Parking lot recommendation method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a parking lot recommendation method and device, electronic equipment and a storage medium, and belongs to the technical field of data processing. The method comprises the steps that first historical parking data manually set and uploaded by a parking lot are acquired, and the first historical parking data at least comprises parking lot attribute information of the parking lot and multi-section historical parking characteristic data of multiple time periods; recording first historical parking data according to a preset rule and respectively storing historical parking characteristic data in different time periods; and when a parking request for the parking lot is received, determining a corresponding time period and corresponding historical parking characteristic data according to the parking request, and feeding back the historical parking characteristic data of the corresponding time period. According to the invention, the historical parking characteristic curve of the corresponding time period is generated according to the manually set and uploaded first historical parking data, so that the vehicle owner or the platform can be used as a reference index for parking lot selection, and the utilization rate and parking income of the parking lot are improved.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly to a parking lot recommendation method, device, electronic device, and storage medium. Background Art

[0002] With the popularization of smart phones and mobile Internet, more and more car owners are used to checking the situation of nearby parking lots through mobile phone APPs, parking platforms, and navigation maps. In the prior art, the data of parking lots is obtained in real time by a parking lot information management platform through network connection with parking lot management devices, including the remaining number of parking spaces, parking fees, and other parking data.

[0003] However, for many old parking lots or some parking lots with devices that cannot be networked, due to technical and cost limitations, these parking lots cannot upload this information to the parking lot information management platform in real time. Due to the lack of support for real-time data, the relevant information of these parking lots cannot be updated in a timely manner. Therefore, when choosing a parking lot, car owners or platform recommendations often give priority to excluding these parking lots with inaccurate or untimely updated information, thus reducing the utilization rate of parking lots. Summary of the Invention

[0004] To solve the above technical problems, embodiments of this application provide a parking lot recommendation method, device, electronic device, and storage medium.

[0005] In a first aspect, embodiments of this application provide a parking lot recommendation method, and the method includes:

[0006] Obtain first historical parking data manually set and uploaded by a parking lot, where the first historical parking data includes at least the parking lot attribute information of the parking lot and multiple segments of historical parking characteristic data for multiple time periods;

[0007] Record the first historical parking data according to a preset rule and store the historical parking characteristic data for different time periods separately;

[0008] When a parking request for the parking lot is received, determine the corresponding time period and the corresponding historical parking characteristic data according to the parking request, and feedback the historical parking characteristic data for the corresponding time period.

[0009] In an implementation manner, the recording the first historical parking data according to a preset rule and storing the historical parking characteristic data for different time periods separately includes:

[0010] When the historical parking characteristic data is a historical parking characteristic curve, store each segment of the historical parking characteristic curve separately according to different classifications for different time periods;

[0011] When the historical parking characteristic data is parking space data, analyze the change of parking space data in the same time period to generate a historical parking characteristic curve for the corresponding time period, and store each segment of the historical parking characteristic curve according to different classifications in different time periods.

[0012] In one embodiment, the method further includes:

[0013] Obtain multiple curve nodes of the historical parking characteristic curve;

[0014] Manually adjust at least one of the curve nodes, and update the historical parking characteristic curve to obtain a new historical parking characteristic curve.

[0015] In one embodiment, the method further includes:

[0016] Receive the second historical parking data manually set and uploaded by the parking lot, and determine whether the second historical parking data is the same as the first historical parking data;

[0017] If not, update the historical parking characteristic curve for the corresponding time period according to the second historical parking data.

[0018] In one embodiment, the method further includes:

[0019] Obtain the evaluation information of the user;

[0020] Determine the target historical parking characteristic curve for the corresponding time period according to the evaluation information, and analyze the evaluation information to mark the recommended value for the target historical parking characteristic curve;

[0021] Determine whether the target historical parking characteristic curve needs to be updated according to the recommended value mark;

[0022] If so, notify the parking lot to re-upload the historical parking data for the corresponding time period.

[0023] In one embodiment, when receiving a parking request for the parking lot, determine the corresponding time period and corresponding historical parking characteristic data according to the parking request, and feedback the historical parking characteristic data for the corresponding time period, including:

[0024] Obtain the parking request initiated by the user for the parking lot, and feedback the historical parking characteristic curve for the corresponding time period to the user;

[0025] Or, obtain the parking request initiated by the parking platform for the parking lot based on the user request, and feedback the historical parking characteristic curve for the corresponding time period to the parking platform.

