Method, device and electronic device for determining road weight

Abstract

The disclosed embodiments disclose a method, apparatus, and electronic device for determining a road weight. The method includes: obtaining a coordinate point string for each second edge in a second topological map, searching for a first edge in a first topological map within a preset distance range around each coordinate point in the coordinate point string, wherein the edges of the first and second topological maps are composed of roads in a digital map; obtaining road parameters for each first edge in a first set of first edges, calculating the distance between the first edge and the second edge, and determining a first edge that matches the second edge based on the road parameters and the distance; and using the road weight of the first edge that matches the second edge as the road weight of the second edge.

Description

Technical Field

[0001] The present disclosure relates to the technical field related to electronic maps, and in particular to a method, device, and electronic device for determining road weights. Background Art

[0002] Route planning is a core issue in the ride-hailing business, and one of the key data points in route planning is road weights. Road weights, also known as edge weights or link weights in a road network, are obtained. Once this road weight data is obtained, route planning is accomplished by using graph search to find the route with the optimal road weight. A common road weight is travel time. Setting road weights based on the basic road network topology provided by the map provider requires ride-hailing companies to accumulate extensive empirical data and incur significant costs.

[0003] Due to commercial considerations, the map providers that ride-hailing companies cooperate with may change. If they change from map provider A to map provider B, the road weights in the road network data provided by map provider A will not be able to be reused by map provider B. The weights need to be re-set based on the road network data of map provider B, which in turn requires the ride-hailing companies to pay a large amount of costs for resetting the road weights. Summary of the Invention

[0004] The embodiments of the present disclosure propose a road weight determination method, a road weight determination device, and an electronic device, which map the road weight in the road network data of map provider A to the road network data of map provider B, thereby solving the problem that when an online car-hailing company switches its map provider partner from map provider A to map provider B, it needs to spend a lot of cost to re-determine the road weight of the road network data of map provider B.

[0005] A first aspect of an embodiment of the present disclosure provides a method for determining a road weight, comprising:

[0006] For each second edge in the second topological graph, obtaining a coordinate point string, and searching for a first edge in the first topological graph within a preset distance range around each coordinate point in the coordinate point string, wherein the edges of the first topological graph and the second topological graph are composed of roads in the digital map;

[0007] In a first set consisting of the first edges, obtaining a road parameter of each of the first edges, calculating a distance between the first edge and the second edge, and determining a first edge that matches the second edge based on the road parameter and the distance;

[0008] The road weight of the first edge that matches the second edge is used as the road weight of the second edge.

[0009] In some embodiments, calculating the distance between the first side and the second side includes:

[0010] Calculating the distances from the two endpoints of the first side to the second side to obtain a first distance value and a second distance value, respectively; calculating the distances from the two endpoints of the second side to the first side to obtain a third distance value and a fourth distance value, respectively;

[0011] Among the first distance value, the second distance value, the third distance value, and the fourth distance value, distance values ​​greater than a first preset threshold are removed, and a maximum value among the remaining distance values ​​is selected as the distance between the first side and the second side.

[0012] In some embodiments, the method further comprises:

[0013] The second edges of the second topological graph for which the road weights have been determined are grouped according to road grade and road width, and the median of the road weights of the second edges in the group is used as the road weight of the group;

[0014] For a second edge in the second topological graph for which a road weight has not been determined, determining a grouping of the second edge according to the road grade and road width of the second edge, and using the road weight of the grouping as the road weight of the second edge;

[0015] If the group does not have another second side whose road weight has been determined, the road weight of the second side is assigned a preset value.

[0016] In some embodiments, determining the first edge that matches the second edge according to the road parameter and the distance includes:

[0017] Selecting a first edge parallel to the second edge in the first set to obtain a second set;

[0018] Remove the first edge whose road parameter is inconsistent with the second edge from the second set to obtain a third set;

[0019] In the third set, the first edge that is closest to the second edge is used as the first edge that matches the second edge.

[0020] In some embodiments, selecting a first edge parallel to the second edge in the first set to obtain a second set includes:

[0021] Among the first distance value, the second distance value, the third distance value, and the fourth distance value, distance values ​​greater than a first preset threshold are removed. If there are more than three remaining distance values ​​and the difference between any two distance values ​​is less than a second preset threshold, it is determined that the first side is parallel to the second side, and the first side is selected to obtain a second set.

