A method, device, equipment and storage medium for dividing regions

Abstract

The present application provides a method, device, equipment and storage medium for dividing an area, wherein the method includes: dividing a plane polygon corresponding to a target area into multiple sub-polygons based on multiple boarding points in the target area; determining the shortest driving path distance between each two sub-polygons; clustering the multiple sub-polygons based on the shortest driving path distance to obtain a clustering result; and dividing the target area into multiple sub-areas based on the clustering result. The present application can realize the division of a target area into multiple sub-areas based on the clustering result, can avoid the drawback that two sub-polygons separated by physical obstacles are easily divided into one sub-area based on the straight-line distance, and can realize accurate division of the target area based on the clustering result.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, equipment and storage medium for dividing an area. Background Art

[0002] When there is an imbalance between supply and demand in the online car-hailing field, the platform service end often needs to divide passengers into different areas based on the boarding point for queuing. In the prior art, the platform service end mainly divides the area based on the longitude and latitude of the boarding point.

[0003] However, since the above-mentioned area division method considers the straight-line distance between the passengers' boarding points, this will result in the boarding points separated by some physical barriers (such as rivers) being divided into the same area, which will reduce the rationality of the area division and further increase the driver's pick-up cost and efficiency. Summary of the invention

[0004] In view of this, the present application provides a method, device, equipment and storage medium for dividing areas to solve the problems existing in the above-mentioned prior art solutions.

[0005] Specifically, the present application is implemented through the following technical solutions:

[0006] According to a first aspect of the present application, a method for dividing a region is proposed, comprising:

[0007] Dividing a plane polygon corresponding to the target area into a plurality of sub-polygons based on a plurality of boarding points within the target area;

[0008] Determining the shortest driving path distance between each two of the sub-polygons;

[0009] Clustering the plurality of sub-polygons based on the shortest driving path distance to obtain a clustering result;

[0010] The target area is divided into a plurality of sub-areas based on the clustering result.

[0011] In one embodiment, dividing the plane polygon corresponding to the target area into a plurality of sub-polygons based on a plurality of boarding points within the target area includes:

[0012] Obtain the latitude and longitude data of multiple boarding points in the target area;

[0013] The plane polygon corresponding to the target area is divided into a plurality of sub-polygons based on the latitude and longitude data of the plurality of boarding points, and each of the sub-polygons contains one of the boarding points.

[0014] In one embodiment, dividing the plane polygon corresponding to the target area into a plurality of sub-polygons based on the latitude and longitude data of the plurality of boarding points includes:

[0015] The planar polygon corresponding to the target area is divided into a plurality of sub-polygons based on the latitude and longitude data of the plurality of boarding points by using the Thiessen polygon Voronoi diagram.

[0016] In one embodiment, determining the shortest driving path distance between each two of the sub-polygons comprises:

[0017] Calculating the driving distance between every two adjacent sub-polygons in the plurality of sub-polygons;

[0018] The shortest driving path distance between every two of the sub-polygons is determined based on the driving distance.

[0019] In one embodiment, determining the shortest driving path distance between every two sub-polygons based on the driving distance comprises:

[0020] Determining a driving distance of at least one path between every two of the sub-polygons in the plurality of sub-polygons based on the driving distance;

[0021] A shortest driving route distance is determined from the driving distances of the at least one route.

[0022] In one embodiment, clustering the plurality of sub-polygons based on the shortest driving path distance comprises:

[0023] The multiple sub-polygons are clustered based on the shortest driving path distance using a k-center point clustering algorithm.

[0024] In one embodiment, dividing the target area into a plurality of sub-areas based on the clustering result includes:

[0025] splicing the sub-polygons of each cluster in the clustering result to obtain a spliced ​​polygon of each cluster;

[0026] The sub-regions corresponding to the multiple stitching polygons are used to determine multiple sub-regions of the target region.

[0027] According to a second aspect of the present application, a device for dividing a region is provided, comprising:

[0028] A polygon division module, used for dividing the plane polygon corresponding to the target area into a plurality of sub-polygons based on a plurality of boarding points in the target area;

[0029] A path distance determination module, used for determining the shortest driving path distance between every two of the sub-polygons;

[0030] A clustering result acquisition module, used for clustering the plurality of sub-polygons based on the shortest driving path distance to obtain a clustering result;

[0031] The target area division module is used to divide the target area into multiple sub-areas based on the clustering result.

