Service coverage division method and device, equipment and storage medium

Abstract

The invention relates to the technical field of maps, and provides a service coverage area division method and device, equipment and a storage medium. The method comprises the following steps: acquiring respective position information of a plurality of target communal facilities contained in a target area, and acquiring a historical vehicle trajectory set associated with the plurality of target communal facilities in a specified historical period; dividing the plurality of target public facilities into a plurality of public facility sets by combining the relative distance between every two target public facilities based on each historical vehicle trajectory set; the communal facilities in different communal facility sets have different scale levels; based on the historical vehicle track set and the public facility set associated with the multiple target public facilities, respectively determining respective service coverage ranges of the multiple target public facilities; wherein the service coverage ranges of the target public facilities belonging to the same public facility set are not overlapped.

Description

Technical Field

[0001] This application relates to the field of map technology, and provides a method, apparatus, device, and storage medium for dividing service coverage areas. Background Technology

[0002] Currently, in smart city-related government applications, it is necessary to statistically analyze the coverage of public facilities in various regions in order to rationally plan public facility resources for areas lacking such resources and increase the allocation of public facility resources. Therefore, it is necessary to divide the service coverage of the same type of public facilities in each region. The types of public facilities can include schools, hospitals, shopping malls, etc., and the service coverage of public facilities can refer to the distribution area of ​​the main service targets of the public facilities in the region.

[0003] Under relevant technologies, when dividing the service coverage of public facilities, a certain area is usually divided into multiple spatial units. Then, based on big data or questionnaire surveys and other technical means, visit data of residents in multiple spatial units to each public facility of the same category in the area are collected. Then, according to the visit ratio reflected in the visit data, each spatial unit is assigned to the service coverage of the public facility with the highest visit ratio.

[0004] When dividing the service coverage of various public facilities using the above method, each spatial unit can only be assigned to the service coverage of one public facility. However, in actual application, residents usually visit more than one public facility of the same type. Therefore, according to the above method, only assigning spatial units to the service coverage of the public facility with the highest visit rate will ignore residents' needs for other public facilities of the same type. At the same time, it cannot accurately reflect the coverage of public facilities in the region, thus failing to provide an accurate basis for the rational planning of public facility resources, and consequently failing to guarantee the coverage rate of public facilities in each region.

[0005] Furthermore, if the public facilities coverage in some areas is normal, but the resulting classification indicates a lack of public facilities resources in these areas, it may lead to the addition of corresponding public facilities in these areas during subsequent urban planning, which in turn results in a redundancy of public facilities resources in these areas. Summary of the Invention

[0006] This application provides a method, apparatus, device, and storage medium for dividing service coverage areas to solve the problems of unreasonable and inaccurate service coverage area division in related technologies.

[0007] In a first aspect, embodiments of this application provide a method for dividing service coverage, including:

[0008] In one possible implementation, the location information of multiple target public facilities within a target area is obtained, as well as the historical vehicle trajectory sets associated with each of the multiple target public facilities within a specified historical period are obtained; wherein the multiple target public facilities have the same facility category; and at least one endpoint of each historical vehicle trajectory is associated with a corresponding target public facility; based on each historical vehicle trajectory set and combined with the relative distance between each pair of target public facilities, the multiple target public facilities are divided into multiple public facility sets; the public facilities in different public facility sets have different scale levels; based on the historical vehicle trajectory sets and public facility sets associated with each of the multiple target public facilities, the service coverage of each of the multiple target public facilities is determined; wherein the service coverage of target public facilities belonging to the same public facility set does not overlap.

[0009] In one possible implementation, obtaining the historical vehicle trajectory set associated with each of the multiple target public facilities within a specified historical period includes: obtaining multiple candidate vehicle trajectories contained in the target area within the specified historical period; wherein the two endpoints of each candidate vehicle trajectory are located within the target area; and performing the following operations for each of the multiple target public facilities: based on the location information of a target public facility, taking at least one candidate vehicle trajectory whose endpoint is associated with the target public facility as a historical vehicle trajectory associated with the target public facility; and combining the obtained historical vehicle trajectories into a historical vehicle trajectory set associated with the target public facility.

[0010] In one possible implementation, the two endpoints include a start point and an end point; the step of using at least one candidate vehicle trajectory associated with the target public facility based on the location information of the target public facility as the historical vehicle trajectory of the target public facility includes: determining the association range of the target public facility based on the location information of the target public facility; and performing the following operations on each of the multiple candidate vehicle trajectories: when the start point or end point of a candidate vehicle trajectory is located within the association range of the target public facility, the candidate vehicle trajectory is used as the historical vehicle trajectory associated with the target public facility.

[0011] In one possible implementation, the step of dividing the multiple target public facilities into multiple public facility sets based on each historical vehicle trajectory set and the relative distance between each pair of target public facilities includes: determining the passenger flow assessment value of each of the multiple target public facilities based on the number of historical vehicle trajectories included in each historical vehicle trajectory set; and performing the following operations for each of the multiple target public facilities: determining the relative distance between each target public facility and each of the other target public facilities, and selecting a target relative distance that meets the preset passenger flow assessment conditions from the relative distances based on the passenger flow assessment values ​​of each of the multiple target public facilities as the distance assessment value of the target public facility; determining the scale level of each of the multiple target public facilities based on the passenger flow assessment value and the distance assessment value of each of the multiple target public facilities, and adding each of the multiple target public facilities to the public facility set corresponding to the corresponding scale level.

[0012] In one possible implementation, the passenger flow assessment conditions include a first assessment condition and a second assessment condition. Under the first assessment condition, the selected target relative distance is greater than the target relative distance selected under the second assessment condition. The step of selecting a target relative distance that meets the preset passenger flow assessment conditions from among the relative distances based on the passenger flow assessment values ​​of the plurality of target public facilities includes: when the passenger flow assessment value of one target public facility is greater than that of all other target public facilities, selecting a target relative distance that meets the first assessment condition from among the relative distances; when the passenger flow assessment value of one target public facility is not greater than that of any other target public facility, selecting a target relative distance that meets the second assessment condition from among the relative distances associated with a reference public facility of the one target public facility; the reference public facility is the target public facility whose passenger flow assessment value is greater than that of the one target public facility.

[0013] In one possible implementation, determining the scale level of each of the multiple target public facilities based on their respective passenger flow assessment values ​​and distance assessment values ​​includes: obtaining a preset number of scale levels, and the passenger flow assessment interval and distance assessment interval corresponding to each scale level; for each of the multiple target public facilities, performing the following operations respectively: in the passenger flow assessment interval and distance assessment interval corresponding to each scale level, determining a target passenger flow assessment interval containing the passenger flow assessment value of one target public facility, and a target distance assessment interval containing the distance assessment value of the one target public facility; and using the scale level corresponding to the target passenger flow assessment interval and the target distance assessment interval as the scale level of the one target public facility.

[0014] In one possible implementation, determining the service coverage of each of the multiple target public facilities based on their respective associated historical vehicle trajectory sets and public facility sets includes: obtaining location information of multiple spatial units within the target area; determining the corresponding passenger flow sets for each of the multiple spatial units based on their respective associated historical vehicle trajectory sets; wherein each passenger flow represents the number of historical vehicle trajectories traveling between the corresponding spatial unit and a target public facility; each passenger flow set includes a one-to-one correspondence between the passenger flow and the target public facility; and determining the spatial units included in the service coverage of each of the multiple target public facilities based on their respective passenger flow sets and the public facility sets to which they belong.

[0015] In one possible implementation, determining the spatial units included in the service coverage of each of the multiple target public facilities based on the respective passenger flow sets of the multiple spatial units and the public facility sets to which the multiple target public facilities belong, includes: performing the following operations for each of the multiple spatial units: selecting one target public facility in each of the public facility sets based on the passenger flow set corresponding to one spatial unit, and assigning the one spatial unit to the service coverage of the selected multiple target public facilities.

[0016] Secondly, embodiments of this application also provide a service coverage area division device, including:

[0017] A communication unit is configured to acquire location information of multiple target public facilities within a target area, and to acquire a set of historical vehicle trajectories associated with each of the multiple target public facilities within a specified historical period; wherein the multiple target public facilities have the same facility category; and at least one endpoint of each historical vehicle trajectory is associated with a corresponding target public facility.

[0018] The level division unit is used to divide the multiple target public facilities into multiple public facility sets based on each historical vehicle trajectory set and the relative distance between each pair of target public facilities; the public facilities in different public facility sets have different scale levels;

[0019] The service coverage division unit is used to determine the service coverage of each of the multiple target public facilities based on their respective historical vehicle trajectory sets and public facility sets; wherein the service coverage of target public facilities belonging to the same public facility set do not overlap.

[0020] In one possible implementation, the communication unit acquires a set of historical vehicle trajectories associated with each of the multiple target public facilities within a specified historical period. Specifically, this is used to: acquire multiple candidate vehicle trajectories contained in the target area within the specified historical period; wherein the two endpoints of each candidate vehicle trajectory are located within the target area; and the trajectory processing unit is used to perform the following operations for each of the multiple target public facilities: based on the location information of a target public facility, taking at least one candidate vehicle trajectory whose endpoint is associated with the target public facility as a historical vehicle trajectory associated with the target public facility; and combining the obtained historical vehicle trajectories into a set of historical vehicle trajectories associated with the target public facility.