[0026] In one embodiment, the historical parking characteristic data further includes: parking space occupancy rate and / or the number of occupied parking spaces;

[0027] Select time periods in which the parking space occupancy rate and / or the number of occupied parking spaces in each of the time periods is greater than or equal to a first preset threshold, and use the corresponding time periods as peak time periods;

[0028] Select time periods in which the parking space occupancy rate and / or the number of occupied parking spaces in each of the time periods is less than a second preset threshold, and use the corresponding time periods as off-peak time periods;

[0029] Determine a parking lot heat map according to the peak time periods and the off-peak time periods.

[0030] In a second aspect, an embodiment of the present application provides a parking lot recommendation device, which includes:

[0031] An acquisition module, configured to acquire first historical parking data manually set and uploaded by a parking lot, where the first historical parking data at least includes the parking lot attribute information of the parking lot and multiple segments of historical parking characteristic data for multiple time periods;

[0032] A calculation module, configured to record the first historical parking data according to a preset rule and store the historical parking characteristic data for different time periods respectively;

[0033] A feedback module, configured to, when receiving a parking request for the parking lot, determine a corresponding time period and corresponding historical parking characteristic data according to the parking request, and feedback the historical parking characteristic data for the corresponding time period.

[0034] In a third aspect, an embodiment of the present application provides a parking lot recommendation device, including a memory and a processor, where the memory is used to store a computer program, and the computer program executes the parking lot recommendation method provided in the first aspect when running on the processor.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and the computer program executes the parking lot recommendation method provided in the first aspect when running on a processor.

[0036] The above-mentioned parking lot recommendation method, device, electronic device and storage medium provided by the present application, wherein the parking lot recommendation method includes: obtaining first historical parking data manually set and uploaded by the parking lot, the first historical parking data at least including the parking lot attribute information of the parking lot and multiple segments of historical parking characteristic data in multiple time periods; recording the first historical parking data according to preset rules and storing the historical parking characteristic data in different time periods respectively; when receiving a parking request for the parking lot, determining the corresponding time period and the corresponding historical parking characteristic data according to the parking request, and feeding back the historical parking characteristic data in the corresponding time period. The present application realizes that even if the parking data of the parking lot equipment cannot be obtained, it is still possible to provide the historical parking characteristic data in the corresponding time period for the vehicle owner or the platform as a reference index for parking lot selection by means of the first historical parking data manually set and uploaded, thereby improving the utilization rate of the parking lot and the parking revenue. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the present application, the accompanying drawings required for the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application and should not be regarded as limiting the protection scope of the present application. In each drawing, similar components are numbered similarly.

[0038] Figure 1 FIG. 1 shows a first flowchart of the parking lot recommendation method provided by an embodiment of the present application;

[0039] Figure 2 FIG. 2 shows a second flowchart of the parking lot recommendation method provided by an embodiment of the present application;

[0040] Figure 3 FIG. 3 shows a third flowchart of the parking lot recommendation method provided by an embodiment of the present application;

[0041] Figure 4 FIG. 4 shows a fourth flowchart of the parking lot recommendation method provided by an embodiment of the present application;

[0042] Figure 5 FIG. 5 shows a fifth flowchart of the parking lot recommendation method provided by an embodiment of the present application;

[0043] Figure 6 FIG. 6 shows a sixth flowchart of the parking lot recommendation method provided by an embodiment of the present application;

[0044] Figure 7 FIG. 7 shows a structural diagram of the parking lot recommendation device provided by an embodiment of the present application;

[0045] Figure 8 Fig. 3 shows a schematic structural diagram of a parking lot recommendation device provided by an embodiment of the present application.

[0046] Icons: 700 - parking lot recommendation device, 701 - acquisition module, 702 - calculation module, 703 - feedback module, 800 - parking lot recommendation equipment, 801 - memory, 802 - processor. Detailed implementation manners

[0047] Next, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments.

[0048] Generally, the components of the embodiments of the present application described and illustrated herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application claimed, but merely represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts fall within the scope of protection of the present application.

[0049] In the following text, the terms "including", "having" and their cognates that can be used in various embodiments of the present application are only intended to indicate specific features, numbers, steps, operations, elements, components or combinations of the foregoing items, and should not be construed as first excluding the existence of one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing items or increasing the possibility of one or more features, numbers, steps, operations, elements, components or combinations of the foregoing items.

[0050] In addition, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0051] Unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the various embodiments of the present application belong. Terms (such as those defined in a general use dictionary) will be interpreted as having the same meaning as the contextual meaning in the relevant technical field and will not be interpreted as having an idealized meaning or being overly formal, unless clearly defined in the various embodiments of the present application.

