Shared bicycle dispatching method and dispatching system

Abstract

The application provides a real-time intelligent scheduling method and system for shared bicycles. Generally, the demand for shared bicycles is obtained based on historical data. In the operation area of shared bicycles, the key and hotspot areas for parking bicycles are monitored in real time. According to the maximum threshold (maximum load that can be carried) of parked vehicles set in the area, the real-time parking quantity, the current quantity and demand quantity of shared bicycles are combined for overall scheduling, so that dynamic intelligent scheduling is realized, and the defects of redundant scheduling resources and uneven scheduling caused by manual scheduling based on experience are solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of shared bicycle dispatching, and particularly relates to a shared bicycle dispatching method and a shared bicycle dispatching system. BACKGROUND

[0002] At present, shared bicycle dispatching mostly needs to be manually performed, and generally only simple vehicle transfer from one place to another is performed, for example, vehicle transfer from a subway stop to a residential area stop at night so that users can ride in the morning of the next day. Such a dispatching scheme only relies on manual experience, and when the number of regions to be dispatched is large, dispatching redundancy is easily caused, dispatching resources are wasted, and dispatching is uneven, and thus the use demand of all dispatching regions cannot be met, and thus there are many deficiencies. SUMMARY

[0003] The shared bicycle dispatching method and the shared bicycle dispatching system provided in the embodiments of the application can solve the following problems: 1. After users use bicycles in an operation region, the bicycles are unevenly parked, bicycles are stacked in some regions, traffic is blocked, and the city appearance is affected; and in some regions, it is difficult to find a bicycle, and citizens have no bicycle to ride when going out. 2. The current parking mode brings many obstacles to subsequent users, for example, the walking time of the subsequent users to the destination is too long after parking, the walking path is too complex to find the destination store, and the disordered parking mode makes it more difficult for subsequent users to find a parking space, and when the number of parked bicycles is large, traffic congestion in the parking lot is easily caused.

[0004] In a first aspect, the embodiments of the application provide a shared bicycle dispatching method, and the shared bicycle dispatching method comprises the following steps.

[0005] obtaining current system time information and information such as the number of parked shared bicycles in each sub-partition in a region to be dispatched;

[0006] determining the number of dispatched shared bicycles and a target sub-partition to be dispatched in each sub-partition in the region to be dispatched according to the current system time information;

[0007] dispatching the shared bicycles in each sub-partition according to the number of dispatched shared bicycles and the target sub-partition to be dispatched in each sub-partition in each region to be dispatched.

[0008] In an optional embodiment, the step of determining the number of dispatched shared bicycles and the target sub-partition to be dispatched in each sub-partition in the region to be dispatched according to the current system time information comprises the following steps.

[0009] According to the current system time information, a comparison table corresponding to each time period and the number of shared bicycle demands in each sub-partition is found, and the comparison table of each time period is different;

[0010] determining, according to the found correspondence table, a scheduled shared bicycle quantity and a scheduled target sub-partition for each sub-partition in the region to be scheduled.

[0011] In an optional embodiment, the determining, according to the found correspondence table, a scheduled shared bicycle quantity and a scheduled target sub-partition for each sub-partition in the region to be scheduled comprises:

[0012] For each sub-partition, determining a supply-demand identity of the sub-partition according to a current shared bicycle quantity and a shared bicycle demand quantity, the supply-demand identity comprising a supply sub-partition and a demand sub-partition;

[0013] For each demand sub-partition, finding a target supply sub-partition from supply sub-partitions bordering the demand sub-partition, the target supply sub-partition being a supply sub-partition with the least number of bordering sub-partitions;

[0014] determining whether a schedulable shared bicycle quantity of the target supply sub-partition meets a shared bicycle demand quantity of the demand sub-partition according to a current shared bicycle quantity of the target supply sub-partition, a shared bicycle demand quantity of the target supply sub-partition, and a shared bicycle quantity of the demand sub-partition, a shared bicycle demand quantity of the demand sub-partition, and if not, finding a target supply sub-partition in a remaining supply sub-partition until the schedulable shared bicycle quantity of all target supply sub-partitions meets the shared bicycle demand quantity of the demand sub-partition, or until all bordering supply sub-partitions are traversed;

[0015] outputting a scheduled quantity of each supply sub-partition and demand sub-partition.

[0016] In an optional embodiment, if the schedulable shared bicycle quantity of all bordering supply sub-partitions does not meet the shared bicycle demand quantity of the demand sub-partition, the scheduling method further comprises:

[0017] merging the demand sub-partition and all bordering supply sub-partitions into a secondary sub-partition;

[0018] taking the secondary sub-partition as a secondary demand sub-partition, finding a target supply sub-partition from supply sub-partitions bordering the secondary demand sub-partition, if the schedulable shared bicycle quantity of all target supply sub-partitions does not meet the shared bicycle demand quantity of the demand sub-partition, merging the current secondary demand sub-partition and all bordering supply sub-partitions into a new secondary sub-partition, and re-finding the target supply sub-partition until the schedulable shared bicycle quantity meets the shared bicycle demand quantity of the demand sub-partition.