[0021] In one possible implementation, the two endpoints include a start point and an end point; the trajectory processing unit, based on the location information of a target public facility, uses candidate vehicle trajectories whose endpoints are associated with the target public facility as historical vehicle trajectories of the target public facility, specifically for: determining the association range of the target public facility based on the location information of the target public facility; and performing the following operations on the multiple candidate vehicle trajectories respectively: when the start point or end point of a candidate vehicle trajectory is located within the association range of the target public facility, the candidate vehicle trajectory is used as a historical vehicle trajectory associated with the target public facility.

[0022] In one possible implementation, the level division unit divides the multiple target public facilities into multiple public facility sets based on each historical vehicle trajectory set and the relative distance between each pair of target public facilities. Specifically, it is used to: determine the passenger flow assessment value of each of the multiple target public facilities based on the number of historical vehicle trajectories included in each historical vehicle trajectory set; and for each of the multiple target public facilities, perform the following operations: determine the relative distance between each target public facility and all other target public facilities, and select a target relative distance that meets the preset passenger flow assessment conditions from each relative distance based on the passenger flow assessment value of each of the multiple target public facilities, as the distance assessment value of the target public facility; and determine the scale level of each of the multiple target public facilities based on the passenger flow assessment value and distance assessment value of each of the multiple target public facilities, and add each of the multiple target public facilities to the public facility set corresponding to the corresponding scale level.

[0023] In one possible implementation, the passenger flow assessment conditions include a first assessment condition and a second assessment condition. Under the first assessment condition, the selected target relative distance is greater than the target relative distance selected under the second assessment condition. The level division unit selects target relative distances that meet the preset passenger flow assessment conditions from the relative distances based on the passenger flow assessment values ​​of the plurality of target public facilities. Specifically, it is used to: select target relative distances that meet the first assessment condition from the relative distances when the passenger flow assessment value of one target public facility is greater than that of any other target public facility; and select target relative distances that meet the second assessment condition from the relative distances associated with the reference public facility of the target public facility when the passenger flow assessment value of one target public facility is not greater than that of any other target public facility. The reference public facility is the target public facility whose passenger flow assessment value is greater than that of the target public facility.

[0024] In one possible implementation, the level classification unit determines the scale level of each of the multiple target public facilities based on their respective passenger flow assessment values ​​and distance assessment values. Specifically, it is used to: obtain a preset number of scale levels, and the passenger flow assessment interval and distance assessment interval corresponding to each scale level; and for each of the multiple target public facilities, perform the following operations respectively: in the passenger flow assessment interval and distance assessment interval corresponding to each scale level, determine a target passenger flow assessment interval that includes the passenger flow assessment value of one target public facility, and a target distance assessment interval that includes the distance assessment value of the one target public facility; and use the scale level corresponding to the target passenger flow assessment interval and the target distance assessment interval as the scale level of the one target public facility.

[0025] In one possible implementation, the service coverage area division unit determines the service coverage area of ​​each of the multiple target public facilities based on the historical vehicle trajectory set and public facility set associated with each of the multiple target public facilities. Specifically, it is used to: obtain the location information of multiple spatial units included in the target area; determine the corresponding passenger flow set of each of the multiple spatial units based on the historical vehicle trajectory set associated with each of the multiple target public facilities; wherein each passenger flow represents the number of historical vehicle trajectories traveling between the corresponding spatial unit and a target public facility; the passenger flow included in each passenger flow set corresponds one-to-one with the target public facility; and determine the spatial units included in the service coverage area of ​​each of the multiple target public facilities based on the passenger flow set corresponding to each of the multiple spatial units and the public facility set to which each of the multiple target public facilities belongs.

[0026] In one possible implementation, the service coverage division unit determines the spatial units included in the service coverage of each of the multiple target public facilities based on the passenger flow sets corresponding to each of the multiple spatial units and the public facility sets to which each of the multiple target public facilities belongs. Specifically, it performs the following operations for each of the multiple spatial units: based on the passenger flow set corresponding to a spatial unit, select a target public facility in each of the public facility sets, and assign the spatial unit to the service coverage of each of the selected multiple target public facilities.

[0027] Thirdly, embodiments of this application also provide a computer device, including a processor and a memory, wherein the memory stores program code, and when the program code is executed by the processor, the processor performs the steps of any of the above-described service coverage division methods.

[0028] Fourthly, embodiments of this application also provide a computer-readable storage medium including program code, which, when the program product is run on a computer device, is used to cause the computer device to perform the steps of any of the above-described service coverage division methods.

[0029] Fifthly, embodiments of this application also provide a computer program product, including computer instructions, which are executed by a processor using the steps of any of the above-described service coverage division methods.

[0030] The beneficial effects of this application are as follows:

[0031] This application provides a method, apparatus, device, and storage medium for dividing service coverage. In this method, multiple target public facilities can be divided into multiple public facility sets based on each historical vehicle trajectory set and the relative distance between each pair of target public facilities. Since the division of public facility sets is not based on empirically determined scale levels, public facilities that do not have a specific division system or whose scale levels are difficult to define in actual applications can be divided into scale levels through a data-driven approach.

[0032] Furthermore, since the service coverage of each of the multiple target public facilities is determined based on the historical vehicle trajectory set and public facility set associated with each of the multiple target public facilities, the scale level of the target public facilities is taken into account when dividing the service coverage. Therefore, the problem of ignoring residents' needs for other public facilities of the same scale level in related technologies can be avoided, thus improving the rationality of the service coverage division.

[0033] Furthermore, since the service coverage of target public facilities belonging to the same set of public facilities does not overlap, the service coverage of target public facilities of the same scale can be mutually exclusive, thereby making the service coverage divided through the embodiments of this application more accurate, thus promoting the rationality of urban planning and helping to optimize the allocation of public facility resources.

[0034] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0035] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0036] Figure 1 This is an optional schematic diagram of an application scenario in the embodiments of this application;

[0037] Figure 2 A flowchart illustrating the method for dividing the service coverage area provided in this application embodiment;

[0038] Figure 3 A schematic diagram of the target public facility provided in the embodiments of this application;

[0039] Figure 4 This is a schematic diagram illustrating another spatial unit division method provided in an embodiment of this application;

[0040] Figure 5 A schematic diagram of candidate vehicle trajectories and historical vehicle trajectories provided for embodiments of this application;

[0041] Figure 6 An exemplary flowchart of the public facility set partitioning method provided in the embodiments of this application;

[0042] Figure 7 A schematic diagram illustrating the process of selecting the target relative distance in an embodiment of this application;

[0043] Figure 8 This is a schematic diagram illustrating the process of dividing a public facility set according to an embodiment of this application;

[0044] Figure 9 A schematic diagram illustrating the selection process of another target relative distance provided in an embodiment of this application;

[0045] Figure 10 A two-dimensional decision-making diagram provided for embodiments of this application;

[0046] Figure 11 This is a schematic diagram illustrating the process of determining the passenger flow matrix provided in an embodiment of this application.

[0047] Figure 12 A schematic diagram of a service coverage area division device provided in an embodiment of this application;

[0048] Figure 13 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of this application;

[0049] Figure 14 This is a schematic diagram of the hardware structure of another computer device that applies an embodiment of this application. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this application. Obviously, the described embodiments are only some embodiments of the technical solutions of this application, and not all embodiments. Based on the embodiments recorded in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the technical solutions of this application.

[0051] The design concept of the embodiments of this application is briefly introduced below:

[0052] Currently, in smart city-related government applications, it is necessary to statistically analyze the coverage of public facilities in various regions in order to rationally plan public facility resources for areas lacking such resources and increase the allocation of public facility resources. Therefore, it is necessary to divide the service coverage of the same type of public facilities in each region. The types of public facilities can include schools, hospitals, shopping malls, etc., and the service coverage of public facilities can refer to the distribution area of ​​the main service targets of the public facilities in the region.

[0053] Under relevant technologies, when dividing the service coverage of public facilities, a certain area is usually divided into multiple spatial units. Then, based on big data or questionnaire surveys and other technical means, visit data of residents in multiple spatial units to each public facility of the same category in the area are collected. Then, according to the visit ratio reflected in the visit data, each spatial unit is assigned to the service coverage of the public facility with the highest visit ratio.

[0054] When dividing the service coverage of various public facilities using the above method, each spatial unit can only be assigned to the service coverage of one public facility. However, in actual application, residents usually visit more than one public facility of the same type. Therefore, according to the above method, only assigning spatial units to the service coverage of the public facility with the highest visit rate will ignore residents' needs for other public facilities of the same type. At the same time, it cannot accurately reflect the coverage of public facilities in the region, thus failing to provide an accurate basis for the rational planning of public facility resources, and consequently failing to guarantee the coverage rate of public facilities in each region.

[0055] Furthermore, if the public facilities coverage in some areas is normal, but the resulting classification indicates a lack of public facilities resources in these areas, it may lead to the addition of corresponding public facilities in these areas during subsequent urban planning, which in turn results in a redundancy of public facilities resources in these areas.

[0056] For example, residents of Community A might choose to treat common illnesses at Clinic A, general illnesses at the nearby district-level hospital B, and serious illnesses at the tertiary hospital C when selecting public medical facilities. In other words, Community A might be covered by the services of Clinic A, District-level Hospital B, and Tertiary Hospital C simultaneously. However, when dividing the service coverage of public medical facilities in this way, it's possible that due to the large number of residents seeking treatment at Clinic A, Community A might be classified as belonging to Clinic A's service coverage. This could result in statistics showing that the area where Community A is located only has coverage for small-scale public medical facilities, lacking coverage for large-scale ones. Consequently, when urban planning is carried out later to add large-scale public medical facilities to Community A, it could lead to a redundancy of public medical facility resources in Community A.