[0052] With the acceleration of the urbanization process, parking lot management has become an important part of urban management. In recent years, parking lot information platforms have gradually emerged. Many car owners and platforms obtain data such as the busy situation of nearby parking lots and parking fee information through the parking lot information platform, so as to make more reasonable parking choices and parking lot recommendations. For example, some parking lot information platforms provide the location information of the parking lot, as well as the real-time parking space occupancy and price changes, which greatly facilitates the parking choices of car owners and also provides convenience for the parking recommendations and marketing promotions of the platform.

[0053] However, due to historical reasons, as well as the limitations of technology and funds in some parking lots or problems such as network failures, there are many old parking lots and parking lots that do not choose to have the ability to upload data. The equipment in these parking lots cannot be connected to the platform or cannot upload parking lot data in real time. The parking lot equipment in these parking lots cannot conduct effective data exchange with the platform, resulting in the platform being unable to obtain relevant information about these parking lots. Therefore, when displaying the information of these parking lots on the platform, only the parking lot attribute information such as the parking lot address, the number of parking spaces, and the parking price is often displayed. For the current number of vacant parking spaces and the number of vacant parking spaces of different types in the parking lot, as well as the real-time parking price and the remaining number of parking packages that need to be updated in a timely manner, this information is often not displayed in the parking lot information displayed by the platform for these parking lots. This leads to concerns for users when choosing a parking lot and for the platform when providing parking recommendations, as they cannot obtain relevant information. Without data support, users and the platform will prioritize excluding these parking lots when choosing a parking lot, reducing the utilization rate and revenue of these parking lots. To solve the above problems, this application proposes a parking lot recommendation method.

[0054] Embodiment 1

[0055] The embodiment of this application provides a parking lot recommendation method.

[0056] See Figure 1 , the parking lot recommendation method includes:

[0057] S101, obtain the first historical parking data manually set and uploaded by the parking lot. The first historical parking data includes at least the parking lot attribute information of the parking lot and multiple segments of historical parking characteristic data for multiple time periods.

[0058] It should be noted that the first historical parking data obtained by manually setting and uploading in the parking lot is usually the first historical parking data manually counted by the staff in the parking lot according to the daily operation data of the parking lot or manually exported from the parking lot server. At the same time, it can also be the empirical data obtained by the parking staff based on daily experience, and then the historical parking characteristic curve manually drawn according to the empirical data, or the first historical parking data of the parking lot obtained and uploaded from the parking lot server in the form of manually installing and uploading scripts.

[0059] It should be noted that the first historical parking data includes, but is not limited to, the parking lot property information of the parking lot and the historical parking characteristic data of multiple time periods. Among them, the historical parking characteristic data can be the historical parking characteristic curves of each time period, or the parking space data of different time periods, where each time period records the continuous change of the parking space data.

[0060] Furthermore, it should be noted that the first historical parking data obtained by manually setting and uploading in the parking lot is usually saved in the Excel or CSV format. At the same time, the historical parking data is verified, and the verified historical parking data is obtained from the historical parking data. The historical parking data format described in the embodiments of the present application is to standardize the types and data formats of the data reported by each parking lot, so that the platform can automatically process the data manually set and uploaded by each parking lot. In actual applications, it can also be set to other formats in addition to the above formats. Therefore, the historical parking data format is not limited to the above formats.

[0061] The verification process is as follows: Check the time sequence to check whether the vehicle entry time and the vehicle exit time are in logical order; Detect duplicate or missing data to check whether there are duplicate records or missing important data; Process abnormal data. If data format errors or abnormal data are found, prompt or automatically filter the data. Among them, the specific verification process can be set according to requirements, and this application does not make any limitations here. The verification of the first historical parking data manually set and uploaded in the parking lot in this application is to eliminate the obvious abnormal data in the first historical parking data and avoid the abnormal data affecting the accuracy of the historical parking characteristic curves of each time period.

[0062] Furthermore, it should be noted that the historical parking characteristic data includes, but is not limited to: one day or some time periods within a day in different types of time periods such as working days, non-working days, holidays, non-holidays, event days, and non-event days, as well as the corresponding number of available parking spaces and parking fee data in different time periods. The data of each time period usually includes at least the parking space occupancy rate and / or the number of remaining parking spaces in the parking lot for a whole day. The parking lot property of the parking lot includes, but is not limited to: the location of the parking lot, the type of the parking lot, the number of parking spaces in the parking lot, whether there is a charging pile, etc.

