Shared bicycle dispatching method based on data fusion and dynamic resource optimization

Abstract

The application provides a shared bicycle dispatching method based on data fusion and dynamic resource optimization, relates to the technical field of data processing, and fuses first position data of a bicycle itself and second position data collected by an environment to obtain fusion position data of each station; generates a dynamic capacity baseline of each station based on historical data, a bicycle movement line and environmental parameters; determines a redundancy value of the station according to the fusion position data of each station and the capacity baseline; and generates shared bicycle dispatching information based on the redundancy value, the position of the station and the attributes of a dispatching device, so that the supply of bicycles can be accurately and efficiently dispatched according to multi-dimensional factors corresponding to different regions, and problems such as uneven distribution of shared bicycles and low dispatching efficiency are solved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a shared bicycle scheduling method based on data fusion and dynamic resource optimization. Background Technology

[0002] In the urban transportation sector, shared bicycles have become an important choice for citizens' short-distance travel due to their convenience and flexibility. Whether it is during the morning and evening rush hours on weekdays, shared bicycle stations near subway stations and office buildings, or parking areas near scenic spots and shopping districts on weekends, are crowded with users borrowing and returning bicycles. For example, during the commuting peak, office workers need to ride shared bicycles from residential areas to subway stations, resulting in a sharp decrease in the number of bicycles at residential stations, while bicycles pile up at stations near subway stations. During holidays, bicycles are in short supply at stations near popular attractions, while a large number of bicycles are idle at stations farther away from attractions. This imbalance between supply and demand makes scientific and efficient shared bicycle scheduling and management key to ensuring user experience and improving resource utilization.

[0003] However, existing shared bicycle dispatching methods have many shortcomings. In terms of dispatching strategy formulation, traditional methods are often based on fixed station capacity assumptions and do not fully consider the impact of dynamic factors such as weather, holidays, and time of day changes on bicycle demand. This leads to a disconnect between the set station capacity and actual demand. In the dispatching execution stage, there is a lack of accurate matching of supply and demand between stations. Either blind dispatching leads to resource waste, or the urgent needs of some stations cannot be met in time. Ultimately, some stations have long-term backlog of bicycles, while other stations have no bicycles available, which reduces the overall operational efficiency of shared bicycles.

[0004] Therefore, how to accurately and efficiently schedule the supply of shared bicycles based on multi-dimensional factors corresponding to different regions, and alleviate problems such as uneven distribution and low scheduling efficiency of shared bicycles, has become an urgent issue to be addressed. Summary of the Invention

[0005] This invention provides a shared bicycle scheduling method based on data fusion and dynamic resource optimization, which can accurately and efficiently schedule bicycle supply according to multi-dimensional factors corresponding to different regions, thereby alleviating problems such as uneven distribution of shared bicycles and low scheduling efficiency.

[0006] A first aspect of the present invention provides a shared bicycle scheduling method based on data fusion and dynamic resource optimization, comprising:

[0007] The first location data of the bicycle itself and the second location data collected from the environment are fused to obtain the fused location data of each station;

[0008] A dynamic capacity baseline for each station is generated based on historical data, bicycle routes, and environmental parameters.

[0009] The redundancy value of each site is determined based on the fused location data and capacity baseline of each site;

[0010] Shared bicycle dispatch information is generated based on redundancy values, station locations, and the attributes of dispatching equipment.

[0011] Optionally, in one possible implementation of the first aspect, the fusion of the first location data of the bicycle itself and the second location data collected from the environment to obtain fused location data for each station includes:

[0012] The first location information is obtained based on the positioning module of each bicycle, and the first location data is obtained by summarizing the first location information of all bicycles located in a station.

[0013] The number of vehicles per vehicle is extracted from the image data of the image acquisition device at each station to obtain the second location data;

[0014] The first location data and the second location data are fused to generate fused location data.

[0015] Optionally, in one possible implementation of the first aspect, the extraction of the number of vehicles from the image data of the image acquisition device at each station to obtain the second location data includes:

[0016] The image of each image acquisition unit in the image acquisition device is divided into normal areas and non-normal areas;

[0017] The first number is obtained by extracting the number of bicycles in the normal area, and the second number is obtained by extracting the number of bicycles in the illegal area.

[0018] Based on the positional correlation between image acquisition units, the first quantity and / or the second quantity are deduplicated, and the second position data is obtained based on the deduplicated first quantity and / or second quantity.

[0019] Optionally, in one possible implementation of the first aspect, the deduplication of the first and / or second quantities based on the positional association between image acquisition units, and the obtaining of the second position data based on the deduplicated first and / or second quantities, includes:

[0020] Based on the user's marking of the image acquisition units, the repeated acquisition areas of any number of image acquisition units are obtained, and the number of repetitions of a single vehicle within the repeated acquisition area is determined.

[0021] Obtain the priority labels of multiple image acquisition units corresponding to the repeated acquisition areas, retain the number of repetitions of the repeated acquisition areas with the highest priority label, and delete the number of repetitions of the repeated acquisition areas with non-highest priority labels from the first number or the second number.

[0022] Optionally, in one possible implementation of the first aspect, generating a dynamic capacity baseline for each station based on historical data, individual vehicle routes, and environmental parameters includes:

[0023] Obtain the merged location data of the station in different time periods from historical data, as well as the number of new and decreased bicycles in the corresponding time periods;

[0024] The corresponding vehicle difference is obtained based on the increase and decrease of the number of vehicles per vehicle. The vehicle difference includes positive and negative vehicle differences.

[0025] Based on the fused location data, single-vehicle difference, single-vehicle movement route, and environmental parameters, a dynamic capacity baseline is generated for each station.

[0026] Optionally, in one possible implementation of the first aspect, generating a dynamic capacity baseline for each station based on the fused location data, single-vehicle difference, single-vehicle movement route, and environmental parameters includes:

[0027] Multiply the first quantity by the first preset value to obtain the first base number, and multiply the second quantity by the second preset value to obtain the second base number, wherein the first preset value is greater than the second preset value;

[0028] The first base number and the second base number are added together to obtain the standard base number. The interval value of the standard base number is determined to obtain the reference capacity. Each base number interval has a preset reference capacity.

[0029] The expected increase in the number of bicycles on cycling routes with the station as the destination is obtained by extracting the number of bicycles within a preset distance in the corresponding historical time period.

[0030] A dynamic capacity baseline is generated for each site based on baseline capacity, expected increments, and environmental parameters.

[0031] Optionally, in one possible implementation of the first aspect, generating a dynamic capacity baseline for each site based on baseline capacity, expected increments, and environmental parameters includes:

[0032] The baseline capacity includes the maximum capacity and the minimum capacity;

[0033] Multiply the expected increment by a preset coefficient to obtain the standard increment, and subtract the minimum standard increment from the minimum capacity to obtain the minimum capacity baseline.