[0057] In view of this, embodiments of this application provide a method, apparatus, device, and storage medium for dividing service coverage areas. The method includes: acquiring location information of multiple target public facilities with the same facility category within a target area; and acquiring historical vehicle trajectory sets associated with each of the multiple target public facilities within a specified historical period. Based on the acquired historical vehicle trajectory sets, and combined with the relative distance between each pair of target public facilities, the multiple target public facilities are divided into multiple public facility sets. Then, based on the historical vehicle trajectory sets and public facility sets associated with each of the multiple target public facilities, the service coverage area of ​​each of the multiple target public facilities is determined.

[0058] Using the above method, multiple target public facilities can be divided into multiple public facility sets based on each historical vehicle trajectory set and the relative distance between each pair of target public facilities. Since the division of public facility sets is not based on empirically determined scale levels, it can achieve scale level division for public facilities that do not have a specific division system or whose scale levels are difficult to define in actual applications through a data-driven approach.

[0059] Furthermore, since the service coverage areas of each of the multiple target public facilities are jointly defined based on their respective historical vehicle trajectory sets and public facility sets, the scale and level of the target public facilities are taken into account when defining the service coverage areas. This avoids the problem in related technologies of neglecting residents' needs for other public facilities of the same scale and level. In addition, since the service coverage areas of target public facilities belonging to the same public facility set do not overlap, the service coverage areas of target public facilities of the same scale and level can be mutually exclusive. This makes the service coverage areas defined through the embodiments of this application more reasonable and accurate, thereby promoting the rationality of urban planning and helping to optimize the allocation of public facility resources.

[0060] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application. Furthermore, the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0061] Figure 1 One application scenario is shown, which includes a terminal device 110 and a server 120. The terminal device 110 can establish a communication connection with the server 120 through a wired network or a wireless network.

[0062] Terminal device 110 can respond to the operation of relevant staff selecting a target area and selecting library as the facility category in a smart city-related government application, and send a statistical request to server 120 to collect statistics on the library coverage of the target area. The target area can be a city, a province, or an administrative region, etc.; the above-mentioned facility category is only an example, and facility categories can also include hospitals, schools, parks, shopping malls, etc.

[0063] Upon receiving a statistics request, server 120 can obtain the location information of multiple libraries within the target area, as well as the historical vehicle trajectory sets associated with each library within a specified historical period. Then, based on the obtained historical vehicle trajectory sets and the relative distance between each pair of target public facilities, the multiple libraries are divided into multiple public facility sets. Next, based on the historical vehicle trajectory sets and public facility sets associated with each library, the service coverage area of ​​each library is determined, and finally, the determined service coverage areas of each library are returned to terminal device 110.

[0064] Terminal device 110 can display the service coverage of each library in the target area on the screen. Relevant staff can determine the library coverage in the target area based on the displayed service coverage of each library, and then build more libraries in local areas with fewer libraries and larger populations, thereby making reasonable plans for library resources in the target area.

[0065] In one possible implementation, terminal device 110 may also send a recommendation request to server 120 to display public facilities of the corresponding facility category for the specific location in response to the service object's operation of selecting the specific location and facility category in a map application.

[0066] After receiving the recommendation request, server 120 can determine the service coverage of multiple target public facilities in the target area where the specific location belongs using the above method. Then, based on the service coverage of the specific location, it recommends target public facilities to the service recipient and returns the recommendation results to terminal device 110.

[0067] For example, if the target area corresponding to the specific location of the service object is city 1 and the facility category is shopping mall, the server can first determine the service coverage of each shopping mall in city 1. Assuming that the specific location is determined to belong to the service coverage of shopping mall A, shopping mall B and shopping mall C, then shopping mall A, shopping mall B and shopping mall C can be returned as recommendation results to terminal device 110.

[0068] In this application embodiment, the terminal device 110 may be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, etc., but is not limited to these.

[0069] The server 120 in this application embodiment can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms. This application does not impose any restrictions on these services.

[0070] It should be noted that, Figure 1 The application scenarios shown are merely illustrative and are not intended to limit the scope of this application.

[0071] This application provides a method for dividing service coverage that can be applied to... Figure 1 In server 120 shown. See also Figure 2 An exemplary flowchart of a method for dividing the service coverage area for embodiments of this application is provided. The method may include the following steps 201-203:

[0072] Step 201: Obtain the location information of each of the multiple target public facilities contained in the target area, and obtain the historical vehicle trajectory set associated with each of the multiple target public facilities within a specified historical period.

[0073] Among these, multiple target public facilities share the same facility category. This category can be represented by categories such as hospitals, schools, parks, and libraries, or by categories such as medical facilities, shopping facilities, entertainment facilities, and educational facilities; this application does not impose any limitation on this. At least one endpoint of each historical vehicle trajectory in the historical vehicle trajectory set is associated with a corresponding target public facility.

[0074] Optionally, when it is necessary to determine the service coverage of target public facilities for multiple facility categories, this can be done by performing the determination separately for each of the multiple facility categories. Figure 2 The process shown is used to achieve this. For example, suppose we need to determine the service coverage of various shopping malls, hospitals, and parks in a target area. We can first designate each shopping mall in the target area as a target public facility, and then execute... Figure 2 The process shown determines the service coverage area of ​​each shopping mall, and then designates each hospital in the target area as a target public facility, through execution. Figure 2 The process shown determines the service coverage of each hospital, and finally identifies each park in the target area as a target public facility, through execution. Figure 2 The process shown determines the service coverage area of ​​each park.

[0075] In some embodiments, the location information of the target public facility may include contour information, which can be represented by a tuple of (facility_id, facility_boundary), where facility_id is the unique identifier of the target public facility and facility_boundary is the coordinate string that makes up the contour of the target public facility.

[0076] See Figure 3 This is a schematic diagram of the target public facility provided in an embodiment of this application. The target area can be divided into multiple spatial units of the same size. Figure 3 Each square in the diagram can represent one spatial unit. Assuming the target public facility is a shopping mall, then... Figure 3 As shown, the target area includes multiple target public facilities, which can be shopping mall A, shopping mall B, and shopping mall C. When obtaining the location information of the target public facilities, the coordinate strings of the outlines of shopping mall A, shopping mall B, and shopping mall C can be obtained separately.

[0077] It should be noted that, as Figure 3 As shown, the outline of the target public facility can be a regular rectangle obtained by preprocessing the outline of the target public facility. Optionally, the outline of the target public facility can also be displayed as an irregular shape according to the actual outline of the target public facility, and this application does not limit this.

[0078] See Figure 4 This is a schematic diagram illustrating another spatial unit division method provided in an embodiment of this application. For example... Figure 4 As shown, except Figure 3 In addition to the spatial unit division method shown, the target area can also be divided into multiple irregular spatial units based on the road distribution in the target area. Figure 3 The lines in the diagram can represent roads or bridges, and each blank area enclosed by lines is a spatial unit. Figure 3 Only one of multiple spatial units is shown. Under this division method, the outline of the target public facility can be determined by scaling the actual outline of the target public facility using a preset scale, for example... Figure 4 Shopping mall D is shown.

[0079] In one possible implementation, before obtaining the historical vehicle trajectory sets associated with each of the multiple target public facilities within a specified historical period, the location information of each spatial unit included in the target area can also be obtained. The location information of each spatial unit may include the outline information of the spatial unit, which, similar to the outline information of the target public facilities, can be represented by a tuple of (cell_id, cell_boundary), where cell_id is the unique identifier of the spatial unit, and cell_boundary is the coordinate string that makes up the outline of the spatial unit.

[0080] Optionally, in the spatial unit division method such as Figure 3 As shown, the location information of each spatial unit may also include the center coordinates of each spatial unit.

[0081] In one possible implementation, when obtaining the historical vehicle trajectory sets associated with multiple target public facilities within a specified historical period, multiple candidate vehicle trajectories contained in the target area within the specified historical period can be obtained. Then, for multiple target public facilities, the following operations are performed respectively: based on the location information of a target public facility, candidate vehicle trajectories with at least one endpoint associated with a target public facility are treated as a historical vehicle trajectory associated with a target public facility, and the obtained historical vehicle trajectories are combined into a set of historical vehicle trajectories associated with a target public facility.

[0082] Based on the above scheme, by combining historical vehicle trajectories associated with at least one endpoint and a target public facility into a historical vehicle trajectory set, the passenger flow of each target public facility can be more clearly determined, thereby providing a basis for subsequently determining the scale level of each target public facility.

[0083] In some embodiments, when obtaining candidate vehicle trajectories, multiple vehicle trajectories that pass through the target area within a specified historical period can be obtained first, and then vehicle trajectories whose two endpoints are both located within the target area can be used as candidate vehicle trajectories to obtain multiple candidate vehicle trajectories.

[0084] Specifically, the acquired vehicle trajectory can be represented by a tuple of (vehicle_id, vehicle_trace), where vehicle_id is the unique identifier of the vehicle, and vehicle_trace is the movement trajectory of the vehicle, which consists of one or more spatiotemporal points. Each spatiotemporal point can be represented by a triple of (x, y, time), where x can represent the longitude information of the spatial coordinates, y can represent the latitude information of the spatial coordinates, and time represents the timestamp information of the corresponding spatiotemporal point.

