WO2019237522A1 - 车辆租赁方法、装置、计算机设备和存储介质 - Google Patents

车辆租赁方法、装置、计算机设备和存储介质 Download PDF

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Publication number
WO2019237522A1
WO2019237522A1 PCT/CN2018/104768 CN2018104768W WO2019237522A1 WO 2019237522 A1 WO2019237522 A1 WO 2019237522A1 CN 2018104768 W CN2018104768 W CN 2018104768W WO 2019237522 A1 WO2019237522 A1 WO 2019237522A1
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rental
incentive
point
vehicle
terminal
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PCT/CN2018/104768
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English (en)
French (fr)
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陈颖聪
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平安科技（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0645—Rental transactions; Leasing transactions

Definitions

  • the present application relates to a vehicle rental method, device, computer equipment, and storage medium.
  • a vehicle rental method, apparatus, computer equipment, and storage medium are provided.
  • a method for leasing a vehicle comprising: acquiring a map of a monitoring area, determining a plurality of rental points in the monitoring area according to the map; and collecting data on the vehicle in and out of a plurality of rental points during multiple monitoring periods of a historical monitoring cycle
  • a vehicle rental device includes: a rental point determination module for acquiring a map of a monitoring area, and determining a plurality of rental points in the monitoring area according to the map; a demand measurement calculation module for collecting multiple leases The shared vehicle access data at multiple monitoring periods in the historical monitoring cycle; input the shared vehicle access data into a preset vehicle rental model to determine the conventional demand for shared vehicles at each of the rental points; a rental strategy generation module For generating a rental strategy for the monitoring area in the multiple monitoring periods of the current monitoring cycle according to the conventional demand; and an incentive resource transfer module for identifying whether a shared vehicle reaches the rental point, based on the rental strategy A resource transfer is performed to a user of the shared vehicle arriving at the rental point.
  • a computer device includes a memory and one or more processors.
  • the memory stores computer-readable instructions.
  • the steps of the vehicle rental method provided in any embodiment of the present application are implemented.
  • One or more non-volatile storage media storing computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors implement the vehicle provided in any one of the embodiments of the present application Steps in the lease method.
  • FIG. 1 is an application scenario diagram of a vehicle rental method according to one or more embodiments.
  • FIG. 2 is a schematic flowchart of a vehicle rental method according to one or more embodiments.
  • FIG. 3A is a structural block diagram of a vehicle rental device according to one or more embodiments.
  • FIG. 3B is a structural block diagram of a vehicle rental device according to another or more embodiments.
  • FIG. 3C is a structural block diagram of a vehicle rental device according to one or more embodiments.
  • FIG. 4 is a block diagram of a computer device according to one or more embodiments.
  • the vehicle leasing method provided in this application can be applied to the application environment shown in FIG. 1.
  • the terminal 102 and the server 104 communicate through a network.
  • the terminal 102 may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices.
  • the server 104 may be implemented by an independent server or a server cluster composed of multiple servers.
  • the server 104 periodically updates the leasing strategy for the shared vehicles in the monitored area. Specifically, the server 104 obtains a map of the monitoring area, and determines a plurality of rental points in the monitoring area according to the map.
  • a shared vehicle application is installed on the terminal 102. Buried points are set in the shared vehicle application in advance, which can collect user's operation behavior data.
  • the server 104 obtains the data of the shared vehicle in and out of multiple rental points during multiple monitoring periods in the historical monitoring cycle through statistical analysis of the operation behavior data of a large number of users.
  • the server 104 inputs shared vehicle access data into a preset vehicle leasing model, determines the conventional demand for shared vehicles at multiple rental points, and generates a rental strategy for the monitoring area during multiple monitoring periods of the current monitoring cycle based on the conventional demand and map. .
  • the server 104 starts recording driving data.
  • the server 104 identifies whether the driving end point is located at a rental point, that is, whether the shared vehicle reaches the rental point.
  • the server 104 transfers resources to the users of the shared vehicle arriving at the leasing point based on the leasing policy of the current monitoring period in the current monitoring cycle.
  • the rental strategy is generated based on the rental points in the monitoring area determined periodically and its regular demand for shared vehicles, which can improve the accuracy of the rental strategy; based on the rental strategy, the user is encouraged to be among multiple rental points.
  • Car sharing transfers can increase vehicle utilization.
  • a method for leasing a vehicle is provided.
  • the method is applied to the server in FIG. 1 as an example, and includes the following steps:
  • Step 202 Obtain a map of the monitoring area, and determine a plurality of rental points in the monitoring area according to the map.
  • the monitoring area refers to the geographical area where shared vehicle rental is required. It can be a city, county, or district.
  • monitoring area A can be Shenzhen
  • monitoring area B can be Nanshan District, Shenzhen.
  • the map of the monitoring area is a graphic depicting the distribution of routes, buildings, mountains, rivers, etc. in the monitoring area using lines, symbols, colors, text notes, etc. at a certain scale. Buildings can be public places, such as parks, bus platforms, subway stations, railway stations, and so on.
  • the server determines multiple rental points in the monitored area based on the distribution information of the routes and buildings in the monitored area recorded by the monitored area map.
  • the monitoring area can be divided into multiple sub-areas according to the area area and the like. Leasing point refers to the sub-area with concentrated building distribution and high passenger flow in the monitoring area.
  • the leasing point in monitoring area B may include science park B1 and coast city B2. Each rental point has a corresponding regional boundary.
  • the regional boundary of the rental point technology park B1 can be: south of Beihuan Road in Nanshan District, west of Qiaocheng West Road, north of Binhai Avenue, Houhai Avenue and east of Shenzhen University.
  • the server in this embodiment re-determines multiple rental points in the monitoring area every other monitoring period, and adjusts the rental points in time according to building migration or route changes, etc., to improve scheduling accuracy.
  • the monitoring period can be freely set according to requirements, such as 1 month.
  • step 204 the data of the access of the shared vehicles at multiple rental points during multiple monitoring periods in the historical monitoring cycle is collected.
  • the monitoring period includes multiple monitoring periods. For example, monitoring period 1 may be 7:00 to 9:00, and monitoring period 2 may be 9:00 to 11:00. Monitoring period can also distinguish between working days and holidays. For example, monitoring period 3 can be working days 7: 00 ⁇ 9: 00, monitoring period 4 can be working days 9: 00 ⁇ 12: 00, monitoring period 5 can be holidays 10 : 00 ⁇ 12: 00 and so on.
  • the duration of the monitoring period can be freely set as required, and the duration of different monitoring periods can be different.
  • the monitoring period divided by the monitoring period corresponding to different lease points can be different.
  • the server calculates the regular demand for shared vehicles at multiple rental points every other monitoring cycle, and updates the rental strategy based on the measurement results. Specifically, the server predicts the conventional demand for the shared vehicle at the rental point during different monitoring periods in the current monitoring cycle based on the data of the shared vehicle's access at different monitoring periods in the historical monitoring period.
  • the shared vehicle access data can be obtained by statistically analyzing the operation behavior data of the shared vehicle application on the terminal when a large number of users use the shared vehicle.
  • the operation behavior data includes a plurality of operation identifiers, such as vehicle reservation, scan code unlocking, vehicle lockout, and the like.
  • the operation identification further includes a vehicle application.
  • a "vehicle application” button has been added to the shared vehicle application program to facilitate vehicle users to actively provide timely feedback on the situation of insufficient supply of shared vehicles in a monitoring area.
  • the shared vehicle access data includes the actual operation times of different operating identifications of each rental point in different monitoring periods.
  • Step 206 Enter the shared vehicle access data into a preset vehicle rental model, and determine the conventional demand for shared vehicles from multiple rental points.
  • Each rental point has a corresponding vehicle rental model during multiple monitoring periods of the monitoring cycle.
  • the vehicle rental model of the rental point technology park B1 during the monitoring period 3 may be B1-3
  • the vehicle rental model during the monitoring period 4 may be B1-4.
  • the historical monitoring period may be one or more monitoring periods before the current monitoring period.
  • the server enters the shared vehicle in and out data of a rental point during a monitoring period of the historical monitoring cycle into the vehicle rental model of the rental point during the corresponding monitoring period. It can determine the regular demand for shared vehicles at the same monitoring period of the current monitoring period. .
  • the conventional demand is the number of vehicles that the rental point usually needs to share during this monitoring period.
  • the vehicle rental model of the current monitoring cycle may be obtained by training a general machine learning model using multiple training sample data.
  • the server obtains training sample data of a rental point during a certain monitoring period.
  • the training sample data can be the actual shared vehicle access data of the rental point during the corresponding monitoring period of the historical monitoring cycle, or the shared vehicle input and output data simulated by the rental point during the corresponding monitoring period.
  • the server marks the shared vehicle demand corresponding to each set of training sample data, that is, adds a corresponding demand label to each set of training sample data.
  • the server inputs the training sample data into the general machine learning model to obtain the predicted demand.
  • the universal machine learning model can be a VGG (Visual Geometry Group Visual Network Group) network model, a GoogleNet (Google Network) network model, or a ResNet (Energy Efficiency Evaluation System) network model.
  • the general machine learning model includes multiple model parameters.
  • the server calculates the difference between the predicted demand and the demand label, adjusts the model parameters of the general machine learning model according to the difference, and continues training until the training stop condition is met, and the vehicle rental model of the rental point in the corresponding monitoring period of the current monitoring cycle is obtained. .
  • the server trains in the above manner to obtain a vehicle rental model corresponding to each rental point during multiple monitoring periods in the current monitoring cycle.