[0034] The environmental coefficient is determined based on the parameter range corresponding to the environmental parameter. Each environmental parameter has a preset environmental coefficient for its corresponding parameter range. The environmental coefficient is multiplied by the maximum capacity to obtain the capacity baseline of the maximum value.

[0035] Alternatively, in one possible implementation of the first aspect, the worse the environmental parameters, the larger the environmental coefficient.

[0036] Optionally, in one possible implementation of the first aspect, determining the redundancy value of a site based on the fused location data and capacity baseline of each site includes:

[0037] The total number of corresponding stations is obtained by summing the first and second quantities in the fused location data;

[0038] If the total quantity is less than the minimum capacity, the redundancy value is negative. The negative redundancy value is obtained by subtracting the total quantity from the median value of the capacity baseline.

[0039] If the total quantity is greater than the maximum capacity, the redundancy value is positive. The positive redundancy value is obtained by subtracting the total quantity from the median value of the maximum capacity.

[0040] Optionally, in one possible implementation of the first aspect, generating shared bicycle dispatch information based on redundancy values, station locations, and dispatch device attributes includes:

[0041] The station with a negative redundancy value is designated as the first station, and the station with a positive redundancy value within a preset range is designated as the second station.

[0042] The redundant station sequence is obtained by sorting all second stations in descending order based on the positive redundancy values.

[0043] Based on the redundancy value of the first station, the corresponding second station and scheduling equipment are determined in the redundant station sequence to generate shared bicycle scheduling information.

[0044] Optionally, in one possible implementation of the first aspect, determining the corresponding second station and scheduling device in the redundant station sequence based on the redundancy value of the first station, and generating shared bicycle scheduling information, includes:

[0045] If the absolute value of the redundancy of the first station is less than or equal to the absolute value of the redundancy of the first second station in the redundancy station sequence;

[0046] Then, the second station whose absolute value of redundancy is greater than or equal to that of the first station and whose absolute value of redundancy is closest to that of the first station is determined as the mutual scheduling station.

[0047] Based on the redundancy value of the first station, the scheduling equipment and the number of equipment with corresponding attributes are determined to obtain the shared bicycle scheduling information.

[0048] Optionally, in one possible implementation of the first aspect, it also includes:

[0049] If the absolute value of the redundancy of the first station is greater than the absolute value of the redundancy of the first second station in the redundancy station sequence;

[0050] After removing the first second station, the remaining second stations are sorted in ascending order to obtain an ascending sequence. The redundancy values ​​of the removed second stations are selected sequentially according to the ascending sequence and added to obtain a sum. If the absolute value of the sum is greater than or equal to the absolute value of the redundancy value of the first station, the corresponding multiple second stations are used as combined scheduling stations.

[0051] Based on the redundancy value of the first station, the scheduling equipment and the number of equipment with corresponding attributes are determined to obtain the shared bicycle scheduling information.

[0052] Optionally, in one possible implementation of the first aspect, obtaining shared bicycle scheduling information by determining the scheduling devices and their quantities based on the redundancy value of the first station includes:

[0053] All scheduling devices within a preset range of the first site are selected as the first scheduling device;

[0054] A scheduling direction is established from the second station toward the first station. The corresponding scheduling equipment is determined based on the redundancy value of the second station. Each type of scheduling equipment has a preset value range for its attributes.

[0055] If the value range of the scheduling device is less than the redundancy value of the second station, the number of devices is obtained by comparing the redundancy value with the maximum value of the value range.

[0056] A second aspect of the present invention provides a storage medium storing a computer program, which, when executed by a processor, is used to implement the method described in the first aspect of the present invention and various possible designs of the first aspect.

[0057] The beneficial effects of this invention are as follows:

[0058] 1. This invention can accurately and efficiently schedule bicycle supply based on multi-dimensional factors corresponding to different regions, alleviating problems such as uneven distribution and low scheduling efficiency of shared bicycles. First, this invention can fuse multi-source data to improve information accuracy. Specifically, by fusing the first location data from the bicycle's own positioning module with the second location data from the station camera image analysis, this invention significantly improves the accuracy of bicycle location and quantity information. During the data collection process, not only are bicycle coordinates accurately obtained through the positioning module, but the image acquisition device is also used to divide normal and illegal areas, and the number of bicycles in different areas is counted separately. Deduplication is performed through the positional correlation between image acquisition units to avoid errors caused by duplicate counting. The final fused location data contains not only the precise location of bicycles and accurate quantity information, but also identifies illegal parking situations, providing a comprehensive and reliable data foundation for subsequent scheduling decisions, effectively solving the problems of incomplete and inaccurate information caused by traditional single data sources.

[0059] 2. This invention can generate a dynamic capacity baseline to improve the accuracy of demand matching. Specifically, based on historical data, bicycle movement routes, and environmental parameters, this invention constructs a dynamic site capacity baseline. First, it analyzes the increase and decrease in bicycles at different historical time periods and integrates location data to calculate the bicycle difference to grasp the trend of quantity changes. Simultaneously, by assigning different weights to the number of bicycles in normal and illegal areas, and combining historical expected increases and environmental parameters, the capacity baseline is adjusted. Through this dynamic capacity assessment mechanism, the capacity baseline can adapt in real time to changes in bicycle supply and demand under different time periods and environments. Compared to traditional fixed capacity settings, this significantly improves the scientific and rational nature of site resource planning.

[0060] 3. This invention can generate accurate shared bicycle scheduling information based on the redundancy value determined by fused location data and dynamic capacity baseline, thereby achieving optimized resource allocation. Specifically, this invention accurately calculates the redundancy value by comparing the actual number of bicycles at each station with the capacity baseline, and uses this as a basis to match supply and demand stations. For stations with insufficient bicycles due to negative redundancy, it prioritizes stations with large positive redundancy values ​​and close proximity as scheduling sources. When a single station cannot meet the demand, it automatically combines multiple stations for collaborative scheduling. Simultaneously, it intelligently selects appropriate scheduling equipment and quantities based on attributes such as the loading capacity and travel speed of the scheduling equipment, ensuring that bicycle scheduling meets station needs while avoiding over-scheduling. This data-driven intelligent scheduling strategy effectively balances the distribution of bicycle resources among stations, reduces vehicle backlog and shortages, and significantly improves the overall operational efficiency and user experience of shared bicycles. Attached Figure Description

[0061] Figure 1A flowchart illustrating a shared bicycle scheduling method based on data fusion and dynamic resource optimization provided by this invention;

[0062] Figure 2 This is a schematic diagram of image region division provided by the present invention. Detailed Implementation

[0063] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0064] like Figure 1 As shown, this invention provides a shared bicycle scheduling method based on data fusion and dynamic resource optimization, including:

[0065] S1 fuses the bicycle's own first location data with the second location data collected from the environment to obtain the fused location data for each station.