[0022] In some embodiments, removing the first edge having a road parameter inconsistent with the second edge from the second set to obtain the third set includes:

[0023] For each first edge in the second set, obtaining a road parameter of the first edge;

[0024] If the road attribute in the road parameter does not match the corresponding attribute of the second edge, removing the corresponding first edge from the second edge set;

[0025] If the difference between the road width value in the road parameter and the road width value of the second edge is greater than a third preset threshold, the corresponding first edge is removed from the second edge set.

[0026] A second aspect of an embodiment of the present disclosure provides a road weight determination device, including:

[0027] a search module configured to obtain a coordinate point string for each second edge in the second topological graph, and search for a first edge in the first topological graph within a preset distance range around each coordinate point in the coordinate point string, wherein the edges of the first topological graph and the second topological graph are composed of roads in the digital map;

[0028] a determination module, configured to obtain a road parameter of each of the first edges in a first set consisting of the first edges, calculate a distance between the first edge and the second edge, and determine a first edge that matches the second edge based on the road parameter and the distance;

[0029] As a module, it is used to use the road weight of the first edge matched with the second edge as the road weight of the second edge.

[0030] A third aspect of the embodiments of the present disclosure provides an electronic device, characterized in that: it includes a memory and a processor,

[0031] The memory is used to store computer programs;

[0032] The processor is configured to implement the road weight determination method according to the first aspect of the present disclosure when executing the computer program.

[0033] A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the road weight determination method according to the first aspect of the present disclosure is implemented.

[0034] The fifth aspect of the embodiment of the present disclosure provides a computer program product, including a computer program and instructions. When the computer program and instructions are executed by a processor, the road weight determination method described in the first aspect of the present disclosure is implemented.

[0035] The embodiment of the present disclosure maps the road weights in the road network data of map A to the road network data of map B as the road weights of the road network data of map B. Since the online car-hailing company already has the road weight data in the road network data of map A, the huge cost required to redetermine the road weights of the road network data of map B is avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The features and advantages of the present disclosure will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the present disclosure in any way. In the accompanying drawings:

[0037] Figure 1 is a schematic diagram of a road weight determination system applicable according to the present disclosure;

[0038] Figure 2 is a flow chart of a method for determining a road weight according to some embodiments of the present disclosure;

[0039] Figure 3 is an example of distance calculation between linkA and linkX according to some embodiments of the present disclosure;

[0040] Figure 4 is an example where linkA and linkX are not parallel according to some embodiments of the present disclosure;

[0041] Figure 5 This is a schematic diagram of a road weight determination device according to some embodiments of the present disclosure.

[0042] Figure 6 This is a schematic diagram of an electronic device according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0043] In the detailed description that follows, many specific details of the present disclosure are set forth by way of example in order to provide a thorough understanding of the relevant disclosure. However, it will be apparent to one of ordinary skill in the art that the present disclosure can be implemented without these details. It should be understood that the use of the terms "system," "device," "unit," and / or "module" in the present disclosure is a method for distinguishing between different parts, elements, parts, or assemblies at different levels in a sequential arrangement. However, these terms may be replaced by other expressions if they can achieve the same purpose.

[0044] It should be understood that when a device, unit, or module is referred to as being "on," "connected to," or "coupled to" another device, unit, or module, it may be directly on, connected to, coupled to, or in communication with the other device, unit, or module, or there may be intervening devices, units, or modules, unless the context clearly indicates an exception. For example, the term "and / or" as used in this disclosure includes any and all combinations of one or more of the associated listed items.

[0045] The terms used in this disclosure are only for describing specific embodiments and are not intended to limit the scope of this disclosure. As shown in the specification and claims of this disclosure, unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of clearly identified features, wholes, steps, operations, elements and / or components, and such expressions do not constitute an exclusive list, and other features, wholes, steps, operations, elements and / or components may also be included.