[0063] It should be understood that by obtaining the historical parking characteristic data for a whole day on different dates, the parking characteristic curve of the parking lot within a day on different dates can be determined. For example, for the parking lot in a business and office area: the peak parking period on weekdays is concentrated from 7:30 to 18:30, and there are relatively sufficient parking spaces at other times. The parking spaces are relatively sufficient throughout the day on weekends and holidays. For the parking lot in a community: the peak parking period on weekdays is concentrated from 19:30 to 7:30, and there are relatively sufficient parking spaces at other times. The whole day on weekends is the peak parking period, and the parking spaces are relatively sufficient throughout the day on holidays. For the parking lot around tourist attractions: the parking spaces are relatively sufficient throughout the day on weekdays, and the whole day on weekends and holidays is the peak parking period. Based on the first historical parking data manually uploaded by the parking lot, the historical parking characteristic curve of the parking lot at different time periods can be drawn. The historical parking characteristic curve includes, but is not limited to, different types of curves such as the curve of the proportion of empty parking spaces, the curve of the number of empty parking spaces, and the parking price curve. The time period in this application can be a time period based on days or a time period based on hours, which is not limited in this application. After obtaining the parking characteristic curves of multiple dates, the corresponding historical parking characteristic curve can be matched according to the type of the current date, so as to predict the most likely parking situation of the parking lot on the current date, and further help the car owner and the platform make parking decisions.

[0064] In this application, the first historical parking data is manually set and uploaded to obtain the historical parking characteristic data of the parking lot, so that the parking lot that cannot be connected to the network or has a network failure can also accurately predict the usage of parking spaces at different time periods according to the manually set and uploaded historical parking characteristic data, and further help the car owner effectively avoid the peak parking period of the parking lot. The relevant prediction results can not only be directly displayed to the user to provide convenience for their travel parking plan, but also be applied to the parking lot recommendation of the platform to improve the accuracy and practicality of the recommendation.

[0065] In an alternative embodiment, as Figure 2 shown, a parking lot recommendation method provided in this application further includes: S1011, receiving the second historical parking data manually set and uploaded by the parking lot, and judging whether the second historical parking data is the same as the first historical parking data; S1012, if not, updating the historical parking characteristic curve of the corresponding time period according to the second historical parking data.

[0066] It should be noted that due to various factors such as changes in nearby office enterprises, changes in the number of residents, and changes in the popularity of scenic spots in different parking lots, the parking characteristics of the parking lot will change. Therefore, it is necessary to require the parking lot to manually set and upload the second historical parking data regularly or irregularly, so as to update the historical parking characteristic curve of the parking lot in time and improve the matching degree between the historical parking characteristic curve of the parking lot and the actual situation.

[0067] Among them, the first historical parking data or the second historical parking data includes: the total number of parking spaces, the number of incoming vehicles in each parking time period, and the number of outgoing vehicles in each parking time period. The occupied number of parking spaces in the \(i\)th parking time period is obtained based on the number of incoming vehicles in the \(i\)th parking time period, the number of outgoing vehicles in the \(i\)th parking time period, and the occupied number of parking spaces in the \((i - 1)\)th parking time period. The parking space occupancy rate and the number of remaining parking spaces in the parking lot in the \(i\)th parking time period are determined based on the occupied number of parking spaces in the \(i\)th parking time period and the total number of parking spaces. By continuously receiving new historical parking data, the historical parking characteristic curve for the corresponding time period obtained previously is dynamically updated to ensure it is always fresh and useful.

[0068] Furthermore, the staff of the parking lot can select the second historical parking data according to their needs. For example, they can choose to import the second historical parking data for parking fees and license plate numbers. By statistically analyzing the second historical parking data, the number of incoming and outgoing vehicles in the parking lot can be counted according to a custom time period. By calculating the difference between the number of incoming vehicles and the number of outgoing vehicles, and determining the sum of the occupied number of parking spaces in the previous time period and the difference, the occupied number of parking spaces in this time period is obtained. By calculating the quotient of this time period and the total number of parking spaces, the parking space occupancy rate is obtained. By calculating the difference between the total number of parking spaces and the occupied number of parking spaces in this time period, the number of remaining parking spaces in the parking lot is obtained.

[0069] For example, there is a parking lot with a total of 500 parking spaces. The number of vehicles entering and leaving is counted every hour. During the one-hour period from 10:00 am to 11:00 am on a weekday, the number of incoming vehicles is 80, and the number of outgoing vehicles is 30. Given that the occupied number of parking spaces in the previous hour (from 9:00 am to 10:00 am) is 200, then the occupied number of parking spaces in this hour is: 200 + 80 - 30 = 250. The occupancy rate from 10:00 am to 11:00 am is: 250 / 500 × 100% = 50%, and the number of remaining parking spaces is: 500 - 250 = 250.

