Method, apparatus, electronic device and storage medium for vehicle scheduling management

Abstract

Embodiments of the present invention disclose a method, apparatus, electronic device, and storage medium for vehicle scheduling management. The user identity information and vehicle identity information are obtained, and then the estimated data and scheduling records are obtained. The estimated data is compared with the scheduling records, and according to the comparison result, the vehicle identity information is displayed on the user side according to the display level. The data related to the occupation and release of the vehicle is reasonably utilized, so that the vehicle information is recommended to the user side in a hierarchical manner, which not only improves the vehicle utilization rate and adaptation rate, but also makes the vehicle allocation more reasonable.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle rental, and in particular, to a method, device, electronic device, and storage medium for vehicle scheduling management. Background Art

[0002] In vehicle rental business, how to improve the vehicle utilization rate is extremely important for reducing rental costs. In related technologies, a vehicle push system is used to display the vehicles in the vehicle platform for users to select, and users select their favorite vehicles for payment and rental. However, there are several problems in the existing vehicle push system: the relevant data on vehicle occupancy or release is not reasonably planned and utilized, resulting in problems such as some vehicles being put into use frequently while other vehicles are idle for a long time. There is also the problem that multiple people choose to rent the same vehicle, resulting in order conflicts and poor customer experience, and customer loss. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method, device, electronic device, and storage medium for vehicle scheduling management to solve the problem that in the existing vehicle rental process, the vehicle scheduling management is simple and crude, resulting in low vehicle rental utilization rate.

[0004] In a first aspect, the present invention provides a method for vehicle scheduling management, including the following steps:

[0005] Obtain user identity information from a user identity library, and retrieve user historical data matching the user identity information from a historical database;

[0006] Obtain estimated data according to the user historical data, where the estimated data includes: estimated reservation time, estimated occupancy duration, and estimated reservation path;

[0007] Obtain vehicle identity information from a vehicle identity library, and retrieve vehicle historical data matching the vehicle identity information from a vehicle usage database;

[0008] Obtain a scheduling record according to the vehicle historical data, where the scheduling record includes: reservation time distribution and reservation path distribution;

[0009] Compare the estimated data with the scheduling record, and make the following judgments in sequence:

[0010] Judge whether the estimated reservation time is outside the reservation time distribution. If not, secondary-display the vehicle identity information on the user side;

[0011] If so, judge whether the time node obtained by adding the estimated occupancy duration to the estimated reservation time is outside the reservation time distribution. If not, intermediate-display the vehicle identity information on the user side;

[0012] If so, determine whether the estimated scheduled path is within the scheduled path distribution. If not, display the vehicle identity information at an intermediate level on the user side.

[0013] If so, display the vehicle identity information at a high level on the user side.

[0014] Furthermore, the method for vehicle scheduling management further includes: when obtaining user identity information from the user identity database, if the user identity information does not exist in the user identity database, create new user identity information and generate initial user historical data, update the new user identity information to the user identity database, and store the initial user historical data in the historical database.

[0015] Furthermore, the user identity information includes: name, phone number, and common address.

[0016] Furthermore, the process of obtaining estimated data based on user historical data includes: obtaining each scheduled time in the user historical data, calculating each scheduled time according to a preset algorithm to obtain the estimated scheduled time; obtaining each rental duration in the user historical data and calculating the average rental duration, and using the average rental duration as the estimated occupancy duration; obtaining each scheduled path in the user historical data and using the most repeated scheduled path as the estimated scheduled path.

[0017] In a second aspect, the present invention provides a device for vehicle scheduling management, including:

[0018] A user-side data retrieval module for obtaining user identity information from the user identity database and retrieving user historical data matching the user identity information from the historical database;

[0019] A user-side estimation determination module for obtaining estimated data based on the user historical data, where the estimated data includes: estimated scheduled time, estimated occupancy duration, and estimated scheduled path;

[0020] A rental-side data retrieval module for obtaining vehicle identity information from the vehicle identity database and obtaining vehicle historical data matching the vehicle identity information from the vehicle usage database;

[0021] A rental-side estimation determination module for obtaining a scheduling record based on the vehicle historical data, where the scheduling record includes: scheduled time distribution and scheduled path distribution;

[0022] A discrimination display module for comparing the estimated data with the scheduling record and displaying the vehicle identity information at a display level on the user side according to the comparison result.