  • the server may use the building distribution information, population density information, or shared vehicle history of the rental point. Adjust the regular demand, such as parking information, to improve the accuracy of the regular demand measurement.
  • Step 208 Generate a leasing policy for the monitoring area in multiple monitoring periods of the current monitoring period according to the conventional demand.
  • the server generates a rental strategy for the rental point in the corresponding monitoring period of the current monitoring period based on the conventional demand for the shared vehicle during the monitoring period of the current monitoring period.
  • the leasing strategy records various incentive conditions and different shares of incentive resources corresponding to each incentive condition.
  • Incentive conditions can be a combination of multiple indicators, such as the driving time, driving route, driving end point is the rental point, the driving point corresponding to the rental point, the combination of the conventional demand for the shared vehicle and the current parking amount.
  • Incentive resources can be capital resources or authority resources. Among them, the funding resources can be voucher resources, red envelope resources, etc., which are not limited.
  • Step 210 Identify whether the shared vehicle arrives at the rental point, and perform resource transfer for the users of the shared vehicle that arrive at the rental point based on the rental policy.
  • the server monitors the use of shared vehicles in the monitored area to identify whether the shared vehicle has reached the rental point. If so, the server transfers resources of the shared vehicle user according to the rental policy of the shared vehicle travel time corresponding to the monitoring period to encourage the vehicle user to schedule the shared vehicle itself. Based on the leasing strategy, vehicle users are encouraged to perform vehicle distribution scheduling among multiple rental points, which not only reduces vehicle scheduling costs, but also improves vehicle scheduling efficiency.
  • multiple rental points can be determined in the monitoring area; based on the shared vehicle access data of multiple rental points during multiple monitoring periods in the historical monitoring cycle, a preset vehicle rental model can be used to predict each The regular demand for shared vehicles at each rental point during the corresponding monitoring period of the current monitoring cycle; according to the regular demand, a rental strategy for each rental point during multiple monitoring periods of the current monitoring period can be generated; whether the shared vehicle travelling has reached the lease Point monitoring, you can transfer resources to users of shared vehicles arriving at the rental point based on the rental strategy.
  • the rental points in the monitored area are determined dynamically and periodically, and the conventional demand for shared vehicles is measured at each rental point, and then the rental strategy is updated based on the calculation results.
  • the rental strategy can be adjusted according to the building migration or route changes in the monitoring area in a timely manner. To improve scheduling accuracy. Incentives to vehicle users based on leasing strategies for shared vehicle transfers between multiple rental points can improve vehicle utilization.
  • determining a plurality of rental points in the monitoring area according to the map includes: dividing the monitoring area into multiple sub-areas; obtaining building distribution information in each sub-area according to the map; obtaining the historical monitoring cycle of each sub-area The average number of parked vehicles; a sub-area where the building distribution information and the average number of parked vehicles meet preset conditions is determined as a rental point in the monitoring area.
  • the server obtains a map of the monitoring area, divides the area on the map according to conditions such as area area, and divides the monitoring area into multiple sub-areas.
  • the server obtains the building distribution information in each sub-area according to the map.
  • Building distribution information includes building properties, building scale, and building distribution concentration.
  • the nature of buildings includes civil and industrial buildings. Among them, civil buildings include not only residential buildings such as residential areas and office buildings, but also public buildings such as hospitals, libraries, stations, shops, and parks. Building size refers to the volume of space occupied by the building. Building distribution concentration refers to the average number of buildings per unit area.
  • the server counts the average number of vehicles parked in the historical monitoring cycle of each sub-region based on the recorded positioning information of multiple shared vehicle historical monitoring cycles. The server determines that each of the sub-regions in which the concentration concentration of civil distribution of buildings reaches the first threshold, the scale of the buildings reaches the second threshold, and the average number of parked vehicles reaches the third threshold is a lease point in the monitoring area.
  • the server may also perform statistics on the population density of each sub-region, and people ’s habitual travel tools, to determine the lease point and further improve the accuracy of the lease point determination.
  • leasing points in the monitoring area are determined according to information on the distribution of the building and information on the multiple dimensions of the average number of vehicles parked, which can improve the accuracy of determining the leasing points.
  • collecting the vehicle access data of a plurality of leasing points during multiple monitoring periods of the historical monitoring cycle includes: pulling the operation behavior logs of the shared vehicle application generated by the terminal during the multiple monitoring periods; The behavior log is parsed to obtain multiple operation behavior fields.
  • the operation behavior fields include operation identification, operation time, and operation position.
  • the operation time is identified as the monitoring period, and the operation position is identified as the lease point. Multiple lease points are monitored at each monitoring point. During the period, the actual operation times corresponding to each operation identifier are separately counted, and the statistical results are used as the shared vehicle access data.
  • the terminal collects the operation behavior data of the user in the shared vehicle application based on the preset buried point, and records the operation behavior data in the operation behavior log.
  • the server arrives at the monitoring cycle, it pulls the operation behavior logs generated in multiple monitoring periods on multiple terminals, analyzes the operation behavior logs, and obtains the operation behavior data of multiple users.
  • the operation behavior data mainly includes user identification and operation identification, operation time, and operation position corresponding to the user's operations such as vehicle reservation, vehicle application, code unlocking, and vehicle locking.
  • the vehicle lock can be a lock operation on the shared vehicle application, or it can be a shared vehicle application that receives a successful lock notification after the user manually closes the lock on the shared vehicle.
  • the server replaces each operation time with the monitoring period to which the operation time belongs, and replaces each operation position with the lease point closest to the operation position according to multiple monitoring periods and multiple lease points of the current monitoring cycle.
  • Table 1 can be transformed into the following Table 2:
  • the server performs statistical processing on the operation behavior data. Specifically, the server counts the number of times that different operations occur at each rental point during multiple monitoring periods, that is, the number of actual operations corresponding to different operation identifiers is counted to obtain the shared vehicle access data in the monitoring area during the historical monitoring period, such as Table III shows:
  • the server performs 01 normalization processing on the shared vehicle access data.
  • the server uses Min-Max normalization (extreme standardization), Z-score normalization, or Decimal scaling (decimal scaling standardization) and other methods to convert each field in the shared vehicle access data (ie, standard three) to 0,1]. Standardizing the data can improve the accuracy of data analysis.
  • the method before performing resource transfer for the user of the shared vehicle arriving at the rental point based on the rental policy, the method further includes: receiving a vehicle reservation request sent by the terminal, and sending the stored shared vehicle distribution map to the terminal in response to the vehicle reservation request;
  • the shared vehicle distribution map includes multiple vehicle icons; captures the selection of the vehicle icons that occur on the shared vehicle distribution map of the terminal; identifies the rental points within a preset distance of the vehicle icon corresponding to the selected operation, based on the identified rental points and
  • the lease strategy generates incentive prompts and sends them to the terminal.
  • the shared vehicle application When a user needs to travel with a shared vehicle, he can make a vehicle reservation in advance based on the shared vehicle application on the terminal.
  • the shared vehicle application generates a vehicle reservation request based on the vehicle reservation operation, and sends the vehicle reservation request to the server.
  • the vehicle reservation request received the location information of the terminal.
  • the server responds to the vehicle reservation request, obtains the shared vehicle distribution map, and sends the shared vehicle distribution map to the terminal.
  • the shared vehicle distribution map includes vehicle icons corresponding to multiple shared vehicles within a preset distance of the terminal location.
  • the user can select a certain vehicle icon on the shared vehicle distribution map to realize the reservation of the corresponding shared vehicle.
  • the server captures a user's selected operation of the vehicle icon that occurs on the shared vehicle distribution map; identifies one or more rental points within a preset distance of the selected icon corresponding to the vehicle icon.
  • the server predicts the possible incentive resources for moving the shared vehicle from the current location to different rental points within a preset distance. Specifically, the server obtains multiple dimensions of information such as the conventional demand for a shared vehicle by a rental point within a preset distance of the shared vehicle in the current period, and the current parking amount of the shared vehicle at the rental point in the current period, and identifies the rental policy based on the rental policy. Incentives that can be satisfied by multiple dimensions of information. If any of the incentive conditions cannot be met, no scheduling incentive will be generated. If the incentive conditions are met, the server obtains the incentive resources corresponding to the incentive conditions.
  • the server obtains the incentive resources that may be generated by moving the shared vehicle from the current location to different rental points within a preset distance in the above manner.
  • the server generates incentive prompts based on multiple rental points and their corresponding scheduling incentives, and pushes the incentive prompts to the terminal to prompt vehicle users to actively park shared vehicles to rental points with a high demand for shared vehicles.
  • the rental point near the current location is identified, and an incentive prompt is generated according to the rental strategy corresponding to the rental point, prompting the vehicle user to park the shared vehicle to a lease with a high demand for the shared vehicle.
  • Points may get incentive resources, thereby increasing vehicle users' enthusiasm for vehicle rental.
  • the method before the resource transfer is performed on the user of the shared vehicle that arrives at the rental point based on the rental policy, the method further includes: when receiving a car use request sent by the terminal, starting to record driving data; the driving data includes the current trip Starting point and driving route; real-time detection of rental points within the preset distance of the shared vehicle based on the driving route; if so, predict the incentives available for this trip based on the rental strategy, driving starting points, and rental points within the preset distance Resources; generate incentive prompts based on the incentive resources and push the incentive prompts to the terminal.
  • the user can scan and unlock based on the shared vehicle application on the terminal.
  • the shared vehicle application generates a car use request according to the code scan unlock operation, and sends the car use request to the server.
  • the server responds to the car request and starts recording driving data.
  • the driving data includes the starting point of the current trip and the driving route that has been driven.
  • the server can obtain the current position of the shared vehicle in real time.