[0070] In the embodiments of the present application, parking data for multiple days can be collected and counted by the staff in the parking lot. Based on this, occupancy curves of parking spaces for one day or certain time periods within a day can be drawn for different types of time periods such as weekdays, non - weekdays, holidays, event days, and non - event days, visually presenting the changing trend of the parking space usage in the parking lot over time during approximate time periods (such as weekday time periods, weekend time periods, holiday time periods, etc.). And according to the needs of car owners and the platform, the parking lot can be intelligently displayed and recommended. Even without real - time data support from the parking lot, the parking lot data collection platform can still provide historical parking characteristic curves for corresponding time periods to users or other platforms, so as to obtain the actual parking lot busy situation and charging information close to the current time period, optimizing the parking decision - making process of car owners and the platform, and improving the utilization rate of parking resources and operating revenue of this part of the parking lot. Of course, it can be understood that the staff can also directly draw historical parking characteristic curves for different time periods according to needs.

[0071] In an alternative embodiment, as Figure 3 shown, the historical parking characteristic data further includes: parking space occupancy rate and / or the number of occupied parking spaces. After step S1012, it includes: S1013, selecting time periods in which the parking space occupancy rate and / or the number of occupied parking spaces in each time period are greater than or equal to a first preset threshold, and taking the corresponding time periods as peak time periods. S1014, selecting time periods in which the parking space occupancy rate and / or the number of occupied parking spaces in each time period are less than a second preset threshold, and taking the corresponding time periods as valley time periods. S1015, determining the parking lot heat map according to the peak time periods and valley time periods.

[0072] In the embodiments of the present application, taking the parking space occupancy rate as an example, the first preset threshold can be set to 80%, and the second preset threshold can be set to 20%. The time periods corresponding to the parking space occupancy rates greater than 80% in each parking time period are taken as peak time periods, and the time periods corresponding to the parking space occupancy rates less than 20% in each parking time period are taken as valley time periods. The parking lot heat map is generated by marking the peak time periods and valley time periods in a day. Among them, the first preset threshold and the second preset threshold can be set according to needs, and the present application does not make any limitations here. Similarly, the parking space vacancy rate and / or the number of vacant parking spaces can also be used as the coordinates of the curve.

[0073] S102, recording the first historical parking data according to preset rules and storing the historical parking characteristic data for different time periods respectively.

[0074] When the historical parking characteristic data is a historical parking characteristic curve, each segment of the historical parking characteristic curve is stored separately according to different classifications in different time periods; when the historical parking characteristic data is parking space data, the change situation of the parking space data in the same time period is analyzed to generate a historical parking characteristic curve for the corresponding time period, and each segment of the historical parking characteristic curve is stored separately according to different classifications in different time periods.

[0075] Optionally, the change situation of the parking space data in the same time period is analyzed to generate a historical parking characteristic curve for the corresponding time period, wherein the algorithms for generating the historical parking characteristic curve include but are not limited to any one of the normal distribution algorithm, Bernoulli distribution algorithm, binomial distribution algorithm, Poisson distribution algorithm, and gamma distribution algorithm.

[0076] In an alternative embodiment, as Figure 4 shown, step S102 further includes: S1021, obtaining a parking request initiated by a user for a parking lot and feeding back the historical parking characteristic curve for the corresponding time period to the user; S1022, or obtaining a parking request initiated by a parking platform for the parking lot based on the user request and feeding back the historical parking characteristic curve for the corresponding time period to the parking platform.

[0077] After the platform generates the historical parking characteristic curves of the parking lot in different time periods, the platform can display the historical parking characteristic curves of the corresponding parking lot in the corresponding time period to the user according to the user's instruction, so that the user can determine whether the current parking lot is in a peak period or a trough period based on the historical parking characteristic curve, and whether the current parking price is in a high-price time period or a low-price time period, so as to decide whether to go to the corresponding parking lot to park and estimate the parking fee, etc.; at the same time, the platform itself will also read the historical parking characteristic curves of each parking lot according to the user's parking demand, and recommend and display parking lots to the user according to the historical parking characteristic curves of each parking lot for the user to choose, which is convenient for the user to quickly find a suitable parking lot.