[0019] In an optional embodiment, the scheduling method further comprises:

[0020] A sub-partition with the largest number of shared bicycle demand is taken as a center sub-partition, and a sub-partition with the smallest number of shared bicycle demand is taken as a divergence sub-partition, a center point connecting the center sub-partition and the divergence sub-partition is formed as a scheduling axis;

[0021] A first scheduling direction of each sub-partition is set as a direction along the scheduling axis, and a second scheduling direction is set as a direction perpendicular to the scheduling axis;

[0022] For each sub-partition, a first scheduling is performed, the first scheduling includes scheduling shared bicycles of adjacent sub-partitions in the first scheduling direction, if the number of shared bicycles in the sub-partition after the first scheduling does not reach the number of shared bicycle demand of the demand sub-partition, a second scheduling is performed, the second scheduling includes scheduling shared bicycles of adjacent sub-partitions in the second scheduling direction.

[0023] In an optional embodiment, the scheduling method further includes:

[0024] User riding destination sub-partition data and riding initial sub-partition data in historical data are acquired;

[0025] According to the user riding destination sub-partition data and the riding initial sub-partition data, a migration path of most users is found, and the destination sub-partition and the initial sub-partition are bound according to the migration path of most users to form a binding relationship;

[0026] According to the number of sub-partitions involved in the migration path corresponding to the binding relationship, a scheduling number of the destination sub-partition to the initial sub-partition is configured;

[0027] According to the scheduling number of the destination sub-partition to the initial sub-partition, in combination with the scheduling shared bicycle number of each sub-partition in each to-be-scheduled region and the scheduling target sub-partition, a scheduling number of the remaining sub-partition is determined;

[0028] Shared bicycle scheduling is performed according to the scheduling number of each sub-partition.

[0029] In an optional embodiment, according to the number of sub-partitions involved in the migration path corresponding to the binding relationship, the scheduling number of the destination sub-partition to the initial sub-partition is configured, including:

[0030] If the number of involved sub-partitions is greater than a first set threshold, and the number of shared bicycle demand of the destination sub-partition decreases in a next time period adjacent to a current time period, the scheduling number of the destination sub-partition to the initial sub-partition is configured as a first number, the first number is a product of the number of shared bicycle demand and a first coefficient;

[0031] If the number of sub-partitions involved is greater than the first set threshold, and the demand for shared bicycles in the target sub-partition increases or remains unchanged in the next time period adjacent to the current time period, the number of bikes to be dispatched from the target sub-partition to the initial sub-partition is configured as the second number, which is the product of the demand for shared bicycles and the second coefficient.

[0032] If the number of sub-partitions involved is less than a first set threshold, the number of times the destination sub-partition is scheduled to the initial sub-partition is configured as a third number, which is the product of the number of shared bicycles required and a third coefficient; wherein, the first coefficient is less than the second coefficient, and the second coefficient is less than the third coefficient.

[0033] In an optional embodiment, the shared bicycle scheduling method further includes:

[0034] If the demand for shared bicycles in a sub-partition is lower than the set demand threshold in the current time period, the sub-partition will be temporarily assigned to an adjacent sub-partition.

[0035] The method of scheduling shared bicycles in each sub-partition based on the number of shared bicycles to be scheduled in each sub-partition of each area to be scheduled and the target sub-partition for scheduling specifically includes: scheduling shared bicycles in each sub-partition based on the reconfigured sub-partitions, according to the number of shared bicycles to be scheduled in each sub-partition of each area to be scheduled and the target sub-partition for scheduling.

[0036] In an optional embodiment, temporarily dividing the sub-partition into adjacent sub-partitions includes:

[0037] Select the sub-partition with the largest difference between the number of shared bicycles and the demand for shared bicycles from the adjacent sub-partitions, and use it as a temporary merged sub-partition. Sub-partitions with a demand for shared bicycles that is lower than a set demand threshold are assigned to the temporary merged sub-partition to form a new sub-partition.

[0038] Secondly, embodiments of this application provide a shared bicycle dispatching system, the shared bicycle dispatching system comprising:

[0039] The acquisition module obtains the current system time information and the number of shared bicycles in each sub-partition of the area to be scheduled;

[0040] The determination module determines the number of shared bicycles to be dispatched and the target sub-partition for dispatching in each sub-partition of the area to be dispatched, based on the current system time information.

[0041] The scheduling module schedules shared bicycles in each sub-region based on the number of shared bicycles to be scheduled in each sub-region within each region to be scheduled and the target sub-region.

[0042] Thirdly, embodiments of this application provide a terminal device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described above.

[0043] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described above.

[0044] The beneficial effects of this application are:

[0045] This application provides a real-time intelligent scheduling method and system for shared bicycles. Under normal circumstances, the demand for shared bicycles is obtained based on historical data. Within the shared bicycle operation area, key and hot spots for bicycle parking are monitored in real time. Based on the maximum threshold for the number of vehicles parked in the area (the maximum load that can be carried), and the real-time number of parked vehicles, the system coordinates the scheduling of shared bicycles according to the current number and demand, thereby achieving dynamic automatic scheduling. This solves the defects of redundancy and uneven distribution of scheduling resources caused by the current need for manual scheduling based on experience. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating the steps of a shared bicycle scheduling method according to an embodiment of this application;

[0048] Figure 2 This is one of the scenario diagrams illustrating a shared bicycle scheduling method provided in an embodiment of this application;

[0049] Figure 3 This is a second scenario illustration of a shared bicycle scheduling method provided in an embodiment of this application;

[0050] Figure 4 This is a schematic diagram of the structure of the shared bicycle dispatching system provided in the embodiments of this application;

[0051] Figure 5 This is a schematic diagram of the structure of the terminal device provided in the embodiments of this application.