[0032] According to a third aspect of the present application, a device for dividing regions is proposed, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the above-mentioned methods for dividing regions when executing the program.

[0033] According to a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute any of the above-mentioned methods for dividing regions.

[0034] It can be seen from the above technical scheme that the present application divides the plane polygon corresponding to the target area into multiple sub-polygons based on multiple boarding points, determines the shortest driving path distance between every two sub-polygons, and then clusters the multiple sub-polygons based on the shortest driving path distance. This can achieve the division of the target area into multiple sub-areas based on the clustering results. Since what is determined is the shortest driving path distance between two sub-polygons, the disadvantage of easily dividing two sub-polygons separated by physical obstacles into one sub-area based on the straight-line distance can be avoided. In addition, since multiple sub-polygons are clustered based on the shortest driving path distance, accurate division of the target area can be achieved based on the clustering results. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flow chart of a method for dividing regions shown in an exemplary embodiment of the present application;

[0036] Figure 2 is a flowchart showing how to divide a plane polygon corresponding to a target area into multiple sub-polygons according to an exemplary embodiment of the present application;

[0037] Figure 3 is a flowchart showing how to determine the shortest driving path distance between every two sub-polygons according to an exemplary embodiment of the present application;

[0038] Figure 4A is a flowchart showing how to determine the shortest driving path distance between every two sub-polygons based on driving distance according to an exemplary embodiment of the present application;

[0039] Figure 4Bis a schematic diagram showing an exemplary embodiment of the present application of dividing a plane polygon corresponding to a target area into a plurality of sub-polygons;

[0040] Figure 5A is a flowchart showing how to divide a target area into multiple sub-areas based on clustering results according to an exemplary embodiment of the present application;

[0041] Figure 5B is a schematic diagram showing an exemplary embodiment of the present application in which a target area is divided into multiple sub-areas;

[0042] Figure 6 is a structural diagram of a device for dividing regions shown in an exemplary embodiment of the present application;

[0043] Figure 7 is a structural diagram of a device for dividing regions shown in another exemplary embodiment of the present application;

[0044] Figure 8 It is a structural diagram of a device for dividing areas shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0045] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0046] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0047] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0048] Figure 1is a flow chart of a method for dividing regions shown in an exemplary embodiment of the present application; this embodiment can be used in a platform server, wherein the platform server may include a server or a server cluster consisting of multiple servers. Figure 1 As shown, the method includes steps S101-S103:

[0049] In step S101: based on a plurality of boarding points in the target area, a plane polygon corresponding to the target area is divided into a plurality of sub-polygons.

[0050] In one embodiment, the server may execute the method of this embodiment before dividing the passengers into different areas for queuing, so as to reasonably divide the target area into multiple sub-areas, and then implement the subsequent step of dividing the passengers into queues corresponding to one of the sub-areas for queuing. This embodiment does not limit this.

[0051] In one embodiment, the type of pick-up point in the target area can be set by the developer according to actual business needs, such as the actual pick-up point for most users, popular pick-up points, or general pick-up points determined based on historical order data, etc. This embodiment does not limit this.

[0052] In one embodiment, the plane polygon corresponding to the target area may include a polygonal area covered by the target area on a preset map.

[0053] In one embodiment, after the server determines the target area to be divided, it can determine multiple boarding points in the target area, and then divide the plane polygon corresponding to the target area into multiple sub-polygons based on the multiple boarding points.

[0054] In one embodiment, the above method of dividing the plane polygon corresponding to the target area into a plurality of sub-polygons can also refer to the following Figure 2 The illustrated embodiment will not be described in detail here.

[0055] In step S102: determining the shortest driving path distance between every two sub-polygons.

[0056] In one embodiment, after the plane polygon corresponding to the target area is divided into a plurality of sub-polygons based on a plurality of boarding points within the target area, the shortest driving path distance between every two of the sub-polygons may be determined.

[0057] In one embodiment, after dividing the plane polygon corresponding to the target area into a plurality of sub-polygons, a plurality of different driving paths from each sub-polygon to another sub-polygon may be determined, wherein each driving path may pass through a different sub-polygon.

[0058] In one embodiment, the shortest driving path distance between the boarding points in two sub-polygons may be determined as the shortest driving path distance between the two sub-polygons.

[0059] It can be understood that, in this embodiment, since the shortest driving path distance between two sub-polygons is determined, the disadvantage of easily dividing two sub-polygons separated by physical obstacles into one sub-area based on the straight-line distance between the two sub-polygons can be avoided, and the rationality and accuracy of subsequent clustering and target area division based on the shortest driving path distance can be improved.

