Site adjustment method, device, computer equipment and storage medium

Abstract

The present application relates to a site adjustment method, device, computer equipment, storage medium and computer program product. The method comprises: determining multiple sites within a target range; determining the status score of each site within the target range according to the site indicator data and riding data of each site within the target range; determining efficient sites and inefficient sites from each site according to the status score of each site, adjusting the site area of ​​the efficient site upward, and deleting the inefficient site. The adoption of this method can enable more shared vehicles to be parked in hot spots, avoiding the problem that some shared vehicles cannot be returned because the parking range of the site is full of cars. By deleting sites with low status scores, scheduling resources can be saved, the scheduling and maintenance efficiency of shared vehicles can be improved, and the rationality of site planning can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of resource management, and in particular to a site adjustment method, apparatus, computer equipment, storage medium and computer program product. Background Art

[0002] With the development of resource management technology, most cities have introduced shared vehicles, such as shared bicycles and shared electric motorcycles. Shared vehicle managers can create shared vehicle stations based on the actual usage of shared vehicles. Users can use and return shared vehicles at shared vehicle stations.

[0003] With the use of shared vehicles, users may use and return vehicles at various locations, and as the number of shared vehicles used at various locations increases, the number of shared vehicle stations increases, and users may choose any station to park their vehicles.

[0004] However, due to changes in the surrounding environment, some shared vehicle stations may only have a small number of shared vehicles parked. As a result, when the management party dispatches and maintains shared vehicles, dispatchers need to track down stations with only a small number of shared vehicles to dispatch and maintain vehicles, resulting in low efficiency in the management of shared vehicles. There may also be a large number of shared vehicles that need to be parked in hot spots, but some shared vehicles cannot be returned because the parking range of the station is full of cars, resulting in problems such as mismatch between the parking range of the station and the use of shared vehicles and unreasonable station planning, which affects the user experience of using shared vehicles. Summary of the invention

[0005] Based on this, it is necessary to provide a site adjustment method, apparatus, computer equipment, computer-readable storage medium and computer program product that can improve the rationality of site planning in response to the above technical problems.

[0006] In a first aspect, the present application provides a site adjustment method, comprising:

[0007] Identify multiple sites within the target area;

[0008] Determine the status score of each station within the target range according to the station indicator data and riding data of each station within the target range, wherein the station indicator data includes the central location and area of ​​the station, and the riding data includes the outgoing order data generated by the station, the incoming order data parked at the station, the illegal parking pop-up window data within a preset range around the station, and the return vehicle click data of each order within the preset range around the station, and the status score is used to represent the activity level of the station, and the higher the activity level of the station, the more times the vehicle is parked at the station;

[0009] According to the status score of each of the sites, efficient sites and inefficient sites are determined from the sites, the site areas of the efficient sites are adjusted upward, and the inefficient sites are deleted.

[0010] In one embodiment, determining the status score of each of the stations within the target range according to the station indicator data and the riding data of each of the stations within the target range includes:

[0011] For each of the sites within the target range, determining a secondary score of the site for each secondary indicator according to the site indicator data and riding data of each of the sites within the target range;

[0012] Determine the first-level score of the site for each first-level indicator according to the second-level score of the site for each second-level indicator;

[0013] The status score of the site is determined according to the first-level score of each first-level indicator of the site.

[0014] In one of the embodiments, the primary indicators include site location, site riding out demand, site riding in demand, user experience and vehicle consumption; the secondary indicators include site effective area ratio, number of site information points, number of riding out orders covered, riding out order resource data, number of riding in orders covered, riding in order resource data, average number of vehicle returns per order, average number of illegal parking pop-up windows per order, consumption speed and parking time.

[0015] In one embodiment, when the primary indicator is the site location, the secondary indicator includes the effective area ratio of the site and the number of site information points.

[0016] Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes:

[0017] Determine, according to the site area of ​​the site and the overlapping area between the site and other sites within the target range, a secondary score of the site for the proportion of the effective area of ​​the site;

[0018] A secondary score of the site for the number of information points at the site is determined according to the number of information points at the site and the number of information points at other sites within the target range.

[0019] In one embodiment, when the primary indicator is the site outbound demand, the secondary indicator includes the outbound order coverage quantity and the outbound order resource data.

[0020] Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes:

[0021] Determine a secondary score of the site for the number of ride-out orders covered by the site according to the average daily number of ride-out orders of the site in the current time period and the average daily number of ride-out orders of other sites within the target range in the current time period;

[0022] Based on the average riding order resource data of multiple riding orders of the site in the current time period and the average riding order resource data of multiple riding orders of other sites within the target range in the current time period, the secondary score of the site for the riding order resource data is determined.

[0023] In one embodiment, when the primary indicator is the site entry demand, the secondary indicator includes the entry order coverage quantity and the entry order resource data.

[0024] Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes:

[0025] Determine the secondary score of the site for the number of ride-in orders covered by the site according to the average daily number of ride-in orders of the site in the current time period and the average daily number of ride-in orders of other sites within the target range in the current time period;

[0026] Based on the average incoming order resource data of multiple incoming orders of the site in the current time period and the average incoming order resource data of multiple incoming orders of other sites within the target range in the current time period, the secondary score of the site for the incoming order resource data is determined.

[0027] In one embodiment, when the primary indicator is user experience, the secondary indicator includes the average number of vehicle returns per order and the average number of illegal parking pop-up windows per order.

[0028] Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes:

[0029] Determine a secondary score of the site for the average number of vehicle returns per order based on the average number of vehicle returns per order at the site in a historical time period and the average number of vehicle returns per order at the site in a current time period;

[0030] According to the average number of illegal parking pop-up windows for each order of the site in the historical time period and the average number of illegal parking pop-up windows for each order of the site in the current time period, a secondary score for the average number of illegal parking pop-up windows for each order of the site is determined.

[0031] In one embodiment, when the primary indicator is vehicle consumption, the secondary indicator includes the consumption speed and the parking time.

[0032] Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes:

[0033] Determine a secondary score of the site for the consumption speed according to the average daily vehicle consumption speed of the site in a historical time period and the average daily vehicle consumption speed of the site in a current time period;

[0034] According to the average parking time of vehicles at the site in the historical time period and the average parking time of vehicles at the site in the current time period, a secondary score of the site for the parking time is determined.

[0035] In one embodiment, determining the first-level score of the site for each first-level indicator according to the second-level score of the site for each second-level indicator includes:

[0036] For each primary indicator of the site, determining a secondary indicator corresponding to the primary indicator;

[0037] The first-level score of the first-level indicator is determined based on the second-level weight of the second-level indicator corresponding to the first-level indicator and the second-level score of the second-level indicator corresponding to the first-level indicator.

[0038] In one embodiment, determining the status score of the site according to the first-level score of the site for each of the first-level indicators includes:

[0039] The status score of the site is determined according to the first-level score of each first-level indicator of the site and the first-level weight of each first-level indicator.

[0040] In one embodiment, determining the efficient site and the inefficient site from each of the sites according to the status score of each of the sites includes:

[0041] According to the status scores of the sites, the sites are sorted in descending order to obtain a sorting result;

[0042] Based on the ranking result, efficient sites and inefficient sites are determined from the sites.