  • the server detects whether a rental point exists within a preset distance of the shared vehicle according to a preset time and frequency.
  • the preset time frequency can be integrated with the server detection resources and detection accuracy settings, such as 1 minute.
  • the server predicts the incentive resources available for the trip according to the lease strategy. Specifically, the server obtains multiple dimensions of information such as the conventional demand for a shared vehicle by a rental point within a preset distance of the shared vehicle in the current period, and the current parking amount of the shared vehicle at the rental point in the current period, and identifies the rental policy based on the rental policy. Incentives that can be satisfied by multiple dimensions of information. If any of the incentive conditions cannot be met, no scheduling incentive will be generated.
  • the server obtains the incentive resources corresponding to the incentive conditions, generates incentive prompts based on the obtained incentive resources, and pushes the incentive prompts to the terminal to prompt the vehicle user to actively park the shared vehicle to a lease with a high demand for the shared vehicle. point.
  • the current location of the shared vehicle is monitored in real time, and the rental point near the current location is identified, and an incentive prompt is generated according to the rental strategy corresponding to the rental point to prompt the vehicle user to park the shared vehicle to Incentive resources that may be obtained for leasing points with a high demand for shared vehicles, thereby increasing the enthusiasm of vehicle users for vehicle rental.
  • the leasing strategy records a variety of incentive conditions and the incentive resources corresponding to each type of incentive condition; based on the leasing strategy, resource transfer for users of shared vehicles arriving at the lease point includes: When a car request is made, start to record driving data; when receiving a return request from the terminal, stop recording driving data; the driving data includes the driving end point and driving time of the current trip; determine whether the driving end point belongs to a rental point and record it as the target Leasing point.
  • the shared vehicle application When the user needs to use the shared vehicle to travel, the user can scan and unlock based on the shared vehicle application on the terminal.
  • the shared vehicle application generates a car use request according to the code scan unlock operation, and sends the car use request to the server.
  • the server responds to the car request and starts recording driving data.
  • the driving data includes the driving time, driving time and driving route of the current trip.
  • the driving route includes a driving start point and a driving end point.
  • the server determines whether the driving end point is located at a rental point. If not, no scheduling incentive is generated. If yes, the lease point at the end of the journey is recorded as the target lease point.
  • the server obtains the current monitoring period corresponding to the travel time, and obtains the conventional demand for the shared vehicle at the target rental point in the next monitoring period.
  • the server obtains the current parking amount of the shared vehicle at the target rental point at the end of driving.
  • the server identifies the incentive conditions that can be satisfied for the current ride, based on multiple dimensions of information such as the driving time, the regular demand for the shared vehicle by the target scheduling node in the next monitoring period, and the current parking volume of the shared vehicle at the end of the drive.
  • the server generates a navigation route according to the driving start point and the driving end point, fits the driving route and the navigation route, and calculates a fitting degree between the driving route and the navigation route.
  • the server identifies this ride based on multiple dimensions of information such as the driving time, the fit of the driving route and the navigation route, the regular demand for the shared vehicle by the target scheduling node in the next monitoring period, and the current parking amount of the shared vehicle at the end of the driving. Incentive conditions that can be met.
  • the shared vehicle is a shared bicycle.
  • the server also obtains the terrain information corresponding to the driving route according to the map of the monitoring area, and calculates the distance and slope of the uphill section and the distance of the downhill section included in the driving route according to the terrain information.
  • the server uses multiple dimensions such as the driving time, the distance of the downhill section and the distance and slope of the uphill section included in the driving route, the regular demand for the shared vehicle by the target scheduling node in the next monitoring period, and the current parking amount of the shared vehicle at the end of the drive Information to identify the incentive conditions that this ride can meet.
  • the server obtains the incentive resource corresponding to the incentive condition, and uses the obtained incentive resource as the actual incentive resource available for the trip.
  • the server transfers the calculated incentive resources to the user ID of the vehicle user corresponding to the shared vehicle. It is easy to understand that if the incentive resource is a capital resource, the server can calculate the original cost of the trip according to the driving time according to the traditional method, and convert the calculated incentive resource into the incentive cost available for the trip. According to the original cost and the incentive cost, , Calculate the actual expenses incurred for this trip, and settle the trip based on the actual expenses.
  • the actual available incentive resources for this trip are calculated in time to improve the timeliness of the transfer of incentive resources, thereby improving the vehicle user ’s vehicle use. Leasing motivation.
  • the leasing strategy records a variety of incentive conditions and incentive resources corresponding to each incentive condition; the method further includes: receiving an incentive prediction request sent by the terminal; the incentive prediction request includes a planned driving start point, a planned driving end point, and Planned driving time; determine whether the planned driving end point belongs to a rental point and record it as the target rental point; if so, generate a navigation route based on the planned driving start point and the planned driving end point; calculate the driving time corresponding to the planned trip based on the navigation route; obtain The target rental point ’s regular demand for shared vehicles in the next monitoring period corresponding to the planned driving time; according to the driving time and regular demand, identify the incentive conditions that this planned trip can meet; obtain the incentive resources corresponding to the incentive conditions, and obtain The obtained incentive resources are fed back to the terminal as prediction results.
  • the shared vehicle application When users plan to travel with a shared vehicle, they can first query the incentive resources that may be obtained through the shared vehicle application on the terminal. Specifically, the user scans and unlocks the code based on the shared vehicle application on the terminal, and enters planned travel information.
  • the planned driving information includes a planned driving start point, a planned driving end point, and a planned driving time.
  • the shared vehicle application generates an incentive prediction request based on the code-unlock operation and the entered planned driving information, and sends the incentive prediction request to the server.
  • the server measures the incentive resources that may be generated by the planned trip in the above manner. Specifically, the server determines whether the planned driving end point is located at a rental point. If not, a prompt indicating that the scheduling incentive is zero is generated, and the prompt is returned to the terminal. If so, the server considers the lease point at the end of the planned travel as the target lease point. The server obtains the current monitoring period corresponding to the planned travel time, and obtains the conventional demand for the shared vehicle at the target rental point in the next monitoring period. The server obtains the current parking amount of the shared vehicle at the target rental point at the current moment. The server generates a navigation route according to the planned starting point and the planned driving end point, and predicts the estimated driving time required for the planned trip based on the navigation route.
  • the server identifies the incentive conditions that the ride can meet based on multiple dimensions of information, such as the estimated driving time, the conventional demand for the shared vehicle in the next monitoring period, and the current parking volume of the shared vehicle at the current moment.
  • the shared vehicle is a shared bicycle.
  • the server also obtains the terrain information corresponding to the navigation route according to the map of the monitoring area, and calculates the distance and slope of the uphill section and the distance of the downhill section included in the navigation route according to the terrain information.
  • the server uses multiple dimensions such as the estimated driving time, the distance of the downhill road section included in the navigation route, the distance and slope of the uphill road section, the general demand for shared vehicles in the next monitoring period by the target scheduling node, and the current parking volume of the shared vehicle at the current moment.
  • the server obtains the incentive resource corresponding to the incentive condition, generates an incentive measurement result based on the obtained incentive resource, and returns the incentive measurement result to the terminal.
  • the user may first query the incentive resources that may be obtained through the shared vehicle application on the terminal, which is convenient for the user to arrange a travel plan according to the dispatch incentive, which is beneficial to the implementation of the shared vehicle rental strategy. This will increase the efficiency of shared vehicle rental.
  • steps in the flowchart of FIG. 2 are sequentially displayed in accordance with the directions of the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless explicitly stated in this document, the execution of these steps is not strictly limited, and these steps can be performed in other orders. Moreover, at least a part of the steps in FIG. 2 may include multiple sub-steps or stages. These sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution of these sub-steps or stages The order is not necessarily performed sequentially, but may be performed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.
  • a vehicle rental device including: a rental point determination module 302, a demand measurement calculation module 304, a rental strategy generation module 306, and an incentive resource transfer module 308, wherein:
  • the lease point determination module 302 is configured to obtain a map of a monitoring area, and determine a plurality of lease points in the monitoring area according to the map.
  • the demand measurement calculation module 304 is used to collect the data of the shared vehicle in and out of multiple rental points during multiple monitoring periods in the historical monitoring cycle; enter the shared vehicle input and output data into a preset vehicle rental model, and determine the multiple rental points for the shared vehicles. Regular demand.
  • the leasing strategy generating module 306 is configured to generate a leasing strategy for a monitoring area in a plurality of monitoring periods of a current monitoring cycle according to a conventional demand.
  • An incentive resource transfer module 308 is used to identify whether the shared vehicle has arrived at the rental point, and perform resource transfer for users of the shared vehicle that arrive at the rental point based on the rental policy.
  • the rental point determination module 302 is further configured to divide the monitoring area into multiple sub-areas; obtain the building distribution information in each sub-area according to the map; obtain the average number of vehicles parked in each sub-area during the historical monitoring cycle; A sub-area where the building distribution information and the average number of parking vehicles meet preset conditions is determined as a rental point in the monitoring area.
  • the demand measurement calculation module 304 is further used to pull the operation behavior log of the shared vehicle application generated by the terminal in multiple monitoring periods; analyze the operation behavior log to obtain multiple operation behavior fields; operation The behavior fields include operation ID, operation time, and operation location; identify the operation time as the monitoring period, and identify the operation position as the lease point; separately perform the actual number of operations corresponding to each operation ID for multiple lease points in each monitoring period Statistics, and use the statistical results as shared vehicle access data.