[0060] In one embodiment, a matrix may be used to represent the shortest driving path distance between each two sub-polygons in a plurality of sub-polygons. For example, the element a(i,j) in the matrix may be used to represent the length of the shortest path from the i-th sub-polygon to the j-th sub-polygon.

[0061] In one embodiment, the above method of determining the shortest driving path distance between each two sub-polygons can also refer to the following Figure 3 The illustrated embodiment will not be described in detail here.

[0062] In step S103: clustering the multiple sub-polygons based on the shortest driving path distance to obtain a clustering result.

[0063] In one embodiment, after the shortest driving path distance between every two sub-polygons is determined, the plurality of sub-polygons may be clustered based on the shortest driving path distance to obtain a clustering result.

[0064] In one embodiment, a k-center point (kmedoids) clustering algorithm may be used to cluster the plurality of sub-polygons based on the shortest driving path distance.

[0065] Among them, the k-center point clustering algorithm is different from other clustering algorithms in that it does not cluster multiple objects according to the coordinates of multiple objects or the Euclidean distances between multiple objects and the cluster center, but clusters multiple objects according to the distance between every two objects in the multiple objects. Therefore, it can further avoid the disadvantage of dividing two sub-polygons separated by physical obstacles into one sub-area.

[0066] It is worth noting that the above-mentioned k-center point clustering algorithm is only used for illustrative purposes. In actual applications, in addition to selecting the above-mentioned k-center point clustering algorithm to cluster multiple sub-polygons, developers can also select other clustering algorithms to cluster multiple sub-polygons according to business needs. The obtained clustering results are also applicable to the subsequent steps of dividing the target area.

[0067] In step S104: the target area is divided into a plurality of sub-areas based on the clustering result.

[0068] In one embodiment, after clustering the multiple sub-polygons based on the shortest driving path distance to obtain a clustering result, the target area can be divided into multiple sub-areas based on the clustering result.

[0069] In one embodiment, after the clustering results of multiple sub-polygons are obtained, a sub-polygon corresponding to each cluster in the clustering results may be determined as a sub-region, thereby dividing the target region into multiple sub-regions.

[0070] In one embodiment, the above method of dividing the target area into multiple sub-areas based on the clustering result can also refer to the following Figure 5A The illustrated embodiment will not be described in detail here.

[0071] As can be seen from the above description, this embodiment divides the plane polygon corresponding to the target area into multiple sub-polygons based on multiple boarding points, determines the shortest driving path distance between every two sub-polygons, and then clusters the multiple sub-polygons based on the shortest driving path distance. This can achieve dividing the target area into multiple sub-areas based on the clustering results. Since what is determined is the shortest driving path distance between two sub-polygons, the disadvantage of easily dividing two sub-polygons separated by physical obstacles into one sub-area based on the straight-line distance can be avoided. In addition, since the multiple sub-polygons are clustered based on the shortest driving path distance, the accurate division of the target area can be achieved based on the clustering results.

[0072] Figure 2 FIG. 1 is a flowchart of an exemplary embodiment of the present application showing how to divide a plane polygon corresponding to a target area into multiple sub-polygons. Based on the above embodiment, this embodiment takes how to divide a plane polygon corresponding to a target area into multiple sub-polygons as an example for exemplary description. Figure 2 As shown, the above step S101 of dividing the plane polygon corresponding to the target area into multiple sub-polygons based on multiple boarding points in the target area may include the following steps S201-S202:

[0073] In step S201, the longitude and latitude data of multiple boarding points in the target area are obtained.

[0074] In one embodiment, after the server determines the target area to be divided, it can determine multiple boarding points in the target area, and then obtain the longitude and latitude data of each of the multiple boarding points in the target area.

[0075] In one embodiment, based on the identification information of each boarding point, the longitude and latitude data of the boarding point can be queried from pre-stored correspondence data between the boarding point identification and the longitude and latitude, which is not limited in this embodiment.

[0076] In one embodiment, the identification information of the above-mentioned boarding point can be freely set by the developer, such as being set to the name or number of the boarding point, etc., and this embodiment does not limit this.

[0077] In step S202, the plane polygon corresponding to the target area is divided into a plurality of sub-polygons based on the latitude and longitude data of the plurality of boarding points, each of the sub-polygons containing one of the boarding points.

