum of the weight values, so that all matching results are comprehensively considered, and the accuracy of the matching result of the map acquisition data and the electronic map data is improved; and because the connecting edge of the undirected weighted graph can be used for reflecting the difference between the map element position relations of the two vertexes corresponding to the connecting edge and is positioned in the preset difference range, the accuracy of the matching result can be ensured when the absolute precision of the map data acquisition equipment is lower, the dependency on the absolute precision acquired by the map data acquisition equipment is reduced, the accuracy of the matching result of the map acquisition data and the electronic map data can be improved when the absolute precision of the map data acquisition equipment is lower, and the accuracy of the matching result of the map acquisition data and the electronic map data can be further improved when the absolute precision of the map data acquisition equipment is higher.

Preferably, in step 104, determining a first target complete sub-graph with a largest sum of the weight values from the undirected weighted graph may specifically include:

and acquiring each complete subgraph in the undirected weighted graph.

And determining the sum of the weight values of the top points corresponding to each complete subgraph.

And determining a first target complete subgraph with the largest sum of the weight values from all the complete subgraphs.

Specifically, after the undirected weighted graph is obtained, each complete subgraph of the undirected weighted graph is obtained by recursively traversing the undirected weighted graph. The recursive traversal procedure is as follows:

the initialization P set is a set formed by vertexes of the undirected weighted graph.

And calculating the sum of the weight values of all the top points of the P set to obtain the sum of the target weight values.

The R set is initialized to an empty set.

Based on a preset division rule, sequentially dividing vertexes in the P set into the bifurcation subsets; the preset division rule is that aiming at each first vertex of the P set, when the bifurcation subset is not an empty set, if the first vertex is not directly connected with each vertex of the bifurcation subset, and when the bifurcation subset is an empty set, the first vertex is divided into the bifurcation subset; otherwise, if the first vertex is directly connected with at least one vertex of the bifurcation subset, skipping the first vertex, and continuing to divide the second first vertex until all the first vertices are divided. The initialization state of the bifurcated subset is an empty set.

Judging whether the bifurcation subset is an empty set or not; if the bifurcated subset is an empty set, a complete subgraph of the undirected weighted graph is constructed based on the vertices in the R set.

If the bifurcation subset is not an empty set, respectively performing the following loop process for each second vertex in the bifurcation subset:

the second vertex is partitioned into a set of R to update the set of R.

And removing the second vertex in the P set and the vertex which is not connected with the second vertex to obtain an updated P set.

And calculating the sum of the weight values of all the top points of the P set to obtain the sum of the current weight values.

And if the sum of the current weight values exceeds the sum of the target weight values, updating the sum of the target weight values based on the sum of the current weight values.

Judging whether the sum of the weighted values of the target set is less than half of the sum of the weighted values of the target set; the target set is a set formed by an R set and a P set.

And if the sum of the weight values of the target set is less than half of the sum of the target weight values, ending the loop process aiming at the second vertex.

If the sum of the weighted values of the target set is not less than half of the sum of the weighted values of the target set, jumping to the step: and sequentially dividing the vertexes in the P set to the bifurcation subsets based on a preset dividing rule until a cyclic process aiming at the second vertex is completed.

Preferably, after the initializing P set is a set formed by vertices of the undirected weighted graph, the method of this embodiment may further include:

for each vertex in the undirected weighted graph, calculating the number of target vertices connected to the vertex.

And sorting the vertexes in the P set according to the number of the target vertexes of each vertex in the P set and a sorting rule that the number of the target vertexes is from large to small, and sorting the at least two vertexes according to a sequence that the weight values are from large to small in the sorting process if the number of the target vertexes of the at least two vertexes is the same, so as to finally obtain a sorting result.

The sequentially dividing the vertexes in the P set into the bifurcation subsets based on the preset dividing rule may specifically include:

and sequentially dividing the vertexes in the P set to the bifurcation subsets according to the sequencing result based on a preset dividing rule.

Preferably, after the step 103 of constructing the undirected weighted graph according to the map element data set, the method of this embodiment may further include:

determining a second target complete subgraph from the undirected weighted graph; the second target complete subgraph is the complete subgraph of the undirected weighted graph, and the sum of the weighted values is only smaller than that of the first target complete subgraph.