[0043] In a second aspect, the present application further provides a site adjustment device, including:

[0044] A first determination module is used to determine multiple sites within a target range;

[0045] A second determination module is used to determine the status score of each of the stations within the target range according to the station indicator data and riding data of each of the stations within the target range, wherein the station indicator data includes the central location and the area of ​​the station, and the riding data includes the outgoing order data generated by the station, the incoming order data parked at the station, the illegal parking pop-up window data within a preset range around the station, and the return vehicle click data of each order within the preset range around the station, and the status score is used to represent the activity level of the station, and the higher the activity level of the station, the more times the vehicle is parked at the station;

[0046] The third determination module is used to determine efficient sites and inefficient sites from the sites according to the status scores of the sites, to increase the site areas of the efficient sites, and to delete the inefficient sites.

[0047] In one embodiment, the second determining module is specifically configured to:

[0048] For each of the sites within the target range, determining a secondary score of the site for each secondary indicator according to the site indicator data and riding data of each of the sites within the target range;

[0049] Determine the first-level score of the site for each first-level indicator according to the second-level score of the site for each second-level indicator;

[0050] The status score of the site is determined according to the first-level score of each first-level indicator of the site.

[0051] In one of the embodiments, the primary indicators include site location, site riding out demand, site riding in demand, user experience and vehicle consumption; the secondary indicators include site effective area ratio, number of site information points, number of riding out orders covered, riding out order resource data, number of riding in orders covered, riding in order resource data, average number of vehicle returns per order, average number of illegal parking pop-up windows per order, consumption speed and parking time.

[0052] In one embodiment, when the primary indicator is the site location, the secondary indicator includes the site effective area ratio and the number of site information points, and the second determination module is specifically configured to:

[0053] Determine, according to the site area of ​​the site and the overlapping area between the site and other sites within the target range, a secondary score of the site for the proportion of the effective area of ​​the site;

[0054] A secondary score of the site for the number of information points at the site is determined according to the number of information points at the site and the number of information points at other sites within the target range.

[0055] In one embodiment, when the primary indicator is the site outbound demand, the secondary indicator includes the outbound order coverage quantity and the outbound order resource data, and the second determination module is specifically configured to:

[0056] Determine a secondary score of the site for the number of ride-out orders covered by the site according to the average daily number of ride-out orders of the site in the current time period and the average daily number of ride-out orders of other sites within the target range in the current time period;

[0057] Based on the average riding order resource data of multiple riding orders of the site in the current time period and the average riding order resource data of multiple riding orders of other sites within the target range in the current time period, the secondary score of the site for the riding order resource data is determined.

[0058] In one embodiment, when the primary indicator is the site entry demand, the secondary indicator includes the entry order coverage quantity and the entry order resource data, and the second determination module is specifically configured to:

[0059] Determine the secondary score of the site for the number of ride-in orders covered by the site according to the average daily number of ride-in orders of the site in the current time period and the average daily number of ride-in orders of other sites within the target range in the current time period;

[0060] Based on the average incoming order resource data of multiple incoming orders of the site in the current time period and the average incoming order resource data of multiple incoming orders of other sites within the target range in the current time period, the secondary score of the site for the incoming order resource data is determined.

[0061] In one embodiment, when the primary indicator is the user experience, the secondary indicator includes the average number of vehicle returns per order and the average number of pop-up windows for illegal parking per order, and the second determination module is specifically configured to:

[0062] Determine a secondary score of the site for the average number of vehicle returns per order based on the average number of vehicle returns per order at the site in a historical time period and the average number of vehicle returns per order at the site in a current time period;

[0063] According to the average number of illegal parking pop-up windows for each order of the site in the historical time period and the average number of illegal parking pop-up windows for each order of the site in the current time period, a secondary score for the average number of illegal parking pop-up windows for each order of the site is determined.

[0064] In one embodiment, when the primary indicator is the vehicle consumption, the secondary indicator includes the consumption speed and the parking time, and the second determination module is specifically configured to:

[0065] Determine a secondary score of the site for the consumption speed according to the average daily vehicle consumption speed of the site in a historical time period and the average daily vehicle consumption speed of the site in a current time period;

[0066] A secondary score for parking time at the site is determined based on the average parking time of vehicles at the site in the historical time period and the average parking time of vehicles at the site in the current time period.

[0067] In one embodiment, the second determining module is specifically configured to:

[0068] For each primary indicator of the site, determining a secondary indicator corresponding to the primary indicator;

[0069] The first-level score of the first-level indicator is determined based on the second-level weight of the second-level indicator corresponding to the first-level indicator and the second-level score of the second-level indicator corresponding to the first-level indicator.

[0070] In one embodiment, the second determining module is specifically configured to:

[0071] The status score of the site is determined according to the first-level score of each first-level indicator of the site and the first-level weight of each first-level indicator.

[0072] In one embodiment, the third determination module is specifically used to:

[0073] According to the status scores of the sites, the sites are sorted in descending order to obtain a sorting result;

[0074] Based on the ranking result, efficient sites and inefficient sites are determined from the sites.

[0075] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned site adjustment method when executing the computer program.

[0076] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above-mentioned site adjustment methods when executed by a processor.

[0077] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned site adjustment method when executed by a processor.

[0078] The site adjustment method, device, computer equipment, storage medium and computer program product determine multiple sites within the target range; determine the status score of each site within the target range according to the site indicator data and riding data of each site within the target range, and the status score is used to characterize the activity of the site; determine the site to be adjusted according to the status score of each site, and adjust the site to be adjusted. By adopting this method, the status scores of multiple sites within the target range can be determined, so as to determine the site to be adjusted according to the status scores of multiple sites. Since a high status score of a site can represent a high activity of the site, by increasing the area of ​​the site with a high status score among the sites to be adjusted, more shared vehicles can be parked in hot spots, avoiding the problem of unreasonable site planning caused by the fact that the parking range of the site is full of cars and some shared vehicles cannot be returned. In addition, since a low status score of a site can represent a low activity of the site and there is no large demand for vehicles, by deleting sites with low status scores, scheduling resources can be saved, the scheduling and maintenance efficiency of shared vehicles can be improved, and the rationality of site planning can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0080] Figure 1 A schematic diagram of a flow chart of a site adjustment method in an embodiment;

[0081] Figure 2 A schematic diagram of a process for determining a status score of a site in one embodiment;

[0082] Figure 3 A schematic diagram of a process for determining a secondary score of a secondary indicator of a site in one embodiment;

[0083] Figure 4 A schematic diagram of a process for determining a secondary score of a secondary indicator of a site in another embodiment;

[0084] Figure 5 A schematic diagram of a process for determining a secondary score of a secondary indicator of a site in another embodiment;

[0085] Figure 6 A schematic diagram of a process for determining a secondary score of a secondary indicator of a site in another embodiment;

[0086] Figure 7 A schematic diagram of a process for determining a secondary score of a secondary indicator of a site in another embodiment;

[0087] Figure 8 A schematic diagram of a process for determining a primary score of a primary indicator in an embodiment;

[0088] Fig. 9 A schematic diagram of a process for determining efficient sites and inefficient sites in one embodiment;

[0089] Fig.10 is a structural block diagram of a site adjustment device in an embodiment;

[0090] Fig.11 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0091] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0092] In an exemplary embodiment, Figure 1 As shown, a site adjustment method is provided. This embodiment uses the method applied to a server as an example for illustration. It can be understood that the method can also be applied to a terminal, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0093] Step 102, determining multiple sites within the target range.

[0094] The site is a parking location for shared vehicles (i.e., shared bicycles and shared electric motorcycles). Each site has a site center point and a site area. Each site can have a unique number to facilitate the server to distinguish each site. The shape of the site is generally circular. The shape of the site can be set by the technician according to the needs. The embodiment of the present application does not limit the shape of the site.