[0046] These and other features and characteristics of the present disclosure, as well as the methods of operation, the functions of the related elements of the structure, the combination of parts, and the economy of manufacture may be better understood with reference to the following description and accompanying drawings, which form a part of this specification. However, it is to be expressly understood that the drawings are for illustration and description purposes only and are not intended to limit the scope of protection of the present disclosure. It is to be understood that the drawings are not drawn to scale.

[0047] Various structural diagrams are used in this disclosure to illustrate various variations of the embodiments of the present disclosure. It should be understood that the preceding or following structures are not intended to limit the present disclosure. The scope of protection of the present disclosure is subject to the claims.

[0048] Figure 1 Schematic diagram of a road weight determination system applicable to the present disclosure. Figure 1 The system shown includes A map business map database, B map business map database and weight mapping server.

[0049] The weight mapping server obtains the road weights of the road network data from the A map database and maps them to the road network data of the B map database, thereby completing the setting of the road weights for the B map database.

[0050] Road weights, also known as edge weights or link weights, are commonly used to represent road travel time. With the prevalence of big data technology, road travel time can often be extracted from users' actual GPS tracks. This sequence of GPS tracks is then matched to links using a road network matching algorithm. A series of statistical analyses allows the speed of each link to be calculated, and combined with the link length, the travel time is derived. However, this approach requires a large amount of track data, and the track data must have high coverage of the mapped road network. However, the tracks of typical ride-hailing companies do not cover the entire national road network. Furthermore, the map matching component of this approach is computationally intensive, and due to the accuracy of track point positioning, it is difficult to distinguish between main and secondary roads.

[0051] The road network data providers for both Map A and Map B described in this application use the GCJ-02 coordinate system when collecting road coordinates. The GCJ-02 coordinate system, also known as the "Mars coordinate system," is a new coordinate system developed by my country's National Bureau of Surveying and Mapping. It's an encrypted version of WGS-84. However, some map providers may encrypt and offset the GCJ-02 coordinates to create new coordinates. As a result, the coordinates of the same point on the same road in Map A and Map B may differ slightly.

[0052] Therefore, the method disclosed in this application is applicable to road network data within China, and the coordinate systems of the road network data of Map Provider A and Map Provider B are both based on the Martian coordinate system or encrypted on the basis of the Martian coordinate system.

[0053] The road network data is represented in this application as a topological graph. The edges of the topological graph are composed of roads in the digital map. The edges have at least two attributes:

[0054] 1. Road rights are set by the ride-hailing company based on historical data.

[0055] 2. Road parameters: Road parameters are provided by map providers.

[0056] In some embodiments of the present disclosure, the fields of the road parameters are as follows:

[0057]

[0058]

[0059] The weight mapping server may be any one of a stand-alone server, a cluster server or a distributed server.

[0060] Figure 2 is a flow chart of a method for determining a road weight according to some embodiments of the present disclosure. In some embodiments, the method for determining a road weight may be performed by Figure 1 The weight mapping server is executed as shown. Figure 2 As shown, the road weight determination method includes the following steps:

[0061] S201, for each second edge in the second topological graph, obtain a coordinate point string, and search for a first edge in the first topological graph within a preset distance range around each coordinate point in the coordinate point string, wherein the edges of the first topological graph and the second topological graph are composed of roads in the digital map.

[0062] Specifically, we get the coordinate point string of linkX and search for the set of edges in A within N meters around each coordinate, referred to as linkA_list. The threshold N here is adjustable, and the threshold depends on the coordinate difference between the two graphs. For example, for the same location in the real world, the coordinates on graph A are (lon1, lat1) and the coordinates on graph B are (lon2, lat2), then the approximate difference can be expressed as Meter estimation. Here, the latitude and longitude coordinate values ​​lon and lat are expressed as decimal points, such as 116.435914, 39.977636. In this case, N should be set to be larger than diff. Finding the edge set of graph A within N meters of the coordinates is implemented using SQL statements in the PostGIS spatial database. For example, the statement to find the edge IDs of graph A within 100 meters of the coordinates (113.925258, 27.628368) is as follows:

[0063] selectidfromgraph_Awherest_dwithin(geom::geography,ST_SetSRID(ST_MakePoint(113.925258,27.628368),4326)::geography,100)

[0064] S202 : In a first set of first edges, obtain a road parameter of each first edge, calculate a distance between the first edge and the second edge, and determine a first edge that matches the second edge based on the road parameter and the distance.