  • the device further includes a scheduling incentive prompt module 310 for receiving a vehicle reservation request sent by the terminal, and sending the stored shared vehicle distribution map to the terminal in response to the vehicle reservation request; the shared vehicle The distribution map includes multiple vehicle icons; captures the selection of vehicle icons that occur on the shared vehicle distribution map of the terminal; identifies the rental points within the preset distance of the vehicle icon corresponding to the selected operation, based on the identified rental points and rental strategy Generate incentive prompts and send them to the terminal.
  • a scheduling incentive prompt module 310 for receiving a vehicle reservation request sent by the terminal, and sending the stored shared vehicle distribution map to the terminal in response to the vehicle reservation request; the shared vehicle The distribution map includes multiple vehicle icons; captures the selection of vehicle icons that occur on the shared vehicle distribution map of the terminal; identifies the rental points within the preset distance of the vehicle icon corresponding to the selected operation, based on the identified rental points and rental strategy Generate incentive prompts and send them to the terminal.
  • the dispatch incentive prompt module 310 is further configured to start recording driving data when receiving a car use request sent by the terminal; the driving data includes the starting point and driving route of the current trip; according to the driving route, real-time detection Whether there is a rental point within the preset distance of the shared vehicle; if so, according to the rental strategy, the starting point of the driving and the rental points within the preset distance, predict the incentive resources available for this trip; generate incentive prompts based on the incentive resources, and give incentive prompts Push to terminal.
  • the leasing strategy records a variety of incentive conditions and incentive resources corresponding to each incentive condition;
  • the incentive resource transfer module 308 is further configured to start recording driving data when a car use request is received from the terminal;
  • the recording of driving data ends;
  • the driving data includes the driving end point and driving time of this trip; determine whether the driving end point belongs to a rental point and record it as the target rental point; if yes, determine the corresponding driving time In the current monitoring period, obtain the conventional demand for the shared vehicle at the target rental point in the next monitoring period; identify the incentive conditions that can be satisfied by this trip based on the conventional demand; obtain the incentive resources corresponding to the incentive conditions; and correspond to the terminal based on the incentive resources
  • the user ID performs resource transfer; otherwise, the lease point within a preset distance of the driving end point is identified, an incentive prompt is generated based on the identified lease point and the rental strategy, and the incentive prompt is sent to the terminal.
  • the leasing strategy records a variety of incentive conditions and incentive resources corresponding to each incentive condition; as shown in FIG. 3C, the device further includes a scheduling incentive prediction module 312 for receiving an incentive prediction request sent by the terminal.
  • Incentive prediction request includes planned starting point, planned driving end point and planned driving time; judging whether the planned driving end point belongs to a rental point and recorded as the target rental point; if so, generate a navigation route based on the planned driving start point and planned driving end point; Route, calculate the travel time corresponding to the planned trip; obtain the target rental point ’s regular demand for shared vehicles in the next monitoring period corresponding to the planned travel time; and identify the travel schedule and regular demand that can be satisfied by the planned trip Incentive conditions; obtain the incentive resources corresponding to the incentive conditions, and feed the obtained incentive resources back to the terminal as a prediction result.
  • Each module in the above vehicle rental device may be implemented in whole or in part by software, hardware, and a combination thereof.
  • the above-mentioned modules may be embedded in the hardware in or independent of the processor in the computer device, or may be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.
  • a computer device is provided.
  • the computer device may be a server, and its internal structure diagram may be as shown in FIG. 4.
  • the computer device includes a processor, a memory, a network interface, and a database connected through a system bus.
  • the processor of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes a non-volatile storage medium and an internal memory.