[0066] Understandably, in order to comprehensively and accurately grasp the actual location and number of bicycles at each station, the primary location data of the bicycle itself and the secondary location data obtained from the analysis of images collected from the environment can be fused to obtain the fused location data of each station. This facilitates subsequent bicycle scheduling and reduces the limitations of single data sources. It also provides a comprehensive and reliable data foundation for subsequent shared bicycle scheduling strategy formulation, thereby achieving more efficient shared bicycle management.

[0067] In some embodiments, the specific implementation of step S1 (the fusion of the first location data of the bicycle itself and the second location data collected from the environment to obtain the fused location data of each station) includes:

[0068] S11: Based on the positioning module of each bicycle, its first location information is obtained, and the first location information of all bicycles located in a station is counted to obtain the first location data.

[0069] Understandably, each bicycle is equipped with a positioning module, which allows for the acquisition of precise first-order location information for each bicycle. For specific stations, such as a pre-defined area around a subway station, a comprehensive statistical analysis is conducted to collect and organize the first-order location information of all bicycles within that station's area, thus obtaining first-order location data. This first-order location data records in detail the specific parking location of each bicycle within the station, intuitively presenting the distribution of bicycles within the station area. This provides location data for subsequent analysis of bicycle location characteristics at the station and for integration with other data, facilitating efficient and accurate bicycle scheduling in the future.

[0070] The positioning module is a positioning device module installed on the bicycle. The first position information is the coordinate position of each bicycle, and the first position data is the set of the first position information of all bicycles within the station area.

[0071] S12, extract the number of vehicles from the image data of the image acquisition device at each station to obtain the second location data.

[0072] Understandably, each station is equipped with an image acquisition device, i.e., a camera, which allows for the analysis of the images captured by the camera. This involves identifying the bicycles and counting their number, thus obtaining second-location data. From an image perspective, this supplements the information about the number of bicycles within the station, facilitating subsequent integration with the first-location data. This enables the system to have a more comprehensive understanding of the bicycle status at each station, knowing not only the location of the bicycles but also the number of bicycles at each station. This provides crucial quantitative information for subsequent comprehensive judgment and decision-making.

[0073] Among them, the image acquisition device is a device for acquiring images, such as a camera; the image data is the image acquired by the image acquisition device; the number of bicycles is the number of bicycles in the station; and the second location data is the number of bicycles located in the location area of ​​each station.

[0074] In some embodiments, the specific implementation of step S12 (extracting the number of vehicles from the image data of each station's image acquisition device to obtain the second location data) includes:

[0075] S121, the image of each image acquisition unit in the image acquisition device is divided into normal area and non-normal area.

[0076] Understandably, in order to analyze the image data acquired by the image acquisition device more accurately, the image of each image acquisition unit can be divided, i.e., such as... Figure 2 As shown, the image area is clearly divided into normal areas and non-compliant areas according to the pre-set standards.

[0077] The normal area is the area that meets specific regulations, meaning that bicycles parked in this area may comply with the regulations. The non-compliant area is the part outside the regulated area, meaning that bicycles parked in this area may not comply with the regulations.

[0078] It is easy to understand that an image acquisition device can be composed of multiple acquisition units so that it can acquire images of the site area from all directions. When dividing the images, the images acquired by each image acquisition unit can be divided. An image acquisition unit is one of the acquisition units in the image acquisition device. For example, when the image acquisition device has 4 cameras, the image acquisition unit is one of the cameras.

[0079] The above implementation method divides the image into regions so that the bicycles in different regions can be processed and analyzed in a targeted manner, thereby improving the accuracy of bicycle counting.

[0080] S122, extract the number of bicycles in the normal area to obtain the first number, and extract the number of bicycles in the illegal area to obtain the second number.

[0081] Understandably, the first number represents the number of bicycles in the normal area, and the second number represents the number of bicycles in the illegal area.

[0082] By counting the number of bicycles in these two areas separately, we can clearly understand the distribution of bicycles in different areas of the station, providing detailed data support for subsequent comprehensive evaluation of the station's bicycle status.

[0083] S123, based on the positional correlation between the image acquisition units, the first quantity and / or the second quantity are deduplicated, and the second position data is obtained based on the deduplicated first quantity and / or second quantity.

[0084] It is understandable that, since the image acquisition device is composed of multiple image acquisition units and the positions of these cameras are related, the same bicycle may be photographed repeatedly within the shooting range of different cameras. Therefore, based on the positional relationship between the image acquisition units, the previously obtained first and second numbers can be deduplicated. That is, the duplicate parts of the bicycle number statistics caused by repeated shooting can be identified and removed. After deduplication, the processed first and second numbers are obtained, and the accurate second location data is finally determined.

[0085] Among them, the location correlation relationship refers to the positional relationship between image acquisition units. The second location data can more realistically reflect the actual number of bicycles in the station, avoid data deviation caused by repeated statistics, and improve the accuracy of the second location data.

[0086] In some embodiments, the specific implementation of step S123 (the deduplication of the first and / or second quantities based on the positional correlation between image acquisition units, and the obtaining of the second position data based on the deduplicated first and / or second quantities) includes:

[0087] S1231, based on the user's marking of the image acquisition units, obtain the repeated acquisition areas of any number of image acquisition units, and determine the number of repetitions of a single vehicle within the repeated acquisition area.

[0088] It is understandable that when multiple cameras are shooting at a site, due to differences in their shooting angles and positions, some areas may be captured by multiple cameras simultaneously, resulting in overlapping acquisition areas. Therefore, the overlapping acquisition areas among these arbitrary multiple image acquisition units can be determined based on the user's marking information on the image acquisition units.

[0089] Among them, users can be maintenance personnel. For example, through operation or settings, users can explicitly indicate that a certain area captured by both camera A and camera B is a duplicate collection area. Then, the number of bicycles in the duplicate collection area can be counted to determine the number of bicycles counted repeatedly in that area, i.e., the duplicate count, so that subsequent deduplication processing can be performed to accurately identify the duplicate collection area and the duplicate count, avoid incorrect bicycle counts, and improve the accuracy of the second location data.

[0090] Among them, the repeated acquisition area is the area acquired simultaneously by multiple image acquisition units, and the number of repetitions is the number of vehicles in the repeated acquisition area.

[0091] S1232, obtain the priority labels of multiple image acquisition units corresponding to the repeated acquisition areas, retain the number of repetitions of the repeated acquisition areas with the highest priority label, and delete the number of repetitions of the repeated acquisition areas with non-highest priority labels from the first number or the second number.