[0085] Optionally, when the specified historical period has a long time span, a vehicle trajectory can refer to the trajectory of a single vehicle's journey; that is, within the specified historical period, the same vehicle can correspond to multiple vehicle trajectories. When the specified historical period has a short time span, a vehicle trajectory can refer to all vehicle trajectories of a single vehicle within the specified historical period; that is, within the specified historical period, the same vehicle corresponds to only one vehicle trajectory.

[0086] In some embodiments, the two endpoints of a historical vehicle trajectory may include a start point and an end point. Based on the location information of a target public facility, when a candidate vehicle trajectory with at least one endpoint associated with a target public facility is considered as a historical vehicle trajectory of that target public facility, the associated range of that target public facility can be determined based on its location information. Then, for the multiple candidate vehicle trajectories, the following operations are performed respectively: when the start point of a candidate vehicle trajectory is within the associated range of a target public facility, or when the end point of a candidate vehicle trajectory is within the associated range of a target public facility, the candidate vehicle trajectory is considered as a historical vehicle trajectory associated with that target public facility.

[0087] It should be noted that the specified historical period can be set according to actual circumstances and experience, such as 3 months, 6 months, etc., and this application does not limit it in this regard.

[0088] Based on the above scheme, since the service recipients of public facilities that are far away usually choose to travel to the corresponding public facilities by means of vehicles, it is possible to determine whether the corresponding candidate vehicle trajectory is a historical vehicle trajectory associated with a target public facility by whether the origin or destination is within the associated range of a target public facility. The actual visitor flow of the corresponding target public facility can be calculated based on the number of vehicle trajectories.

[0089] In some embodiments, when determining the associated range of a target public facility based on its location information, different methods for determining the associated range can be selected depending on the spatial unit division method. For example, according to... Figure 3 When dividing spatial units as shown, the spatial unit containing a target public facility can be used as the corresponding associated scope. According to... Figure 4 When dividing spatial units as shown, a correlation distance threshold can be set, and areas less than the correlation distance threshold from a target public facility can be used as the corresponding correlation range. Alternatively, to improve correlation accuracy, the spatial unit containing the target public facility, as well as the roads adjacent to the target public facility, can also be used as the corresponding correlation range. It should be noted that the method for determining the correlation range is not limited to the above methods. Relevant personnel can also set the method for determining the correlation range based on experience or actual conditions, and this application does not limit this.

[0090] In one example, based on Figure 3 The target public facilities shown are listed below. Figure 5 This is a schematic diagram of candidate vehicle trajectories and historical vehicle trajectories provided for embodiments of this application. Firstly, the spatial units located in shopping malls A through C can be respectively considered as the respective associated ranges of shopping malls A through C. For example, Figure 5 As shown, shopping mall A covers four spatial units; therefore, the area comprised of these four units can be considered the associated scope of shopping mall A. Similarly, the associated scopes of shopping malls B and C can be represented by the dashed boxes surrounding each of them. Assuming the specified historical period is three months, then... Figure 5 As shown, within 3 months, there may be 4 trajectories passing through the target area: Trajectory 1 to Trajectory 5. Figure 3 The endpoint of a trajectory is indicated by an arrow, and the starting point is indicated by the tail of the arrow. Trajectory 1 has neither its starting nor ending point within the target area, and the starting point of trajectory 3 is also outside the target area; therefore, trajectories 1 and 3 are not candidate vehicle trajectories. Trajectories 2, 4, and 5, on the other hand, all have their starting and ending points within the target area; therefore, trajectories 2, 4, and 5 are all candidate vehicle trajectories.

[0091] Among the candidate vehicle trajectories, the starting point of trajectory 2 is located within the associated range of shopping mall B, so trajectory 2 can be considered as a historical vehicle trajectory associated with shopping mall B; the starting point and ending point of trajectory 4 are not within the associated range of any shopping mall, so it can be determined that trajectory 4 is not a historical vehicle trajectory associated with any shopping mall; the starting point of trajectory 5 is within the associated range of shopping mall A, and the ending point is within the associated range of shopping mall C. Since trajectory 5 does not meet the condition that an endpoint is associated with a target public facility, it can be determined that trajectory 5 is not a historical vehicle trajectory associated with any shopping mall.

[0092] In one possible implementation, when the server obtains the historical vehicle trajectory sets associated with multiple target public facilities within a specified historical period, it can construct spatial indexes for each spatial unit and target public facility within the target area after acquiring the outline information of each spatial unit and target public facility. Then, for each candidate vehicle trajectory, a spatial query is performed using the constructed spatial index, and the historical vehicle trajectory sets associated with each of the multiple target public facilities are determined based on the query results. For example, if the query result indicates that the starting point of the candidate vehicle trajectory is associated with target public facility A, and the ending point is associated with a spatial unit that is not a target public facility; or if the query result indicates that the starting point of the candidate vehicle trajectory is associated with a spatial unit that is not a target public facility, and the ending point is associated with target public facility A, then the candidate vehicle trajectory can be determined to be a historical vehicle trajectory associated with target public facility A.

[0093] It should be noted that methods for constructing spatial indexes can include, but are not limited to, quadtrees, R-trees, etc.

[0094] In one possible implementation, to avoid the influence of vehicle trajectories of staff at the target public facility on determining the service coverage area of ​​the target public facility, thereby improving the accuracy of service coverage determination, candidate vehicle trajectories can be filtered based on the staff's vehicle identifier. This ensures that the candidate vehicle trajectory corresponding to the staff's vehicle identifier is not a historical vehicle trajectory associated with the target public facility. For example, assuming a staff member of target public facility A has a vehicle identifier of 'aaa', when obtaining candidate vehicle trajectories, if there is a candidate vehicle trajectory with the vehicle identifier 'aaa' associated with target public facility A, it can be determined that this candidate vehicle trajectory is not a historical vehicle trajectory associated with target public facility A. However, if a candidate vehicle trajectory with the vehicle identifier 'aaa' is associated with target public facility B, it can still be considered a historical vehicle trajectory associated with target public facility B.

[0095] Step 202: Based on each historical vehicle trajectory set, and combined with the relative distance between each pair of target public facilities, divide the multiple target public facilities into multiple public facility sets.

[0096] Different sets of public facilities correspond to different scale levels, while the target public facilities in the same set of public facilities have the same scale level.

[0097] In one possible implementation, see [link to relevant documentation]. Figure 6 This is an exemplary flowchart of a method for partitioning a public facility set provided in an embodiment of this application. Step 202 can be performed according to... Figure 6 The process shown is executed as follows:

[0098] Step 2021: Based on the number of historical vehicle trajectories included in each historical vehicle trajectory set, determine the passenger flow assessment value for each of the multiple target public facilities.

[0099] In some embodiments, when the server determines the passenger flow assessment value of a target public facility, it may use the number of historical vehicle trajectories included in the historical vehicle trajectory set associated with the target public facility as the passenger flow assessment value of the target public facility.

[0100] For example, if the set of historical vehicle trajectories associated with target public facility A includes 50 historical vehicle trajectories, then the passenger flow assessment value of target public facility A can be determined to be 50.

[0101] In one possible implementation, when determining the passenger flow assessment value for multiple target public facilities, the number of historical vehicle trajectories included in each historical vehicle trajectory set can be used as the total passenger flow of the corresponding target public facility. Then, the total passenger flow of each target public facility can be standardized, and the standardized value can be used as the passenger flow assessment value.

[0102] Specifically, the server can use the Min-Max standardization method to first determine the maximum and minimum values ​​of the total passenger flow of each target public facility, and then determine the passenger flow assessment value corresponding to the total passenger flow of each target public facility through formula (1).

[0103] Formula (1) is x' = (x - min) / (max - min).

[0104] In the formula, x' represents the passenger flow assessment value corresponding to x, x represents the total passenger flow, max represents the maximum value in the total passenger flow, and min represents the minimum value in the total passenger flow.

[0105] It should be understood that the server can also use the Z-score standardization method to standardize the total passenger flow of each target public facility to obtain the corresponding passenger flow assessment value. For specific methods, please refer to the description in the relevant technology, which will not be repeated here.

[0106] Step 2022: For multiple target public facilities, perform the following operations respectively: determine the relative distance between each target public facility and all other target public facilities, and based on the passenger flow assessment values ​​of each of the multiple target public facilities, select the target relative distance that meets the preset passenger flow assessment conditions from the relative distances as a distance assessment value of a target public facility.

[0107] In some embodiments, when determining the relative distance between a target public facility and other target public facilities, the server may use the straight-line distance between the target public facility and other target public facilities as the relative distance. Alternatively, based on the navigation capabilities of an electronic map, the road navigation distance between the target public facility and other target public facilities may be used as the relative distance.

[0108] Specifically, a distance matrix W can be constructed based on the relative distance between each pair of target public facilities. When the number of target public facilities is M, the size of the distance matrix W is M×M, and the value of W[i][j] is the relative distance between the i-th public facility and the j-th public facility.

[0109] In one possible implementation, passenger flow assessment conditions may include a first assessment condition and a second assessment condition. Under the first assessment condition, the selected target relative distance is greater than the target relative distance selected under the second assessment condition. When the server selects a target relative distance that meets the preset passenger flow assessment conditions from among the relative distances based on the passenger flow assessment values ​​of multiple target public facilities, it can first compare the passenger flow assessment value of one target public facility with the passenger flow assessment values ​​of each of the other target public facilities, and determine whether the passenger flow assessment condition is the first assessment condition or the second assessment condition based on the comparison results.

[0110] When the passenger flow assessment value of a target public facility is greater than the passenger flow assessment values ​​of all other target public facilities, the target relative distance that meets the first assessment condition is selected from the relative distances.