[0023] The discrimination and display module includes:

[0024] A first discrimination unit, configured to determine whether the estimated scheduled time is outside the scheduled time distribution. If not, the vehicle identity information is secondarily displayed on the user side;

[0025] A second discrimination unit, configured to, if the determination result of the first discrimination unit is yes, determine whether the time node obtained by adding the estimated occupancy duration to the estimated scheduled time is outside the scheduled time distribution. If not, the vehicle identity information is moderately displayed on the user side;

[0026] A third discrimination unit, configured to, if the determination result of the second discrimination unit is yes, determine whether the estimated scheduled path is within the scheduled path distribution. If not, the vehicle identity information is moderately displayed on the user side;

[0027] A fourth discrimination unit, configured to, if the determination result of the third discrimination unit is yes, highly display the vehicle identity information on the user side.

[0028] Further, the device for vehicle scheduling management further includes: a query module, configured to obtain the login data of the user side and determine whether there is vehicle identity information in the user identity library; a new creation module, configured to, when the determination result of the query module is no, create new vehicle identity information and generate initial user historical data; an update module, configured to update the new vehicle identity information to the user identity library, and store the initial user historical data in the historical database.

[0029] Further, the vehicle identity information includes: name, phone number, and common address.

[0030] Further, the user-side estimation and determination module includes: an estimated scheduled time calculation unit, configured to obtain each scheduled time in the user historical data, calculate each scheduled time according to a preset algorithm, and obtain the estimated scheduled time; an estimated occupancy duration calculation unit, configured to obtain each rental duration in the user historical data, calculate the average rental duration, and use the average rental duration as the estimated occupancy duration; an estimated scheduled path calculation unit, configured to obtain each scheduled path in the user historical data, and use the most frequently repeated scheduled path as the estimated scheduled path.

[0031] In a third aspect, an embodiment of the present invention provides an electronic device, which includes: a housing, a processor, a memory, a circuit board, and a power supply circuit. Among them, the circuit board is arranged inside the space surrounded by the housing, and the processor and the memory are arranged on the circuit board; the power supply circuit is used to supply power to each circuit or device of the above-mentioned electronic device; the memory is used to store executable program codes; the processor runs a program corresponding to the executable program codes by reading the executable program codes stored in the memory, and is used to execute the method for vehicle scheduling management described in any of the foregoing implementation manners.

[0032] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement the method for vehicle scheduling management described in any of the foregoing implementation manners.

[0033] A method, device, electronic device, and storage medium for vehicle scheduling management provided by an embodiment of the present invention obtain user identity information and vehicle identity information, and then obtain estimated data and scheduling records, and rationally utilize data related to the occupation and release of vehicles, so as to classify and recommend vehicle information to the user terminal, which not only improves the vehicle utilization rate and matching rate, but also makes vehicle allocation more reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0035] Figure 1 It is a schematic flowchart of a method for vehicle scheduling management according to the present invention;

[0036] Figure 2 It is a schematic module diagram of a device for vehicle scheduling management according to the present invention;

[0037] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] The following will describe the embodiments of the present invention in detail with reference to the drawings. It should be clear that the described embodiments are only some embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0039] As Figure 1 shown, the present invention provides a method for vehicle scheduling management applied to an electronic device, which includes the following steps:

[0040] Step 101: Obtain the login data of the user terminal.

[0041] Step 102: Determine whether there is user identity information of the currently logged-in user in the user identity library.

[0042] Step 103: If the judgment result of step 102 is non-existence, create new user identity information and generate initial user historical data, update the new user identity information to the user identity library, and store the initial user historical data in the historical database.

[0043] Step 104: If the judgment result of step 102 is existence, obtain the user identity information from the user identity library.

[0044] The user identity library stores the user identity information of all registered car rental users. Among them, the user identity information includes: name, phone number, and common address.

[0045] When the user needs to rent a car again, obtain the user's login data and extract the user's name and phone number from the login data, find the user identity information corresponding to the current user according to the phone number, and verify whether the search result is correct according to the name.

[0046] Step 105: Retrieve the user historical data matching the user identity information from the historical database.

[0047] The historical database stores the data of all registered car rental users who have completed car rental operations. User historical data refers to the recorded data generated during the user's car rental process, such as the reserved time point of car rental, rental duration, rental path, rental times, vehicle usage characteristic information, etc. The vehicle usage characteristic information includes: vehicle model, number of vehicle seats, vehicle color, etc.

[0048] After obtaining the user identity information in step 104, it is possible to search in the historical database based on the obtained user identity information and retrieve the user historical data corresponding to the user identity information, so as to obtain the relevant data reflecting the current user's car rental habits, which is convenient for subsequent analysis.