[0092] Understandably, each image acquisition unit is assigned a priority label during pre-setting to indicate its importance or reliability in data acquisition and processing. The priority labels of multiple image acquisition units corresponding to duplicate acquisition areas are obtained; for example, camera A's priority label is higher than camera B's. During deduplication, the number of duplicates in the duplicate acquisition area with the highest priority label is retained because the data in that area is considered more reliable or important. For other duplicate acquisition areas with non-highest priority labels, their corresponding number of duplicates is removed from the previously obtained first count (number of vehicles in normal areas) or second count (number of vehicles in violation areas). In this way, redundant data caused by duplicate acquisition can be effectively removed, making the count of vehicles more accurate.

[0093] Among them, the priority label is the information label that prioritizes data processing, and it can be preset.

[0094] S13, fuse the first position data and the second position data to generate fused position data.

[0095] Understandably, by combining location information and quantity information, more comprehensive integrated location data is generated. This integrated location data can not only reflect the specific parking location of bicycles within the station, but also accurately reflect the quantity of bicycles, so that subsequent operations such as determining the station's capacity baseline and scheduling shared bicycles can be carried out based on the integrated location data.

[0096] Among them, the fused location data is a composite data that includes the first location data and the second location data.

[0097] S2 generates a dynamic capacity baseline for each station based on historical data, bicycle routes, and environmental parameters.

[0098] Understandably, in order to make the generated capacity baseline more in line with the actual operation and to provide a scientific reference for the reasonable scheduling of shared bicycles, multiple factors can be integrated for comprehensive consideration, taking into account the changes in the station's bicycle capacity under different times and external conditions, so as to improve the overall operational efficiency of the shared bicycle system.

[0099] Among them, historical data refers to the bicycle data corresponding to historical moments, bicycle movement routes refer to the routes taken by shared bicycles, environmental parameters refer to the meteorological data corresponding to the weather, and capacity baseline refers to the minimum and maximum capacity of the corresponding stations.

[0100] It's easy to understand that different weather conditions affect how users use bicycles. For example, bicycles are used more on sunny days than on rainy days, which in turn affects the number of bicycles at each station and consequently the bicycle dispatching schedule.

[0101] In some embodiments, the specific implementation of step S2 (generating a dynamic capacity baseline for each station based on historical data, single-vehicle travel routes, and environmental parameters) includes:

[0102] S21, obtain the merged location data of the station in different time periods from the historical data, as well as the number of new and decreased bicycles in the corresponding time periods.

[0103] Understandably, by extracting the merged location data of each station from historical data records for different specific time periods (such as 8:00 to 8:15), this merged location data comprehensively reflects the actual location and number of bicycles at the station during the corresponding time period. At the same time, it can also obtain the data on the number of new bicycles added and the number of bicycles removed at the station during that time period.

[0104] Among them, the increase in bicycles refers to the number of bicycles newly entering the station, and the decrease in bicycles refers to the number of bicycles leaving the station.

[0105] Through the above implementation methods, the present invention can obtain the number of new and decreased bicycles, so as to analyze the dynamic changes in the number of bicycles at the station.

[0106] S22, based on the increase and decrease of the number of vehicles, the corresponding vehicle difference is obtained, and the vehicle difference includes positive vehicle difference and negative vehicle difference.

[0107] It is understandable that the difference per vehicle is the difference between the number of new and new stations, that is, the difference between the number of new vehicles and the number of vehicles reduced.

[0108] Specifically, when the increase in the number of bicycles is greater than the decrease in the number of bicycles, a positive bicycle difference is obtained, which means that the number of bicycles at the station has increased during this period. Conversely, when the increase in the number of bicycles is less than the decrease in the number of bicycles, a negative bicycle difference is obtained, which indicates that the number of bicycles at the station has decreased.

[0109] By calculating the difference in the number of vehicles per station, we can clearly understand the net change in the number of vehicles per station in each time period, so as to determine the dynamic changes in the station capacity baseline.

[0110] S23, Based on the fused location data, single-vehicle difference, single-vehicle movement route, and environmental parameters, generate a dynamic capacity baseline for each station.

[0111] Understandably, by combining the previously obtained fused location data and single-vehicle difference data with information such as bicycle movement routes and environmental parameters, a dynamic capacity baseline for each station is generated. The fused location data reflects the current bicycle distribution status of the station, the single-vehicle difference data reflects the trend of quantity change, the bicycle movement routes help to understand the source and destination of bicycles, and environmental parameters (such as weather, holidays, etc.) will affect the usage demand and flow of bicycles. By combining these factors, the generated capacity baseline can dynamically and comprehensively reflect the reasonable bicycle capacity of the station under different conditions.

[0112] In some embodiments, the specific implementation of step S23 (generating a dynamic capacity baseline for each station based on the fused location data, single-vehicle difference, single-vehicle movement route, and environmental parameters) includes:

[0113] S231, multiply the first quantity by the first preset value to obtain the first base number, multiply the second quantity by the second preset value to obtain the second base number, wherein the first preset value is greater than the second preset value.

[0114] Understandably, for each station, the number of bicycles in the normal area and the violation area are processed separately. The first number is multiplied by a pre-set first preset value to obtain the first base number. Similarly, the second number is multiplied by a pre-set second preset value to obtain the second base number.

[0115] The first base number is the number of bicycles in the normal area, which is the product of the total number of bicycles in all normal areas within the station and the first preset value. The second base number is the number of bicycles in the violation area, which is the product of the total number of bicycles in all violation areas within the station and the second preset value.

[0116] It's easy to understand why the first preset value is greater than the second preset value. This is because, under normal circumstances, the number of bicycles in the violation area (the second number) is less than the number of bicycles in the normal area (the first number). In this way, when calculating the base number, the number of bicycles in the normal area can be given greater weight, thus more reasonably reflecting the actual situation of the site.

[0117] S232, add the first base number and the second base number to obtain the standard base number, determine the interval value of the standard base number to obtain the reference capacity, and each base number interval has a preset reference capacity.

[0118] Understandably, after obtaining the first and second base numbers, they are added together to obtain the standard base number. The standard base number takes into account the number of bicycles in both normal and illegal areas. Then, based on different pre-set base number intervals, the interval value of the standard base number can be determined. Each base number interval corresponds to a preset baseline capacity. By determining the interval in which the standard base number is located, the corresponding baseline capacity of the station can be obtained.

[0119] The standard base is the sum of the first base and the second base, and the baseline capacity is the baseline capacity of the station. It is an important basic value for generating the dynamic capacity baseline. It reflects the approximate single-vehicle capacity of the station without considering other factors.

[0120] S233: Extract the expected increase in the number of bicycles on cycling routes with the station as the destination within a preset distance in the corresponding historical time period.