[0065] Specifically, in order to calculate the distance between the first edge and the second edge, we need to first define the distance from a point to an edge.

[0066] Figure 3 This is an example graph for calculating the distance between linkA and linkX. Figure 3 In [1], the distance between the endpoint n3 of linkA and the edge linkX is calculated as follows:

[0067] First, take the coordinate string of edge linkX, for example [p1, p2, p3, p4], where p1, p2, p3, and p4 are all decimal latitude and longitude values, such as (116.23452, 39.123213). First, encrypt the edge coordinate string and calculate the distances between two adjacent points in the string: dist(p1, p2), dist(p2, p3), dist(p3, p4), and dist{p4, p5}. If the distance between adjacent points is large, for example, greater than 10 meters, add several points using linear interpolation. For example, if dist(p1, p2) is greater than 10 meters, and the coordinates of p1 are (lon1, lat1) and p2 are (lon2, lat2), add several points in both the longitude and latitude directions at a step size of 10 / 100000. For example, the coordinates of the first point added are (lon1+10 / 100000, lat1+10 / 100000), the coordinates of the second point are (lon1+20 / 100000, lat1+20 / 100000), and the coordinates of the kth point are (lon1+k*10 / 100000, lat1+k*10 / 100000), and so on until the coordinates exceed lon2, lat2. After encryption, the original coordinate string [p1, p2, p3, p4] becomes the new coordinate string [p1..pi...p2...p3...p4]. Calculate the Euclidean distance between each coordinate in the new coordinate string and point n3, and find the closest distance, which is used as the closest distance measure from point n3 to linkX.

[0068] After clarifying the calculation method of point to edge, we calculate the "distance" between each linkA in linkA_list and linkX in turn. Here, the distance between two edges is calculated according to the maximum and minimum distance. Figure 3 As shown, the first endpoint of linkX is n1 and n2 respectively, and the first and last endpoints of linkA are n3 and n6 respectively. Calculate the closest distance between the endpoint of linkA and linkX, and the closest distance between the endpoint of linkX and linkA, and get four distances. Considering that Figure A and Figure B interrupt the road differently, the lengths of linkA and linkX may be different. Therefore, the distances greater than a certain threshold are removed. According to experience, 10 meters can be selected. The threshold here is adjustable. The maximum value is selected from the remaining distances as the distance measure between linkA and linkX. If there are not at least 3 distances less than or equal to 10 meters among these four distances, it means that linkA and linkX are far away and do not match. Figure 3, the distance between the nearest points of n1 on linkA is dist(n1,n3), the distance between the nearest points of n2 on linkA is dist(n2,n4), the nearest distance of n3 on linkX is dist(n3,n5), and the nearest distance of n6 on linkB is dist(n6,n2). Since dist(n6,n2) is large, max{dist(n1,n3),dist(n2,n4),dist(n3,n5)} is taken as the distance metric between linkA and linkX.

[0069] For each linkA in linkA_list, calculate whether linkA and linkX are approximately parallel, and remove linkA that is not parallel. The method for calculating the parallel relationship between linkA and linkX is as follows: According to the above method, find the closest distance between the two endpoints of linkA and linkX, and the closest distance between the two endpoints of linkX and linkA, for a total of 4 distances. If there are not at least 3 distances less than or equal to 10 meters among these four distances, it means that linkA and linkX are far away, and the judgment of whether they are parallel will not be continued. Remove distances greater than 10 meters, and compare the remaining at least 3 distances in pairs. If the difference between them is not large (such as less than or equal to 2 meters, the threshold here is adjustable), they are considered to be approximately parallel. If Figure 3 As shown, compare whether the differences between dist(n1,n3), dist(n2,n4), and dist(n3,n5) are all less than or equal to 2 meters. If so, linkA and linkX are considered to be approximately parallel. Figure 4 For non-parallel samples, dist(n2,n4) is significantly larger than dist(n1,n3) and dist(n1,n5).