Based on a preset evaluation standard, obtaining an evaluation result aiming at the first target complete subgraph according to the first target complete subgraph and the second target complete subgraph; the evaluation result is used for reflecting the difference degree of the sum of the weight values between the first target complete sub-graph and the second target complete sub-graph and the difference degree between the number of the first map elements contained in the first target complete sub-graph and the number of the first map elements contained in the map acquisition data.

In the practical application process, after all the complete subgraphs of the undirected weighted graph are obtained, the sum of the weight values of the top points of all the complete subgraphs is calculated for each complete subgraph, and the sum of the weight values of all the complete subgraphs is obtained. And then, sorting all the complete subgraphs in a descending order according to the sum of the weight values, wherein the complete subgraph ranked at the first position is a first target complete subgraph, and the complete subgraph ranked at the second position is a second target complete subgraph.

Then, calculating the difference degree of the sum of the weight values of the first target complete subgraph and the second target complete subgraph according to the following calculation formula:

wherein, accuracy ₁ And representing the difference degree of the sum of the weight values of the first target complete subgraph and the second target complete subgraph.

And calculating the difference degree between the number of the first map elements contained in the first target complete subgraph and the number of the first map elements contained in the map acquisition data according to the following calculation formula:

wherein, accuracy ₂ Representing a degree of difference between the number of first map elements contained in the first target complete sub-graph and the number of first map elements contained in the map capture data.

Finally, the matching accuracy of the first target complete subgraph is calculated according to the following calculation formula:

the higher the matching accuracy of the complete subgraph of the first target is, the higher the accuracy of the matching result is. Therefore, the accuracy of the quantitative matching result is realized, and the accuracy reference basis of the matching result can be provided when the matching result is used subsequently.

Preferably, step 102 may specifically include:

and matching the map acquisition data with the electronic map data to determine a driving road of the map data acquisition equipment.

And segmenting the driving road to obtain a plurality of road sections.

And aiming at any road, dividing the related data of the first map element at the position of the any road in the map acquisition data and the related data of the second map element at the position of the any road in the electronic map data into the map element data set.

Specifically, the map data collection device may obtain a driving road of the map data collection device by inputting the map data collection data and the electronic map data into a Hidden Markov Model (HMM). And then, carrying out average segmentation on the driving road to obtain a plurality of road sections. Then, for any one of the roads, a first map element located at the road is determined from the map acquisition data, and a second map element located at the road is determined from the electronic map data. And finally, dividing the related data of the first map element in the map acquisition data and the related data of the second map element in the electronic map data into the map element data set.

Based on the same idea, the embodiment of the present specification further provides a device corresponding to the above method. Fig. 3 is a schematic structural diagram of a device for matching electronic map data and map collection data according to an embodiment of the present disclosure. As shown in fig. 3, the apparatus includes: the map acquisition data acquisition module 31, the map element data set determination module 32, the undirected weighted graph construction module 33 and the first target complete subgraph determination module 34.

The map data acquisition module 31 is configured to acquire map data acquired by the map data acquisition device.

The map element data set determining module 32 is configured to determine a map element data set according to data related to a first map element at a target road segment in the map collecting data and data related to a second map element at the target road segment in the electronic map data.

The undirected weighted graph construction module 33 is used for constructing an undirected weighted graph according to the map element data set; for each vertex of the undirected weighted graph, the first map element corresponding to the vertex is matched with the second map element corresponding to the vertex, and the weight value of the vertex is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; for each connecting edge of the undirected weighted graph, the connecting edge is used for reflecting that the difference degree between the map element position relations of two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex.

And a first target complete sub-graph determining module 34, configured to determine, from the undirected weighted graph, a first target complete sub-graph with a largest sum of the weight values, so as to obtain a matching result between the electronic map data and the map acquisition data.

Preferably, the undirected weighted graph construction module 33 may be specifically configured to:

for any one first map element, determining a target second map element with the same element type as that of the first map element from the second map elements; and if the distance value between the first map element and any one of the target second map elements is within a preset distance range, constructing a vertex in the undirected weighted graph by using the first map element and any one of the target second map elements.

Preferably, the undirected weighted graph construction module 33 may be specifically configured to:

and for each vertex in the undirected weighted graph, determining the directed distance between the first map element corresponding to the vertex and the second map element corresponding to the vertex according to the relevant data of the first map element corresponding to the vertex and the relevant data of the second map element corresponding to the vertex.

And aiming at any two vertexes in the undirected weighted graph, if the difference degree between the directed distances corresponding to the any two vertexes is within the preset difference degree range, constructing a connecting edge between the any two vertexes.