[0121] Understandably, the number of bicycles on cycling routes with the station as the destination is extracted from historical data within a preset distance, such as 1 kilometer, for the corresponding time period, and this number is determined as the expected increase.

[0122] The expected increment is the number of bikes expected to be added to the target site, which is a range of numbers. The expected increment reflects how many bikes are expected to flow to the site in similar historical time periods and areas. For example, the expected increment could be (50 bikes, 80 bikes). By analyzing the bike movement routes in historical data, we can make a preliminary prediction of the future trend of bike numbers, so as to improve the accuracy of the site capacity baseline.

[0123] S234 generates a dynamic capacity baseline for each site based on baseline capacity, expected increments, and environmental parameters.

[0124] Understandably, baseline capacity provides a basic reference for capacity, while expected increments take into account possible future changes in the number of bikes, and environmental parameters (such as weather conditions, weekdays or holidays) will affect bike usage and mobility.

[0125] For example, when the weather is bad, the mobility of bicycles may decrease. At this time, it is necessary to adjust the capacity baseline according to the adjustment rules corresponding to the environmental parameters. By taking into account these factors, the generated dynamic capacity baseline can more accurately reflect the number of bicycles that the site can actually accommodate under different conditions, so as to improve the scheduling and management of shared bicycles.

[0126] In some embodiments, a specific implementation of step S234 (the generation of a dynamic capacity baseline for each site based on baseline capacity, expected increment, and environmental parameters) includes:

[0127] S2341, the reference capacity includes the maximum capacity and the minimum capacity.

[0128] Understandably, defining the baseline capacity is not a single value, but rather encompasses two key indicators: maximum capacity and minimum capacity.

[0129] The maximum capacity represents the upper limit of the number of bicycles that a station can accommodate under ideal conditions, while the minimum capacity represents the lower limit of the number of bicycles that a station needs to maintain during normal operation. These two values ​​define the range boundaries for subsequent dynamic adjustment of the capacity baseline, ensuring that the adjusted capacity baseline is within a reasonable and feasible range, so as to improve the accuracy of shared bicycle storage and scheduling at the station.

[0130] S2342, multiply the expected increment by a preset coefficient to obtain the standard increment, and subtract the minimum standard increment from the minimum capacity to obtain the minimum capacity baseline.

[0131] Understandably, the expected increment is first multiplied by a preset coefficient to obtain the standard increment. The preset coefficient is set in advance based on actual operational experience and data analysis and is used to make reasonable quantitative adjustments to the expected increment. Then, the minimum standard increment is subtracted from the minimum capacity to obtain the minimum capacity baseline.

[0132] For example, if the minimum capacity is 100 vehicles and the calculated standard increment is 15 vehicles, then the adjusted minimum capacity baseline is 85 vehicles. This implementation method combines the prediction of future changes in the number of vehicles (expected increment) and dynamically adjusts the baseline capacity from the lower limit perspective, so that the capacity baseline can better fit the actual needs and ensure that the station can still meet basic operational needs when the number of vehicles decreases.

[0133] The standard increment is the amount added under standard conditions, which is the product of the expected increment and the preset coefficient.

[0134] It is easy to understand that when the expected increment is a numerical range, the maximum and minimum values ​​in the expected increment are multiplied by the preset coefficients to obtain the standard increment. The standard increment is also a numerical range. Then, the minimum capacity can be subtracted from the minimum standard increment to obtain the capacity baseline corresponding to the minimum value. The minimum standard increment is the minimum value in the standard increment.

[0135] S2343, determine the environmental coefficient based on the parameter range corresponding to the environmental parameter. Each environmental parameter has a preset environmental coefficient in the parameter range corresponding to the environmental parameter. Multiply the environmental coefficient by the maximum capacity to obtain the capacity baseline of the maximum value.

[0136] Understandably, based on current environmental parameters (such as weather conditions, whether it is a holiday, etc.), the parameter range to which it belongs is determined. Each environmental parameter range corresponds to a pre-set environmental coefficient. The worse the environmental parameters (such as severe weather, special holidays, etc., which lead to a decrease in bicycle usage and mobility), the larger the corresponding environmental coefficient. After determining the environmental coefficient, it is multiplied by the maximum capacity to obtain the maximum capacity baseline. This means that when environmental conditions are poor, considering the reduced mobility of bicycles, more bicycles may be stranded at the station. Therefore, by increasing the environmental coefficient, the maximum capacity baseline is increased to reserve space for the possible increase in the number of bicycles, thereby dynamically adjusting the upper limit of the station's capacity and enabling the capacity baseline to better adapt to the operational needs under different environments.

[0137] Among them, the parameter range is the numerical range corresponding to the environmental parameters, and the environmental coefficient is a pre-set value that corresponds one-to-one with the environmental range.

[0138] The worse the environmental parameters, the larger the environmental coefficient.

[0139] It is understandable that worse environmental parameters indicate that environmental factors have a significant impact on capacity changes; that is, the worse the environment, the greater the fluctuation in demand for bicycles.

[0140] For example, there is a preset table for environmental parameters and environmental coefficients. For instance, when the environment is in heavy rain, the preset table has an environmental coefficient corresponding to the heavy rain parameter, and when it is in moderate rain, there is also a corresponding environmental coefficient. Furthermore, the environmental coefficient for heavy rain is greater than that for moderate rain.

[0141] S3 determines the redundancy value of each site based on the fused location data and capacity baseline of each site.

[0142] Understandably, the redundancy value of a site is determined by comparing the actual number of bikes reflected in the merged location data of each site with the capacity baseline of that site.

[0143] The redundancy value is the redundancy of the current number of bicycles at a station relative to the reasonable capacity. This redundancy value is used to formulate targeted shared bicycle scheduling strategies to help optimize the allocation of bicycle resources among various stations.

[0144] In some embodiments, a specific implementation of step S3 (determining the redundancy value of a site based on the fused location data and capacity baseline of each site) includes:

[0145] S31, calculate the sum of the first and second quantities in the fused location data to obtain the total number of corresponding stations.

[0146] Understandably, the merged location data is processed by adding the number of bicycles in normal areas (first count) to the number of bicycles in violation areas (second count) to calculate the total number of bicycles at the corresponding station.

[0147] The total number represents the actual number of bicycles currently existing within the station. This data serves as the basis for subsequent comparison with the capacity baseline and determination of redundancy values, improving the accuracy of assessing the bicycle quantity status at each station and providing rationality and accuracy for bicycle scheduling between stations.

[0148] S32, if the total quantity is less than the minimum capacity, the redundancy value is negative, and the median value of the capacity baseline is subtracted from the total quantity to obtain a negative redundancy value.