  • the non-volatile storage medium stores an operating system, computer-readable instructions, and a database.
  • the internal memory provides an environment for the operation of the operating system and computer-readable instructions in a non-volatile storage medium.
  • the database of the computer equipment is used to store the monitoring area map, rental strategy and so on.
  • the network interface of the computer device is used to communicate with an external terminal through a network connection.
  • the computer-readable instructions are executed by a processor to implement a vehicle rental method.
  • FIG. 4 is only a block diagram of a part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer equipment to which the scheme of the present application is applied.
  • the specific computer equipment may be Include more or fewer parts than shown in the figure, or combine certain parts, or have a different arrangement of parts.
  • One or more non-volatile storage media storing computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors implement the vehicle provided in any one of the embodiments of the present application Steps in the lease method.
  • Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory can include random access memory (RAM) or external cache memory.
  • RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

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Abstract

一种车辆租赁方法，包括：获取监控区域的地图，根据地图在监控区域确定多个租赁点；采集多个租赁点在历史监控周期多个监控时段的共享车辆出入数据；将共享车辆出入数据输入预设的车辆租赁模型，确定多个租赁点分别对共享车辆的常规需求量；根据常规需求量，生成监控区域在当前监控周期多个监控时段的租赁策略；识别共享车辆是否到达租赁点，基于租赁策略对到达租赁点的共享车辆的用户进行资源转移。

Description

车辆租赁方法、装置、计算机设备和存储介质
本申请要求于2018年6月15日提交中国专利局，申请号为2018106199623，申请名称为“车辆租赁方法、装置、计算机设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及一种车辆租赁方法、装置、计算机设备和存储介质。
背景技术
共享单车、共享汽车等共享车辆已经成为城市中新兴的出行方式，可以有效满足城市人群的出行需求。但发明人意识到，基于传统模式的车辆租赁方式，难以保证共享车辆的有效迁移，导致车辆使用率不足的问题。
发明内容
根据本申请公开的各种实施例，提供一种车辆租赁方法、装置、计算机设备和存储介质。
一种车辆租赁方法，所述方法包括：获取监控区域的地图，根据所述地图在所述监控区域确定多个租赁点；采集多个租赁点在历史监控周期多个监控时段的共享车辆出入数据；将所述共享车辆出入数据输入预设的车辆租赁模型，确定多个所述租赁点分别对共享车辆的常规需求量；根据所述常规需求量，生成所述监控区域在当前监控周期多个监控时段的租赁策略；及识别共享车辆是否到达所述租赁点，基于所述租赁策略对到达租赁点的所述共享车辆的用户进行资源转移。
一种车辆租赁装置，所述装置包括：租赁点确定模块，用于获取监控区域的地图，根据所述地图在所述监控区域确定多个租赁点；需求量测算模块，用于采集多个租赁点在历史监控周期多个监控时段的共享车辆出入数据；将所述共享车辆出入数据输入预设的车辆租赁模型，确定多个所述租赁点分别对共享车辆的常规需求量；租赁策略生成模块，用于根据所述常规需求量，生成所述监控区域在当前监控周期多个监控时段的租赁策略；及激励资源转移模块，用于识别共享车辆是否到达所述租赁点，基于所述租赁策略对到达租赁点的所述共享车辆的用户进行资源转移。
一种计算机设备，包括存储器和一个或多个处理器，存储器中存储有计算机可读指令，计算机可读指令被处理器执行时实现本申请任意一个实施例中提供的车辆租赁方法的步骤。
一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器实现本申请任意一个实施例中提供的车辆租赁方法的步骤。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其它的附图。
图1为根据一个或多个实施例中车辆租赁方法的应用场景图。
图2为根据一个或多个实施例中车辆租赁方法的流程示意图。
图3A为根据一个或多个实施例中车辆租赁装置的结构框图。
图3B为根据另或多个一个实施例中车辆租赁装置的结构框图。
图3C为根据又或多个一个实施例中车辆租赁装置的结构框图。
图4为根据一个或多个实施例中计算机设备的框图。
具体实施方式
为了使本申请的技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
本申请提供的车辆租赁方法，可以应用于如图1所示的应用环境中。终端102与服务器104通过网络进行通信。终端102可以但不限于是各种个人计算机、笔记本电脑、智能手机、平板电脑和便携式可穿戴设备，服务器104可以用独立的服务器或者是多个服务器组成的服务器集群来实现。服务器104周期性更新对监控区域内共享车辆的租赁策略。具体的，服务器104获取监控区域的地图，根据地图在监控区域确定多个租赁点。终端102上安装了共享车辆应用程序。共享车辆应用程序中预先设置了埋点，能够对用户的操作行为数据进行采集。服务器104通过对大量用户的操作行为数据统计分析，获取多个租赁点在历史监控周期多个监控时段的共享车辆出入数据。服务器104将共享车辆出入数据输入预设的车辆租赁模型，确定多个租赁点分别对共享车辆的常规需求量，根据常规需求量及地图，生成监控区域在当前监控周期多个监控时段的租赁策略。接收到终端102发送的用车请求时，服务器104开始记录行驶数据。当行驶结束时，服务器104识别行驶终点是否位于一个租赁点，即识别共享车辆是否到达租赁点。若到达租赁点，服务器104基于当前监控周期当前监控时段的租赁策略对到达租赁点的共享车辆的用户进行资源转移。上述车辆租赁过程，根据周期性动态确定的监控区域内的租赁点及其对共享车辆的常规需求量生成租赁策略，可以提高租赁策略准确性；基于租赁策略激励用户自己在多个租赁点之间进行共享车辆转移，可以提高车辆使用率。
在其中一个实施例中，如图2所示，提供了一种车辆租赁方法，以该方法应用于图1中的服务器为例进行说明，包括以下步骤：
步骤202，获取监控区域的地图，根据地图在监控区域确定多个租赁点。
监控区域是指需要进行共享车辆租赁的地理区域，可以是以市、县或区为单位的区域， 如监控区域A可以是深圳市，监控区域B可以是深圳市南山区等，对此不作限制。监控区域的地图是按一定的比例运用线条、符号、颜色、文字注记等描绘显示监控区域内路线、建筑、山川河流等分布情况的图形。建筑可以是公共场所，如公园、公交站台、地铁站、火车站等。
服务器根据监控区域地图记录的监控区域内路线和建筑的分布信息，在监控区域内确定多个租赁点。根据区域面积等可以将监控区域划分为多个子区域。租赁点是指监控区域中建筑分布集中、客流量大的子区域，如监控区域B内的租赁点可以包括科技园B1，海岸城B2等。每个租赁点具有对应的区域界线，如租赁点科技园B1的区域界线可以是：南山区北环路以南，侨城西路以西，滨海大道以北，后海大道及深圳大学以东区域。
值得注意的是，本实施例服务器每隔一个监控周期重新确定一次监控区域内的多个租赁点，以及时根据建筑迁移或路线变迁等进行租赁点调整，提高调度准确性。监控周期可以根据需求自由设定，如1个月等。
步骤204，采集多个租赁点在历史监控周期多个监控时段的共享车辆出入数据。
监控周期包括多个监控时段，如监控时段1可以是7:00～9:00，监控时段2可以是9:00～11:00等。监控时段还可以对工作日和节假日进行区分，如监控时段3可以是工作日7:00～9:00，监控时段4可以是工作日9:00～12:00，监控时段5可以是节假日10:00～12:00等。监控时段的时长可以根据需要自由设置，不同监控时段的时长可以不同。此外，不同租赁点对应监控周期对监控时段的划分可以不同。
服务器每隔一个监控周期对多个租赁点对共享车辆的常规需求量进行一次测算，并根据测算结果进行租赁策略更新。具体的，服务器基于租赁点在历史监控周期不同监控时段的共享车辆出入数据，预测该租赁点在当前监控周期不同监控时段对共享车辆的常规需求量。共享车辆出入数据可以是对大量用户使用共享车辆时在终端上共享车辆应用程序的操作行为数据统计分析得到的。操作行为数据包括多个操作标识，如车辆预约、扫码解锁、车辆关锁等。在另一个实施例中，操作标识还包括车辆申请。共享车辆应用程序中新增了“车辆申请”按钮，以方便车辆用户主动对某个监控区域共享车辆供不应求的情况进行及时反馈。共享车辆出入数据包括每个租赁点在不同监控时段的不同操作标识的实际操作次数。
步骤206，将共享车辆出入数据输入预设的车辆租赁模型，确定多个租赁点分别对共享车辆的常规需求量。
每个租赁点在监控周期的多个监控时段分别具有对应的车辆租赁模型。例如，在上述举例中，租赁点科技园B1在监控时段3的车辆租赁模型可以是B1-3，在监控时段4的车辆租赁模型可以是B1-4。历史监控周期可以是当前监控周期之前的一个或多个监控周期。服务器将一个租赁点在历史监控周期某个监控时段的共享车辆出入数据输入该租赁点在相应监控时段的车辆租赁模型，可以确定该租赁点在当前监控周期同一监控时段对共享车辆的常规需求量。常规需求量是租赁点在该监控时段通常需要共享车辆的数量。