[0052] Figure label:

[0053] 1 - Sub-partition; 11, 12, 13 - Sub-partitions adjacent to sub-partition 11; 21 - Sub-partition to be scheduled; 22 - Target sub-partition for scheduling; 20 - Scheduling direction; 23 and 21 are both sub-partitions adjacent to sub-partition 22; 31 - First scheduling direction. Detailed Implementation

[0054] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0055] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0056] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0057] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0058] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0059] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0060] In a first aspect, embodiments of this application provide a method for scheduling shared bicycles, the method comprising:

[0061] S1: Obtain the current system time information and the number of shared bicycles parked in each sub-zone of the area to be scheduled;

[0062] S2: Based on the current system time information, determine the number of shared bicycles to be dispatched and the target sub-partition for dispatching in each sub-partition of the area to be dispatched;

[0063] S3: Based on the number of shared bikes to be dispatched in each sub-region of each area to be dispatched and the target sub-region, dispatch the shared bikes in each sub-region.

[0064] This application provides a real-time intelligent scheduling method and system for shared bicycles. Generally, the demand for shared bicycles is based on historical data. Within the shared bicycle operating area, key and hotspot areas for bicycle parking are monitored in real time. Based on the maximum parking threshold (maximum load capacity) set for each area, and the real-time parking situation, combined with the current number of shared bicycles and the demand, a unified scheduling system is implemented to achieve dynamic intelligent scheduling. This solves the shortcomings of current shared bicycle scheduling methods that rely on manual experience, resulting in redundant and uneven distribution of scheduling resources.

[0065] The embodiments of this application will be described in detail below.

[0066] In this embodiment of the application, the current system time information is the time of the server system's internal timer. Generally, the time of the server system's internal timer is synchronized with world time, but this application does not impose any restrictions on this.

[0067] In the scenario of this application, the area to be scheduled includes multiple sub-partitions. The size of each sub-partition can be the same or different. Specifically, the configuration of the sub-partitions can be based on geographical location, such as configuring sub-partitions according to geographical locations such as residential areas and subway stations.

[0068] Currently, the dispatching of shared bicycles is almost entirely done manually, relying on experience to move them from residential areas to subway stations, or vice versa. This application can obtain the number of shared bicycles that need to be dispatched and the target sub-regions for dispatching in each time period based on historical data.

[0069] Specifically, this application provides a method for shared bicycle scheduling based on a lookup table generated from historical data. In this embodiment, the number of shared bicycles to be scheduled and the target sub-partition to be scheduled are determined according to the current system time information. Figure 1 As shown, it includes:

[0070] S21: Based on the current system time information, find the corresponding time and the number of shared bicycles required for each sub-partition in the lookup table. The lookup table is different for each time period.

[0071] S22: Determine the number of shared bicycles to be dispatched and the target sub-region to be dispatched in each sub-region of the area to be dispatched based on the lookup table found.

[0072] Specifically, the lookup table in this application is a table showing the correspondence between the time period and the number of shared bicycles required in each sub-region. This lookup table can be obtained through pre-calibration, for example, by retrieving the number of shared bicycles in the current sub-region through the system, configuring sufficient shared bicycles in that sub-region, and counting the decrease or increase in the number of shared bicycles within a time period to determine the number of shared bicycles required in that time period, i.e., the minimum number of shared bicycles that need to be configured. In this way, the number of shared bicycles required in each time period can be obtained, thus generating the lookup table in this application. It can be seen that each time period in this application corresponds to a lookup table, and one lookup table corresponds to one time period. Each lookup table includes the number of shared bicycles required in each sub-region within the corresponding time period, so the number of shared bicycles required in each sub-region for each time period can be queried.

[0073] Based on the current system time, this application embodiment obtains the number of shared bicycles required for each sub-partition by looking up a lookup table. Then, based on the number of shared bicycles required and the actual number of shared bicycles in the current sub-partition, the total number of shared bicycles to be scheduled for each sub-partition and the target sub-partition to be scheduled are obtained.

[0074] The following is a detailed description of step S22 of this application. In the embodiments of this application, step S22, namely, determining the number of shared bicycles to be dispatched and the target sub-region of the dispatch area based on the found lookup table, includes:

[0075] S221: For each sub-partition, determine the supply and demand identity of the sub-partition based on the current number of shared bicycles and the demand for shared bicycles. The supply and demand identity includes supply sub-partitions and demand sub-partitions.

[0076] S222: For each demand sub-partition, find the target supply sub-partition from the supply sub-partitions adjacent to the demand sub-partition, wherein the target supply sub-partition is the supply sub-partition with the fewest adjacent sub-partitions.

[0077] S223: Based on the current number of shared bicycles and the demand for shared bicycles in the target supply sub-partition, and the corresponding number of shared bicycles and the demand for shared bicycles in the demand sub-partition, determine whether the number of schedulable shared bicycles in the target supply sub-partition meets the demand for shared bicycles in the demand sub-partition. If not, search for the target supply sub-partition in the remaining supply sub-partitions until the number of schedulable shared bicycles in all current target supply sub-partitions reaches the demand for shared bicycles in the demand sub-partition, or until all adjacent supply sub-partitions are traversed.

[0078] S224: Output the number of schedules for each supply sub-partition and demand sub-partition.