[0078] In the embodiment of the present application, the historical parking characteristic curve further includes: a parking space occupancy rate curve, by determining multiple key parking time periods on the 24-hour time axis, then determining the time interval and occupancy rate change range between two key time points, and then evenly distributing the occupancy rate values of the intermediate points according to a linear relationship to generate a parking space occupancy rate curve. The historical parking characteristic curve further includes: a parking price curve, by determining the parking prices of multiple key parking time periods on the 24-hour time axis, then determining the time interval and parking price change range between two key time points, and then evenly distributing the occupancy rate values of the intermediate points according to a linear relationship to generate a parking price change curve.

[0079] In an alternative embodiment, as Figure 5As shown, after step S1021, it includes: S1023, obtaining multiple curve nodes of the historical parking characteristic curve. S1024, manually adjusting at least one curve node and updating the historical parking characteristic curve to obtain a new historical parking characteristic curve.

[0080] It should be understood that the historical parking characteristic data obtained based on the first historical parking data can be a historical parking characteristic curve calculated by the server at the platform end according to a preset algorithm, or a historical parking characteristic curve directly set and uploaded. Since the actual situations of different parkings are different, after the historical parking characteristic curve is output, multiple curve nodes can be marked on the historical parking characteristic curve subsequently, which is convenient for adjusting the historical parking characteristic curve in a manual adjustment manner, so that the historical parking characteristic curve better conforms to the current actual situation. It should be noted that the adjustment permission of the historical parking characteristic curve is usually only open to platform staff and parking lot staff, but it will also be open to users. However, the adjustment of the curve by users needs to be reviewed before it becomes valid data.

[0081] In the embodiment of the present application, by checking the obtained historical parking characteristic curve, it is judged whether there is an unreasonable mutation situation. By setting a reasonable mutation threshold, the rationality of the historical parking characteristic curve is judged. If the mutation between adjacent time periods is too large, such as 100% at 8 o'clock and 25% at 9 o'clock, the user is reminded to optimize the historical parking characteristic curve, or a smooth transition curve for selection is generated. The data can be adjusted by dragging the curve nodes, and the historical parking characteristic curve can be automatically re-completed.

[0082] The present application simplifies data entry and reduces the burden on parking lot management personnel through automatic completion and smoothing optimization, while ensuring the rationality of the regular curve. It enables parking lot management personnel to conveniently upload and maintain data and reduces the operation difficulty.

[0083] S103, when receiving a parking request for a parking lot, determining the corresponding time period and corresponding historical parking characteristic data according to the parking request, and feeding back the historical parking characteristic data of the corresponding time period.

[0084] In an embodiment of the present application, by collecting and statistically analyzing parking data over multiple days, historical parking characteristic curves for weekdays, non-weekdays, holidays, and non-holidays can be plotted based on this. This visually presents the changing trend of parking space usage over time and intelligently recommends parking lots according to the needs of vehicle owners. Even without real-time data support, vehicle owners can still obtain information on the approximate actual busyness and charges of parking lots, optimizing the parking decision-making process. By setting the basic information of the parking lot or analyzing historical parking lot records, the present application enables parking lots in an offline environment and an environment where historical parking data cannot be obtained to predict current parking data, providing more parking options for vehicle owners.

[0085] In an alternative embodiment, as Figure 6 shown, after step S103, it includes: S104, obtaining the evaluation information of the user. S105, determining the target historical parking characteristic curve for the corresponding time period according to the evaluation information, and analyzing the evaluation information to mark the recommended value for the target historical parking characteristic curve. S106, determining whether the target historical parking characteristic curve needs to be updated according to the recommended value mark. S107, when it is yes, notifying the parking lot to re-upload the historical parking data for the corresponding time period.

[0086] It should be noted that, by marking the recommended value for the target historical parking characteristic curve according to the evaluation information of the user, if the evaluation feedback by the user is that the parking prediction is inaccurate, the target historical parking characteristic curve for the corresponding time period is updated to ensure that the curve can accurately reflect the actual parking pattern, thereby effectively preventing the inaccurate curve from being frequently pushed to the user and avoiding reducing the user experience due to inaccurate recommendations.