Preferably, the undirected weighted graph constructing module 33 may specifically include:

and the map element attribute similarity determining submodule is used for calculating the map element attribute similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex aiming at any vertex in the undirected weighted graph.

And the importance degree value determining submodule is used for calculating the importance degree value of the vertex according to at least one of the category and the length of the second map element corresponding to the vertex.

And the weight value determining submodule is used for calculating the product of the map element attribute similarity and the importance degree value to obtain the weight value of the vertex.

Preferably, the map element attribute similarity determining sub-module may specifically include:

and the target attribute determining unit is used for determining the target attribute of the first map element corresponding to the vertex.

And the target attribute similarity determining unit is used for calculating the target attribute similarity of the target attribute by adopting a preset attribute similarity calculation rule corresponding to the type of the target attribute aiming at each target attribute.

And the map element attribute similarity determining unit is used for calculating the average value of the target attribute similarity of the target attribute to obtain the map element attribute similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex.

Preferably, the target attribute similarity determining unit may be specifically configured to:

if the type of the target attribute is a continuous attribute, determining the first target attribute similarity of the target attribute according to the map element similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the map element similarity is positively correlated with the first target attribute similarity.

If the type of the target attribute is a discrete attribute, determining second target attribute similarity of the target attribute according to the element type of the first map element corresponding to the vertex and the element type of the second map element corresponding to the vertex; when the similarity of the second target attribute is a first preset value, the element type of the first map element corresponding to the vertex is the same as the element type of the second map element corresponding to the vertex; and when the similarity of the second target attribute is a second preset value, the element type of the first map element corresponding to the vertex is different from the element type of the second map element corresponding to the vertex.

The importance level value determination submodule may be specifically configured to:

and judging whether the first map element corresponding to the vertex is a point element or not.

And if the first map element corresponding to the vertex is a point element, determining that the importance degree value of the vertex is a third preset value.

If the first map element corresponding to the vertex is not a point element, determining an importance degree value aiming at the vertex according to the element length of the second map element corresponding to the vertex; the element length of the second map element corresponding to the vertex is positively correlated with the importance degree value of the vertex.

Preferably, the first target complete subgraph determining module 34 may specifically include:

and the complete subgraph determining sub-module is used for acquiring each complete subgraph in the undirected weighted graph.

And the weight value sum determining submodule is used for determining the weight value sum of each top point corresponding to each complete subgraph.

And the first target complete subgraph determining sub-module is used for determining a first target complete subgraph with the largest sum of the weight values from all the complete subgraphs.

Preferably, the complete subgraph determination submodule may be specifically configured to:

for each vertex in the undirected weighted graph, calculating the number of target vertices connected to the vertex; determining an order in which the vertices are visited relative to other vertices in the target set based on the number of target vertices connected to the vertex and the weight values of the vertices; the target set is a set formed by all the vertexes in the undirected weighted graph; and acquiring each complete subgraph in the undirected weighted graph according to each vertex in the target set based on the access sequence.

Preferably, the apparatus of this embodiment may further include:

the evaluation result is used for determining a second target complete subgraph from the undirected weighted graph; the second target complete subgraph is a complete subgraph of the undirected weighted graph, and the sum of the weighted values is only smaller than that of the first target complete subgraph; then, based on a preset evaluation standard, obtaining an evaluation result aiming at the first target complete subgraph according to the first target complete subgraph and the second target complete subgraph; the evaluation result is used for reflecting the difference degree of the sum of the weight values between the first target complete sub-graph and the second target complete sub-graph and the difference degree between the number of the first map elements contained in the first target complete sub-graph and the number of the first map elements contained in the map acquisition data.

The map element data set determining module 32 is specifically configured to:

and matching the map acquisition data with the electronic map data to determine a driving road of the map data acquisition equipment.

And splitting the driving road to obtain a plurality of road sections.

And aiming at any road, dividing the related data of the first map element at the position of the any road in the map acquisition data and the related data of the second map element at the position of the any road in the electronic map data into the map element data set.

Based on the same idea, the embodiment of the present specification further provides a device corresponding to the method.

Fig. 4 is a schematic structural diagram of a device for matching electronic map data and map collection data provided in an embodiment of the present specification. As shown in fig. 4, the apparatus 400 may include:

at least one processor 410; and the number of the first and second groups,

a memory 430 communicatively coupled to the at least one processor; wherein,

the memory 430 stores instructions 420 executable by the at least one processor 410 to enable the at least one processor 410 to:

and acquiring map acquisition data acquired by the map data acquisition equipment.