[0079] Specifically, in step S221, the supply and demand status of each sub-partition is first determined based on the current number of shared bicycles and the demand for shared bicycles. This supply and demand status determines the sub-partition's "supply and demand" of shared bicycles, that is, whether the sub-partition dispatches shared bicycles to other sub-partitions or borrows shared bicycles from other sub-partitions. Generally, the current number of shared bicycles can be directly subtracted from the demand for shared bicycles. If the result is positive, it is considered a supply sub-partition; if the result is negative, it is considered a demand sub-partition.

[0080] In step S222, firstly, the sub-partitions that are demand sub-partitions are identified. Then, using the demand sub-partition as the center, the supply sub-partitions among all the sub-partitions adjacent to it are searched. It should be understood that not all adjacent supply sub-partitions will supply shared bicycles to the demand sub-partition. In this embodiment, for this detailed scheduling, with the goal of minimizing scheduling cost or scheduling range, the supply sub-partition with the fewest adjacent sub-partitions is selected as the target supply sub-partition. That is, the target supply sub-partition is bound to the demand sub-partition. For example, if the sub-partitions adjacent to partition A include B, C, D, E, and F, while B, C, and D are adjacent to partitions A and B, C, and D are adjacent to partitions B and F, then the demand sub-partition will supply the demand sub-partition. If D in DEF has the fewest adjacent sub-partitions (e.g., three), and BCEF has more than three adjacent sub-partitions, then D is selected as the target supply sub-partition for partition A. In this way, each demand sub-partition is bound to a target supply sub-partition with the highest priority. Since this target supply sub-partition has the fewest adjacent sub-partitions, the probability of it supplying other sub-partitions is smaller, making it easier to clearly define the binding relationship of each sub-partition. This ensures that when adding demand sub-partitions later, the impact on the overall scheduling architecture is minimized, and adjustments to the overall scheduling architecture are easier when necessary.

[0081] Subsequently, this embodiment of the application performs an iterative operation to determine whether the number of shared bicycles that can be scheduled in the target supply sub-partition meets the number of shared bicycles required by the demand sub-partition. If not, in addition to the target supply sub-partition that is prioritized for scheduling, the number of shared bicycles to be scheduled also needs to be added from other sub-partitions to ensure the demand of the demand sub-partition.

[0082] Subsequently, if the number of schedulable shared bicycles in all adjacent supply sub-regions does not reach the number of shared bicycles required by the demand sub-region, and there are no other adjacent supply sub-regions at this time, the scheduling method further includes:

[0083] S224: Merge the aforementioned demand sub-region and all adjacent supply sub-regions into a second-level sub-region;

[0084] S225: The secondary sub-partition is used as the secondary demand sub-partition. The target supply sub-partition is searched from the supply sub-partitions adjacent to the secondary demand sub-partition. If the number of schedulable shared bicycles in all current target supply sub-partitions does not reach the number of shared bicycles required by the demand sub-partition, the current secondary demand sub-partition is merged with all adjacent supply sub-partitions to form a new secondary sub-partition. The target supply sub-partition is searched again until the number of schedulable shared bicycles reaches the number of shared bicycles required by the demand sub-partition.

[0085] In this embodiment, if the supply volume of all adjacent supply sub-regions is less than that of the supply sub-regions, the current demand sub-region and all adjacent supply sub-regions are combined to form a secondary sub-region. This secondary sub-region is used as a replacement for the current demand sub-region, thereby expanding the entire scheduling scope with the demand sub-region as the atomic center. In this way, the entire scheduling is based on each demand sub-region as the atomic center, forming a "local" priority matching scheduling strategy through free diffusion. This ensures that the scheduling cost and speed of each sub-region are at the optimal level. Through the local priority scheduling strategy, the whole can automatically achieve optimal scheduling.

[0086] For example, such as Figure 2 As shown, Figure 2 This is a schematic diagram of the sub-partitions of the area to be scheduled based on the concept of this application. It should be understood that the division of sub-partitions in this application is merely illustrative, intended to show that the shape and size of the sub-partitions are not limited to a fixed value, but can be rationally configured according to actual conditions or geographical information. This application does not impose any restrictions on this. Figure 2 In the illustrated embodiment, it can be seen that the adjacent sub-partitions of sub-partition 1 are 11, 12 and 13. Sub-partition 21 is scheduled to sub-partition 22 through scheduling direction 20, so 21 is the supply sub-partition and 22 is the demand sub-partition. At this time, the supply sub-partition 21 is selected from the adjacent sub-partitions 21, 23 and 13 of the demand sub-partition 22. The selection logic is as shown in the above embodiment, and will not be repeated here.

[0087] Furthermore, based on the core idea of ​​the "local" priority scheduling strategy, this application further provides a parallel scheme. While the "local" priority scheduling strategy in the above embodiments is based on "local surface" scheduling formed by adjacent sub-partitions, this embodiment can further provide a scheme based on "local linear" scheduling. Specifically, the scheduling method further includes:

[0088] S41: Take the sub-partition with the highest current demand for shared bicycles as the central sub-partition, and the sub-partition with the lowest current demand for shared bicycles as the divergent sub-partition. Connect the center points of the central sub-partition and the divergent sub-partition to form a scheduling axis.