[0095] In the embodiment of the present application, the server can periodically count the parking locations of shared vehicles and establish a site for shared vehicles based on the activity level of each parking location. The more times a shared vehicle is parked around a certain location, the higher the activity level of the location. When the activity level of the location is higher than a certain activity level threshold, the server can establish a site with the location as the center based on a preset site area.

[0096] The server determines a target range within the current time period, and the target range may be a city or a large geographical area including multiple sites.

[0097] Then, the server determines a plurality of sites included in the target range within the current time period.

[0098] Exemplarily, when the time period is seven natural days and the target range is City A, the server determines the seven days before the current natural day as the current time period, and within the scope of City A, determines all sites within the scope of City A based on the location data of each site stored in the server.

[0099] Step 104, determining the status score of each station within the target range according to the station indicator data and riding data of each station within the target range.

[0100] Among them, the status score is used to characterize the activity level of the site. The higher the activity level of the site, the more times the vehicle is parked at the site. Site indicator data may include but are not limited to the central location of the site, the area of ​​the site, etc.; riding data may include but are not limited to the outbound order data generated by the site, the inbound order data parked at the site, the illegal parking pop-up window data within a preset range around the site (for example, a five-meter range outside the site), and the return click data of each order within a preset range around the site. The specific content of the site indicator data and riding data can also be adaptively added or deleted by technical personnel. The embodiments of this application do not limit the specific content of the site indicator data and riding data.

[0101] In the embodiment of the present application, the server may store the site indicator data and riding data of each site. The server determines the status score of each site in the target range within the current time period based on the site indicator data and riding data of each site in the target range. The status score of the site is positively correlated with the activity level of the site. The higher the status score of the site, the higher the activity level of the site.

[0102] Step 106, according to the status score of each site, determine the efficient sites and the inefficient sites from each site, increase the site area of ​​the efficient sites, and delete the inefficient sites.

[0103] In the embodiment of the present application, the server determines the activity level of each site according to the status score of each site in the current time period, and determines the site to be adjusted according to the activity level of each site. Then, the server adjusts each site to be adjusted.

[0104] For example, the server may adjust the area of ​​each site to be adjusted according to the activity level of the site to be adjusted.

[0105] Specifically, the server can increase the site area of ​​the high-efficiency site, where the upward adjustment method may include increasing the site area (i.e., increasing the site radius based on the center position of the site), adding a new site within a preset range of the high-efficiency site (for example, outside the five-meter range or within the fifteen-meter range outside the site), etc. The embodiment of the present application does not specifically limit the method of increasing the site area.

[0106] Specifically, the server can determine the area to be increased for each high-efficiency site based on the status scores of the high-efficiency sites and the number of high-efficiency sites. For example, the server compares the status scores of the high-efficiency sites. When the status score of high-efficiency site A is 50% higher than the status score of high-efficiency site B, the server's site area increase for high-efficiency site A can be 50% of the site area increase for high-efficiency site B.

[0107] After determining the inefficient site, the server can delete or retain the inefficient site according to the actual situation.

[0108] The present application does not specifically limit the specific method of determining the area to be increased for each high-efficiency site according to the status score of the high-efficiency site and the number of the high-efficiency sites.

[0109] In the above-mentioned site adjustment method, multiple sites within the target range are determined; according to the site indicator data and riding data of each site within the target range, the status score of each site within the target range is determined, and the status score is used to characterize the activity of the site; according to the status score of each site, the site to be adjusted is determined, and the site to be adjusted is adjusted. By adopting this method, the status scores of multiple sites within the target range can be determined, so that the site to be adjusted is determined according to the status scores of multiple sites. Since a high status score of a site can represent a high level of activity of the site, by increasing the area of ​​the site with a high status score among the sites to be adjusted, more shared vehicles can be parked in hot spots, avoiding the problem of unreasonable site planning caused by the fact that the parking range of the site is full of cars and some shared vehicles cannot be returned. In addition, since a low status score of a site can represent a low level of activity of the site and there is no large demand for vehicles, by deleting sites with low status scores, scheduling resources can be saved, the scheduling and maintenance efficiency of shared vehicles can be improved, and the rationality of site planning can be improved.

[0110] In an exemplary embodiment, Figure 2 As shown, step 104 includes:

[0111] Step 202, for each station within the target range, determine the secondary score of the station for each secondary indicator based on the station indicator data and riding data of each station within the target range.

[0112] In the embodiment of the present application, the server calculates the secondary scores of each secondary indicator for each site within the target range according to the secondary scores of each site within the target range within the current time period.

[0113] Step 204, determining the first-level score of the site for each first-level indicator according to the second-level score of the site for each second-level indicator.

[0114] In the embodiment of the present application, the server performs a weighted sum calculation based on the secondary scores of each site for each secondary indicator to determine the primary scores of each site for each primary indicator.

[0115] Step 206, determining the status score of the site according to the first-level score of each first-level indicator of the site.

[0116] In the embodiment of the present application, the server performs a weighted sum calculation based on the first-level score of each site for each first-level indicator to determine the status score of each site in the current time period.

[0117] In this embodiment, the server can determine the secondary score of the secondary indicator based on the site indicator data and riding data of each site within the target range, and determine the status score of each site in the current time period based on the secondary score of the secondary indicator. Since the site indicator data and riding data of each site within the target range are fully referenced, a status score that can more accurately characterize the activity level of the site can be obtained, which improves the accuracy of determining the activity level of the site and facilitates subsequent adjustment of the site based on the status score of each site.

[0118] In an exemplary embodiment, the primary indicators include site location, site riding out demand, site riding in demand, user experience and vehicle consumption; the secondary indicators include site effective area ratio, number of site information points, number of riding out orders covered, riding out order resource data, number of riding in orders covered, riding in order resource data, average number of vehicle returns per order, average number of illegal parking pop-up windows per order, consumption speed and parking time.

[0119] In an exemplary embodiment, Figure 3 As shown, when the primary indicator is the site location, the secondary indicators include the site effective area ratio and the number of site information points, and step 202 includes:

[0120] Step 302: Determine a secondary score of the site for the proportion of the effective area of ​​the site according to the site area of ​​the site and the overlapping area between the site and other sites within the target range.

[0121] In the embodiment of the present application, the server can determine the site area and center position of the site in the pre-stored site indicator data according to the unique number of the site. For example, the server determines that the site area of ​​the site 1001 is 25 square meters and the center position is (39°28'N, 115°25'E) according to the pre-stored site indicator data according to the unique number of the site 1001.

[0122] Then, by analogy, the server obtains the site area and center position of other sites within the target range, thereby determining sites that overlap with the site in area. Further, the server determines the area that overlaps with any other site.

[0123] For example, the area of ​​site A is 25 square meters, the server determines that the overlapping area between site A and site B is 5.5 square meters, and the overlapping area between site A and site C is 1.5 square meters. Therefore, the server determines that the overlapping area between site A and other sites within the target range is: 5.5+1.5=7 square meters.

[0124] Then, the server determines the secondary score of the effective area ratio of the site in the secondary indicator according to the site area of ​​the site and the overlapping area between the site and other sites within the target range. The method for determining the secondary score of the effective area ratio of the site can refer to formula (I), and the specific content is as follows:

[0125] Formula (I)

[0126] Among them, Q1 represents the secondary score of the site for the proportion of the effective area of ​​the site, and the value range of Q1 is between 0 and 1; S1 represents the overlapping area between the site and other sites within the target range; S2 represents the area of ​​the site itself.