当前监控周期的车辆租赁模型可以是利用多个训练样本数据对通用机器学习模型训练得到的。具体的，服务器获取一个租赁点在某个监控时段的训练样本数据。训练样本数据可以是租赁点在历史监控周期相应监控时段实际的共享车辆出入数据，也可以是编写的租赁点在 相应监控时段模拟的共享车辆出入数据。服务器标注每组训练样本数据对应的共享车辆需求量，即针对每组训练样本数据添加对应的需求量标签。服务器将训练样本数据输入通用机器学习模型，得到预测需求量。通用机器学习模型可以是VGG(Visual Geometry Group视觉集合组)网络模型、GoogleNet(谷歌网络)网络模型或ResNet(能效评估系统)网络模型等。通用机器学习模型包括多个模型参数。服务器计算预测需求量与需求量标签的差异，根据差异调整通用机器学习模型的模型参数并继续训练，直至满足训练停止条件时结束训练，得到该租赁点在当前监控周期相应监控时段的车辆租赁模型。服务器按照上述方式训练得到每个租赁点在当前监控周期多个监控时段分别对应的车辆租赁模型。
在另一个实施例中，服务器在基于共享车辆出入数据计算得到某个租赁点多个监控时段对共享车辆的常规需求量后，可以根据该租赁点的建筑分布信息、人口密度信息或共享车辆历史停放信息等对常规需求量进行调整，以提高常规需求量的测算准确度。
步骤208，根据常规需求量，生成监控区域在当前监控周期多个监控时段的租赁策略。
服务器基于租赁点在当前监控周期某个监控时段对共享车辆的常规需求量，生成该租赁点在当前监控周期相应监控时段的租赁策略。租赁策略记录了多种激励条件及每种激励条件对应的不同份额的激励资源。激励条件可以是多种指标组合，如行驶时长、行驶路线、行驶终点为租赁点、行驶终点对应租赁点对共享车辆的常规需求量和当前停放量的组合等。激励资源可以是资金资源或权限资源等。其中，资金资源可以是代金券资源、红包资源等，对此不作限制。
步骤210，识别共享车辆是否到达租赁点，基于租赁策略对到达租赁点的共享车辆的用户进行资源转移。
在当前监控周期内，服务器对监控区域内共享车辆的使用情况进行监测，识别出行的共享车辆是否到达租赁点。若是，服务器根据共享车辆出行时间对应监控时段的租赁策略，对该共享车辆的用户进行资源转移，以激励车辆用户自身对共享车辆进行调度。基于租赁策略激励车辆用户在多个租赁点之间进行车辆分布调度，不仅减少车辆调度成本，还可以提高车辆调度效率。
本实施例中，根据监控区域的地图，可以在监控区域确定多个租赁点；基于多个租赁点在历史监控周期多个监控时段的共享车辆出入数据，可以利用预设的车辆租赁模型预测每个租赁点在当前监控周期相应监控时段对共享车辆的常规需求量；根据常规需求量，可以生成每个租赁点在当前监控周期多个监控时段的租赁策略；通过对出行的共享车辆是否到达租赁点进行监测，可以基于租赁策略对到达租赁点的共享车辆的用户进行资源转移。周期性动态确定的监控区域内的租赁点，并对各个租赁点对共享车辆的常规需求量进行测算，进而根据测算结果更新租赁策略，可以及时根据监控区域建筑迁移或路线变迁等进行租赁策略调整，提高调度准确性。基于租赁策略激励车辆用户在多个租赁点之间进行共享车辆转移，可以提高车辆使用率。
在其中一个实施例中，根据地图在监控区域确定多个租赁点，包括：将监控区域划分为多个子区域；根据地图获取每个子区域内的建筑分布信息；获取每个子区域在历史监控周期 的车辆平均停放数量；将建筑分布信息以及车辆平均停放数量均满足预设条件的子区域，确定为监控区域的一个租赁点。
服务器获取监控区域的地图，在地图上根据区域面积等条件进行区域划分，将监控区域划划分为多个子区域。服务器根据地图获取每个子区域内的建筑分布信息。建筑分布信息包括建筑性质、建筑规模和建筑分布集中度等。建筑性质包括民用建筑和工业建筑等。其中，民用建筑不仅包括居民区、办公楼等住宅建筑，还包括医院、图书馆、车站、商店、公园等公共建筑。建筑规模是指建筑所占空间体积。建筑分布集中度是指单位区域面积内的平均建筑数量。服务器基于记录的多个共享车辆历史监控周期的定位信息，统计每个子区域在历史监控周期的车辆平均停放数量。服务器将民用建筑的建筑分布集中度达到第一阈值，建筑规模达到第二阈值，车辆平均停放数量达到第三阈值的每个子区域确定为监控区域的一个租赁点。
在另一个实施例中，服务器还可以对每个子区域的人口密度、人们习惯出行工具等信息进行统计，用于租赁点的确定，进一步提高租赁点确定的准确性。
本实施例中，根据建筑分布信息以及车辆平均停放数量多个维度的信息确定监控区域的租赁点，可以提高租赁点确定的准确性。
在其中一个实施例中，采集多个租赁点在历史监控周期多个监控时段的共享车辆出入数据，包括：拉取终端在多个监控时段生成的对共享车辆应用程序的操作行为日志；对操作行为日志进行解析，得到多个操作行为字段；操作行为字段包括操作标识、操作时间和操作位置；将操作时间识别为监控时段，将操作位置识别为租赁点；对多个租赁点在每个监控时段内每个操作标识对应的实际操作次数分别进行统计，将统计结果作为共享车辆出入数据。
终端基于预置埋点采集到用户在共享车辆应用程序的操作行为数据，将操作行为数据记录在操作行为日志中。服务器在监控周期到达时，在多个终端分别拉取多个监控时段生成的操作行为日志，对操作行为日志进行解析，得到多个用户的操作行为数据。如表一所示，操作行为数据主要包括用户标识及对应用户进行车辆预约、车辆申请、扫码解锁、车辆关锁等操作的操作标识、操作时间和操作位置。车辆关锁可以是在共享车辆应用程序上的关锁操作，也可以是用户在共享车辆上手动关锁后共享车辆应用程序接收到关锁成功提示。
表一
Figure PCTCN2018104768-appb-000001
服务器根据当前监控周期的多个监控时段及多个租赁点，将每个操作时间替换为该操作 时间所属的监控时段，将每个操作位置替换为距离该操作位置最近的租赁点。如此，上述表一可以转化为如下表二：
表二
用户标识 操作标识 监控时段 租赁点
用户甲 车辆预约 工作日7:00～9:00 A
用户甲 车辆申请 工作日7:00～9:00 A
用户甲 扫码解锁 工作日7:00～9:00 A
… … … …
用户乙 扫码解锁 工作日17:00～19:00 B
用户乙 车辆关锁 工作日17:00～19:00 C
用户乙 扫码解锁 工作日17:00～19:00 C
服务器对操作行为数据进行统计处理。具体的，服务器对每个租赁点在多个监控时段分别发生不同操作的次数进行统计，即对不同操作标识对应的实际操作次数进行统计，得到监控区域在历史监控周期的共享车辆出入数据，如表三所示：
表三
Figure PCTCN2018104768-appb-000002
在另一个实施例中，服务器对共享车辆出入数据进行01标准化处理。具体的，服务器利用Min-Max标准化法(极值标准化)、Z-score标准化法或Decimal scalling(小数定标标准化)等方法对共享车辆出入数据(即标三)中的每个字段转化为[0,1]之间的数字。对数据进行标准化处理可以提高数据分析精度。
本实施例中，通过对大量车辆用户对共享车辆应用程序的操作行为数据统计分析，可以一定程度上了解该监控区域在历史监控周期共享车辆的出入情况，从而可以将统计结果作为监控区域在历史监控周期的共享车辆出入数据。
在其中一个实施例中，基于租赁策略对到达租赁点的共享车辆的用户进行资源转移之前，还包括：接收终端发送的车辆预约请求，响应车辆预约请求将存储的共享车辆分布图发送至终端；共享车辆分布图包括多个车辆图标；捕获终端在共享车辆分布地图发生的对车辆图标的选定操作；识别选定操作对应车辆图标预设距离范围内的租赁点，基于识别到的租赁点及租赁策略生成激励提示，将激励提示发送至终端。
当用户需要使用共享车辆出行时，可以基于终端上的共享车辆应用程序提前进行车辆预 约。共享车辆应用程序根据车辆预约操作生成车辆预约请求，将车辆预约请求发送至服务器。车辆预约请求接待了终端的位置信息。服务器响应车辆预约请求，获取共享车辆分布图，将共享车辆分布图发送至终端。共享车辆分布图包括终端所在位置预设距离范围内的多个共享车辆对应的车辆图标。用户可以通过在共享车辆分布地图选定某个车辆图标，实现对相应共享车辆的预约。服务器捕获用户在共享车辆分布地图发生的对车辆图标的选定操作；识别选定操作对应车辆图标预设距离范围内的一个或多个租赁点。
服务器根据租赁策略，预测将共享车辆从当前位置移动至预设距离范围内的不同租赁点，可能产生的激励资源。具体的，服务器获取共享车辆预设距离范围内的租赁点在当前时段对共享车辆的常规需求量，以及该租赁点在当前时段共享车辆的当前停放量等多个维度的信息，根据租赁策略识别多个维度的信息能够满足的激励条件。若不能满足任一激励条件，则不产生调度激励。若满足激励条件，服务器获取该激励条件对应的激励资源。服务器按照上述方式获取将共享车辆从当前位置移动至预设距离范围内的不同租赁点分别可能产生的激励资源。服务器基于多个租赁点及分别对应的调度激励生成激励提示，将激励提示推送至终端，以提示车辆用户主动将共享车辆停放至对共享车辆需求量大的租赁点。
本实施例中，在车辆用户进行共享车辆预约时，识别当前位置附近的租赁点，根据该租赁点对应的租赁策略生成激励提示，提示车辆用户将共享车辆停放至对共享车辆需求量大的租赁点可能得到的激励资源，从而提高车辆用户进行车辆租赁积极性。
在其中一个实施例中，基于租赁策略对到达租赁点的共享车辆的用户进行资源转移之前，还包括：在接收到终端发送的用车请求时，开始记录行驶数据；行驶数据包括本次出行的行驶起点和行驶路线；根据行驶路线，实时检测共享车辆预设距离范围内是否存在租赁点；若是，根据租赁策略、行驶起点及预设距离范围内的租赁点，预测本次出行可得的激励资源；基于激励资源生成激励提示，将激励提示推送至终端。
当用户需要使用共享车辆出行时，可以基于终端上的共享车辆应用程序扫码解锁，共享车辆应用程序根据扫码解锁操作生成用车请求，将用车请求发送至服务器。服务器响应用车请求，开始记录行驶数据。行驶数据包括本次出行的行驶起点和已经行驶的行驶路线。根据行驶路线，服务器可以实时获取共享车辆的当前位置。服务器按照预设时间频率检测共享车辆预设距离范围内是否存在租赁点。预设时间频率可以综合服务器检测资源以及检测精度设置，如1分钟等。
若检测到共享车辆预设距离范围内存在租赁点，服务器根据租赁策略预测本次出行可得的激励资源。具体的，服务器获取共享车辆预设距离范围内的租赁点在当前时段对共享车辆的常规需求量，以及该租赁点在当前时段共享车辆的当前停放量等多个维度的信息，根据租赁策略识别多个维度的信息能够满足的激励条件。若不能满足任一激励条件，则不产生调度激励。若满足激励条件，服务器获取该激励条件对应的激励资源，基于获取到的激励资源生成激励提示，将激励提示推送至终端，以提示车辆用户主动将共享车辆停放至对共享车辆需求量大的租赁点。
本实施例中，在车辆用户使用共享车辆出行时，实时监测共享车辆当前位置，并识别当 前位置附近的租赁点，根据该租赁点对应的租赁策略生成激励提示，提示车辆用户将共享车辆停放至对共享车辆需求量大的租赁点可能得到的激励资源，从而提高车辆用户进行车辆租赁积极性。
在其中一个实施例中，租赁策略记录了多种激励条件及每种激励条件对应的激励资源；基于租赁策略对到达租赁点的共享车辆的用户进行资源转移，包括：在接收到终端发送的用车请求时，开始记录行驶数据；在接收到终端发送的还车请求时，结束记录行驶数据；行驶数据包括本次出行的行驶终点和行驶时间；判断行驶终点是否属于一个租赁点，记作目标租赁点。若是，执行若是，确定行驶时间对应的当前的监控时段，获取目标租赁点在下一个监控时段对共享车辆的常规需求量；根据常规需求量，识别本次出行能够满足的激励条件；获取激励条件对应的激励资源，基于激励资源对终端对应用户标识进行资源转移；否则，识别在行驶终点预设距离范围内的租赁点，基于识别到的租赁点及租赁策略生成激励提示，将激励提示发送至终端。