[0089] S42: Set the first scheduling direction of each sub-partition to be along the scheduling axis, and the second scheduling direction to be perpendicular to the scheduling axis;

[0090] S43: For each sub-partition, perform a first scheduling, which includes scheduling shared bicycles in sub-partitions adjacent to each other in the first scheduling direction. If the number of shared bicycles in the sub-partition after the first scheduling does not reach the number of shared bicycles required by the required sub-partition, perform a second scheduling, which includes scheduling shared bicycles in sub-partitions adjacent to each other in the second scheduling direction.

[0091] In this embodiment, in step S41, the sub-partition with the highest demand for shared bicycles is first defined as the "central sub-partition," and the sub-partition with the lowest demand for shared bicycles is defined as the "divergent sub-partition." In this way, the line connecting the "central sub-partition" and the "divergent sub-partition" can be used as the overall scheduling optimization direction. At this point, after the overall scheduling optimization direction is determined, by setting scheduling strategies along the scheduling axis and perpendicular to the scheduling axis, "local" priority scheduling can be formed in the direction of this line. In this way, the scheduling is limited to linear scheduling along the scheduling axis and perpendicular to the scheduling axis, thereby ensuring that the scheduling cost and scheduling speed of each sub-partition are at the optimal level. Through the local priority scheduling strategy, the whole can automatically achieve optimal scheduling.

[0092] Specifically, such as Figure 3 As shown in the embodiment of this application, sub-partition 32 is the central sub-partition and sub-partition 33 is the divergent sub-partition. At this time, the first scheduling direction 31 is the scheduling direction of linear local priority, and the second scheduling direction is configured perpendicular to the first scheduling direction 31. This application will not elaborate on this.

[0093] Based on the description of the two embodiments above, in the preferred embodiment of this application, other scheduling strategies can be further combined. Specifically, the scheduling method further includes:

[0094] S01: Retrieve user cycling destination sub-partition data and cycling initial sub-partition data from historical data;

[0095] S02: Based on the user's destination sub-partition data and initial sub-partition data, find the migration path of the majority of users, and bind the destination sub-partition and the initial sub-partition according to the migration path of the majority of users to form a binding relationship;

[0096] S03: Configure the number of times the destination sub-partition is scheduled to the initial sub-partition based on the number of sub-partitions involved in the migration path corresponding to the binding relationship;

[0097] S04: Based on the number of bikes scheduled from the destination sub-partition to the initial sub-partition, and combined with the number of shared bikes scheduled in each sub-partition within each area to be scheduled and the target sub-partition, determine the number of bikes scheduled in the remaining sub-partitions.

[0098] S05: Dispatch shared bicycles based on the number of bicycles to be dispatched in each sub-partition.

[0099] It should be noted that, in the embodiments of this application, the user's riding destination sub-region data and riding initial sub-region data in the historical data can be obtained by statistically analyzing the user's riding destination and starting point. This application does not impose any restrictions on this. At the same time, the historical data is collected by the user actively reporting when using shared bicycles, which will not be elaborated upon in this application.

[0100] In this embodiment, the consistency of user group behavior is further considered. Scheduling can be based on users' historical ride data. Specifically, for example, when a user rides back and forth between the K community group point and the J subway point, the sub-district where K community and J subway point are located should be the most needed for scheduling. At this time, by finding the migration path of the majority of users, the destination sub-district and the initial sub-district are bound according to the migration path of the majority of users, forming a binding relationship. In this way, the binding relationship is based on the relationship of real direct demand. Then, according to the number of sub-districts involved in the migration path corresponding to the binding relationship, the number of scheduling from the destination sub-district to the initial sub-district is configured. That is, the more sub-districts involved in the migration path, the less the number of scheduling from the destination sub-district to the initial sub-district, and vice versa. This is combined with the local priority scheduling strategy of the two embodiments mentioned above to finally form a scheduling scheme.

[0101] For example, if the number of sub-partitions involved in the corresponding migration path is 10, which the system defines as a large number, the cost of scheduling to the destination sub-partition is higher. In this case, the number of scheduling from the destination sub-partition to the initial sub-partition can be dynamically reduced, for example, by reducing the number of scheduling to 10% of the total number of scheduling. At this time, the remaining 90% of the scheduling needs to be completed in coordination with the scheduling of other sub-partitions. Meanwhile, the remaining 90% of the scheduling is configured according to the two local priority implementations mentioned above, thereby achieving overall coordinated scheduling. In this way, by adjusting the two schemes for dynamic scheduling, the consistency of the user group can be fully considered while ensuring local priority, and the influence of the distance from the destination sub-partition to the initial sub-partition can be eliminated by adjusting the weights.

[0102] Furthermore, in an optional embodiment of this application, configuring the number of scheduling sub-partitions from the destination sub-partition to the initial sub-partition based on the number of sub-partitions involved in the migration path corresponding to the binding relationship includes:

[0103] S031: If the number of sub-partitions involved is greater than the first set threshold, and the demand for shared bicycles in the target sub-partition decreases in the next time period adjacent to the current time period, configure the scheduling quantity from the target sub-partition to the initial sub-partition as the first quantity, where the first quantity is the product of the demand for shared bicycles and the first coefficient.

[0104] S032: If the number of sub-partitions involved is greater than the first set threshold, and the demand for shared bicycles in the target sub-partition increases or remains unchanged in the next time period adjacent to the current time period, configure the scheduling quantity from the target sub-partition to the initial sub-partition as a second quantity, where the second quantity is the product of the demand for shared bicycles and a second coefficient.