[0111] When the passenger flow assessment value of a target public facility is not greater than the passenger flow assessment value of any other target public facility, select the target relative distance that meets the second assessment condition from the relative distances associated with the reference public facility of the target public facility, wherein the reference public facility is the target public facility whose passenger flow assessment value is greater than that of the target public facility.

[0112] In one example, the first evaluation criterion could be selecting the largest relative distance from all relative distances as the target relative distance. The second evaluation criterion could be selecting the smallest relative distance from all relative distances associated with the reference public facility as the target relative distance.

[0113] See Figure 7 This is a schematic diagram illustrating the selection process of the target relative distance provided in this application embodiment. Assume the target area includes shopping malls A through E, where the customer flow assessment value for shopping mall A is 0.2, for shopping mall B it is 0.8, for shopping mall C it is 0.6, for shopping mall D it is 0.3, and for shopping mall E it is 0.5. It is evident that shopping mall B is the target public facility with the highest customer flow assessment value. Therefore, the first assessment condition is used for shopping mall B, and the second assessment condition is used for shopping mall A and shopping malls C through E.

[0114] Based on this, such as Figure 7As shown, for shopping mall A, shopping malls B through E are all corresponding reference public facilities. Among them, shopping mall D is the closest to shopping mall A. Therefore, the relative distance 1 between shopping mall A and shopping mall D is the target relative distance for shopping mall A. For shopping mall B, the furthest from shopping mall B is shopping mall C. Therefore, the relative distance 2 between shopping mall B and shopping mall C is the target relative distance for shopping mall B. For shopping mall C, the corresponding reference public facilities only include shopping mall B. Therefore, the relative distance 2 between shopping mall C and shopping mall B is the target relative distance for shopping mall C. For shopping mall D, the corresponding reference public facilities include shopping malls B, C, and E. Among them, shopping mall B is the closest to shopping mall D. Therefore, the relative distance 3 between shopping mall D and shopping mall B is the target relative distance for shopping mall D. For shopping mall E, the corresponding reference public facilities include shopping malls B and C. Among them, shopping mall C is the closest to shopping mall E. Therefore, the relative distance 4 between shopping mall E and shopping mall C is the target relative distance for shopping mall E.

[0115] The relative distance between any two shopping malls can be obtained from the distance matrix W constructed for shopping malls A to E. Based on the obtained relative distance, the nearest reference public facility can be determined, or the farthest target public facility can be determined.

[0116] Optionally, when using the target relative distance as the distance assessment value, the standardized target relative distance can be used as the distance assessment value. For specific standardization methods, please refer to the description of the standardization method for total passenger flow above, which will not be repeated here.

[0117] In some embodiments, each element in the distance matrix W can also be a standardized relative distance. When each element in the distance matrix W is a standardized relative distance, the target relative distance obtained from the distance matrix W can be directly used as the distance evaluation value.

[0118] Based on the above scheme, for target public facilities with different passenger flows, distance assessment values ​​can be determined by different methods, so that the distance assessment value can characterize the range of advantages of the target public facility, and thus the distance assessment value can be used as a reference for judging the scale level of the target public facility.

[0119] Step 2023: Based on the passenger flow assessment value and distance assessment value of each of the multiple target public facilities, determine the scale level of each of the multiple target public facilities, and add the multiple target public facilities to the public facility group corresponding to the corresponding scale level.

[0120] Based on the above scheme, by classifying multiple target public facilities by scale level, public facilities that do not have a specific classification system or whose scale level is difficult to define in actual application can be classified by scale level through a data-driven approach. Furthermore, for public facilities for which it is difficult to obtain a specific classification system, the above method can also be used to classify scale level, thus achieving data accessibility.

[0121] In one possible implementation, step 2023 can be specifically executed as follows: Obtain the preset number of scale levels and the corresponding scale levels. Then, for multiple target public facilities, perform the following operations respectively: In the passenger flow assessment interval and distance assessment interval corresponding to each scale level, determine the target passenger flow assessment interval containing the passenger flow assessment value of one target public facility and the target distance assessment interval containing the distance assessment value of one target public facility, and then use the scale level corresponding to the target passenger flow assessment interval and the target distance assessment interval as a scale level of one target public facility.

[0122] For example, assuming there are 3 preset scale levels, scale level 1 corresponds to a passenger flow assessment range of [0-0.3] and a distance assessment range of [0-0.3], scale level 2 corresponds to a passenger flow assessment range of (0.3-0.6] and a distance assessment range of (0.3-0.6], and scale level 3 corresponds to a passenger flow assessment range of (0.6-1] and a distance assessment range of (0.6-1). If a target public facility has a passenger flow assessment value of 0.7 and a distance assessment value of 0.8, then the scale level corresponding to the target public facility can be determined to be scale level 3.

[0123] It should be noted that there can be multiple passenger flow assessment intervals and distance assessment intervals corresponding to the scale level, which can be set based on experience or actual conditions. This application does not limit this.

[0124] Based on the above scheme, by using passenger flow assessment intervals and distance assessment intervals corresponding to multiple scale levels, multiple target public facilities can be divided into public facility clusters of different scale levels. This allows the scale level of target public facilities to be classified based on their passenger flow and whether there are nearby target public facilities with even higher passenger flow. This method enables the classification of public facilities that lack a specific classification system or whose scale levels are difficult to define, through a data-driven approach.

[0125] Another possible implementation involves iteratively determining the scale level for each target public facility. First, select target public facilities whose passenger flow assessment value is not less than the passenger flow assessment threshold and whose distance assessment value is not less than the distance assessment threshold. Add these selected target public facilities to the public facility set as targets of the same scale level. Then, using the remaining target public facilities as a benchmark, determine their respective distance assessment values. Continue this process, selecting the next scale level's corresponding public facility set, and so on, until the iteration stops, completing the partitioning of the public facility set.

[0126] For details, see Figure 8 A schematic diagram illustrating the process of dividing a public facility set according to an embodiment of this application. The process includes:

[0127] Step 801: Obtain the preset number of scale levels H.

[0128] Where H can be a positive integer, and when H equals 1, multiple target public facilities can be directly treated as a set of public facilities to execute step 203.

[0129] For example, suppose we need to divide multiple target public facilities into 3 public facility sets, then H can be set to 3.

[0130] Step 802: Initialize the scale level k and the set of public facilities to be partitioned.

[0131] Upon initial execution, the scale level k is initialized to 1, and the set of public facilities to be divided is initialized to include all target public facilities included in the target area.

[0132] Step 803: Determine the distance assessment value of each target public facility included in the current public facility cluster to be divided.

[0133] If the previous step after step 803 is step 802, then the current set of public facilities to be divided includes all target public facilities within the target area. If the previous step after step 803 is step 806, then the current set of public facilities to be divided is the set of public facilities to be divided updated in step 805. Based on the target public facilities included in the current set of public facilities to be divided, the distance assessment value of each target public facility included in the set is determined.

[0134] For example, suppose the set of public facilities to be partitioned includes, for example, Figure 7 The distance assessment values ​​between shopping malls A and E shown can be determined based on... Figure 7 The relative distance to the target is used to determine this. See also Figure 9This is a schematic diagram illustrating the selection process of another target relative distance provided in an embodiment of this application. Assuming the updated set of public facilities to be partitioned includes shopping mall A, shopping mall D, and shopping mall E, then... Figure 9 As shown, the target relative distance for shopping mall A remains relative distance 1; however, since only shopping mall E has a higher customer flow assessment value than shopping mall D in the current cluster of public facilities to be divided, the target relative distance for shopping mall D becomes the relative distance 5 between shopping mall D and shopping mall E; and since shopping mall E is the target public facility with the highest customer flow assessment value in the current cluster of public facilities to be divided, and the distance between shopping mall E and shopping mall D is the farthest, the target relative distance for shopping mall E becomes the relative distance 5 between shopping mall E and shopping mall D. Then, the respective distance assessment values ​​can be determined based on the current target relative distances of shopping malls A, D, and E.

[0135] Step 804: Based on the passenger flow assessment value and distance assessment value, determine the target public facility with the current public facility concentration scale level k to be divided.

[0136] The target public facility to be classified into a centralized scale level k can be determined by comparing the passenger flow assessment value with a threshold value and the distance assessment value with a threshold value. For example, both the passenger flow assessment threshold and the distance assessment threshold can be 0.5.

[0137] To more clearly display the distribution of passenger flow assessment values ​​and distance assessment values ​​for each target public facility, a two-dimensional decision map can be created with passenger flow assessment values ​​on the horizontal axis and distance assessment values ​​on the vertical axis. The target public facilities in the current cluster to be divided can then be mapped onto this two-dimensional decision map. See also... Figure 10 A two-dimensional decision-making diagram provided for an embodiment of this application, such as Figure 10 As shown, the larger the x-coordinate and y-coordinate of the data point corresponding to the target public facility, the larger the scale of the target public facility and the farther away it is from the target public facility with a larger scale. It is a relatively advantageous target public facility in its neighboring area. Therefore, these target public facilities with large x-coordinate and y-coordinate (e.g., both greater than 0.5) can be divided into the public facility set corresponding to the current scale level k.

[0138] It should be noted that, in Figure 8 In the method embodiment shown, the value of k is negatively correlated with the size of the target public facility, that is, the size of the target public facility with a size level of 1 is greater than the size of the target public facility with a size level of 2.