当用户需要使用共享车辆出行时，可以基于终端上的共享车辆应用程序扫码解锁，共享车辆应用程序根据扫码解锁操作生成用车请求，将用车请求发送至服务器。服务器响应用车请求，开始记录行驶数据。行驶数据包括本次出行的行驶时间、行驶时长和行驶路线等。行驶路线包括行驶起点和行驶终点。服务器判断行驶终点是否位于一个租赁点所在位置。若否，则不产生调度激励。若是，将行驶终点所在租赁点记作目标租赁点。服务器获取行驶时间对应的当前的监控时段，获取目标租赁点在下一个监控时段对共享车辆的常规需求量。服务器获取目标租赁点在行驶结束时共享车辆的当前停放量。服务器根据行驶时长、目标调度节点在下一监控时段对共享车辆的常规需求量及行驶结束时共享车辆的当前停放量等多个维度的信息，识别本次骑行能够满足的激励条件。
在另一个实施例中，服务器根据行驶起点和行驶终点生成导航路线，将行驶路线与导航路线拟合，计算行驶路线与导航路线的拟合度。服务器根据行驶时长、行驶路线与导航路线的拟合度、目标调度节点在下一监控时段对共享车辆的常规需求量及行驶结束时共享车辆的当前停放量等多个维度的信息，识别本次骑行能够满足的激励条件。
在又一个实施例中，若共享车辆为共享单车。服务器还根据监控区域的地图，获取行驶路线对应的地形信息，根据地形信息计算行驶路线包含的上坡路段的路程和坡度，以及下坡路段的路程。服务器根据行驶时长、行驶路线包含的下坡路段的路程及上坡路段的路程和坡度、目标调度节点在下一监控时段对共享车辆的常规需求量及行驶结束时共享车辆的当前停放量等多个维度的信息，识别本次骑行能够满足的激励条件。
服务器获取该激励条件对应的激励资源，将获取到的激励资源作为本次出行实际可得的激励资源。服务器将计算得到的激励资源转移至共享车辆对应车辆用户的用户标识。容易理解，若激励资源为资金资源，服务器可以按照传统方式根据行驶时长计算本次出行产生的原始费用，将计算得到的激励资源转换为本次出行可得的激励费用，根据原始费用和激励费用，计算本次出行产生的实际费用，基于实际费用进行出行结算。
本实施例中，在车辆用户用车完毕时，基于记录的行驶数据及预先生成的租赁策略，及 时计算本次出行实际可得的激励资源，提高激励资源转移及时性，进而提高车辆用户进行车辆租赁积极性。
在其中一个实施例中，租赁策略记录了多种激励条件及每种激励条件对应的激励资源；该方法还包括：接收终端发送的激励预测请求；激励预测请求包含计划行驶起点、计划行驶终点和计划行驶时间；判断计划行驶终点是否属于一个租赁点，记作目标租赁点；若是，根据计划行驶起点和计划行驶终点，生成导航路线；根据导航路线，计算本次计划出行对应的行驶时长；获取目标租赁点在计划行驶时间对应的下一个监控时段对共享车辆的常规需求量；根据行驶时长和常规需求量，识别本次计划出行能够满足的激励条件；获取激励条件对应的激励资源，将获取到的激励资源作为预测结果反馈至终端。
用户在计划使用共享车辆出行时，可以先通过终端上共享车辆应用程序查询本次出行可能得到的激励资源。具体的，用户基于终端上的共享车辆应用程序扫码解锁，并录入计划行驶信息。计划行驶信息包括计划行驶起点、计划行驶终点和计划行驶时间等。共享车辆应用程序根据扫码解锁操作及录入的计划行驶信息生成激励预测请求，将激励预测请求发送至服务器。
服务器按照上述方式测算本次计划出行可能产生的激励资源。具体的，服务器判断计划行驶终点是否位于一个租赁点所在位置。若否，则生成调度激励为零的提示，将该提示返回至终端。若是，服务器将计划行驶终点所在租赁点记作目标租赁点。服务器获取计划行驶时间对应的当前的监控时段，获取目标租赁点在下一个监控时段对共享车辆的常规需求量。服务器获取目标租赁点当前时刻共享车辆的当前停放量。服务器根据计划行驶起点和计划行驶终点，生成导航路线，根据导航路线预测本次计划出行需要的预计行驶时长。
服务器根据预计行驶时长、目标调度节点在下一监控时段对共享车辆的常规需求量及当前时刻共享车辆的当前停放量等多个维度的信息，识别本次骑行能够满足的激励条件。
在另一个实施例中，若共享车辆为共享单车。服务器还根据监控区域的地图，获取导航路线对应的地形信息，根据地形信息计算导航路线包含的上坡路段的路程和坡度，以及下坡路段的路程。服务器根据预计行驶时长、导航路线包含的下坡路段的路程及上坡路段的路程和坡度、目标调度节点在下一监控时段对共享车辆的常规需求量及当前时刻共享车辆的当前停放量等多个维度的信息，识别本次计划出行可能满足的激励条件。服务器获取该激励条件对应的激励资源，基于获取到的激励资源生成激励测算结果，将激励测算结果返回至终端。
本实施例中，用户在计划使用共享车辆出行时，可以先通过终端上共享车辆应用程序查询本次出行可能得到的激励资源，方便用户根据调度激励安排出行计划，利于共享车辆租赁策略的实施，进而提高共享车辆租赁效率。
应该理解的是，虽然图2的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，图2中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以 与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
在其中一个实施例中，如图3A所示，提供了一种车辆租赁装置，包括：租赁点确定模块302、需求量测算模块304、租赁策略生成模块306和激励资源转移模块308，其中：
租赁点确定模块302，用于获取监控区域的地图，根据地图在监控区域确定多个租赁点。
需求量测算模块304，用于采集多个租赁点在历史监控周期多个监控时段的共享车辆出入数据；将共享车辆出入数据输入预设的车辆租赁模型，确定多个租赁点分别对共享车辆的常规需求量。
租赁策略生成模块306，用于根据常规需求量，生成监控区域在当前监控周期多个监控时段的租赁策略。
激励资源转移模块308，用于识别共享车辆是否到达租赁点，基于租赁策略对到达租赁点的共享车辆的用户进行资源转移。
在其中一个实施例中，租赁点确定模块302还用于将监控区域划分为多个子区域；根据地图获取每个子区域内的建筑分布信息；获取每个子区域在历史监控周期的车辆平均停放数量；将建筑分布信息以及车辆平均停放数量均满足预设条件的子区域，确定为监控区域的一个租赁点。
在其中一个实施例中，需求量测算模块304还用于拉取终端在多个监控时段生成的对共享车辆应用程序的操作行为日志；对操作行为日志进行解析，得到多个操作行为字段；操作行为字段包括操作标识、操作时间和操作位置；将操作时间识别为监控时段，将操作位置识别为租赁点；对多个租赁点在每个监控时段内每个操作标识对应的实际操作次数分别进行统计，将统计结果作为共享车辆出入数据。
在其中一个实施例中，如图3B所示，该装置还包括调度激励提示模块310，用于接收终端发送的车辆预约请求，响应车辆预约请求将存储的共享车辆分布图发送至终端；共享车辆分布图包括多个车辆图标；捕获终端在共享车辆分布地图发生的对车辆图标的选定操作；识别选定操作对应车辆图标预设距离范围内的租赁点，基于识别到的租赁点及租赁策略生成激励提示，将激励提示发送至终端。
在其中一个实施例中，调度激励提示模块310还用于在接收到终端发送的用车请求时，开始记录行驶数据；行驶数据包括本次出行的行驶起点和行驶路线；根据行驶路线，实时检测共享车辆预设距离范围内是否存在租赁点；若是，根据租赁策略、行驶起点及预设距离范围内的租赁点，预测本次出行可得的激励资源；基于激励资源生成激励提示，将激励提示推送至终端。
在其中一个实施例中，租赁策略记录了多种激励条件及每种激励条件对应的激励资源；激励资源转移模块308还用于在接收到终端发送的用车请求时，开始记录行驶数据；在接收到终端发送的还车请求时，结束记录行驶数据；行驶数据包括本次出行的行驶终点和行驶时间；判断行驶终点是否属于一个租赁点，记作目标租赁点；若是，确定行驶时间对应的当前的监控时段，获取目标租赁点在下一个监控时段对共享车辆的常规需求量；根据常规需求量， 识别本次出行能够满足的激励条件；获取激励条件对应的激励资源；基于激励资源对终端对应用户标识进行资源转移；否则，识别在行驶终点预设距离范围内的租赁点，基于识别到的租赁点及租赁策略生成激励提示，将激励提示发送至终端。
在其中一个实施例中，租赁策略记录了多种激励条件及每种激励条件对应的激励资源；如图3C所示，该装置还包括调度激励预测模块312，用于接收终端发送的激励预测请求；激励预测请求包含计划行驶起点、计划行驶终点和计划行驶时间；判断计划行驶终点是否属于一个租赁点，记作目标租赁点；若是，根据计划行驶起点和计划行驶终点，生成导航路线；根据导航路线，计算本次计划出行对应的行驶时长；获取目标租赁点在计划行驶时间对应的下一个监控时段对共享车辆的常规需求量；根据行驶时长和常规需求量，识别本次计划出行能够满足的激励条件；获取激励条件对应的激励资源，将获取到的激励资源作为预测结果反馈至终端。
关于车辆租赁装置的具体限定可以参见上文中对于车辆租赁方法的限定，在此不再赘述。上述车辆租赁装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在其中一个实施例中，提供了一种计算机设备，该计算机设备可以是服务器，其内部结构图可以如图4所示。该计算机设备包括通过系统总线连接的处理器、存储器、网络接口和数据库。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作系统、计算机可读指令和数据库。该内存储器为非易失性存储介质中的操作系统和计算机可读指令的运行提供环境。该计算机设备的数据库用于存储监控区域地图、租赁策略等。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机可读指令被处理器执行时以实现一种车辆租赁方法。
本领域技术人员可以理解，图4中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
一个或多个存储有计算机可读指令的非易失性存储介质，计算机可读指令被一个或多个处理器执行时，使得一个或多个处理器实现本申请任意一个实施例中提供的车辆租赁方法的步骤。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成的，计算机可读指令可存储于一非易失性计算机可读取存储介质中，该计算机可读指令在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可 包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Rambus)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (20)

  1. 一种车辆租赁方法，所述方法包括：
    获取监控区域的地图，根据所述地图在所述监控区域确定多个租赁点；
    采集多个所述租赁点在历史监控周期多个监控时段的共享车辆出入数据；
    将所述共享车辆出入数据输入预设的车辆租赁模型，确定多个所述租赁点分别对共享车辆的常规需求量；
    根据所述常规需求量，生成所述监控区域在当前监控周期多个监控时段的租赁策略；及
    识别共享车辆是否到达所述租赁点，基于所述租赁策略对到达所述租赁点的共享车辆的用户进行资源转移。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述地图在所述监控区域确定多个租赁点，包括：
    将所述监控区域划分为多个子区域；
    根据所述地图获取每个所述子区域内的建筑分布信息；
    获取每个所述子区域在所述历史监控周期的车辆平均停放数量；及
    将所述建筑分布信息以及所述车辆平均停放数量均满足预设条件的子区域，确定为所述监控区域的一个所述租赁点。
  3. 根据权利要求1所述的方法，其特征在于，所述采集多个租赁点在历史监控周期多个监控时段的共享车辆出入数据，包括：