[0105] S033: If the number of sub-partitions involved is less than the first set threshold, configure the scheduling quantity of the destination sub-partition to the initial sub-partition as a third quantity, wherein the third quantity is the product of the demand quantity of shared bicycles and a third coefficient; wherein the first coefficient is less than the second coefficient, and the second coefficient is less than the third coefficient.

[0106] In this embodiment, furthermore, multiple different weight coefficients can be set, so that when there are many sub-partitions on the migration path, the strategy of prioritizing local scheduling is the main approach, while considering user group consistency factors is secondary. When there are few sub-partitions, the strategy of prioritizing local scheduling is secondary, while considering user group consistency factors is the main approach, thereby achieving the optimal overall scheduling effect.

[0107] Furthermore, in this embodiment, for some persistent sub-partitions, there may be insufficient users to participate in scheduling. However, in some scenarios, although the sub-partition does not need to schedule shared bicycles, it can be "lent" to other sub-partitions for scheduling through other means. In this case, the sub-partition can be temporarily assigned to other sub-partitions and become part of those sub-partitions to jointly schedule shared bicycles. In this way, inactive sub-partitions can be reused for use by other sub-partitions. In this embodiment, the shared bicycle scheduling method further includes:

[0108] S001: If the demand for shared bicycles in a sub-partition during the current time period is lower than the set demand threshold, the sub-partition will be temporarily assigned to an adjacent sub-partition.

[0109] The method of scheduling shared bicycles in each sub-partition based on the number of shared bicycles to be scheduled in each sub-partition of each area to be scheduled and the target sub-partition for scheduling specifically includes: scheduling shared bicycles in each sub-partition based on the reconfigured sub-partitions, according to the number of shared bicycles to be scheduled in each sub-partition of each area to be scheduled and the target sub-partition for scheduling.

[0110] In this way, for sub-partitions that do not need to be scheduled for a long time, they can be temporarily merged with surrounding sub-partitions to form new sub-partitions. When the new sub-partitions are scheduled, they are essentially temporarily borrowing the sub-partitions that do not need to be scheduled for a long time. This can create a buffer between some sub-partitions with long scheduling lengths in the overall scheduling optimization, forming a stable buffer zone for the overall scheduling.

[0111] Furthermore, this application provides a scheme for temporarily dividing the sub-partition into adjacent sub-partitions, specifically including:

[0112] Select the sub-partition with the largest difference between the number of shared bicycles and the demand for shared bicycles from the adjacent sub-partitions, and use it as a temporary merged sub-partition. Sub-partitions with a demand for shared bicycles that is lower than a set demand threshold are assigned to the temporary merged sub-partition to form a new sub-partition.

[0113] In this embodiment, the merged sub-partition is the one with the largest difference between the number of shared bicycles and the demand for shared bicycles. This sub-partition is equivalent to the one that is scheduled the most and requires the most scheduling in the whole. After merging to form a temporary merged sub-partition, the number of its adjacent sub-partitions or the number of sub-partitions along the first and second scheduling directions increases exponentially, thereby optimizing the local unevenness caused by local priority scheduling. In particular, for the sub-partition with the largest difference between the number of shared bicycles and the demand for shared bicycles, the local priority scheduling strategy can easily lead to a more complex scheduling strategy in this area. However, after absorbing a sub-partition, its "local" scheduling range expands, reducing the complex impact of the local priority strategy in this area and making the overall optimization more uniform.

[0114] It should be understood that the schematic diagrams in this application are for illustrative purposes only, and their shapes and sizes are not intended to limit the sub-partitions. It should be understood that the shapes of the sub-partitions in the embodiments of this application are generally irregular closed shapes, which will not be elaborated upon in this application.

[0115] Secondly, embodiments of this application provide a shared bicycle dispatching system, such as... Figure 4 As shown, the shared bicycle dispatching system includes:

[0116] Module 100 obtains the current system time information and the number of shared bicycles in each sub-partition of the area to be scheduled;

[0117] The determination module 200 determines the number of shared bicycles to be scheduled and the target sub-partition to be scheduled in each sub-partition of the area to be scheduled, based on the current system time information.

[0118] The scheduling module 300 schedules shared bicycles in each sub-region based on the number of shared bicycles to be scheduled in each sub-region within each region to be scheduled and the target sub-region.

[0119] This application provides a shared bicycle scheduling system that divides the entire scheduling area into zones and then coordinates the scheduling based on the current number of shared bicycles and the demand. The demand for shared bicycles is based on historical data, thereby achieving dynamic automatic scheduling. This solves the problem of redundant and uneven scheduling resources caused by the current need for manual scheduling based on experience.

[0120] Figure 5 This application provides a schematic diagram of the structure of a terminal device 400. The terminal device 400 includes: at least one processor 401. Figure 5 The diagram shows only one processor, a memory 402, and a computer program 403 stored in the memory 402 and executable on the at least one processor 401, which, when executed by the processor 401, performs the steps in the above method embodiments.