[0087] The parking lot recommendation method provided in this embodiment obtains the first historical parking data manually uploaded by the parking lot. The first historical parking data includes at least the parking lot attribute information of the parking lot and multiple historical data for multiple time periods; uses a preset algorithm to calculate and store the historical parking characteristic curves of the parking lot for different time periods according to the first historical parking data; when receiving a parking request for the parking lot, determines the corresponding time period and the corresponding historical parking characteristic curve according to the parking request, and feeds back the historical parking characteristic curve for the corresponding time period. By obtaining the first historical parking data manually uploaded by the parking lot, calculating and generating the historical parking characteristic curves of the parking lot for different time periods, and feeding back the historical parking characteristic curve for the corresponding time period according to the parking request, the present application realizes that even if the parking data of the parking lot equipment cannot be obtained, it is still possible to provide the historical parking characteristic curve for the corresponding time period based on the first historical parking data manually uploaded for vehicle owners or platforms as a reference index for parking lot selection, thereby improving the utilization rate of the parking lot.

[0088] Embodiment 2

[0089] In addition, an embodiment of the present application provides a parking lot recommendation device.

[0090] As Figure 7 shown, the parking lot recommendation device 700 includes:

[0091] An acquisition module 701, configured to acquire first historical parking data manually set and uploaded by a parking lot, where the first historical parking data at least includes the parking lot attribute information of the parking lot and multiple segments of historical parking characteristic data for multiple time periods;

[0092] A calculation module 702, configured to record the first historical parking data according to a preset rule and store the historical parking characteristic data for different time periods respectively;

[0093] A feedback module 703, configured to, when receiving a parking request for a parking lot, determine the corresponding time period and the corresponding historical parking characteristic data according to the parking request, and feedback the historical parking characteristic data for the corresponding time period.

[0094] The parking lot recommendation device 700 provided in this embodiment can implement the parking lot recommendation method provided in Embodiment 1. To avoid repetition, it will not be elaborated here.

[0095] The parking lot recommendation device provided in this embodiment calculates and generates historical parking characteristic curves of the parking lot at different time periods by acquiring the first historical parking data manually uploaded by the parking lot, and feeds back the historical parking characteristic curves for the corresponding time periods according to the parking request, realizing that even if the parking data of the parking lot equipment cannot be obtained, the historical parking characteristic curves for the corresponding time periods can still be provided based on the first historical parking data manually uploaded for the reference of car owners or platforms as indicators for parking lot selection, thereby improving the utilization rate of the parking lot.

[0096] Embodiment 3

[0097] An embodiment of the present application further provides a parking lot recommendation device. For details, please refer to Figure 8 , Figure 8 , which is the basic structural block diagram of the parking lot recommendation device in this embodiment.

[0098] The parking lot recommendation device 800 includes a memory 801 and a processor 802 that are communicatively connected to each other via a system bus. It should be noted that only the parking lot recommendation device 800 having the memory 801 and the processor 802 is shown in the figure, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented. Among them, those skilled in the art of this technology can understand that the parking lot recommendation device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0099] The parking lot recommendation device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The parking lot recommendation device can perform human-computer interaction with the user through means such as a keyboard, a mouse, a remote control, a touchpad, or a voice control device.

[0100] The memory 801 includes at least one type of readable storage medium. The readable storage medium includes flash memory, hard disks, multimedia cards, card-type memories (such as SD or D-slot compatibility test memories, etc.), random access memories (RAMs), static random access memories (SRAMs), read-only memories (ROMs), electrically erasable programmable read-only memories (EEPROMs), programmable read-only memories (PROMs), magnetic memories, magnetic disks, optical disks, etc. In some embodiments, the memory 801 can be an internal storage unit of the parking lot recommendation device 800, such as the hard disk or memory of the parking lot recommendation device 800. In other embodiments, the memory 801 can also be an external storage device of the parking lot recommendation device 800, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the parking lot recommendation device 800. Of course, the memory 801 can also include both the internal storage unit and the external storage device of the parking lot recommendation device 800. In this embodiment, the memory 801 is generally used to store the operating system and various application software installed on the parking lot recommendation device 800, such as computer-readable instructions for the slot compatibility test method. In addition, the memory 801 can also be used to temporarily store various data that have been output or will be output.

[0101] The processor 802 may be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other parking lot recommendation chips in some embodiments. The processor 802 is generally used to control the overall operation of the parking lot recommendation device 800. In this embodiment, the processor 802 is used to run the computer-readable instructions stored in the memory 801 or process data, such as running the computer-readable instructions of the slot compatibility test method.

[0102] The parking lot recommendation device provided in this embodiment may execute the above-mentioned parking lot recommendation method. Here, the parking lot recommendation method may be the parking lot recommendation methods of the above various embodiments.

[0103] Embodiment 4

[0104] This application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the parking lot recommendation method provided in Embodiment 1.

[0105] In this embodiment, the computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disc, etc.