[0139] In one possible implementation, for each target public facility, its standardized passenger flow assessment value and distance assessment value can be weighted and summed to determine the scale assessment value of the target public facility. Then, the scale assessment value is compared with the scale assessment threshold to determine the target public facility with the current scale level of public facility concentration k. The distance assessment value has a greater weight than the passenger flow assessment value. For example, the weight of the distance assessment value can be 0.6 and the weight of the passenger flow assessment value can be 0.4. The specific values ​​of the weight of the distance assessment value, the weight of the passenger flow assessment value, and the scale assessment threshold can be set according to the actual situation or experience. This application does not limit this.

[0140] Step 805: Update the scale level k and the set of public facilities to be partitioned.

[0141] Let k = k + 1, and delete the target public facility determined in step 804 from the current set of public facilities to be divided, thereby updating the set of public facilities to be divided.

[0142] For example, assuming the current set of public facilities to be divided includes shopping malls A to E, and the target public facilities determined in step 804 are shopping malls B and C, then the updated set of public facilities to be divided can include shopping malls A, D, and E.

[0143] Step 806: Is k equal to H?

[0144] If k is not equal to H, then return to step 803; if k is equal to H, then the iteration termination condition is determined, and at least one remaining target public facility in the current public facility set to be divided is added to the public facility set corresponding to the Hth scale level, so as to obtain the public facility sets corresponding to each of the H scale levels.

[0145] Step 203: Based on the historical vehicle trajectory set and public facility set associated with each of the multiple target public facilities, determine the service coverage area of ​​each of the multiple target public facilities.

[0146] Among them, the service coverage of target public facilities belonging to the same set of public facilities does not overlap.

[0147] In one possible implementation, step 203 can be specifically executed as follows: Based on the historical vehicle trajectory sets associated with each of the multiple target public facilities, determine the corresponding passenger flow sets for each of the multiple spatial units. Then, based on the passenger flow sets corresponding to each of the multiple spatial units and the public facility sets to which each of the multiple target public facilities belongs, determine the spatial units included in the service coverage area of ​​each of the multiple target public facilities.

[0148] Each passenger flow represents the number of historical vehicle trajectories traveling between a corresponding spatial unit and a target public facility, and each passenger flow cluster includes a one-to-one correspondence between the passenger flow and the target public facility.

[0149] Specifically, after obtaining the historical vehicle trajectory sets associated with each of the multiple target public facilities, as well as the location information of each spatial unit included in the target area, a passenger flow matrix V can be defined for the multiple target public facilities. The passenger flow matrix V can include M rows and N columns, where M represents the number of spatial units included in the target area, N represents the number of target public facilities included in the target area, and V[i][j] represents the number of historical vehicle trajectories between the i-th spatial unit and the j-th target public facility.

[0150] When determining the value of each element in the passenger flow matrix V, we can first initialize V[i][j] = 0, and then update the corresponding elements of the passenger flow matrix V based on the starting point and ending point of each historical vehicle trajectory, so as to obtain the complete passenger flow matrix V. Each row in the passenger flow matrix V is a passenger flow set corresponding to the corresponding spatial unit.

[0151] See Figure 11 This is a schematic diagram illustrating the process of determining the passenger flow matrix provided in this embodiment of the application. Assume the target area comprises 18 spatial units, with the upper left spatial unit designated as the first spatial unit and the lower right spatial unit as the 18th spatial unit. The target public facilities included in the target area are shopping mall A and shopping mall B. The historical vehicle trajectory set for shopping mall A includes 6 historical vehicle trajectories, and the historical vehicle trajectory set for shopping mall B includes 4 historical vehicle trajectories. By designating shopping mall A as the first target public facility and shopping mall B as the second public facility, the passenger flow matrix V on the right can be obtained based on each historical vehicle trajectory.

[0152] Specifically, for the first spatial unit, since there is one historical vehicle trajectory associated with shopping mall A, V[1][1] = 1; since there is no historical vehicle trajectory associated with shopping mall B, V[1][2] = 0. For example, for the third spatial unit, since there is neither a historical vehicle trajectory associated with shopping mall A nor a historical vehicle trajectory associated with shopping mall B, V[3][1] = V[3][2] = 0. By analogy, the passenger flow matrix for each target public facility in the target area can be obtained.

[0153] In addition, each row of the passenger flow matrix V is a passenger flow set corresponding to the corresponding spatial unit. For example, the first row of the passenger flow matrix V is the passenger flow set corresponding to the first spatial unit. The first passenger flow in the passenger flow set represents the number of historical vehicle trajectories from the first spatial unit to shopping mall A, or from shopping mall A to the first spatial unit. The second passenger flow represents the number of historical vehicle trajectories from the first spatial unit to shopping mall B, or from shopping mall B to the first spatial unit.

[0154] In one possible implementation, after obtaining the passenger flow set corresponding to each spatial unit, when determining the spatial units included in the service coverage of each of the multiple target public facilities based on the passenger flow set corresponding to each of the multiple spatial units and the public facility set to which each of the multiple target public facilities belongs, the following operations can be performed for each of the multiple spatial units: based on the passenger flow set corresponding to a spatial unit, select one target public facility in each public facility set, and assign a spatial unit to the service coverage of each of the selected multiple target public facilities.

[0155] For example, suppose there are three sets of public facilities: Public Facility Set 1 to Public Facility Set 3. Public Facility Set 1 includes Target Public Facility A to Target Public Facility D, Public Facility Set 2 includes Target Public Facility E to Target Public Facility G, and Public Facility Set 3 includes Target Public Facility H to Target Public Facility K. For spatial unit a, assuming that based on the passenger flow set corresponding to spatial unit a, Target Public F is selected in Public Facility Set 1, and Target Public F is selected in Public Facility Set 3, then spatial unit a can be assigned to the service coverage area of ​​Target Public Facility D, Target Public F, and Target Public F. That is, the service coverage area of ​​Target Public F includes spatial unit a, the service coverage area of ​​Target Public F includes spatial unit a, and the service coverage area of ​​Target Public F includes spatial unit a.

[0156] In some embodiments, when selecting a target public facility in each public facility set based on the passenger flow set corresponding to a spatial unit, the target public facility that satisfies formula (2) can be selected based on the above passenger flow matrix V.

[0157]

[0158] In the formula, f ik F represents the target public facility selected by the public facility set corresponding to the scale level k in the i-th spatial unit. k This represents the set of public facilities corresponding to scale level k.

[0159] For example, suppose Figure 11If shopping mall A and shopping mall B belong to the same set of public facilities, then for the first spatial unit, since shopping mall A has the largest customer flow, the first spatial unit can be assigned to the service coverage area of ​​shopping mall A.

[0160] Based on the above scheme, by identifying a target public facility in each public facility cluster, a spatial unit can be assigned to the service coverage of only one target public facility at each scale level, thus achieving mutual exclusivity of service coverage between target public facilities of the same scale level. It also allows a spatial unit to be assigned to different target public facilities at different scale levels, which better meets the needs of residents in real life and avoids the problem of ignoring residents' needs for other public facilities of the same type. This helps relevant staff to clarify the coverage status of public facilities in various regions.

[0161] In one possible implementation, there exists a scenario where, when the target area is small and the spatial units are densely divided, residents of units closer to the target public facility can walk there. Therefore, it's possible that some units, despite being very close to a target public facility, might have very low visitor volumes as determined by the aforementioned methods. For example... Figure 11 The 7th spatial unit (i.e., the 1st spatial unit in the 2nd row) is very close to shopping mall A, but V[7][1] = 0. To avoid the problem of inaccurate service coverage division caused by this scenario, spatial units within the associated range of target facility A can be directly assigned to the service coverage of target facility A. Alternatively, a range threshold can be set for each target public facility. After determining the range of each target public facility using the above method, spatial units within the range threshold of the target public facility that are not assigned to the service coverage can be assigned to the service coverage of the corresponding target public facility. For example, the range threshold can be set to 1km, 1.5km, etc., which is not limited in this application.

[0162] Based on the same inventive concept as the above-described method embodiments, this application also provides a service coverage area division device. For example... Figure 12 The service coverage area division device 1200 shown may include:

[0163] The communication unit 1201 is used to acquire the location information of multiple target public facilities contained in the target area, and to acquire the historical vehicle trajectory set associated with each of the multiple target public facilities within a specified historical period; wherein the multiple target public facilities have the same facility category; and at least one endpoint of each historical vehicle trajectory is associated with the corresponding target public facility.

[0164] The level division unit 1202 is used to divide the multiple target public facilities into multiple public facility sets based on each historical vehicle trajectory set and the relative distance between each pair of target public facilities; the public facilities in different public facility sets have different scale levels;

[0165] The service coverage division unit 1203 is used to determine the service coverage of each of the multiple target public facilities based on the historical vehicle trajectory set and public facility set associated with each of the multiple target public facilities; wherein the service coverage of target public facilities belonging to the same public facility set do not overlap.

[0166] In one possible implementation, the communication unit 1201 acquires a set of historical vehicle trajectories associated with each of the multiple target public facilities within a specified historical period, specifically for: acquiring multiple candidate vehicle trajectories contained in the target area within the specified historical period; wherein, the two endpoints of each candidate vehicle trajectory are located within the target area; the trajectory processing unit 1204 is configured to perform the following operations for each of the multiple target public facilities: based on the location information of a target public facility, taking at least one candidate vehicle trajectory whose endpoint is associated with the target public facility as a historical vehicle trajectory associated with the target public facility; and combining the obtained historical vehicle trajectories into a set of historical vehicle trajectories associated with the target public facility.