[0070] Then filter by link attributes: For each linkA in linkA_list, check whether linkA's road attributes, such as primary and secondary road markings, elevated road markings, and tunnel markings, are consistent with linkX. If not, the link is not matched. Check whether linkA's road width is close to that of linkX. Due to the varying measurement accuracy of the two maps, the width of the same road measured at the two locations may not be exactly the same. Therefore, a tolerance threshold can be set. If the width difference is significant, such as 30 meters and 130 meters, the link is not matched.

[0071] For the remaining links in linkA_list, select the link closest to linkX as the matching link.

[0072] S203: Using the road weight of the first edge that matches the second edge as the road weight of the second edge.

[0073] In some embodiments of the present disclosure, the method further includes completing the weights of the links that were not successfully mapped in the above steps. Completion method: The links with weights obtained in Figure B are grouped according to road grade + road width, and the median weight of each group is calculated to obtain a mapping table of road grade + road width => weight. For example, the median weight of all links with a road grade of 01 and a road width of 30 in Figure B is 7382, and then a record of "01, 30" => 7382 is recorded in the mapping table. For links that were not successfully mapped, a table lookup is performed to assign weights based on their road grade + road width. If no corresponding value is found in the table lookup, the default value is filled in.

[0074] Figure 5 Schematic diagram of a road weight determination device according to some embodiments of the present disclosure. The road weight determination device 500 includes a search module 510, a determination module 520, and a module 530. The road weight determination function can be performed by Figure 1 The weight mapping server is executed as shown.

[0075] A search module 510 is configured to obtain a coordinate point string for each second edge in the second topological graph, and search for a first edge in the first topological graph within a preset distance range around each coordinate point in the coordinate point string, wherein the edges of the first topological graph and the second topological graph are composed of roads in the digital map;

[0076] a determination module 520 configured to obtain a road parameter of each of the first edges in a first set of the first edges, calculate a distance between the first edge and the second edge, and determine a first edge that matches the second edge based on the road parameter and the distance;

[0077] As module 530, it is configured to use the road weight of the first edge that matches the second edge as the road weight of the second edge.

[0078] Figure 6 This is a schematic diagram of an electronic device according to some embodiments of the present disclosure, wherein the electronic device 600 includes a memory 620 and a processor 610, wherein the memory 620 is used to store a computer program; and the processor 610 is used to implement the road weight determination method described in S201-S203 when executing the computer program.

[0079] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the road weight determination method described in S201-S203 is implemented.

[0080] One embodiment of the present application provides a computer program product, including a computer program and instructions. When the computer program and instructions are executed by a processor, the road weight determination method described in S201-S203 is implemented.

[0081] To sum up, the road weight determination method, road weight determination device, electronic device, computer-readable storage medium and program product provided in the various embodiments of the present application map the road weight in the business road network data of map A to the road network data of map B as the road weight of the business road network data of map B. Because the online car-hailing company already has the road weight data in the business road network data of map A, it avoids the huge cost required to re-determine the road weight of the business road network data of map B.

[0082] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding descriptions in the aforementioned device embodiments and will not be repeated here.

[0083] Although the subject matter described herein is provided in the general context of being executed in conjunction with the execution of an operating system and application programs on a computer system, those skilled in the art will recognize that other implementations may also be performed in conjunction with other types of program modules. Generally speaking, program modules include routines, programs, components, data structures, and other types of structures that perform specific tasks or implement specific abstract data types. Those skilled in the art will appreciate that the subject matter described herein may be practiced using other computer system configurations, including handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like, and may also be used in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0084] Those skilled in the art will appreciate that the units and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0085] It should be understood that the above-described specific embodiments of the present disclosure are merely illustrative of or explanation of the principles of the present disclosure and do not constitute limitations on the present disclosure. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present disclosure shall be included within the scope of protection of the present disclosure. In addition, the claims appended to the present disclosure are intended to cover all variations and modifications that fall within the scope and metes and bounds of the appended claims, or equivalents of such scope and metes and bounds.