[0127] The higher the secondary score of the effective area ratio of a site, the more active the site is. If a site does not overlap with any other site, it will get full marks (i.e., the secondary indicator of the site, the effective area ratio of the site is 1); if the areas of any two sites overlap or coincide, the effective area ratio of the site created earlier will remain unchanged.

[0128] Step 304: Determine the secondary score of the site for the number of information points in the site according to the number of information points in the site and the number of information points in other sites within the target range.

[0129] In an embodiment of the present application, after determining any site, the server can determine the number of information points (POI, Point of Interest, any non-geographically meaningful points on the map, such as shops, bars, gas stations, hospitals, train stations, etc.) contained in the site range in the map based on the central location and site area of ​​the site, and use the number of information points contained in the site range as one of the site indicator data.

[0130] The server determines the minimum number of information points of the sites within the target range and the maximum number of information points of the sites according to the number of information points in the site and the number of information points in other sites within the target range.

[0131] Exemplarily, when the number of information points in site A is 1, the number of information points in site B is 2, the number of information points in site C is 3, and the number of information points in site D is 2, the server determines that the minimum number of information points of the sites within the target range is 1 (i.e., site A), and the maximum number of information points of the sites is 3 (i.e., site C).

[0132] The server determines the secondary score of the number of information points of the site for the secondary indicator, the number of information points of the site, according to the number of information points in the site, the minimum number of information points of the site within the target range, and the maximum number of information points of the site. The method for determining the secondary score of the number of information points of the site can refer to formula (II), and the specific content is as follows:

[0133] Formula (II)

[0134] Among them, Q2 represents the secondary score of the site for the number of site information points, and the value range of Q2 is between 0 and 1; P represents the number of information points of a site within the target range; Pmin represents the minimum number of information points of the site within the target range; Pmax represents the maximum number of information points of the site within the target range.

[0135] Among them, the more information points contained in the site, the more cycling demand there is in the site, the more active the site is, and the better the site quality is.

[0136] In this embodiment, the server can determine the secondary score of the proportion of the effective area of ​​the secondary indicator site and the number of information points of the secondary indicator site, so as to facilitate the subsequent implementation of determining the primary score of the primary indicator site location based on the secondary score of the proportion of the effective area of ​​the secondary indicator site and the number of information points of the secondary indicator site.

[0137] In an exemplary embodiment, Figure 4 As shown, when the primary indicator is the site outbound demand, the secondary indicators include the outbound order coverage quantity and the outbound order resource data, and step 202 includes:

[0138] Step 402, determining a secondary score for the site's coverage of ride-out orders based on the site's average daily number of ride-out orders in the current time period and the average daily number of ride-out orders of other sites within the target range in the current time period.

[0139] Among them, a ride-out order refers to a vehicle usage order generated within the current station and taking the current station as the starting point.

[0140] In the embodiment of the present application, the server can count the outbound orders of each station within the target range in the current time period (for example, the seven natural days before the current time) to obtain the total outbound orders of each station in the current time period. Then, the server can determine the average daily outbound orders of each station in the current time period.

[0141] The server determines the minimum average daily number of ride orders for sites in the target range within the current time period and the maximum average daily number of ride orders for sites within the target range within the current time period based on the average daily number of ride orders for the site within the current time period and the average daily number of ride orders for other sites within the target range within the current time period.

[0142] The server determines the secondary score of the site for the number of ride-out orders covered based on the average daily number of ride-out orders of the site in the current time period, the minimum average daily number of ride-out orders of the sites in the target range in the current time period, and the maximum average daily number of ride-out orders of the site. The method for determining the secondary score of the site for the number of ride-out orders covered can refer to formula (III), which includes:

[0143] Formula (III)

[0144] Among them, Q3 represents the secondary score of the site for the number of ride-out orders covered, and the value range of Q3 is between 0 and 1; C represents the average daily number of ride-out orders of the site in the current time period; Cmin represents the minimum average daily number of ride-out orders of the site in the target range in the current time period; Cmax represents the maximum average daily number of ride-out orders of the site in the target range in the current time period.

[0145] Among them, the more outbound orders generated within the site, the more active the site is, the greater the value generated by the site, and the better the site quality.

[0146] Step 404, based on the average outbound order resource data of multiple outbound orders of the site in the current time period, and the average outbound order resource data of multiple outbound orders of other sites within the target range in the current time period, determine the secondary score of the site for the outbound order resource data.

[0147] In an embodiment of the present application, the server can obtain the riding orders of shared vehicles at each site in the current time period, and obtain the order resource data of each riding order at each site in the current time period (such as the average order value of the order). The server determines the average riding order resource data of multiple riding orders at each site in the current time period based on the order resource data of multiple riding orders at each site in the current time period.

[0148] The server determines the smallest average outgoing order resource data and the largest average outgoing order resource data in the target range within the current time period based on the average outgoing order resource data of multiple outgoing orders of the site within the current time period and the average outgoing order resource data of multiple outgoing orders of other sites within the target range within the current time period.

[0149] The server determines the secondary score of the site's outbound order resource data for the secondary indicator based on the average outbound order resource data of multiple outbound orders in the current time period, the smallest average outbound order resource data in the target range in the current time period, and the largest average outbound order resource data. The method for determining the secondary score of the site's outbound order resource data can refer to formula (IV), which includes:

[0150] Formula (IV)

[0151] Among them, Q4 represents the secondary score of the site for the riding order resource data, and the value range of Q4 is between 0 and 1; A represents the average riding order resource data of multiple riding orders of the site in the current time period; Amin represents the smallest average riding order resource data in the target range in the current time period; Amax represents the largest average riding order resource data in the target range in the current time period.

[0152] Among them, the higher the outgoing order resource data, the more active the site is, the greater the value generated by each order, and the better the site quality.

[0153] In this embodiment, the server can determine the secondary score of the secondary indicator riding out order coverage quantity and the secondary indicator riding out order resource data, so as to facilitate the subsequent implementation of determining the primary score of the primary indicator site riding out demand based on the secondary indicator riding out order coverage quantity and the secondary indicator riding out order resource data.

[0154] In an exemplary embodiment, Figure 5 As shown, when the primary indicator is the site entry demand, the secondary indicators include the entry order coverage quantity and the entry order resource data, and step 202 includes:

[0155] Step 502, determining the secondary score of the site for the number of ride-in orders covered based on the average daily number of ride-in orders of the site in the current time period and the average daily number of ride-in orders of other sites within the target range in the current time period.

[0156] Among them, the ride-in order refers to a vehicle use order that ends in the current station and takes the current station as the end point.

[0157] In the embodiment of the present application, the server can count the incoming ride orders of each station within the target range in the current time period (for example, the seven natural days before the current time) to obtain the total number of incoming ride orders for each station in the current time period. Then, the server can determine the average number of incoming ride orders per day for each station in the current time period.

[0158] The server determines the minimum average daily number of incoming orders for sites in the target range within the current time period and the maximum average daily number of incoming orders for sites based on the average daily number of incoming orders for the site within the current time period and the average daily number of incoming orders for other sites within the target range within the current time period.

[0159] The server determines the secondary score of the site for the number of ride-in orders covered based on the average daily number of ride-in orders of the site in the current time period, the minimum average daily number of ride-in orders of the sites in the target range in the current time period, and the maximum average daily number of ride-in orders of the site. The method for determining the secondary score of the site for the number of ride-in orders covered can refer to formula (V), which includes:

[0160] Formula (V)

[0161] Among them, Q5 represents the secondary score of the site for the number of ride-in orders covered, and the value range of Q5 is between 0 and 1; R represents the average daily number of ride-in orders of the site in the current time period; Rmin represents the minimum average daily number of ride-in orders of the site in the target range in the current time period; Rmax represents the maximum average daily number of ride-in orders of the site in the target range in the current time period.