[0167] In one possible implementation, the two endpoints include a start point and an end point; the trajectory processing unit 1204, based on the location information of a target public facility, uses candidate vehicle trajectories whose endpoints are associated with the target public facility as historical vehicle trajectories of the target public facility, specifically for: determining the association range of the target public facility based on the location information of the target public facility; and performing the following operations on the multiple candidate vehicle trajectories respectively: when the start point or end point of a candidate vehicle trajectory is located within the association range of the target public facility, the candidate vehicle trajectory is used as a historical vehicle trajectory associated with the target public facility.

[0168] In one possible implementation, the level division unit 1202 divides the multiple target public facilities into multiple public facility sets based on each historical vehicle trajectory set and the relative distance between each pair of target public facilities. Specifically, it is used to: determine the passenger flow assessment value of each of the multiple target public facilities based on the number of historical vehicle trajectories included in each historical vehicle trajectory set; and for each of the multiple target public facilities, perform the following operations: determine the relative distance between each target public facility and each of the other target public facilities, and select a target relative distance that meets the preset passenger flow assessment conditions from each relative distance based on the passenger flow assessment value of each of the multiple target public facilities, as the distance assessment value of the target public facility; and determine the scale level of each of the multiple target public facilities based on the passenger flow assessment value and the distance assessment value of each of the multiple target public facilities, and add each of the multiple target public facilities to the public facility set corresponding to the corresponding scale level.

[0169] In one possible implementation, the passenger flow assessment conditions include a first assessment condition and a second assessment condition. Under the first assessment condition, the selected target relative distance is greater than the target relative distance selected under the second assessment condition. The level division unit 1202 selects target relative distances that meet the preset passenger flow assessment conditions from the relative distances based on the passenger flow assessment values ​​of the plurality of target public facilities. Specifically, it is used to: select target relative distances that meet the first assessment condition from the relative distances when the passenger flow assessment value of one target public facility is greater than that of any other target public facility; and select target relative distances that meet the second assessment condition from the relative distances associated with the reference public facility of the target public facility when the passenger flow assessment value of one target public facility is not greater than that of any other target public facility. The reference public facility is the target public facility whose passenger flow assessment value is greater than that of the target public facility.

[0170] In one possible implementation, the level classification unit 1202 determines the scale level of each of the multiple target public facilities based on their respective passenger flow assessment values ​​and distance assessment values. Specifically, it is used to: obtain a preset number of scale levels, and the passenger flow assessment interval and distance assessment interval corresponding to each scale level; and for each of the multiple target public facilities, perform the following operations respectively: in the passenger flow assessment interval and distance assessment interval corresponding to each scale level, determine a target passenger flow assessment interval that includes the passenger flow assessment value of one target public facility, and a target distance assessment interval that includes the distance assessment value of the one target public facility; and use the scale level corresponding to the target passenger flow assessment interval and the target distance assessment interval as the scale level of the one target public facility.

[0171] In one possible implementation, the service coverage segmentation unit 1203 determines the service coverage of each of the multiple target public facilities based on the historical vehicle trajectory sets and public facility sets associated with each of the multiple target public facilities. Specifically, it is used to: obtain the location information of multiple spatial units included in the target area; determine the passenger flow sets corresponding to each of the multiple spatial units based on the historical vehicle trajectory sets associated with each of the multiple target public facilities; wherein each passenger flow represents the number of historical vehicle trajectories traveling between the corresponding spatial unit and a target public facility; the passenger flow included in each passenger flow set corresponds one-to-one with the target public facility; and determine the spatial units included in the service coverage of each of the multiple target public facilities based on the passenger flow sets corresponding to each of the multiple spatial units and the public facility sets to which each of the multiple target public facilities belongs.

[0172] In one possible implementation, the service coverage division unit 1203 determines the spatial units included in the service coverage of each of the multiple target public facilities based on the respective passenger flow sets of the multiple spatial units and the public facility sets to which the multiple target public facilities belong. Specifically, it is used to perform the following operations for each of the multiple spatial units: based on the passenger flow set corresponding to a spatial unit, select a target public facility in each of the public facility sets, and assign the spatial unit to the service coverage of the selected multiple target public facilities.

[0173] For ease of description, the above sections are divided into modules (or units) according to their functions and described separately. In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program with a predetermined function, which works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functions of that module or unit.

[0174] After introducing the service coverage division method and apparatus of the exemplary embodiments of this application, the computer device according to another exemplary embodiment of this application will be introduced next.

[0175] Those skilled in the art will understand that various aspects of this application can be implemented as a system, method, or program product. Therefore, various aspects of this application can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, collectively referred to herein as a "circuit," "module," or "system."

[0176] Based on the same inventive concept as the above-described method embodiments, this application also provides a computer device. In one embodiment, the computer device may be a server, such as... Figure 1 The server 120 is shown. In this embodiment, the computer device is structured as follows: Figure 13 As shown, it may include at least a memory 1301, a communication module 1303, and at least one processor 1302.

[0177] The memory 1301 is used to store computer programs executed by the processor 1302. The memory 1301 may mainly include a program storage area and a data storage area. The program storage area may store the operating system and programs required to run instant messaging functions, etc.; the data storage area may store various instant messaging information and operation instruction sets, etc.

[0178] Memory 1301 may be volatile memory, such as random-access memory (RAM); memory 1301 may also be non-volatile memory, such as read-only memory, flash memory, hard disk drive (HDD), or solid-state drive (SSD); or memory 1301 may be any other medium capable of carrying or storing a desired computer program having the form of instructions or data structures and accessible by a computer, but is not limited thereto. Memory 1301 may be a combination of the above-described memories.

[0179] Processor 1302 may include one or more central processing units (CPUs) or digital processing units, etc. Processor 1302 is used to implement the above-mentioned service coverage division method when calling computer programs stored in memory 1301.

[0180] The communication module 1303 is used to communicate with terminal devices and other servers.

[0181] This application embodiment does not limit the specific connection medium between the memory 1301, communication module 1303, and processor 1302. This application embodiment... Figure 13 The memory 1301 and the processor 1302 are connected via a bus 1304, and the bus 1304 is in Figure 13 The diagram uses thick lines to describe the connections between other components; these are for illustrative purposes only and should not be considered limiting. The 1304 bus can be divided into address bus, data bus, control bus, etc. For ease of description, Figure 13 It is described using only a thick line, but does not indicate that there is only one bus or one type of bus.

[0182] The memory 1301 stores a computer storage medium, which stores computer-executable instructions for implementing the service coverage division method of this application embodiment. The processor 1302 is used to execute the above-described service coverage division method, such as... Figure 2 As shown.

[0183] In another embodiment, the computer device can also be other computer devices, such as... Figure 1 The terminal device 110 is shown. In this embodiment, the structure of the computer device can be as follows: Figure 14 As shown, it includes components such as: communication component 1410, memory 1420, display unit 1430, camera 1440, sensor 1450, audio circuit 1460, Bluetooth module 1470, processor 1480, etc.

[0184] The communication component 1410 is used to communicate with a server. In some embodiments, it may include a Wireless Fidelity (WiFi) module, which is a short-range wireless transmission technology, and the electronic device can send and receive information through the WiFi module.

[0185] The memory 1420 can be used to store software programs and data. The processor 1480 executes various functions of the terminal device 110 and performs data processing by running the software programs or data stored in the memory 1420. The memory 1420 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. The memory 1420 stores an operating system that enables the terminal device 110 to run. In this application, the memory 1420 may store the operating system and various applications, and may also store computer programs that execute the service coverage division method of the embodiments of this application.

[0186] The display unit 1430 can also be used to display information input by an object or information provided to an object, as well as a graphical user interface (GUI) for various menus of the terminal device 110. Specifically, the display unit 1430 may include a display screen 1432 disposed on the front of the terminal device 110. The display screen 1432 may be configured as a liquid crystal display, a light-emitting diode, or the like.

[0187] The display unit 1430 can also be used to receive input digital or character information and generate signal inputs related to object settings and function control of the terminal device 110. Specifically, the display unit 1430 may include a touch screen 1431 disposed on the front of the terminal device 110, which can collect touch operations on or near the object, such as clicking a button, dragging a scroll box, etc.

[0188] The touchscreen 1431 can be placed on top of the display screen 1432, or the touchscreen 1431 and the display screen 1432 can be integrated to realize the input and output functions of the terminal device 110. After integration, it can be referred to as a touch display screen. In this application, the display unit 1430 can display the application and the corresponding operation steps.

[0189] Camera 1440 can be used to capture still images, and objects can publish images captured by camera 1440 through an application. There can be one or multiple cameras 1440. An optical image of an object is generated through a lens and projected onto a photosensitive element. The photosensitive element can be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, which is then transmitted to processor 1480 to be converted into a digital image signal.

[0190] The terminal device may also include at least one sensor 1450, such as an accelerometer 1451, a proximity sensor 1452, a fingerprint sensor 1453, and a temperature sensor 1454. The terminal device may also be equipped with other sensors such as a gyroscope, barometer, hygrometer, thermometer, infrared sensor, light sensor, and motion sensor.

[0191] Audio circuitry 1460, speaker 1461, and microphone 1462 provide an audio interface between the device and terminal device 110. Audio circuitry 1460 converts received audio data into electrical signals, transmits them to speaker 1461, and speaker 1461 converts them into sound signals for output. Terminal device 110 may also be equipped with volume buttons for adjusting the volume of the sound signal. On the other hand, microphone 1462 converts collected sound signals into electrical signals, which are then received by audio circuitry 1460, converted into audio data, and output to communication component 1410 for transmission to, for example, another terminal device 110, or to memory 1420 for further processing.