[0106] The computer-readable storage medium provided in this embodiment can implement the parking lot recommendation method provided in Embodiment 1. To avoid repetition, it will not be elaborated here.

[0107] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or terminal. Without more limitations, the element defined by the statement "including a..." does not exclude the existence of another identical element in the process, method, article or terminal including the element.

[0108] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described example methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of the present application.

[0109] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them fall within the protection scope of the present application.

Claims

1. A parking lot recommendation method, characterized in that: The method comprises: Acquire first historical parking data manually set and uploaded by the parking lot, wherein the first historical parking data at least includes parking lot attribute information of the parking lot and multiple sections of historical parking characteristic data in multiple time periods; Record the first historical parking data according to a preset rule and store the historical parking characteristic data of different time periods respectively; When a parking request for the parking lot is received, a corresponding time period and corresponding historical parking characteristic data are determined according to the parking request, and the historical parking characteristic data of the corresponding time period is fed back.

2. The parking lot recommendation method according to claim 1, characterized in that: The recording of the first historical parking data according to a preset rule and storing the historical parking characteristic data of different time periods respectively include: When the historical parking characteristic data is a historical parking characteristic curve, each section of the historical parking characteristic curve is stored according to different classifications of different time periods; When the historical parking characteristic data is parking space data, the parking space data changes in the same time period are analyzed to generate a historical parking characteristic curve for the corresponding time period, and each section of the historical parking characteristic curve is stored according to different classifications of different time periods.

3. The parking lot recommendation method according to claim 2, characterized in that: The method further comprises: Acquire a plurality of curve nodes of the historical parking characteristic curve; At least one of the curve nodes is manually adjusted, and the historical parking characteristic curve is updated to obtain a new historical parking characteristic curve.

4. The parking lot recommendation method according to claim 2, characterized in that: The method further comprises: receiving second historical parking data manually set and uploaded by the parking lot, and determining whether the second historical parking data is the same as the first historical parking data; If they are not the same, the historical parking characteristic curve of the corresponding time period is updated according to the second historical parking data.

5. The parking lot recommendation method according to claim 2, characterized in that: The method further comprises: Get user evaluation information; Determine a target historical parking characteristic curve for a corresponding time period according to the evaluation information, and analyze the evaluation information to mark the target historical parking characteristic curve with a recommended value; Determining whether the target historical parking characteristic curve needs to be updated according to the recommended value mark; If yes, the parking lot is notified to re-upload the historical parking data of the corresponding time period.

6. The parking lot recommendation method according to claim 2, characterized in that: When receiving a parking request for the parking lot, determining a corresponding time period and corresponding historical parking characteristic data according to the parking request, and feeding back the historical parking characteristic data of the corresponding time period, including: Acquire a parking request initiated by a user for the parking lot, and feed back a historical parking characteristic curve of a corresponding time period to the user; Or, a parking request initiated by the parking platform for the parking lot based on a user request is obtained, and a historical parking characteristic curve of a corresponding time period is fed back to the parking platform.

7. The parking lot recommendation method according to any one of claims 1 to 6, characterized in that: The historical parking characteristic data also includes: parking space occupancy rate and / or number of occupied parking spaces; Selecting a time period that is greater than or equal to a first preset threshold value from among the parking space occupancy rates and / or the number of occupied parking spaces in each of the time periods, and taking the corresponding time period as a peak time period; Selecting a time period that is less than a second preset threshold value from the parking space occupancy rate and / or the number of occupied parking spaces in each time period, and using the corresponding time period as a valley time period; A parking lot thermal curve is determined according to the peak time period and the valley time period.

8. A parking lot recommendation device, characterized in that: The device comprises: An acquisition module, used to acquire first historical parking data manually set and uploaded by a parking lot, wherein the first historical parking data at least includes parking lot attribute information of the parking lot and multiple segments of historical parking characteristic data in multiple time periods; a calculation module, recording the first historical parking data according to a preset rule and storing the historical parking characteristic data of different time periods respectively; The feedback module is used to determine a corresponding time period and corresponding historical parking characteristic data according to the parking request when receiving a parking request for the parking lot, and to feed back the historical parking characteristic data of the corresponding time period.

9. A parking lot recommendation device, characterized in that: include: Memory, used to store programs; A processor, configured to implement the parking lot recommendation method according to any one of claims 1 to 7 by executing the program stored in the memory.

10. A computer-readable storage medium, characterized in that: The computer program stores a computer program, which executes the parking lot recommendation method according to any one of claims 1 to 7 when running on a processor.

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