[0162] Among them, the more ride-in orders generated within the site, the more active the site is, the greater the value generated by the site, and the better the site quality.

[0163] Step 504, determine the secondary score of the site for the incoming order resource data based on the average incoming order resource data of multiple incoming orders of the site in the current time period and the average incoming order resource data of multiple incoming orders of other sites within the target range in the current time period.

[0164] In an embodiment of the present application, the server can obtain the ride-in orders of shared vehicles at each site in the current time period, and obtain the order resource data of each ride-in order at each site in the current time period (such as the average order value of the order). The server determines the average ride-in order resource data of multiple ride-in orders at each site in the current time period based on the order resource data of multiple ride-in orders at each site in the current time period.

[0165] The server determines the smallest average order resource data and the largest average order resource data in the target range within the current time period based on the average order resource data of multiple orders received by the site within the current time period and the average order resource data of multiple orders received by other sites within the target range within the current time period.

[0166] The server determines the secondary score of the site's incoming order resource data for the secondary indicator based on the average incoming order resource data of multiple incoming orders of the site in the current time period, the smallest average incoming order resource data in the target range in the current time period, and the largest average incoming order resource data. The method for determining the secondary score of the site's incoming order resource data can refer to formula (six), which includes:

[0167] Formula (VI)

[0168] Among them, Q6 represents the secondary score of the site for the riding order resource data, and the value range of Q6 is between 0 and 1; B represents the average riding order resource data of multiple riding orders of the site in the current time period; Bmin represents the smallest average riding order resource data in the target range in the current time period; Bmax represents the largest average riding order resource data in the target range in the current time period.

[0169] Among them, the higher the order resource data, the more active the site is, the greater the value generated by each order, and the better the site quality.

[0170] In this embodiment, the server can determine the secondary score of the secondary indicator riding-in order coverage quantity and the secondary indicator riding-in order resource data, so as to facilitate the subsequent implementation of determining the primary score of the primary indicator site riding-in demand based on the secondary indicator riding-in order coverage quantity and the secondary score of the secondary indicator riding-in order resource data.

[0171] In an exemplary embodiment, Figure 6 As shown, when the primary indicator is user experience, the secondary indicators include the average number of vehicle returns per order and the average number of illegal parking pop-up windows per order, and step 202 includes:

[0172] Step 602, determining a secondary score for the station's average number of vehicle returns per order based on the station's average number of vehicle returns per order in a historical time period and the station's average number of vehicle returns per order in a current time period.

[0173] Among them, any time period before the current time period can be used as a historical time period, for example, any consecutive seven natural days before the current time period can be used as a historical time period.

[0174] In the embodiment of the present application, the server can detect whether the user returns the vehicle during each order and record the number of times the user returns the vehicle. The server records the number of times the user returns the vehicle during each order as one of the riding data.

[0175] For each station, the server determines the ride-in orders within a preset range of the station (e.g., a range of three meters outside the station), and determines the number of returns for each ride-in order (i.e., the number of times the user returns the vehicle). Then, the server obtains the ride-in orders for each station in a historical time period, and determines the average number of returns for multiple ride-in orders for each station in the historical time period.

[0176] The server determines the minimum number of vehicle returns per order and the maximum number of vehicle returns per order for the site based on the average number of vehicle returns per order for the site in each historical time period and the average number of vehicle returns per order for the site in the current time period.

[0177] Then, the server determines the secondary score of the site for the secondary indicator, average number of returns per order, based on the average number of returns per order for the site in the current time period, the minimum number of returns per order for the site, and the maximum number of returns per order for the site. The method for determining the secondary score for the average number of returns per order for the site can refer to formula (VII), and the specific content is as follows:

[0178] Formula (VII)

[0179] Among them, Q7 represents the secondary score of the station for the average number of vehicle returns per order, and the value range of Q7 is between 0 and 1; Y represents the average number of vehicle returns per order at the station in the current time period; Ymin represents the minimum number of vehicle returns per order at the station; Ymax represents the maximum number of vehicle returns per order at the station.

[0180] Among them, the more times the user returns the vehicle, the more difficult it is to return the vehicle and the worse the station quality is.

[0181] Step 604, based on the average number of illegal parking pop-up windows for the site in the historical time period and the average number of illegal parking pop-up windows for the site in the current time period, determine the secondary score for the site for the average number of illegal parking pop-up windows for the site.

[0182] In the embodiment of the present application, the server can detect whether a parking violation pop-up window is generated during each order and record the number of parking violation pop-ups generated. The server records the number of parking violation pop-ups generated during each order as one of the riding data.

[0183] For each station, the server determines the ride-in orders within a preset range of the station (e.g., a three-meter range outside the station), and determines the number of illegal parking pop-up windows for each ride-in order (i.e., the number of illegal parking pop-up windows generated). Then, the server obtains the ride-in orders for each station in a historical time period, and determines the average number of illegal parking pop-up windows for multiple ride-in orders for each station in the historical time period.

[0184] The server determines the minimum number of illegal parking pop-up windows per order and the maximum number of illegal parking pop-up windows per order for the site based on the average number of illegal parking pop-up windows per order for the site in each historical time period and the average number of illegal parking pop-up windows per order for the site in the current time period.

[0185] Then, the server determines the secondary score of the site for the secondary indicator, the average number of illegal parking pop-up windows, based on the average number of illegal parking pop-up windows for the site in the current time period, the minimum average number of illegal parking pop-up windows for the site, and the maximum average number of illegal parking pop-up windows for the site. The method for determining the secondary score for the average number of illegal parking pop-up windows for the site can refer to formula (VIII), and the specific content is as follows:

[0186] Formula (8)

[0187] Among them, Q8 represents the secondary score of the site for the average number of illegal parking pop-up windows, and the value range of Q8 is between 0 and 1; W represents the average number of illegal parking pop-up windows of the site in the current time period; Wmin represents the minimum number of illegal parking pop-up windows of the site; Wmax represents the maximum number of illegal parking pop-up windows of the site.

[0188] Among them, the more illegal parking pop-up windows appear, the more difficult it is to return the vehicle and the worse the quality of the station.

[0189] In this embodiment, the server can determine the secondary scores of the secondary indicators of the average number of vehicle returns per order and the average number of pop-up windows for illegal parking per order, so as to facilitate the subsequent implementation of determining the effect of the first-level score of the first-level indicator user experience based on the second-level scores of the second-level indicators of the average number of vehicle returns per order and the average number of pop-up windows for illegal parking per order.

[0190] In an exemplary embodiment, Figure 7 As shown, when the primary indicator is vehicle consumption, the secondary indicators include consumption speed and parking time, and step 202 includes:

[0191] Step 702, determining the secondary score of the station for the consumption speed according to the average daily vehicle consumption speed of the station in the historical time period and the average daily vehicle consumption speed of the station in the current time period.

[0192] Among them, any time period before the current time period can be regarded as a historical time period.