[0192] The Bluetooth module 1470 is used to interact with other Bluetooth devices that also have a Bluetooth module via the Bluetooth protocol. For example, a terminal device can establish a Bluetooth connection with a wearable electronic device (such as a smartwatch) that also has a Bluetooth module through the Bluetooth module 1470, thereby exchanging data.

[0193] The processor 1480 is the control center of the terminal device, connecting various parts of the terminal through various interfaces and lines. It executes various functions and processes data by running or executing software programs stored in the memory 1420 and calling data stored in the memory 1420. In some embodiments, the processor 1480 may include one or more processing units; the processor 1480 may also integrate an application processor and a baseband processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the baseband processor mainly handles wireless communication. It is understood that the baseband processor may not be integrated into the processor 1480. In this application, the processor 1480 can run the operating system, applications, user interface display and touch response, as well as the service coverage division method of the embodiments of this application. Furthermore, the processor 1480 is coupled to the display unit 1430.

[0194] Furthermore, it should be noted that in the specific implementation of this application, object data related to the division of service coverage is involved. When the above embodiments of this application are applied to specific products or technologies, permission or consent from the object is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0195] In some possible implementations, various aspects of the service coverage division method provided in this application can also be implemented in the form of a program product, which includes a computer program. When the program product is run on a computer device, the computer program causes the computer device to perform the steps in the service coverage division method according to the various exemplary embodiments of this application described above. For example, the computer device can perform actions such as... Figure 2 The steps are shown in the figure.

[0196] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0197] The program product of the embodiments of this application may employ a portable compact disc read-only memory (CD-ROM) and include a computer program, and may run on an electronic device. However, the program product of this application is not limited thereto. In this document, the readable storage medium may be any tangible medium that contains or stores a program that may be used by or in conjunction with a command execution system, apparatus, or device.

[0198] A readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a readable computer program. This propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting a program for use by or in conjunction with a command execution system, apparatus, or device.

[0199] Computer programs contained on readable media may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0200] Computer programs for performing the operations of this application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The computer program can execute entirely on the user's computer device, partially on the user's computer device, as a standalone software package, partially on the user's computer device and partially on a remote computer device, or entirely on a remote computer device. In cases involving remote computer devices, the remote computer device can be connected to the user's computer device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer device (e.g., via the Internet using an Internet service provider).

[0201] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0202] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0203] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can 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, etc.) containing a computer-usable computer program.

[0204] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can 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, produce a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0205] These computer program commands may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the commands stored in the computer-readable storage medium produce an article of manufacture including command means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0206] These computer program commands can also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing the commands executed on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0207] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0208] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method of service coverage partitioning, characterized by, The method comprises: obtaining position information of each of a plurality of target public facilities included in a target area, and obtaining a set of historical vehicle trajectories associated with each of the plurality of target public facilities in a specified historical period; wherein the plurality of target public facilities have the same facility category; and at least one endpoint of each historical vehicle trajectory is associated with a corresponding target public facility; based on each set of historical vehicle trajectories, and in combination with the relative distance between each two of the target public facilities, the plurality of target public facilities are divided into a plurality of public facility sets; the public facilities in different public facility sets have different scale levels; based on the set of historical vehicle trajectories associated with each of the plurality of target public facilities and the public facility sets, the service coverage of each of the plurality of target public facilities is determined respectively; wherein the service coverage of the target public facilities belonging to the same public facility set does not overlap.

2. The method of claim 1, wherein, The method comprises: obtaining a plurality of candidate vehicle trajectories included in the target area in the specified historical period; wherein the two endpoints of each candidate vehicle trajectory are located within the target area; for each of the plurality of target public facilities, the following operations are performed respectively: based on the position information of a target public facility, the candidate vehicle trajectories having at least one endpoint associated with the target public facility are selected as the historical vehicle trajectories associated with the target public facility; the obtained historical vehicle trajectories are combined into a set of historical vehicle trajectories associated with the target public facility.

3. The method of claim 2, wherein, The two endpoints include a starting point and an ending point; and the operation of selecting, based on the position information of a target public facility, the candidate vehicle trajectories having at least one endpoint associated with the target public facility as the historical vehicle trajectories associated with the target public facility, comprises: determining the association range of the target public facility based on the position information of the target public facility; for each of the plurality of candidate vehicle trajectories, the following operations are performed respectively: when the starting point or the ending point of a candidate vehicle trajectory is located within the association range of the target public facility, the candidate vehicle trajectory is selected as the historical vehicle trajectory associated with the target public facility.

4. The method according to any one of claims 1 to 3, characterized in that, The operation of dividing, based on each set of historical vehicle trajectories, and in combination with the relative distance between each two of the target public facilities, the plurality of target public facilities into a plurality of public facility sets, comprises: determining a passenger flow evaluation value of each of the plurality of target public facilities based on the number of historical vehicle trajectories included in each set of historical vehicle trajectories; for each of the plurality of target public facilities, the following operations are performed respectively: the relative distance between the target public facility and each of the other target public facilities is determined respectively, and based on the passenger flow evaluation value of each of the plurality of target public facilities, a target relative distance meeting a preset passenger flow evaluation condition is selected from each relative distance as a distance evaluation value of the target public facility. Determine a scale level of each of the target public facilities based on the passenger flow evaluation value and the distance evaluation value of each of the target public facilities, and add the target public facilities to a corresponding public facility set according to the scale level.

5. The method of claim 4, wherein, The passenger flow evaluation condition includes a first evaluation condition and a second evaluation condition, and a target relative distance selected under the first evaluation condition is greater than a target relative distance selected under the second evaluation condition. The target relative distance is selected from the relative distances based on the passenger flow evaluation value of each of the target public facilities, and includes: When the passenger flow evaluation value of the target public facility is greater than that of any other target public facility, the target relative distance meeting the first evaluation condition is selected from the relative distances. When the passenger flow evaluation value of the target public facility is not greater than that of any other target public facility, the target relative distance meeting the second evaluation condition is selected from the relative distances associated with the reference public facility of the target public facility, and the reference public facility is a target public facility whose passenger flow evaluation value is greater than that of the target public facility.

6. The method of claim 4, wherein, The scale level of each of the target public facilities is determined based on the passenger flow evaluation value and the distance evaluation value of each of the target public facilities, and includes: A preset number of scale levels, and a passenger flow evaluation interval and a distance evaluation interval corresponding to each scale level are obtained. For the target public facilities, the following operations are performed respectively: In the passenger flow evaluation interval and the distance evaluation interval corresponding to each scale level, a target passenger flow evaluation interval containing the passenger flow evaluation value of a target public facility and a target distance evaluation interval containing the distance evaluation value of the target public facility are determined. The scale level corresponding to the target passenger flow evaluation interval and the target distance evaluation interval is taken as the scale level of the target public facility.

7. The method according to any one of claims 1 to 3, characterized in that, The service coverage range of each of the target public facilities is determined based on the historical vehicle trajectory set and the public facility set associated with each of the target public facilities, and includes: The position information of a plurality of spatial units included in the target region is obtained. Based on the historical vehicle trajectory set associated with each of the target public facilities, a corresponding passenger flow set of each of the spatial units is determined, wherein each passenger flow represents the number of historical vehicle trajectories traveling between the corresponding spatial unit and a target public facility; and each passenger flow in the passenger flow set corresponds one-to-one to the target public facility. Based on the corresponding passenger flow set of each of the spatial units and the public facility set to which each of the target public facilities belongs, the spatial units included in the service coverage range of each of the target public facilities are determined.

8. The method of claim 7, wherein, The spatial units included in the service coverage range of each of the target public facilities are determined based on the corresponding passenger flow set of each of the spatial units and the public facility set to which each of the target public facilities belongs, and includes: For the plurality of spatial units, the following operations are performed respectively: Based on a passenger flow set corresponding to a spatial unit, a target public facility is selected from each of the public facility sets, and the spatial unit is attributed to the service coverage range of each of the selected target public facilities.

9. A service coverage partitioning apparatus, characterized by comprising: The method comprises the steps of: The communication unit is configured to acquire position information of each of a plurality of target public facilities included in a target area, and acquire a historical vehicle trajectory set associated with each of the plurality of target public facilities in a specified historical period; wherein the plurality of target public facilities have the same facility category; and at least one endpoint of each historical vehicle trajectory is associated with a corresponding target public facility; The level division unit is configured to divide the plurality of target public facilities into a plurality of public facility sets based on each historical vehicle trajectory set and the relative distance between each two target public facilities; and public facilities in different public facility sets have different size levels; The service coverage range division unit is configured to determine the service coverage range of each of the plurality of target public facilities based on the historical vehicle trajectory set associated with each of the plurality of target public facilities and the public facility set; and the service coverage ranges of target public facilities belonging to the same public facility set do not overlap.

10. A computer device, comprising: The device comprises a processor and a memory, wherein the memory stores program code, and when the program code is executed by the processor, the processor executes the steps of the method in any one of claims 1-8.

11. A computer readable storage medium characterized by, The device comprises program code, and when the program code is executed on a computer device, the program code is used to make the computer device execute the steps of the method in any one of claims 1-8.

12. A computer program product, characterised in that, The device comprises computer instructions, and when the computer instructions are executed by a processor, the steps of the method in any one of claims 1-8 are implemented.

Images