[0078] In one embodiment, after obtaining the latitude and longitude data of multiple boarding points in the target area, the plane polygon corresponding to the above target area can be divided into multiple sub-polygons based on the latitude and longitude data of the multiple boarding points, and each of the sub-polygons contains one of the boarding points.

[0079] For example, if multiple sub-polygons are divided based on the latitude and longitude data of the boarding points, each sub-polygon can contain only one point, that is, the plane polygon can be divided into 800 sub-polygons based on 800 boarding points.

[0080] In one embodiment, the Thiessen polygon voronoi diagram may be used to divide the plane polygon corresponding to the target area into a plurality of sub-polygons based on the latitude and longitude data of the plurality of boarding points.

[0081] It is worth noting that by using the Voronoi diagram to divide the plane polygon into multiple sub-polygons based on the boarding points, it can be ensured that the distances between the boarding points in two adjacent sub-polygons and the common dividing line of the two sub-polygons are equal. In addition, it can be ensured that any point in each sub-polygon (such as a new boarding point generated later) is closer to the boarding point in this sub-polygon than to the boarding points in other sub-polygons, which is conducive to improving the accuracy of subsequent clustering.

[0082] In one embodiment, the shortest driving path distance between the boarding points in two sub-polygons may be determined as the shortest driving path distance between the two sub-polygons. Therefore, when the distances between the boarding points in two adjacent sub-polygons and the common dividing line of the two sub-polygons are equal, the driving path distance between the two sub-polygons may be calculated based on twice the distance between the boarding point of one of the adjacent sub-polygons and the common dividing line of the two sub-polygons, which may simplify the process of calculating the driving path distance between the two sub-polygons.

[0083] From the above description, it can be seen that this embodiment obtains the longitude and latitude data of multiple boarding points in the target area, and divides the plane polygon corresponding to the target area into multiple sub-polygons based on the longitude and latitude data of the multiple boarding points. It can be realized that the plane polygon corresponding to the target area is divided into multiple sub-polygons based on the multiple boarding points in the target area, and then the shortest driving path distance between every two sub-polygons can be subsequently determined, and clustering and division of the target area can be performed based on the shortest driving path distance, which can improve the rationality and accuracy of the target area division.

[0084] Figure 3 FIG. 1 is a flowchart of an exemplary embodiment of the present application showing how to determine the shortest driving path distance between every two sub-polygons. Based on the above embodiment, this embodiment takes how to determine the shortest driving path distance between every two sub-polygons as an example for exemplary description. Figure 3 As shown, the determination of the shortest driving path distance between each two sub-polygons in the above step S102 may include the following steps S301-S302:

[0085] In step S301 , the driving distance between every two adjacent sub-polygons in the plurality of sub-polygons is calculated.

[0086] In one embodiment, after the plane polygon corresponding to the target area is divided into multiple sub-polygons based on multiple boarding points in the target area, the driving distance between each two adjacent sub-polygons in the multiple sub-polygons can be calculated, and then the shortest driving path distance between each two sub-polygons in the multiple sub-polygons can be calculated based on the driving distance between the two adjacent sub-polygons.

[0087] In one embodiment, the driving distance between the boarding points in each two adjacent sub-polygons may be calculated, and the distance may be determined as the driving distance between the two adjacent sub-polygons.

[0088] In step S302, the shortest driving path distance between every two sub-polygons is determined based on the driving distance.

[0089] In one embodiment, after calculating the driving distance between every two adjacent sub-polygons in the plurality of sub-polygons, a plurality of different driving paths between every two adjacent sub-polygons may be determined based on the driving distance between the two adjacent sub-polygons.

[0090] In one embodiment, each of the driving paths mentioned above may be formed by connecting driving paths between two adjacent sub-polygons.

[0091] In one embodiment, the above method of determining the shortest driving path distance between each two sub-polygons based on the driving distance can also refer to the following Figure 4A The illustrated embodiment will not be described in detail here.

[0092] As can be seen from the above description, this embodiment calculates the driving distance between each two adjacent sub-polygons in the multiple sub-polygons, and determines the shortest driving path distance between each two sub-polygons based on the driving distance. This can achieve the determination of the shortest driving path distance between each two sub-polygons based on the driving distance between adjacent sub-polygons, avoid the disadvantage of dividing two sub-polygons separated by physical obstacles into one sub-area based on the straight-line distance, reduce the number of times the navigation distance is requested, and thus reduce the computing burden of the server.