[0149] It is understandable that when the calculated total number of bikes at a station is less than the minimum capacity in the station's capacity baseline, it indicates that the number of bikes at the station is insufficient. In this case, the redundancy value is recorded as negative. To quantify the degree of this insufficiency, the negative redundancy value can be obtained by calculating the difference between the median value of the capacity baseline (i.e., the middle value of the capacity baseline range) and the total number.

[0150] Among them, the magnitude of the negative redundancy value reflects the gap between the station and the lower limit of the reasonable number of bicycles, providing a quantitative reference for subsequently dispatching bicycles from other stations to supplement the station. The median value is the middle value of the capacity baseline range.

[0151] S33, if the total quantity is greater than the maximum capacity, the redundancy value is positive, and the median value of the maximum capacity minus the total quantity is used to obtain the positive redundancy value.

[0152] It is understandable that if the total number of bicycles at a station exceeds the maximum capacity in the station's capacity baseline, it means that there are too many bicycles at the station. In this case, the redundancy value is recorded as positive. The positive redundancy value can be obtained by calculating the difference between the median value of the maximum capacity and the total number of bicycles.

[0153] The positive redundancy value is the degree to which a station exceeds its reasonable capacity limit for bicycles. This value is used to subsequently relocate excess bicycles from a station to other stations with insufficient bicycles, thereby balancing the distribution of bicycle resources among stations and improving the accuracy of bicycle scheduling strategies.

[0154] S4 generates shared bicycle dispatch information based on redundancy values, station locations, and dispatch equipment attributes.

[0155] Understandably, by comprehensively considering factors such as the redundancy of stations, their geographical location, and the attributes of dispatching equipment, reasonable shared bicycle dispatching information can be generated to effectively allocate shared bicycles among different stations, balance the number of bicycles at each station, and improve the efficiency and service quality of shared bicycles.

[0156] Among them, the shared bicycle dispatch information is the dispatch information for adjusting shared bicycles. For example, it can be to move redundant bicycles at station A to station B with a negative redundancy value based on the redundancy value, so as to improve bicycle dispatch efficiency.

[0157] In some embodiments, the specific implementation of step S4 (generating shared bicycle dispatch information based on redundancy values, station locations, and dispatch device attributes) includes:

[0158] S41, the station with a negative redundancy value is identified as the first station, and the station with a positive redundancy value within a preset range is identified as the second station.

[0159] Understandably, in order to determine the target stations for bike dispatching, the redundancy values ​​of each station can be analyzed. Stations with negative redundancy values ​​are identified as the first station, characterized by an insufficient number of bikes. Then, within a preset range centered on the first station (e.g., a region with a certain radius centered on the first station), stations with positive redundancy values ​​are identified as the second station, i.e., stations with more bikes. Through this filtering, the stations that need to replenish bikes (the first station) and the stations where bikes can be dispatched (the second station) are clearly identified, thus determining the target stations for subsequent dispatching operations.

[0160] The first station is a station with a shortage of vehicles, i.e., a station with a negative redundancy value. The second station is a station with an abundance of vehicles, i.e., a station with a positive redundancy value within a preset range. The preset range is a pre-defined area.

[0161] S42, based on the positive redundancy values, sort all second stations in descending order to obtain the redundancy station sequence.

[0162] Understandably, in order for the scheduling process to prioritize dispatching from the stations with the largest number of surplus bicycles, the second stations can be sorted in descending order based on their positive redundancy values ​​to obtain a sequence of redundant stations. The larger the positive redundancy value, the more surplus bicycles there are at that station. The sequence of redundant stations arranges the second stations from highest to lowest redundancy so that the stations that need to be dispatched can be quickly identified later.

[0163] S43, based on the redundancy value of the first station, determine the corresponding second station and scheduling equipment in the redundant station sequence, and generate shared bicycle scheduling information.

[0164] Understandably, based on the magnitude of the negative redundancy value of the first station, a search and matching process is performed in the redundant station sequence. The goal is to find a second station that can meet the bicycle demand of the first station. At the same time, considering the attributes of the dispatching equipment, such as the loading capacity and travel speed of different types of dispatching equipment, a suitable dispatching equipment is determined to perform the bicycle dispatching task from the second station to the first station. Finally, the selected second station information, dispatching equipment information, and related dispatching details are integrated to generate shared bicycle dispatching information. This shared bicycle dispatching information will guide the actual shared bicycle dispatching operation, ensuring that bicycles can be smoothly dispatched from the second station with more bicycles to the first station with fewer bicycles, thus achieving a balance in the number of bicycles between stations.

[0165] Among them, the dispatching equipment is the equipment used to dispatch shared bicycles to different stations, such as trucks.

[0166] In some embodiments, the specific implementation of step S43 (determining the corresponding second station and scheduling device in the redundant station sequence based on the redundancy value of the first station, and generating shared bicycle scheduling information) includes:

[0167] S431, if the absolute value of the redundancy of the first station is less than or equal to the absolute value of the redundancy of the first second station in the redundancy station sequence.

[0168] Understandably, the absolute value of the redundancy at the first station is compared with the absolute value of the redundancy at the first and second stations in the redundancy station sequence. The first station is a station with a shortage of vehicles, so its redundancy value is negative. The second station is a station with an excess of vehicles, so its redundancy value is positive. When the absolute value of the redundancy at the first station is less than or equal to the absolute value of the redundancy at the first and second stations in the redundancy station sequence, it means that the number of spare vehicles at the first and second stations is sufficient to meet the first station's demand for vehicles, so as to select a suitable second station and dispatching equipment in the future.

[0169] S432 then determines the second station as the mutual scheduling station, which is the station whose absolute value of redundancy is greater than or equal to that of the first station and whose absolute value of redundancy is closest to that of the first station.

[0170] Understandably, after determining that the absolute value of the redundancy of the first station is less than or equal to the absolute value of the redundancy of the first second station in the redundancy station sequence, a suitable second station can be further searched in the redundancy station sequence as a mutual scheduling station. Specifically, second stations whose absolute value of redundancy is greater than or equal to the absolute value of the redundancy of the first station will be selected. Then, among the selected stations, the second station whose absolute value of redundancy is closest to that of the first station will be selected. The purpose of selecting the closest station is to minimize the number of vehicles to be scheduled while meeting the needs of the first station, thereby improving scheduling efficiency and avoiding unnecessary waste of resources.

[0171] Among them, the mutual dispatch station is the second station selected to dispatch a single vehicle to the first station.

[0172] Through the above implementation methods, the present invention identifies mutual scheduling stations, clarifies specific target stations for subsequent scheduling operations, facilitates the generation of shared bicycle scheduling information, and improves scheduling efficiency.

[0173] S433: Based on the redundancy value of the first station, determine the corresponding attributes of the scheduling equipment and the number of equipment to obtain shared bicycle scheduling information.