    拉取终端在多个监控时段生成的对共享车辆应用程序的操作行为日志；
    对所述操作行为日志进行解析，得到多个操作行为字段；所述操作行为字段包括操作标识、操作时间和操作位置；
    将操作时间识别为所述监控时段，将操作位置识别为所述租赁点；及
    对多个租赁点在每个监控时段内每个操作标识对应的实际操作次数分别进行统计，将统计结果作为所述共享车辆出入数据。
  4. 根据权利要求1所述的方法，其特征在于，所述基于所述租赁策略对到达租赁点的共享车辆的用户进行资源转移之前，所述方法还包括：
    接收终端发送的车辆预约请求，响应所述车辆预约请求将存储的共享车辆分布图发送至所述终端；所述共享车辆分布图包括多个车辆图标；
    捕获终端在所述共享车辆分布地图发生的对所述车辆图标的选定操作；及
    识别所述选定操作对应车辆图标预设距离范围内的租赁点，基于识别到的租赁点及所述租赁策略生成激励提示，将所述激励提示发送至所述终端。
  5. 根据权利要求1所述的方法，其特征在于，所述基于所述租赁策略对到达所述租赁点的共享车辆的用户进行资源转移之前，所述方法还包括：
    在接收到终端发送的用车请求时，开始记录行驶数据；所述行驶数据包括本次出行的 行驶起点和行驶路线；
    根据所述行驶路线，实时检测共享车辆预设距离范围内是否存在租赁点；
    若是，根据所述租赁策略、行驶起点及预设距离范围内的租赁点，预测本次出行可得的激励资源；及
    基于所述激励资源生成激励提示，将所述激励提示推送至所述终端。
  6. 根据权利要求1所述的方法，其特征在于，所述租赁策略记录了多种激励条件及每种激励条件对应的激励资源；所述基于所述租赁策略对到达所述租赁点的共享车辆的用户进行资源转移，包括：
    在接收到终端发送的用车请求时，开始记录行驶数据；
    在接收到终端发送的还车请求时，结束记录行驶数据；所述行驶数据包括本次出行的行驶终点和行驶时间；
    判断所述行驶终点是否属于一个所述租赁点，记作目标租赁点；
    若是，确定所述行驶时间对应的当前的监控时段，获取所述目标租赁点在下一个监控时段对所述共享车辆的常规需求量；根据所述常规需求量，识别本次出行能够满足的激励条件；获取所述激励条件对应的激励资源；基于所述激励资源对所述终端对应用户标识进行资源转移；及
    否则，识别在所述行驶终点预设距离范围内的租赁点，基于识别到的租赁点及所述租赁策略生成激励提示，将所述激励提示发送至所述终端。
  7. 根据权利要求1所述的方法，其特征在于，所述租赁策略记录了多种激励条件及每种激励条件对应的激励资源；所述方法还包括：
    接收终端发送的激励预测请求；所述激励预测请求包含计划行驶起点、计划行驶终点和计划行驶时间；
    判断所述计划行驶终点是否属于一个所述租赁点，记作目标租赁点；
    若是，根据所述计划行驶起点和所述计划行驶终点，生成导航路线；
    根据所述导航路线，计算本次计划出行对应的行驶时长；
    获取所述目标租赁点在所述计划行驶时间对应的下一个监控时段对共享车辆的常规需求量；及
    根据所述行驶时长和所述常规需求量，识别本次计划出行能够满足的激励条件；获取所述激励条件对应的激励资源，将获取到的激励资源作为预测结果反馈至所述终端。
  8. 一种车辆租赁装置，所述装置包括：
    租赁点确定模块，用于获取监控区域的地图，根据所述地图在所述监控区域确定多个租赁点；
    需求量测算模块，用于采集多个租赁点在历史监控周期多个监控时段的共享车辆出入数据；将所述共享车辆出入数据输入预设的车辆租赁模型，确定多个所述租赁点分别对共享车辆的常规需求量；
    租赁策略生成模块，用于根据所述常规需求量，生成所述监控区域在当前监控周期多个监控时段的租赁策略；及
    激励资源转移模块，用于识别共享车辆是否到达所述租赁点，基于所述租赁策略对到达租赁点的所述共享车辆的用户进行资源转移。
  9. 一种计算机设备，包括存储器及一个或多个处理器，所述存储器中储存有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    监测终端发布的制度信息，对所述制度信息进行分词得到对应的原始词语集合；所述原始词语集合包括多个原始词语；
    对各个原始词语进行同义扩展，生成每个原始词语对应的扩展词语集合；
    根据各个扩展词语集合形成所述制度信息对应的扩展制度信息集合；
    将所述扩展制度信息集合输入预设的制度管理模型，得到所述制度信息对应的目标类别；及
    获取多个目标信息树分别对应的类别标注，筛选包含与所述目标类别对应类别标注的目标信息树，将所述制度信息添加至筛选得到的目标信息树。
  10. 根据权利要求9所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：
    将所述监控区域划分为多个子区域；
    根据所述地图获取每个所述子区域内的建筑分布信息；
    获取每个所述子区域在所述历史监控周期的车辆平均停放数量；及
    将所述建筑分布信息以及所述车辆平均停放数量均满足预设条件的子区域，确定为所述监控区域的一个所述租赁点。
  11. 根据权利要求9所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：
    拉取终端在多个监控时段生成的对共享车辆应用程序的操作行为日志；
    对所述操作行为日志进行解析，得到多个操作行为字段；所述操作行为字段包括操作标识、操作时间和操作位置；
    将操作时间识别为所述监控时段，将操作位置识别为所述租赁点；及
    对多个租赁点在每个监控时段内每个操作标识对应的实际操作次数分别进行统计，将统计结果作为所述共享车辆出入数据。
  12. 根据权利要求9所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：
    接收终端发送的车辆预约请求，响应所述车辆预约请求将存储的共享车辆分布图发送至所述终端；所述共享车辆分布图包括多个车辆图标；
    捕获终端在所述共享车辆分布地图发生的对所述车辆图标的选定操作；及
    识别所述选定操作对应车辆图标预设距离范围内的租赁点，基于识别到的租赁点及所述租赁策略生成激励提示，将所述激励提示发送至所述终端。
  13. 根据权利要求9所述的计算机设备，其特征在于，所述处理器执行所述计算机可读指令时还执行以下步骤：
    在接收到终端发送的用车请求时，开始记录行驶数据；所述行驶数据包括本次出行的行驶起点和行驶路线；
    根据所述行驶路线，实时检测共享车辆预设距离范围内是否存在租赁点；
    若是，根据所述租赁策略、行驶起点及预设距离范围内的租赁点，预测本次出行可得的激励资源；及
    基于所述激励资源生成激励提示，将所述激励提示推送至所述终端。
  14. 根据权利要求9所述的计算机设备，其特征在于，所述租赁策略记录了多种激励条件及每种激励条件对应的激励资源；所述处理器执行所述计算机可读指令时还执行以下步骤：
    在接收到终端发送的用车请求时，开始记录行驶数据；
    在接收到终端发送的还车请求时，结束记录行驶数据；所述行驶数据包括本次出行的行驶终点和行驶时间；
    判断所述行驶终点是否属于一个所述租赁点，记作目标租赁点；
    若是，确定所述行驶时间对应的当前的监控时段，获取所述目标租赁点在下一个监控时段对所述共享车辆的常规需求量；根据所述常规需求量，识别本次出行能够满足的激励条件；获取所述激励条件对应的激励资源；基于所述激励资源对所述终端对应用户标识进行资源转移；及
    否则，识别在所述行驶终点预设距离范围内的租赁点，基于识别到的租赁点及所述租赁策略生成激励提示，将所述激励提示发送至所述终端。
  15. 一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    监测终端发布的制度信息，对所述制度信息进行分词得到对应的原始词语集合；所述原始词语集合包括多个原始词语；
    对各个原始词语进行同义扩展，生成每个原始词语对应的扩展词语集合；
    根据各个扩展词语集合形成所述制度信息对应的扩展制度信息集合；
    将所述扩展制度信息集合输入预设的制度管理模型，得到所述制度信息对应的目标类别；及
    获取多个目标信息树分别对应的类别标注，筛选包含与所述目标类别对应类别标注的目标信息树，将所述制度信息添加至筛选得到的目标信息树。
  16. 根据权利要求15所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    将所述监控区域划分为多个子区域；
    根据所述地图获取每个所述子区域内的建筑分布信息；
    获取每个所述子区域在所述历史监控周期的车辆平均停放数量；及
    将所述建筑分布信息以及所述车辆平均停放数量均满足预设条件的子区域，确定为所述监控区域的一个所述租赁点。
  17. 根据权利要求15所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    拉取终端在多个监控时段生成的对共享车辆应用程序的操作行为日志；
    对所述操作行为日志进行解析，得到多个操作行为字段；所述操作行为字段包括操作标识、操作时间和操作位置；
    将操作时间识别为所述监控时段，将操作位置识别为所述租赁点；及
    对多个租赁点在每个监控时段内每个操作标识对应的实际操作次数分别进行统计，将统计结果作为所述共享车辆出入数据。
  18. 根据权利要求15所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    接收终端发送的车辆预约请求，响应所述车辆预约请求将存储的共享车辆分布图发送至所述终端；所述共享车辆分布图包括多个车辆图标；
    捕获终端在所述共享车辆分布地图发生的对所述车辆图标的选定操作；及
    识别所述选定操作对应车辆图标预设距离范围内的租赁点，基于识别到的租赁点及所述租赁策略生成激励提示，将所述激励提示发送至所述终端。
  19. 根据权利要求15所述的存储介质，其特征在于，所述计算机可读指令被所述处理器执行时还执行以下步骤：
    在接收到终端发送的用车请求时，开始记录行驶数据；所述行驶数据包括本次出行的行驶起点和行驶路线；
    根据所述行驶路线，实时检测共享车辆预设距离范围内是否存在租赁点；
    若是，根据所述租赁策略、行驶起点及预设距离范围内的租赁点，预测本次出行可得的激励资源；及
    基于所述激励资源生成激励提示，将所述激励提示推送至所述终端。
  20. 根据权利要求15所述的存储介质，其特征在于，所述租赁策略记录了多种激励条件及每种激励条件对应的激励资源；所述计算机可读指令被所述处理器执行时还执行以下步骤：
    在接收到终端发送的用车请求时，开始记录行驶数据；
    在接收到终端发送的还车请求时，结束记录行驶数据；所述行驶数据包括本次出行的行驶终点和行驶时间；
    判断所述行驶终点是否属于一个所述租赁点，记作目标租赁点；
    若是，确定所述行驶时间对应的当前的监控时段，获取所述目标租赁点在下一个监控时段对所述共享车辆的常规需求量；根据所述常规需求量，识别本次出行能够满足的激励条件；获取所述激励条件对应的激励资源；基于所述激励资源对所述终端对应用户标识进行资源转移；及
    否则，识别在所述行驶终点预设距离范围内的租赁点，基于识别到的租赁点及所述租赁策略生成激励提示，将所述激励提示发送至所述终端。
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