[0121] The terminal device 400 may be a desktop computer, laptop, handheld computer, or cloud server, etc. This terminal device may include, but is not limited to, a processor 401 and a memory 402. Those skilled in the art will understand that... Figure 5 This is merely an example of terminal device 400 and does not constitute a limitation on terminal device 400. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0122] The processor 401 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0123] In some embodiments, the memory 402 may be an internal storage unit of the terminal device 400, such as a hard disk or memory of the terminal device 400. In other embodiments, the memory 402 may be an external storage device of the terminal device 400, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 400. Further, the memory 402 may include both internal and external storage units of the terminal device 400. The memory 402 is used to store the operating system, applications, boot loader, data, and other programs, such as the program code of the computer program. The memory 402 can also be used to temporarily store data that has been output or will be output.

[0124] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0125] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps in the above-described method embodiments.

[0126] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the above-described method embodiments.

[0127] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0128] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0129] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0130] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0131] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0132] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for scheduling shared bicycles, characterized in that, The method for dispatching shared bicycles includes: Obtain the current system time information and the number of shared bicycles parked in each sub-zone of the area to be scheduled; Based on the current system time information, determine the number of shared bicycles to be dispatched in each sub-partition of the area to be dispatched and the target sub-partition for dispatching; Based on the number of shared bikes to be dispatched in each sub-region of each area to be dispatched and the target sub-region, the shared bikes in each sub-region are dispatched. The scheduling method further includes: using the sub-region with the highest current demand for shared bicycles as the central sub-region, and the sub-region with the lowest current demand for shared bicycles as the diverging sub-region; connecting the center points of the central sub-region and the diverging sub-regions to form a scheduling axis; setting a first scheduling direction for each sub-region as along the scheduling axis, and a second scheduling direction as perpendicular to the scheduling axis; for each sub-region, performing a first scheduling, which includes scheduling shared bicycles in sub-regions adjacent to the first scheduling direction; if the number of shared bicycles in the sub-region after the first scheduling does not reach the demand for shared bicycles in the demanding sub-region, performing a second scheduling, which includes scheduling shared bicycles in sub-regions adjacent to the second scheduling direction; or... The scheduling method further includes: The step of determining the number of shared bicycles to be dispatched and the target sub-partition for dispatching in each sub-partition of the area to be dispatched based on the current system time information includes: looking up a table corresponding to the time of each time period and the number of shared bicycles parked and the demand for each sub-partition, with each time period having a different table; and determining the number of shared bicycles to be dispatched and the target sub-partition for dispatching in each sub-partition of the area to be dispatched based on the found table. The step of determining the number of shared bicycles to be dispatched and the target sub-partitions for dispatching each sub-partition within the area to be dispatched based on the lookup table includes: for each sub-partition, determining the supply and demand status of the sub-partition based on the current number of shared bicycles parked and the number of shared bicycles demanded, wherein the supply and demand status includes supply sub-partitions and demand sub-partitions; for each demand sub-partition, searching for a target supply sub-partition from the supply sub-partitions adjacent to the demand sub-partition, wherein the target supply sub-partition is the supply sub-partition with the fewest adjacent sub-partitions; based on the current number of shared bicycles parked and the number of shared bicycles demanded in the target supply sub-partition, and the corresponding number of shared bicycles parked and the number of shared bicycles demanded in the demand sub-partition, determining whether the number of shared bicycles that can be dispatched in the target supply sub-partition meets the number of shared bicycles demanded in the demand sub-partition; if not, searching for a target supply sub-partition in the remaining supply sub-partitions until the number of shared bicycles that can be dispatched in all current target supply sub-partitions reaches the number of shared bicycles demanded in the demand sub-partition, or until all adjacent supply sub-partitions are traversed; and outputting the dispatch quantity for each supply sub-partition and demand sub-partition. If the number of dispatchable shared bicycles in all adjacent supply sub-regions does not reach the number of shared bicycles required by the demand sub-region, the demand sub-region and all adjacent supply sub-regions are merged into a second-level sub-region. The second-level sub-region is then used as a second-level demand sub-region. A target supply sub-region is searched among the supply sub-regions adjacent to the second-level demand sub-region. If the number of dispatchable shared bicycles in all current target supply sub-regions does not reach the number of shared bicycles required by the demand sub-region, the current second-level demand sub-region is merged with all adjacent supply sub-regions into a new second-level sub-region, and the target supply sub-region is searched again until the number of dispatchable shared bicycles reaches the number of shared bicycles required by the demand sub-region.

2. The method for scheduling shared bicycles according to claim 1, characterized in that, The scheduling method further includes: Retrieve user cycling destination sub-partition data and cycling initial sub-partition data from historical data; Based on the user's destination sub-partition data and initial sub-partition data, find the migration path of the majority of users, and bind the destination sub-partition and the initial sub-partition according to the migration path of the majority of users to form a binding relationship; Configure the number of times the destination sub-partition is scheduled to the initial sub-partition based on the number of sub-partitions involved in the migration path corresponding to the binding relationship; Based on the number of bikes scheduled from the target sub-partition to the initial sub-partition, and combined with the number of shared bikes scheduled in each sub-partition within each area to be scheduled and the target sub-partition, the number of bikes scheduled in the remaining sub-partitions is determined. Shared bikes are scheduled based on the number of bikes to be dispatched in each sub-zone.