[0193] In the embodiment of the present application, the server can count the number of vehicles flowing into each station from the initial moment of the current natural day to the initial moment of the next natural day, the number of vehicles parked at each station at the initial moment of the current natural day (i.e., the number of vehicles parked at the station at 0:00 a.m. of the current natural day), and the number of vehicles flowing out of each station from the initial moment of the current natural day to the initial moment of the next natural day at the initial moment of each natural day (e.g., 0:00 a.m. of each day), and determine the vehicle consumption rate of the current natural day. The method for determining the vehicle consumption rate can be referred to as shown in formula (IX), and the specific content is as follows:

[0194] Formula (IX)

[0195] Among them, V represents the vehicle consumption rate of a certain station in the current natural day; N1 represents the number of vehicles flowing out of the station from the initial moment of the current natural day to the initial moment of the next natural day; N2 represents the number of vehicles flowing into the station from the initial moment of the current natural day to the initial moment of the next natural day; N3 represents the number of vehicles parked at the station at the initial moment of the current natural day.

[0196] After determining the daily vehicle consumption rate of each station, the server can determine the average daily vehicle consumption rate of each station in the historical time period with each time period as a target.

[0197] Then, the server determines the minimum average daily vehicle consumption rate and the maximum average daily vehicle consumption rate of the site according to the average daily vehicle consumption rate of the site in the historical time period and the average daily vehicle consumption rate of the site in the current time period.

[0198] The server determines the secondary score of the consumption speed for the secondary indicator of the site based on the average daily vehicle consumption speed of the site in the current time period, the minimum average daily vehicle consumption speed of the site, and the maximum average daily vehicle consumption speed. The method for determining the secondary score of the site for the consumption speed can refer to formula (10), and the specific content is as follows:

[0199] Formula (10)

[0200] Among them, Q10 represents the secondary score of the station for consumption speed, and the value range of Q10 is between 0 and 1; K represents the average daily vehicle consumption speed of the station in the current time period; Kmin represents the minimum average daily vehicle consumption speed of the station; Kmax represents the maximum average daily vehicle consumption speed of the station.

[0201] Among them, the faster the vehicle consumption rate is, the more active the site is and the better the site quality is.

[0202] Step 704, determining a secondary score for parking time of the station according to the average parking time of vehicles at the station in the historical time period and the average parking time of vehicles at the station in the current time period.

[0203] In the embodiment of the present application, the server can count the time during which the vehicle has neither an incoming order nor an outgoing order, i.e., the parking time of the vehicle, for each shared vehicle. The server determines the average parking time of vehicles at each station in the historical time period based on the parking time of multiple vehicles at each station.

[0204] The server determines the minimum and maximum parking times per vehicle at the site according to the average parking times per vehicle at the site in the historical time period and the average parking times per vehicle at the site in the current time period.

[0205] Then, the server determines the secondary score of the parking time for the secondary indicator of the station according to the average parking time of the vehicles in the current time period, the minimum average parking time of the vehicles in the station, and the maximum average parking time of the vehicles in the station. The method for determining the secondary score of the parking time for the station can refer to formula (XI), and the specific content is as follows:

[0206] Formula (XI)

[0207] Among them, Q11 represents the secondary score of the station for parking time, and the value range of Q11 is between 0 and 1; T represents the average parking time of each vehicle at the station in the current time period; Tmin represents the minimum parking time of each vehicle at the station; Tmax represents the maximum parking time of each vehicle at the station.

[0208] Among them, the longer the average parking time of vehicles, the higher the possibility of vehicle accumulation, which indicates that the activity level of the site is lower and the quality of the site is worse.

[0209] In this embodiment, the server can determine the secondary scores of the secondary indicator consumption speed and the secondary indicator parking time, so as to facilitate the subsequent implementation of determining the primary score of the primary indicator vehicle consumption based on the secondary score of the secondary indicator consumption speed and the secondary indicator parking time.

[0210] In an exemplary embodiment, Figure 8 As shown, step 204 includes:

[0211] Step 802: for each primary indicator of the site, determine the secondary indicator corresponding to the primary indicator.

[0212] In the embodiment of the present application, the correspondence between the primary index and the secondary index may be pre-stored in the server.

[0213] The server determines the secondary indicator corresponding to each primary indicator for each primary indicator of the site and the corresponding relationship between the primary indicator and the secondary indicator.

[0214] Exemplarily, when the first-level indicator is the site location, the second-level indicators corresponding to the first-level indicator are the proportion of the effective area of ​​the site and the number of site information points; when the first-level indicator is the demand for riding out of the site, the second-level indicators corresponding to the first-level indicator are the number of riding out orders covered and the riding out order resource data; when the first-level indicator is the demand for riding in of the site, the second-level indicators corresponding to the first-level indicator are the number of riding in orders covered and the riding in order resource data; when the first-level indicator is user experience, the second-level indicators corresponding to the first-level indicator are the average number of vehicle returns per order and the average number of illegal parking pop-up windows per order; when the first-level indicator is vehicle consumption, the second-level indicators corresponding to the first-level indicator are the consumption speed and parking time.

[0215] Step 804, based on the secondary weight of the secondary indicator corresponding to the primary indicator and the secondary score of the secondary indicator corresponding to the primary indicator, determine the primary score of the primary indicator.

[0216] In the embodiment of the present application, the weights of each secondary indicator (i.e., secondary weight) may be pre-stored in the server. Since each primary indicator corresponds to multiple secondary indicators, the sum of the secondary weights of the secondary indicators corresponding to each primary indicator is 1. The weights of each secondary indicator may be set by technical personnel according to needs in actual applications. For example, the secondary weight of the effective area ratio of the site is 0.3, and the secondary weight of the number of site information points is 0.7; the secondary weight of the number of outbound orders covered is 0.9, the secondary weight of outbound order resource data is 0.1, the secondary weight of the number of inbound orders covered is 0.9, and the secondary weight of inbound order resource data is 0.1; the secondary weight of the average number of car returns per order is 0.9, and the secondary weight of the average number of illegal parking pop-up windows per order is 0.1; the secondary weight of the consumption speed is 0.9, and the secondary weight of the parking time is 0.1.

[0217] The server performs a weighted sum calculation based on the secondary weight of the secondary indicator corresponding to the primary indicator and the secondary score of the secondary indicator corresponding to the primary indicator to determine the primary score of the primary indicator. The method for determining the primary score of the primary indicator can refer to formula (XII), and the specific content is as follows:

[0218] Formula (12)

[0219] Among them, S1 represents the first-level score of the first-level indicator; s1 represents the second-level score of the second-level indicator 1; w1 represents the second-level weight of the second-level indicator 1; s2 represents the second-level score of the second-level indicator 2; w2 represents the second-level weight of the second-level indicator 2.

[0220] In this embodiment, the server can perform weighted sum processing on multiple secondary indicators corresponding to the primary indicators, thereby determining the primary score of the site for each primary indicator, which facilitates the subsequent determination of the site's status score based on the primary scores of each primary indicator of the site.

[0221] In an exemplary embodiment, step 206 includes:

[0222] The status score of the site is determined based on the first-level score of each first-level indicator and the first-level weight of each first-level indicator.

[0223] Among them, the higher the status score of the site, the more active the site is and the better the site quality is.

[0224] In the embodiment of the present application, the server may also pre-store the weights of each first-level indicator (i.e., first-level weight), and the sum of the first-level weights of each first-level indicator is 1. The weights of each first-level indicator may be set by technicians according to requirements in actual applications, for example, the first-level weight of the station location is 0.2, the first-level weight of the station outgoing demand is 0.4, the first-level weight of the station incoming demand is 0.2, the first-level weight of the user experience is 0.1, and the first-level weight of the vehicle consumption is 0.1.