Determining a map element data set according to the relevant data of the first map element at the target road section in the map acquisition data and the relevant data of the second map element at the target road section in the electronic map data;

constructing an undirected weighted graph according to the map element data set; for each vertex of the undirected weighted graph, the first map element corresponding to the vertex is matched with the second map element corresponding to the vertex, and the weight value of the vertex is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; for each connecting edge of the undirected weighted graph, the connecting edge is used for reflecting that the difference degree between the map element position relations of two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex;

and determining a first target complete subgraph with the maximum sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus shown in fig. 4, since it is substantially similar to the method embodiment, the description is simple, and reference may be made to the partial description of the method embodiment for relevant points.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical blocks. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is an integrated circuit whose Logic functions are determined by a user programming the Device. A digital symbol system is "integrated" onto a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate a dedicated integrated circuit chip. Furthermore, nowadays, instead of manually manufacturing an Integrated Circuit chip, such programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as ABEL (Advanced Boolean Expression Language), AHDL (alternate Hardware Description Language), traffic, CUPL (computer unified programming Language), HDCal, jhddl (Java Hardware Description Language), lava, lola, HDL, PALASM, rhyd (Hardware Description Language), and vhigh-Language (Hardware Description Language), which is currently used in most popular applications. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, apparatuses, modules or units described in the above embodiments may be specifically implemented by a computer chip or an entity, or implemented by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises that element.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art to which the present application pertains. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (13)

1. A method for matching electronic map data with map acquisition data is characterized by comprising the following steps:

acquiring map acquisition data acquired by map data acquisition equipment;

determining a map element data set according to the relevant data of the first map element at the target road section in the map acquisition data and the relevant data of the second map element at the target road section in the electronic map data;

constructing an undirected weighted graph according to the map element data set; the weight value of the vertex of the undirected weighted graph is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the connecting edge of the undirected weighted graph is used for reflecting that the difference degree between the map element position relations of the two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex;

and determining a first target complete subgraph with the maximum sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data.

2. The method according to claim 1, wherein the constructing an undirected weighted graph from the set of map element data comprises:

for any one first map element, determining a target second map element with the same element type as that of the first map element from the second map elements;

and if the distance value between the first map element and any one of the target second map elements is within a preset distance range, constructing a vertex in the undirected weighted graph by using the first map element and any one of the target second map elements.

3. The method according to claim 2, wherein the constructing an undirected weighted graph from the set of map element data comprises:

for each vertex in the undirected weighted graph, determining a directed distance between the first map element corresponding to the vertex and the second map element corresponding to the vertex according to the related data of the first map element corresponding to the vertex and the related data of the second map element corresponding to the vertex;

and aiming at any two vertexes in the undirected weighted graph, if the difference degree between the directed distances corresponding to the any two vertexes is within the preset difference degree range, constructing a connecting edge between the any two vertexes.

4. The method according to claim 2, wherein the constructing an undirected weighted graph from the set of map element data comprises:

calculating map element attribute similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex aiming at any vertex in the undirected weighted graph;

calculating an importance degree value of the vertex according to at least one of the category and the length of the second map element corresponding to the vertex;

and calculating the product of the map element attribute similarity and the importance degree value to obtain the weight value of the vertex.

5. The method according to claim 4, wherein the calculating of the map element attribute similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex specifically comprises:

determining a target attribute of the first map element corresponding to the vertex;

aiming at each target attribute, adopting a preset attribute similarity calculation rule corresponding to the type of the target attribute to calculate the target attribute similarity of the target attribute;

and calculating the average value of the target attribute similarity of the target attribute to obtain the map element attribute similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex.

6. The method according to claim 5, wherein the calculating the target attribute similarity of the target attribute by using a preset attribute similarity calculation rule corresponding to the type of the target attribute specifically includes:

if the type of the target attribute is a continuous attribute, determining the first target attribute similarity of the target attribute according to the map element similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the map element similarity and the first target attribute similarity are in positive correlation;

if the type of the target attribute is a discrete attribute, determining second target attribute similarity of the target attribute according to the element type of the first map element corresponding to the vertex and the element type of the second map element corresponding to the vertex; when the similarity of the second target attribute is a first preset value, the element type of the first map element corresponding to the vertex is the same as the element type of the second map element corresponding to the vertex; and when the similarity of the second target attribute is a second preset value, the element type of the first map element corresponding to the vertex is different from the element type of the second map element corresponding to the vertex.