3. The method for scheduling shared bicycles according to claim 2, characterized in that, Based on the number of sub-partitions involved in the migration path corresponding to the binding relationship, configure the number of scheduling requests from the destination sub-partition to the initial sub-partition, including: If the number of sub-partitions involved is greater than the first set threshold, and the demand for shared bicycles in the target sub-partition decreases in the next time period adjacent to the current time period, the number of times the target sub-partition is scheduled to the initial sub-partition is configured as the first number, where the first number is the product of the demand for shared bicycles and the first coefficient. If the number of sub-partitions involved is greater than the first set threshold, and the demand for shared bicycles in the target sub-partition increases or remains unchanged in the next time period adjacent to the current time period, the number of bikes to be dispatched from the target sub-partition to the initial sub-partition is configured as the second number, which is the product of the demand for shared bicycles and the second coefficient. If the number of sub-partitions involved is less than a first set threshold, the number of times the destination sub-partition is scheduled to the initial sub-partition is configured as a third number, which is the product of the number of shared bicycles required and a third coefficient; wherein, the first coefficient is less than the second coefficient, and the second coefficient is less than the third coefficient.

4. The method for scheduling shared bicycles according to claim 2, characterized in that, The shared bicycle dispatching method also includes: If the demand for shared bicycles in a sub-partition is lower than the set demand threshold in the current time period, the sub-partition will be temporarily assigned to an adjacent sub-partition. The method of scheduling shared bicycles in each sub-partition based on the number of shared bicycles to be scheduled in each sub-partition of each area to be scheduled and the target sub-partition for scheduling specifically includes: scheduling shared bicycles in each sub-partition based on the reconfigured sub-partitions, according to the number of shared bicycles to be scheduled in each sub-partition of each area to be scheduled and the target sub-partition for scheduling.

5. The method for scheduling shared bicycles according to claim 4, characterized in that, The step of temporarily dividing the sub-partition into adjacent sub-partitions includes: Select the sub-partition with the largest difference between the number of shared bicycles and the demand for shared bicycles from the adjacent sub-partitions, and use it as a temporary merged sub-partition. Sub-partitions with a demand for shared bicycles that is lower than a set demand threshold are assigned to the temporary merged sub-partition to form a new sub-partition.

6. A dispatching system for shared bicycles, characterized in that, The shared bicycle dispatch system includes: The acquisition module obtains the current system time information and the number of shared bicycles parked in each sub-zone of the area to be scheduled; The determination module determines the number of shared bicycles to be dispatched and the target sub-partition for dispatching in each sub-partition of the area to be dispatched, based on the current system time information. The scheduling module schedules shared bicycles in each sub-region based on the number of shared bicycles to be scheduled in each sub-region within each region to be scheduled and the target sub-region. The shared bicycle scheduling system further uses the sub-region with the highest current demand for shared bicycles as the central sub-region and the sub-region with the lowest current demand as the diverging sub-regions. A scheduling axis is formed by connecting the center points of the central and diverging sub-regions. A first scheduling direction for each sub-region is defined as along the scheduling axis, and a second scheduling direction is defined as perpendicular to the scheduling axis. For each sub-region, a first scheduling operation is performed, which includes scheduling shared bicycles in sub-regions adjacent to the first scheduling direction. If, after the first scheduling, the number of shared bicycles in the sub-region does not reach the demand for shared bicycles in the required sub-region, a second scheduling operation is performed, which includes scheduling shared bicycles in sub-regions adjacent to the second scheduling direction. Alternatively... The shared bicycle dispatching system is further configured to, when determining the number of shared bicycles to be dispatched in each sub-region of the area to be dispatched and the target sub-region based on the current system time information, look up a reference table corresponding to the time period and the number of shared bicycles parked and the demand in each sub-region, with each time period having a different reference table; determine the number of shared bicycles to be dispatched in each sub-region of the area to be dispatched and the target sub-region based on the found reference table; when determining the number of shared bicycles to be dispatched in each sub-region of the area to be dispatched and the target sub-region based on the found reference table, for each sub-region, determine the supply and demand status of the sub-region based on the current number of shared bicycles parked and the demand in each sub-region, the supply and demand status including supply sub-regions and demand sub-regions; for each demand sub-region, find the target supply sub-region from the supply sub-regions adjacent to the demand sub-region, the target supply sub-region being the supply sub-region with the fewest adjacent sub-regions; and based on the current number of shared bicycles parked and the demand in the target supply sub-region, and the corresponding number of shared bicycles parked and the demand in the demand sub-region. The process involves determining whether the number of schedulable shared bicycles in the target supply sub-partition meets the shared bicycle demand of the demand sub-partition. If not, it searches for target supply sub-partitions among the remaining supply sub-partitions until the number of schedulable shared bicycles in all current target supply sub-partitions reaches the shared bicycle demand of the demand sub-partition, or until all adjacent supply sub-partitions are traversed. The process outputs the schedulable number for each supply sub-partition and demand sub-partition. If the number of schedulable shared bicycles in all adjacent supply sub-partitions does not reach the shared bicycle demand of the demand sub-partition, the demand sub-partition is reset. The sub-region and all adjacent supply sub-regions are merged into a second-level sub-region. The second-level sub-region is then used as a second-level demand sub-region. The target supply sub-region is searched from the supply sub-regions adjacent to the second-level demand sub-region. If the number of schedulable shared bicycles in all current target supply sub-regions does not reach the number of shared bicycles required by the demand sub-region, the current second-level demand sub-region is merged with all adjacent supply sub-regions into a new second-level sub-region. The target supply sub-region is then searched again until the number of schedulable shared bicycles reaches the number of shared bicycles required by the demand sub-region.

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