[0093] Figure 4A FIG. 1 is a flowchart showing how to determine the shortest driving path distance between each two sub-polygons based on driving distance according to an exemplary embodiment of the present application. Based on the above embodiment, this embodiment takes how to determine the shortest driving path distance between each two sub-polygons based on driving distance as an example for exemplary description. Figure 4A As shown, the determination of the shortest driving path distance between every two sub-polygons based on the driving distance in the above step S302 may include the following steps S401-S402:

[0094] In step S401 , the driving distance of at least one path between every two of the sub-polygons in the plurality of sub-polygons is determined based on the driving distance.

[0095] In one embodiment, after the driving distance between every two adjacent sub-polygons in the plurality of sub-polygons is calculated, the driving distance of at least one path between every two adjacent sub-polygons in the plurality of sub-polygons may be determined based on the driving distance.

[0096] In step S402, the shortest driving path distance is determined from the driving distances of the at least one path.

[0097] In one embodiment, after determining the driving distance of at least one path between each two of the sub-polygons in the plurality of sub-polygons based on the driving distance, the shortest driving path distance can be determined from the driving distance of the at least one path. Wherein, each driving path is formed by connecting the driving paths between two adjacent sub-polygons (that is, each sub-polygon can only directly reach its adjacent sub-polygon, and to reach the non-adjacent sub-polygon, it needs to be indirectly reached through the adjacent sub-polygon), and then the distance of each driving path can be determined, and the shortest driving path distance can be determined.

[0098] For example, Figure 4B FIG. 1 is a schematic diagram showing an exemplary embodiment of the present application in which a planar polygon corresponding to a target area is divided into a plurality of sub-polygons. Figure 4B As shown, the plane polygon 001 corresponding to the target area is divided into sub-polygons a, b, c, and d. Therefore, the driving distance between each two adjacent sub-polygons in the sub-polygons a, b, c, and d can be calculated, such as ab, ac, bc, bd, and cd. On this basis, the shortest driving path distance between each two sub-polygons can be determined based on these driving distances. Taking the calculation of the shortest driving path distance between sub-polygons a and d as an example, there can be multiple driving paths between sub-polygon a and sub-polygon d, including: abd driving path and acd driving path, and each driving path is connected by the driving paths between two adjacent sub-polygons. Further, the distances of the two driving paths can be calculated, and the distances of the two driving paths can be compared or sorted to determine the shortest driving path between sub-polygon a and sub-polygon d, such as the abd driving path.

[0099] Based on the same method, the shortest driving paths between a to b, a to c, b to d, and c to d can be determined, which will not be described in detail here.

[0100] As can be seen from the above description, this embodiment determines the driving distance of at least one path between every two of the sub-polygons in the multiple sub-polygons based on the driving distance, and determines the shortest driving path distance from the driving distance of the at least one path. This can achieve the determination of the shortest driving path distance between every two of the sub-polygons based on the driving distance, and then achieve subsequent clustering and division of the target area based on the shortest driving path distance, which can improve the rationality and accuracy of the target area division.

[0101] Figure 5A FIG. 1 is a flowchart of an exemplary embodiment of the present application showing how to divide a target area into multiple sub-areas based on clustering results; based on the above embodiment, this embodiment takes how to divide a target area into multiple sub-areas based on clustering results as an example for exemplary description. Figure 5A As shown, the above step S104 of dividing the target area into multiple sub-areas based on the clustering result may include the following steps S501-S502:

[0102] In step S501, the sub-polygons of each cluster in the clustering result are spliced ​​to obtain a spliced ​​polygon of each cluster.

[0103] In one embodiment, after the plurality of sub-polygons are clustered based on the shortest driving path distance to obtain a clustering result, the sub-polygons of each cluster in the clustering result may be spliced ​​to obtain a spliced ​​polygon of each cluster.

[0104] For example, Figure 5B FIG. 1 is a schematic diagram showing an exemplary embodiment of the present application in which a target area is divided into multiple sub-areas. Figure 5B As shown, after obtaining the two clustering results of {a, b, c, d} and {e, f, g, h}, the sub-polygons of the two clusters can be spliced ​​respectively, that is, the sub-polygons a, b, c and d are spliced ​​to obtain the spliced ​​polygon 011; and, the sub-polygons e, f, g and h are spliced ​​to obtain the spliced ​​polygon 012.