[0225] The server performs a weighted sum calculation based on the first-level weight of the first-level indicator and the first-level score of the first-level indicator to determine the status score of the site. The method for determining the status score of the site can refer to formula (13), and the specific content is as follows:

[0226] Formula (13)

[0227] Among them, S represents the status score of the site; S1 represents the first-level score of the first-level indicator 1; W1 represents the first-level weight of the first-level indicator 1; S2 represents the first-level score of the first-level indicator 2; W2 represents the first-level weight of the first-level indicator 2; S3 represents the first-level score of the first-level indicator 3; W3 represents the first-level weight of the first-level indicator 3; S4 represents the first-level score of the first-level indicator 4; W4 represents the first-level weight of the first-level indicator 4; S5 represents the first-level score of the first-level indicator 5; W5 represents the first-level weight of the first-level indicator 5.

[0228] In this embodiment, the server can determine the status score of the site based on the first-level score of each first-level indicator and the first-level weight of each first-level indicator. Since multiple indicators are fully considered and weighted sum calculation is performed on multiple indicators, a status score that can more accurately characterize the activity level of the site can be obtained, thereby improving the accuracy of determining the activity level of the site and facilitating subsequent adjustments to the site based on the status scores of each site.

[0229] In an exemplary embodiment, Fig. 9 As shown, step 106 includes:

[0230] Step 902: sort the sites in descending order according to the status scores of the sites to obtain a sorting result.

[0231] In the embodiment of the present application, the server sorts the sites according to the status scores of the sites in descending order to obtain a sorting result.

[0232] Exemplarily, the server determines the ranking result as site A-site B-site C-site D-site E.

[0233] Step 904: Based on the ranking result, determine the efficient sites and the inefficient sites from the sites.

[0234] In the embodiment of the present application, the server determines a first preset number of sites from each site as efficient sites, and determines a second preset number of sites from each site as inefficient sites based on the sorting result.

[0235] The preset number may be determined according to the number of sites within the target range, for example, the preset number is 20% of the number of sites.

[0236] Exemplarily, when the preset number is 1, the server regards site A as an efficient site and site E as an inefficient site according to the sorting result.

[0237] In this embodiment, the server may determine the activity ranking of the sites based on the status score of each site, and determine efficient sites with high activity and inefficient sites with low activity among the sites according to the ranking result.

[0238] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0239] Based on the same inventive concept, the embodiment of the present application also provides a site adjustment device for implementing the site adjustment method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more site adjustment device embodiments provided below can refer to the limitations of the site adjustment method above, and will not be repeated here.

[0240] In an exemplary embodiment, Fig.10 As shown, a site adjustment device 1000 is provided, comprising: a first determination module 1002, a second determination module 1004 and a third determination module 1006, wherein:

[0241] A first determination module 1002 is used to determine a plurality of sites within a target range;

[0242] The second determination module 1004 is used to determine the status score of each of the stations within the target range based on the station indicator data and riding data of each of the stations within the target range, the station indicator data including the central location and area of ​​the station, the riding data including the outgoing order data generated by the station, the incoming order data parked at the station, the illegal parking pop-up window data within a preset range around the station, and the return click data of each order within a preset range around the station, the status score is used to characterize the activity level of the station, and the higher the activity level of the station, the more times the vehicle is parked at the station.

[0243] The third determination module 1006 is used to determine efficient sites and inefficient sites from the sites according to the status scores of the sites, increase the site areas of the efficient sites, and delete the inefficient sites.

[0244] By using the site adjustment device provided by the embodiment of the present disclosure, it is possible to determine the status scores of multiple sites within the target range, thereby determining the site to be adjusted based on the status scores of the multiple sites. Since a high status score of a site can represent a high level of activity of the site, by increasing the area of ​​the site with a high status score among the sites to be adjusted, more shared vehicles can be parked in hot spots, thus avoiding the problem of unreasonable site planning caused by the site parking range being full of cars and some shared vehicles being unable to return. In addition, since a low status score of a site can represent a low level of activity of the site and there is no large demand for vehicles, by deleting sites with low status scores, it is possible to save scheduling resources, improve the scheduling and maintenance efficiency of shared vehicles, and improve the rationality of site planning.

[0245] In one embodiment, the second determining module is specifically configured to:

[0246] For each of the sites within the target range, determining a secondary score of the site for each secondary indicator according to the site indicator data and riding data of each of the sites within the target range;

[0247] Determine the first-level score of the site for each first-level indicator according to the second-level score of the site for each second-level indicator;

[0248] The status score of the site is determined according to the first-level score of each first-level indicator of the site.

[0249] In one embodiment, the primary indicators include site location, site outbound demand, site inbound demand, user experience and vehicle consumption; the secondary indicators include site effective area ratio, number of site information points, number of outbound orders covered, outbound order resource data, number of inbound orders covered, inbound order resource data, average number of vehicle returns per order, average number of illegal parking pop-up windows per order, consumption speed and parking duration.

[0250] In one embodiment, when the primary indicator is the site location, the secondary indicator includes the site effective area ratio and the number of site information points, and the second determination module is specifically configured to:

[0251] Determine, according to the site area of ​​the site and the overlapping area between the site and other sites within the target range, a secondary score of the site for the proportion of the effective area of ​​the site;

[0252] A secondary score of the site for the number of information points at the site is determined according to the number of information points at the site and the number of information points at other sites within the target range.

[0253] In one embodiment, when the primary indicator is the site outbound demand, the secondary indicator includes the outbound order coverage quantity and the outbound order resource data, and the second determination module is specifically configured to:

[0254] Determine a secondary score of the site for the number of ride-out orders covered by the site according to the average daily number of ride-out orders of the site in the current time period and the average daily number of ride-out orders of other sites within the target range in the current time period;

[0255] Based on the average riding order resource data of multiple riding orders of the site in the current time period and the average riding order resource data of multiple riding orders of other sites within the target range in the current time period, the secondary score of the site for the riding order resource data is determined.

[0256] In one embodiment, when the primary indicator is the site entry demand, the secondary indicator includes the entry order coverage quantity and the entry order resource data, and the second determination module is specifically used to:

[0257] Determine the secondary score of the site for the number of ride-in orders covered by the site according to the average daily number of ride-in orders of the site in the current time period and the average daily number of ride-in orders of other sites within the target range in the current time period;

[0258] Based on the average incoming order resource data of multiple incoming orders of the site in the current time period and the average incoming order resource data of multiple incoming orders of other sites within the target range in the current time period, the secondary score of the site for the incoming order resource data is determined.

[0259] In one embodiment, when the primary indicator is the user experience, the secondary indicator includes the average number of vehicle returns per order and the average number of pop-up windows for illegal parking per order, and the second determination module is specifically configured to:

[0260] Determine a secondary score of the site for the average number of vehicle returns per order based on the average number of vehicle returns per order at the site in a historical time period and the average number of vehicle returns per order at the site in a current time period;

[0261] According to the average number of illegal parking pop-up windows for each order of the site in the historical time period and the average number of illegal parking pop-up windows for each order of the site in the current time period, a secondary score for the average number of illegal parking pop-up windows for each order of the site is determined.

[0262] In one embodiment, when the primary indicator is the vehicle consumption, the secondary indicator includes the consumption speed and the parking duration, and the second determination module is specifically configured to:

[0263] Determine a secondary score of the site for the consumption speed according to the average daily vehicle consumption speed of the site in a historical time period and the average daily vehicle consumption speed of the site in a current time period;

[0264] A secondary score for parking time at the site is determined based on the average parking time of vehicles at the site in the historical time period and the average parking time of vehicles at the site in the current time period.