[0174] Understandably, different dispatching devices have different attributes, such as loading capacity and driving speed. The system will select dispatching devices with appropriate loading capacity based on the number of vehicles that need to be added at the first station (determined by the redundancy value) and calculate the required number of devices.

[0175] For example, if the first station needs to replenish 50 bicycles, and the loading capacity of dispatch device A is 10 bicycles, then it will be determined that 5 dispatch devices A are needed. Finally, the determined information of the second station, the attribute information of the dispatch devices, and the number of devices are integrated to generate detailed shared bicycle dispatch information. The shared bicycle dispatch information will guide the actual dispatch operation, ensuring that shared bicycles can be accurately and efficiently allocated from the second station with more bicycles to the first station with fewer bicycles, and achieving a reasonable balance in the number of bicycles between stations.

[0176] In some embodiments, it also includes:

[0177] A1, if the absolute value of the redundancy of the first station is greater than the absolute value of the redundancy of the first second station in the redundancy station sequence.

[0178] Understandably, comparing the absolute value of the redundancy at the first station (the station with a shortage of bikes) with the absolute value of the redundancy at the first second station (the station with an abundance of bikes) in the redundancy station sequence, if the absolute value of the redundancy at the first station is larger, it indicates that the number of extra bikes at the first second station is insufficient to meet the demand for bikes at the first station. In this case, it is necessary to further consider other second stations to jointly complete the bike allocation for the first station.

[0179] A2. After removing the first second station, sort the remaining second stations in ascending order to obtain an ascending sequence. Select the redundant value of the removed second station in order according to the ascending sequence and add it to the sum. If the absolute value of the sum is greater than or equal to the absolute value of the redundant value of the first station, then the corresponding multiple second stations are used as combined scheduling stations.

[0180] Understandably, once it is determined that the first second station cannot meet the needs of the first station, it can be removed from the redundant station sequence. Then, the remaining second stations are sorted in ascending order according to their positive redundancy values, resulting in an ascending sequence. In this ascending sequence, stations with fewer redundant vehicles are listed first. Subsequently, second stations can be selected sequentially according to the ascending sequence. The redundancy value of the selected station is added to the redundancy value of the removed first second station to obtain a sum. The server will continue to perform selection and summation operations until the absolute value of the sum is greater than or equal to the absolute value of the redundancy value of the first station. At this point, these second stations participating in the summation calculation will be determined as combined scheduling stations.

[0181] Among them, the ascending sequence is the station sequence obtained by sorting the remaining second stations in ascending order after removing the first second station in the redundant station sequence, and the combined scheduling station is a combination of multiple selected second stations.

[0182] Through the above implementation method, a group of second stations that can jointly meet the bicycle demand of the first station can be found, thus achieving a more reasonable bicycle allocation.

[0183] A3. Based on the redundancy value of the first station, the scheduling equipment and the number of equipment with corresponding attributes are determined to obtain the shared bicycle scheduling information.

[0184] Understandably, different dispatching devices have different attributes, such as loading capacity and driving speed. The server will select dispatching devices with suitable loading capacity based on the number of vehicles that need to be added at the first station, and calculate the required number of devices.

[0185] For example, if the first station needs to replenish 80 bicycles, and the loading capacity of dispatch device B is 20 bicycles, then the system will determine that 4 dispatch devices B are needed. Finally, the information of the combined dispatch stations, the attribute information of the dispatch devices, and the number of devices are integrated to generate complete shared bicycle dispatch information. The shared bicycle dispatch information will guide the actual dispatch operation, ensuring that shared bicycles can be accurately and efficiently allocated from multiple combined dispatch stations to the first station with a shortage of bicycles, and achieving a reasonable balance in the number of bicycles between stations.

[0186] In some embodiments, a specific implementation of step A3 (determining the scheduling devices and the number of devices based on the redundancy value of the first station to obtain shared bicycle scheduling information) includes:

[0187] A31, obtain all scheduling devices within the preset range of the first site as the first scheduling device.

[0188] Understandably, the server will first determine a preset range centered on the first site. This range can be a geographical area set according to the actual situation, such as a circular area with the first site as the center and a certain distance as the radius. Then, the server will collect all available scheduling devices within this preset range and classify them as the first scheduling device.

[0189] The types of dispatching equipment can be diverse, such as vans and tricycles, which may participate in subsequent shared bicycle dispatching tasks. By acquiring the first dispatching equipment, a variety of dispatching equipment can be selected for subsequent appropriate dispatching.

[0190] A32 establishes a scheduling direction from the second station toward the first station, determines the corresponding scheduling equipment based on the redundancy value of the second station, and each type of scheduling equipment has a preset value range for its attributes.

[0191] Understandably, the server uses the second station as the starting point and the first station as the ending point to determine a scheduling direction. This scheduling direction is the direction in which the bicycles are scheduled and adjusted, which helps to clarify the route direction of bicycle scheduling and ensure the directionality and orderliness of the scheduling work. Thus, based on the redundancy value of the second station (i.e. the number of extra bicycles at that station), a matching scheduling device is selected from the first scheduling devices.

[0192] Each type of scheduling device has a pre-set value range, which represents the range of the number of vehicles that the device can carry. For example, the value range of van A indicates that it can carry 100 vehicles. The server selects the scheduling device that can reasonably carry the excess vehicles at the second station by comparing the redundancy value of the second station with the value ranges of various scheduling devices.

[0193] A33. If the value range of the scheduling equipment is less than the redundancy value of the second station, the number of equipment is obtained by comparing the redundancy value with the maximum value of the value range.

[0194] Understandably, when the range of the scheduling device selected by the server is less than the redundancy value of the second station, it means that using only one scheduling device of this type cannot transport all the excess bicycles from the second station. In this case, the server will calculate the required number of devices based on the redundancy value of the second station and the maximum value of the range of the scheduling device.

[0195] The number of devices refers to the number of devices that can be scheduled.

[0196] For example, if the second station has 400 extra bicycles, and the maximum value range of van A is 100 bicycles, then 4 vans A are needed to complete the scheduling task. Through calculation, the server can accurately determine the number of scheduling devices required to complete the scheduling task, thereby improving the shared bicycle scheduling information and ensuring that the scheduling work can be executed efficiently and accurately.

[0197] The present invention also provides a storage medium storing a computer program, which, when executed by a processor, is used to implement the methods provided in the various embodiments described above.

[0198] The storage medium can be a computer storage medium or a communication medium. A communication medium includes any medium that facilitates the transfer of computer programs from one location to another. A computer storage medium can be any available medium accessible to a general-purpose or special-purpose computer. For example, the storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be a component of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). This ASIC can also be located within a user device. Alternatively, the processor and storage medium can exist as discrete components in a communication device. Storage media can be read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage devices, etc.