[0105] In step S502, the sub-regions corresponding to the multiple stitching polygons are used to determine multiple sub-regions of the target region.

[0106] In one embodiment, after the stitching polygons of each cluster are obtained, the sub-regions corresponding to the multiple stitching polygons can be used to determine the multiple sub-regions of the target region.

[0107] Still refer to Figure 5B In the illustrated embodiment, after the stitching polygon 011 and the stitching polygon 012 are obtained, the sub-regions corresponding to the stitching polygon 011 and the stitching polygon 012 can be determined as two sub-regions of the target region 010 .

[0108] From the above description, it can be seen that this embodiment obtains the stitching polygons of each cluster by splicing the sub-polygons of each cluster in the clustering results, and determines the multiple sub-regions of the target area by the sub-regions corresponding to the multiple stitching polygons. It can achieve dividing the target area into multiple sub-regions based on the clustering results, which can improve the accuracy of dividing the target area.

[0109] Figure 6 FIG. 1 is a structural diagram of a device for dividing regions shown in an exemplary embodiment of the present application. Figure 6 As shown, the device includes: a polygon division module 110, a path distance determination module 120, a clustering result acquisition module 130 and a target area division module 140, wherein:

[0110] A polygon division module 110, configured to divide a plane polygon corresponding to the target area into a plurality of sub-polygons based on a plurality of boarding points within the target area;

[0111] A path distance determination module 120, for determining the shortest driving path distance between every two of the sub-polygons;

[0112] A clustering result acquisition module 130, configured to cluster the plurality of sub-polygons based on the shortest driving path distance to obtain a clustering result;

[0113] The target region division module 140 is configured to divide the target region into a plurality of sub-regions based on the clustering result.

[0114] As can be seen from the above description, this embodiment divides the plane polygon corresponding to the target area into multiple sub-polygons based on multiple boarding points, determines the shortest driving path distance between every two sub-polygons, and then clusters the multiple sub-polygons based on the shortest driving path distance. This can achieve dividing the target area into multiple sub-areas based on the clustering results. Since what is determined is the shortest driving path distance between two sub-polygons, the disadvantage of easily dividing two sub-polygons separated by physical obstacles into one sub-area based on the straight-line distance can be avoided. In addition, since the multiple sub-polygons are clustered based on the shortest driving path distance, the accurate division of the target area can be achieved based on the clustering results.

[0115] Figure 7 is a structural diagram of a device for dividing a region shown in another exemplary embodiment of the present application; wherein the polygon division module 210, the path distance determination module 220, the clustering result acquisition module 230 and the target region division module 240 are the same as the aforementioned Figure 6 The functions of the polygon division module 110, the path distance determination module 120, the clustering result acquisition module 130 and the target area division module 140 in the illustrated embodiment are the same and will not be described in detail herein. Figure 7 As shown, the polygon partitioning module 210 may include:

[0116] A latitude and longitude data acquisition unit 211 is used to acquire the latitude and longitude data of multiple boarding points in the target area;

[0117] The polygon division unit 212 is used to divide the plane polygon corresponding to the target area into multiple sub-polygons based on the latitude and longitude data of the multiple boarding points, and each of the sub-polygons contains one of the boarding points.

[0118] In one embodiment, the polygon division unit 212 is further configured to use a Thiessen polygon voronoi diagram to divide the plane polygon corresponding to the target area into a plurality of sub-polygons based on the longitude and latitude data of the plurality of boarding points.

[0119] In one embodiment, the path distance determination module 220 may include:

[0120] A driving distance calculation unit 221, configured to calculate a driving distance between every two adjacent sub-polygons in the plurality of sub-polygons;

[0121] The path distance determining unit 222 is configured to determine the shortest driving path distance between every two of the sub-polygons based on the driving distance.

[0122] In one embodiment, the path distance determining unit 222 may also be used to:

[0123] Determining a driving distance of at least one path between every two of the sub-polygons in the plurality of sub-polygons based on the driving distance;

[0124] A shortest driving route distance is determined from the driving distances of the at least one route.

[0125] In one embodiment, the clustering result acquisition module 230 is further configured to cluster the plurality of sub-polygons based on the shortest driving path distance using a k-center point clustering algorithm.

[0126] In one embodiment, the target area division module 240 may include:

[0127] A splicing polygon acquisition unit 241 is used to splice the sub-polygons of each cluster in the clustering result to obtain a splicing polygon of each cluster;

[0128] The target area division unit 242 is used to determine multiple sub-areas of the target area from the sub-areas corresponding to the multiple stitching polygons.