7. The method according to claim 4, wherein the calculating the importance degree value of the vertex according to at least one of the category and the length of the second map element corresponding to the vertex comprises:

judging whether the first map element corresponding to the vertex is a point element or not;

if the first map element corresponding to the vertex is a point element, determining that the importance degree value of the vertex is a third preset value;

if the first map element corresponding to the vertex is not a point element, determining an importance degree value aiming at the vertex according to the element length of the second map element corresponding to the vertex; the element length of the second map element corresponding to the vertex is positively correlated with the importance degree value of the vertex.

8. The method according to claim 1, wherein the determining a first target complete sub-graph with a largest sum of the weight values from the undirected weighted graph specifically includes:

acquiring each complete subgraph in the undirected weighted graph;

determining the sum of the weight values of the vertexes corresponding to each complete subgraph;

and determining a first target complete subgraph with the largest sum of the weight values from all the complete subgraphs.

9. The method according to claim 8, wherein the obtaining of each complete subgraph in the undirected weighted graph specifically comprises:

for each vertex in the undirected weighted graph, calculating the number of target vertices connected to the vertex;

determining an order of visited of the vertices relative to other vertices in the target set according to the number of target vertices connected to the vertices and the weight values of the vertices; the target set is a set formed by all the vertexes in the undirected weighted graph;

and acquiring each complete subgraph in the undirected weighted graph according to each vertex in the target set based on the access sequence.

10. The method of claim 1, wherein after constructing the undirected weighted graph from the set of map element data, further comprising:

determining a second target complete subgraph from the undirected weighted graph; the second target complete subgraph is a complete subgraph of the undirected weighted graph, and the sum of weighted values is only smaller than that of the first target complete subgraph;

based on a preset evaluation standard, obtaining an evaluation result aiming at the first target complete subgraph according to the first target complete subgraph and the second target complete subgraph; the evaluation result is used for reflecting the difference degree of the sum of the weighted values between the first target complete subgraph and the second target complete subgraph and the difference degree between the number of the first map elements contained in the first target complete subgraph and the number of the first map elements contained in the map collecting data.

11. The method according to claim 1, wherein determining a set of map element data from data relating to a first map element at a target road segment in the map acquisition data and data relating to a second map element at the target road segment in the electronic map data comprises:

matching the map acquisition data with the electronic map data to determine a driving road of the map data acquisition equipment;

segmenting the driving road to obtain a plurality of road sections;

and aiming at any road, dividing the related data of the first map element at the position of the any road in the map acquisition data and the related data of the second map element at the position of the any road in the electronic map data into the map element data set.

12. An apparatus for matching electronic map data with map acquisition data, comprising:

the map data acquisition module is used for acquiring map data acquired by the map data acquisition equipment;

the map element data set determining module is used for determining a map element data set according to the relevant data of a first map element at a target road section in the map acquisition data and the relevant data of a second map element at the target road section in the electronic map data;

the undirected weighted graph construction module is used for constructing an undirected weighted graph according to the map element data set; the weight value of the vertex of the undirected weighted graph is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the connecting edge of the undirected weighted graph is used for reflecting that the difference degree between the map element position relations of the two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex;

and the first target complete sub-graph determining module is used for determining a first target complete sub-graph with the largest sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data.

13. An apparatus for matching electronic map data with map acquisition data, comprising:

at least one processor; and (c) a second step of,

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to:

acquiring map acquisition data acquired by map data acquisition equipment;

determining a map element data set according to the relevant data of a first map element at a target road section in the map acquisition data and the relevant data of a second map element at the target road section in the electronic map data;

constructing an undirected weighted graph according to the map element data set; the weight value of the vertex of the undirected weighted graph is used for reflecting the similarity between the first map element corresponding to the vertex and the second map element corresponding to the vertex; the connecting edge of the undirected weighted graph is used for reflecting that the difference degree between the map element position relations of the two vertexes corresponding to the connecting edge is within a preset difference degree range; the map element position relationship is the position relationship of the first map element corresponding to any vertex relative to the second map element corresponding to any vertex;

and determining a first target complete subgraph with the maximum sum of the weight values from the undirected weighted graph to obtain a matching result between the electronic map data and the map acquisition data.

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