[0265] In one embodiment, the second determining module is specifically configured to:

[0266] For each primary indicator of the site, determining a secondary indicator corresponding to the primary indicator;

[0267] The first-level score of the first-level indicator is determined based on the second-level weight of the second-level indicator corresponding to the first-level indicator and the second-level score of the second-level indicator corresponding to the first-level indicator.

[0268] In one embodiment, the second determining module is specifically configured to:

[0269] The status score of the site is determined according to the first-level score of each first-level indicator of the site and the first-level weight of each first-level indicator.

[0270] In one embodiment, the third determination module is specifically configured to:

[0271] According to the status scores of the sites, the sites are sorted in descending order to obtain a sorting result;

[0272] Based on the ranking result, the efficient site and the inefficient site are determined from the sites.

[0273] Each module in the above-mentioned site adjustment device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0274] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.11As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data related to each site adjustment method. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a site adjustment method is implemented.

[0275] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0276] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0277] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0278] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0279] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0280] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0281] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0282] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A site adjustment method, characterized in that: The method comprises: Identify multiple sites within the target area; For each of the stations within the target range, the secondary score of the station for each secondary indicator is determined according to the station indicator data and riding data of each of the stations within the target range; the station indicator data includes the central location and area of ​​the station, and the riding data includes the outgoing order data generated by the station, the incoming order data parked at the station, the illegal parking pop-up window data within a preset range around the station, and the return click data of each order within a preset range around the station; Determine the first-level score of the site for each first-level indicator according to the second-level score of the site for each second-level indicator; Determine the status score of the site according to the first-level score of each first-level indicator of the site; the status score is used to represent the activity level of the site, and the higher the activity level of the site, the more vehicles park at the site; According to the status score of each of the sites, determining efficient sites and inefficient sites from the sites, upwardly adjusting the site area of ​​the efficient sites, and deleting the inefficient sites; The secondary index at least includes the effective area ratio of the site, and the secondary score of the site for each secondary index is determined according to the site index data and riding data of each site within the target range, including: Determine the overlapping areas of the site and other sites within the target range respectively, and sum the overlapping areas corresponding to the sites to obtain a target overlapping area; Determining the overlap area ratio according to the ratio of the target overlap area to the area of ​​the site; The difference between 1 and the overlapping area ratio is used as the secondary score of the site for the effective area ratio of the site.

2. The method according to claim 1, characterized in that The first-level indicators include site location, site outbound riding demand, site inbound riding demand, user experience and vehicle consumption; the second-level indicators also include the number of site information points, the number of outbound riding orders covered, outbound riding order resource data, the number of inbound riding orders covered, inbound riding order resource data, the average number of vehicle returns per order, the average number of illegal parking pop-up windows per order, consumption speed and parking duration.

3. The method according to claim 2, characterized in that In the case where the primary indicator is the site location, the secondary indicator also includes the number of site information points. The determining, according to the site indicator data and the riding data of each site within the target range, the secondary score of the site for each secondary indicator, further includes: A secondary score of the site for the number of information points at the site is determined according to the number of information points at the site and the number of information points at other sites within the target range.

4. The method according to claim 2, characterized in that: In the case where the primary indicator is the site outbound demand, the secondary indicator includes the outbound order coverage quantity and the outbound order resource data. Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes: Determine a secondary score of the site for the number of ride-out orders covered by the site according to the average daily number of ride-out orders of the site in the current time period and the average daily number of ride-out orders of other sites within the target range in the current time period; Based on the average outgoing order resource data of multiple outgoing orders of the site in the current time period and the average outgoing order resource data of multiple outgoing orders of other sites in the target range in the current time period, the secondary score of the outgoing order resource data of the site is determined.

5. The method according to claim 2, characterized in that: In the case where the primary indicator is the site entry demand, the secondary indicator includes the entry order coverage quantity and the entry order resource data. Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes: Determine the secondary score of the site for the number of ride-in orders covered by the site according to the average daily number of ride-in orders of the site in the current time period and the average daily number of ride-in orders of other sites within the target range in the current time period; Based on the average incoming order resource data of multiple incoming orders of the site in the current time period and the average incoming order resource data of multiple incoming orders of other sites within the target range in the current time period, the secondary score of the site for the incoming order resource data is determined.

6. The method according to claim 2, characterized in that When the primary indicator is the user experience, the secondary indicators include the average number of vehicle returns per order and the average number of illegal parking pop-up windows per order. Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes: Determine a secondary score of the site for the average number of vehicle returns per order based on the average number of vehicle returns per order at the site in a historical time period and the average number of vehicle returns per order at the site in a current time period; According to the average number of illegal parking pop-up windows for each order of the site in the historical time period and the average number of illegal parking pop-up windows for each order of the site in the current time period, a secondary score for the average number of illegal parking pop-up windows for each order of the site is determined.

7. The method according to claim 2, characterized in that When the primary indicator is the vehicle consumption, the secondary indicators include the consumption speed and the parking time. Determining the secondary score of each secondary indicator of the site according to the site indicator data and the riding data of each site within the target range includes: Determine a secondary score of the site for the consumption speed according to the average daily vehicle consumption speed of the site in a historical time period and the average daily vehicle consumption speed of the site in a current time period; According to the average parking time of vehicles at the site in the historical time period and the average parking time of vehicles at the site in the current time period, a secondary score of the site for the parking time is determined.

8. The method according to claim 1, characterized in that Determining the first-level score of the site for each first-level indicator according to the second-level score of the site for each second-level indicator includes: For each primary indicator of the site, determining a secondary indicator corresponding to the primary indicator; The first-level score of the first-level indicator is determined based on the second-level weight of the second-level indicator corresponding to the first-level indicator and the second-level score of the second-level indicator corresponding to the first-level indicator.

9. The method according to claim 1, characterized in that: Determining the status score of the site according to the first-level score of each first-level indicator of the site includes: The status score of the site is determined according to the first-level score of each first-level indicator of the site and the first-level weight of each first-level indicator.

10. The method according to claim 1, characterized in that Determining efficient sites and inefficient sites from the sites according to the status scores of the sites includes: According to the status scores of the sites, the sites are sorted in descending order to obtain a sorting result; Based on the ranking result, efficient sites and inefficient sites are determined from the sites.

11. A site adjustment device, characterized in that: The device comprises: A first determination module is used to determine multiple sites within a target range; The second determination module is used to determine, for each of the stations within the target range, the secondary score of the station for each secondary indicator according to the station indicator data and riding data of each of the stations within the target range; determine the primary score of the station for each primary indicator according to the secondary score of the station for each secondary indicator; determine the status score of the station according to the primary score of the station for each primary indicator; wherein the station indicator data includes the central location and station area of ​​the station, the riding data includes the riding out order data generated by the station, the riding in order data parked at the station, the illegal parking pop-up window data within a preset range around the station, and the return vehicle click data of each order within a preset range around the station, and the status score is used to represent the activity level of the station, and the higher the activity level of the station, the more times the vehicle is parked at the station; A third determination module is used to determine efficient sites and inefficient sites from the sites according to the status scores of the sites, to increase the site areas of the efficient sites, and to delete the inefficient sites; Among them, the secondary index at least includes the proportion of the effective area of ​​the site. The second determination module is also used to respectively determine the overlapping area between the site and other sites within the target range, and sum up the overlapping areas corresponding to the site to obtain the target overlapping area; determine the overlapping area proportion according to the ratio of the target overlapping area to the area of ​​the site; and use the difference between 1 and the overlapping area proportion as the secondary score of the site for the proportion of the effective area of ​​the site.

12. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 10 are implemented.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

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