[0199] The present invention also provides a program product including execution instructions stored in a storage medium. At least one processor of the device can read the execution instructions from the storage medium, and the execution instructions by the at least one processor cause the device to implement the methods provided in the various embodiments described above.

[0200] In the above-described terminal or server embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0201] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention 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 or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A shared bicycle scheduling method based on data fusion and dynamic resource optimization, characterized in that, include: The first location data of the bicycle itself and the second location data collected from the environment are fused to obtain the fused location data for each station. This includes: extracting the number of bicycles from the image data of the image acquisition device at each station to obtain the second location data, including: The image of each image acquisition unit in the image acquisition device is divided into normal areas and non-normal areas; The first number is obtained by extracting the number of bicycles in the normal area, and the second number is obtained by extracting the number of bicycles in the illegal area. Based on the positional correlation between image acquisition units, the first quantity and / or the second quantity are deduplicated, and the second position data is obtained based on the deduplicated first quantity and / or the second quantity. A dynamic capacity baseline for each station is generated based on historical data, bicycle routes, and environmental parameters, including: Obtain the merged location data of the station in different time periods from historical data, as well as the number of new and decreased bicycles in the corresponding time periods; The corresponding vehicle difference is obtained based on the increase and decrease of the number of vehicles per vehicle. The vehicle difference includes positive and negative vehicle differences. Based on the fused location data, single-vehicle difference, single-vehicle movement route, and environmental parameters, a dynamic capacity baseline is generated for each station, including: Multiply the first quantity by the first preset value to obtain the first base number, and multiply the second quantity by the second preset value to obtain the second base number, wherein the first preset value is greater than the second preset value; The first base number and the second base number are added together to obtain the standard base number. The interval value of the standard base number is determined to obtain the reference capacity. Each base number interval has a preset reference capacity. The expected increase in the number of bicycles on cycling routes with the station as the destination is obtained by extracting the number of bicycles within a preset distance in the corresponding historical time period. A dynamic capacity baseline is generated for each site based on baseline capacity, expected increments, and environmental parameters; The redundancy value of each site is determined based on the fused location data and capacity baseline of each site; Shared bicycle dispatch information is generated based on redundancy values, station locations, and the attributes of dispatching equipment.

2. The method according to claim 1, characterized in that, The first location data of the bicycle itself and the second location data collected from the environment are fused to obtain the fused location data for each station, including: The first location information is obtained based on the positioning module of each bicycle, and the first location data is obtained by summarizing the first location information of all bicycles located in a station. The first location data and the second location data are fused to generate fused location data.

3. The method according to claim 1, characterized in that, The deduplication process based on the positional correlation between image acquisition units to determine the first and / or second quantities, and the subsequent deduplication of the first and / or second quantities to obtain the second position data, includes: Based on the user's marking of the image acquisition units, the repeated acquisition areas of any number of image acquisition units are obtained, and the number of repetitions of a single vehicle within the repeated acquisition area is determined. Obtain the priority labels of multiple image acquisition units corresponding to the repeated acquisition areas, retain the number of repetitions of the repeated acquisition areas with the highest priority label, and delete the number of repetitions of the repeated acquisition areas with non-highest priority labels from the first number or the second number.

4. The method according to claim 1, characterized in that, The process of generating a dynamic capacity baseline for each site based on baseline capacity, expected increments, and environmental parameters includes: The baseline capacity includes the maximum capacity and the minimum capacity; Multiply the expected increment by a preset coefficient to obtain the standard increment, and subtract the minimum standard increment from the minimum capacity to obtain the minimum capacity baseline. The environmental coefficient is determined based on the parameter range corresponding to the environmental parameter. Each environmental parameter has a preset environmental coefficient for its corresponding parameter range. The environmental coefficient is multiplied by the maximum capacity to obtain the capacity baseline of the maximum value.

5. The method according to claim 1, characterized in that, The process of determining the redundancy value of a site based on the fused location data and capacity baseline for each site includes: The total number of corresponding stations is obtained by summing the first and second quantities in the fused location data; If the total quantity is less than the minimum capacity, the redundancy value is negative. The negative redundancy value is obtained by subtracting the total quantity from the median value of the capacity baseline. If the total quantity is greater than the maximum capacity, the redundancy value is positive. The positive redundancy value is obtained by subtracting the total quantity from the median value of the maximum capacity.

6. The method according to claim 1, characterized in that, The process of generating shared bicycle dispatch information based on redundancy values, station locations, and dispatch device attributes includes: The station with a negative redundancy value is designated as the first station, and the station with a positive redundancy value within a preset range is designated as the second station. The redundant station sequence is obtained by sorting all second stations in descending order based on the positive redundancy values. Based on the redundancy value of the first station, the corresponding second station and scheduling equipment are determined in the redundant station sequence to generate shared bicycle scheduling information.

7. The method according to claim 6, characterized in that, The process of determining the corresponding second station and scheduling device in the redundant station sequence based on the redundancy value of the first station, and generating shared bicycle scheduling information, includes: If the absolute value of the redundancy of the first station is less than or equal to the absolute value of the redundancy of the first second station in the redundancy station sequence; Then, the second station whose absolute value of redundancy is greater than or equal to that of the first station and whose absolute value of redundancy is closest to that of the first station is determined as the mutual scheduling station. Based on the redundancy value of the first station, the scheduling equipment and the number of equipment with corresponding attributes are determined to obtain the shared bicycle scheduling information.

8. The method according to claim 6, characterized in that, Also includes: If the absolute value of the redundancy of the first station is greater than the absolute value of the redundancy of the first second station in the redundancy station sequence; After removing the first second station, the remaining second stations are sorted in ascending order to obtain an ascending sequence. The redundancy values ​​of the removed second stations are selected sequentially according to the ascending sequence and added to obtain a sum. If the absolute value of the sum is greater than or equal to the absolute value of the redundancy value of the first station, the corresponding multiple second stations are used as combined scheduling stations. Based on the redundancy value of the first station, the scheduling equipment and the number of equipment with corresponding attributes are determined to obtain the shared bicycle scheduling information.

9. The method according to claim 7 or 8, characterized in that, The process of determining the scheduling devices and their quantities based on the redundancy value of the first station to obtain shared bicycle scheduling information includes: All scheduling devices within a preset range of the first site are selected as the first scheduling device; A scheduling direction is established from the second station toward the first station. The corresponding scheduling equipment is determined based on the redundancy value of the second station. Each type of scheduling equipment has a preset value range for its attributes. If the value range of the scheduling device is less than the redundancy value of the second station, the number of devices is obtained by comparing the redundancy value with the maximum value of the value range.

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