[0129] It is worth noting that all the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present disclosure, which will not be described one by one here.

[0130] The embodiment of the device for dividing regions of the present invention can be applied to network devices. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. Taking software implementation as an example, as a device in a logical sense, the processor of the device in which it is located reads the corresponding computer program instructions in the non-volatile memory into the memory and runs it, wherein the computer program is used to execute the above Figure 1 to Figure 5A The method for dividing regions provided in the embodiment shown in the figure. From the hardware level, Figure 8 The hardware structure diagram of the device for dividing regions of the present invention is shown in FIG. Figure 8 In addition to the processor, network interface, memory and non-volatile memory shown, the device may also include other hardware, such as a forwarding chip responsible for processing messages, etc.; from the hardware structure, the device may also be a distributed device, which may include multiple interface cards to expand message processing at the hardware level. On the other hand, the present application also provides a computer-readable storage medium, which stores a computer program, and the computer program is used to execute the above Figure 1 to Figure 5AThe illustrated embodiment provides a method for dividing areas.

[0131] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0132] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0133] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0134] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for dividing a region, characterized in that: The method is performed before passengers are divided into different areas for queuing; the method comprises: Dividing a plane polygon corresponding to the target area into a plurality of sub-polygons based on a plurality of boarding points within the target area; Determining the shortest driving path distance between each two of the sub-polygons; Clustering the plurality of sub-polygons based on the shortest driving path distance to obtain a clustering result; Dividing the target area into a plurality of sub-areas based on the clustering result; The passengers are divided into queues corresponding to one of the sub-areas for queuing.

2. The method according to claim 1, characterized in that The step of dividing a plane polygon corresponding to the target area into a plurality of sub-polygons based on a plurality of boarding points within the target area includes: Obtain the latitude and longitude data of multiple boarding points in the target area; The plane polygon corresponding to the target area is divided into a plurality of sub-polygons based on the latitude and longitude data of the plurality of boarding points, and each of the sub-polygons contains one of the boarding points.

3. The method according to claim 2, characterized in that The dividing the plane polygon corresponding to the target area into a plurality of sub-polygons based on the latitude and longitude data of the plurality of boarding points comprises: The planar polygon corresponding to the target area is divided into a plurality of sub-polygons based on the latitude and longitude data of the plurality of boarding points by using the Thiessen polygon Voronoi diagram.

4. The method according to claim 1, characterized in that: The determining the shortest driving path distance between each two of the sub-polygons comprises: Calculating the driving distance between every two adjacent sub-polygons in the plurality of sub-polygons; The shortest driving path distance between every two of the sub-polygons is determined based on the driving distance.

5. The method according to claim 4, characterized in that The determining the shortest driving path distance between every two sub-polygons based on the driving distance comprises: Determining a driving distance of at least one path between every two of the sub-polygons in the plurality of sub-polygons based on the driving distance; A shortest driving route distance is determined from the driving distances of the at least one route.

6. The method according to claim 1, characterized in that The clustering of the plurality of sub-polygons based on the shortest driving path distance comprises: The multiple sub-polygons are clustered based on the shortest driving path distance using a k-center point clustering algorithm.

7. The method according to any one of claims 1 to 6, characterized in that: The step of dividing the target area into a plurality of sub-areas based on the clustering result includes: splicing the sub-polygons of each cluster in the clustering result to obtain a spliced ​​polygon of each cluster; The sub-regions corresponding to the multiple stitching polygons are used to determine multiple sub-regions of the target region.

8. A device for dividing regions, characterized in that: include: A polygon division module, before dividing passengers into different areas for queuing, is used to divide the plane polygon corresponding to the target area into multiple sub-polygons based on multiple boarding points in the target area; A path distance determination module, used for determining the shortest driving path distance between each two sub-polygons before dividing the passengers into different areas for queuing; A clustering result acquisition module, before dividing the passengers into different areas for queuing, is used to cluster the multiple sub-polygons based on the shortest driving path distance to obtain a clustering result; The target area division module is used to divide the target area into multiple sub-areas based on the clustering result before dividing the passengers into different areas for queuing; wherein the multiple sub-areas obtained by division are used to divide the passengers into queues corresponding to one of the sub-areas for queuing.

9. A device for dividing areas, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for dividing areas as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute the method for dividing areas described in any one of claims 1 to 7.

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