Claims

1. A method for determining road weight, characterized in that: include: For each second edge in the second topological graph, a coordinate point string is obtained, and a first edge in the first topological graph within a preset distance range around each coordinate point in the coordinate point string is searched, wherein the first The edges of the topological graph and the second topological graph are composed of roads in the digital map; In a first set consisting of the first edges, obtaining a road parameter of each of the first edges, calculating a distance between the first edge and the second edge, and determining a first edge that matches the second edge based on the road parameter and the distance; The road weight of the first edge that matches the second edge is used as the road weight of the second edge. value; The calculating the distance between the first side and the second side includes: Calculate the distances from the two endpoints of the first side to the second side to obtain the first distance value and the second distance value respectively; calculate the distances from the two endpoints of the second side to the first side to obtain the first distance value and the second distance value respectively. a third distance value and a fourth distance value; Remove distance values ​​greater than a first preset threshold from the first distance value, the second distance value, the third distance value, and the fourth distance value, and select a maximum value from the remaining distance values ​​as the distance between the first side and the second side; The second edges of the second topological graph for which the road weights have been determined are grouped according to road grade and road width, and the median of the road weights of the second edges in the group is used as the road weight of the group; For a second edge in the second topological graph for which a road weight has not been determined, determining a grouping of the second edge according to the road grade and road width of the second edge, and using the road weight of the grouping as the road weight of the second edge; If the group does not have another second side with a determined road weight, Road weights are assigned preset values.

2. The method according to claim 1, characterized in that Determining the first side matching the second side according to the road parameter and the distance includes: Selecting a first edge parallel to the second edge in the first set to obtain a second set; Remove the first edge whose road parameter is inconsistent with the second edge from the second set to obtain a third set; In the third set, the first edge that is closest to the second edge is used as the first edge that matches the second edge.

3. The method according to claim 2, characterized in that The selected Selecting a first side parallel to the second side to obtain a second set includes: Among the first distance value, the second distance value, the third distance value, and the fourth distance value, distance values ​​greater than a first preset threshold are removed. If there are more than three remaining distance values ​​and the difference between any two distance values ​​is less than a second preset threshold, it is determined that the first side is parallel to the second side, and the first side is selected to obtain a second set.

4. The method according to claim 3, characterized in that The step of removing the first edge whose road parameter is inconsistent with the second edge from the second set to obtain the third set includes: For each first edge in the second set, obtaining a road parameter of the first edge; If the road attribute in the road parameter does not match the corresponding attribute of the second edge, removing the corresponding first edge from the second edge set; If the difference between the road width value in the road parameter and the road width value of the second edge is greater than a third preset threshold, the corresponding first edge is removed from the second edge set.

5. A road weight determination device, characterized in that: include: A search module is configured to obtain a coordinate point string for each second edge in the second topological graph, and search for a first edge in the first topological graph within a preset distance range around each coordinate point in the coordinate point string. Wherein, the edges of the first topological graph and the second topological graph are composed of roads in the digital map; A determination module is configured to obtain, in a first set consisting of the first edges, each of the first edges. road parameters of the edge, calculating a distance between the first edge and the second edge, and determining a first edge that matches the second edge based on the road parameters and the distance; as a module, configured to use the road weight of the first edge that matches the second edge as the road weight of the second edge; The calculating the distance between the first side and the second side includes: Calculating the distances from the two endpoints of the first side to the second side to obtain a first distance value and a second distance value, respectively; calculating the distances from the two endpoints of the second side to the first side to obtain a third distance value and a fourth distance value, respectively; Remove distance values ​​greater than a first preset threshold from the first distance value, the second distance value, the third distance value, and the fourth distance value, and select a maximum value from the remaining distance values ​​as the distance between the first side and the second side; The second edges of the second topological graph for which the road weights have been determined are grouped according to road grade and road width, and the median of the road weights of the second edges in the group is used as the road weight of the group; For a second edge in the second topological graph for which a road weight has not been determined, determining a grouping of the second edge according to the road grade and road width of the second edge, and using the road weight of the grouping as the road weight of the second edge; If the group does not have another second side whose road weight has been determined, the road weight of the second side is assigned a preset value.

6. An electronic device, characterized in that: including memory and processor, The memory is used to store computer programs; The processor is configured to implement the method according to any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

8. A computer program product, comprising a computer program and instructions, which, when executed by a processor, implement the method according to any one of claims 1 to 4.

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