[0049] Step 106: Obtain estimated data according to the user historical data. Among them, the estimated data includes: estimated reservation time, estimated occupancy duration, and estimated reservation path.

[0050] Step 106 specifically includes the following steps:

[0051] Obtain each scheduled time in the user's historical data, calculate each scheduled time according to a preset algorithm, and obtain the estimated scheduled time. For example, the scheduled time points for car rental recorded in the user's historical data are 15:00, 15:30, and 16:00. According to the preset algorithm, the calculated estimated scheduled time is 15:30. The obtained estimated scheduled time can indicate that the user is likely to rent a car around 15:30. Among them, any existing algorithm can be used for the preset algorithm, and only need to calculate an average value-close time point by integrating all time nodes.

[0052] Obtain each car rental duration in the user's historical data, calculate the average car rental duration, and use the average car rental duration as the estimated occupancy duration. For example, the car rental durations recorded in the user's historical data are 4 hours, 5 hours, and 9 hours. Then, take the average of the three durations to get 6 hours. Then, use 6 hours as the current user's average car rental duration, that is, further as the estimated occupancy duration of the vehicle.

[0053] Obtain each scheduled route in the user's historical data, and use the most frequently repeated scheduled route as the estimated scheduled route. The route can be pre-divided. The following takes long-distance vehicle use as an example to illustrate.

[0054] For example, taking the city as the unit, a user's car rental journey is successively passing through City A, City B, and City C; another car rental journey is successively passing through City A, City B, and City D; and another car rental journey is successively passing through City A, City B, and City E.

[0055] Pre-mark the code number of City A as 01, the code number of City B as 02, the code number of City C as 03, the code number of City D as 04, and the code number of City E as 05. The marking method is preset, and the codes of each city are different from each other. For short-distance vehicle use, code marking can be carried out in each district and county within the city, or code marking can be carried out at the intersection posts of the roads.

[0056] The sequences of the three journeys are 010203, 010204, and 010205. By comparison, the most frequently repeated is 0102. Then, take the route from City A to City B as the estimated scheduled route of the vehicle.

[0057] From the above process, it can be seen that the three elements of the estimated scheduled time, the estimated occupancy duration, and the estimated scheduled route can reflect the user's car rental habits and can be used as a user portrait. When the above three factors that can reflect the user's car rental habits are obtained, it is possible to more accurately and quickly predict the current user's car rental needs based on the user's historical data.

[0058] Step 107: Obtain vehicle identity information from the vehicle identity database.

[0059] The vehicle identity database stores the vehicle identity information of all vehicles. Among them, the vehicle identity information includes: vehicle number, vehicle model, color, placement location, etc.

[0060] When a car rental browsing request sent by the user terminal is received, any unrented vehicle is extracted from the vehicle identity database, and the vehicle identity information of the current vehicle is obtained.

[0061] Step 108: Obtain the vehicle historical data that matches the vehicle identity information from the vehicle usage database.

[0062] The vehicle usage database stores the usage records of all vehicles. The vehicle historical data refers to the usage records generated during the rental process of each vehicle. After each rental of a vehicle, a usage record file will be generated, which records, for example, the rental duration of the vehicle, the rental time period, the route passed during the vehicle rental, etc.

[0063] After the vehicle identity information is obtained in Step 107, it is possible to search in the vehicle usage database based on the vehicle identity information. For example, search in the vehicle usage database based on the vehicle number, and retrieve the vehicle historical data corresponding to the vehicle identity information.

[0064] Step 109: Obtain the scheduling record according to the vehicle historical data. Among them, the scheduling record includes: scheduled time distribution and scheduled path distribution.

[0065] For example, in the vehicle historical data, the scheduled time periods of the vehicle are 09:00 - 12:00, 11:00 - 15:00, 10:00 - 16:00, 09:00 - 13:00. The overlapping time period of the four time periods is 11:00 - 12:00, and the number of occurrences of the time point 09:00 is more than that of other time points. Then, the start time point 11:00 of the overlapping time period is extended forward by one and a half hours, which is 09:30. The end time point 12:00 of the overlapping time period is extended backward by one hour, which is 13:00. Finally, 09:30 - 13:00 can be used as the scheduled time distribution.

[0066] For example, in the vehicle historical data, the path of the vehicle being scheduled once is passing through location A, location B, and location C in sequence; the path of being scheduled again is passing through location A, location B, and location D in sequence; the path of being scheduled another time is passing through location A, location B, and location E in sequence. The repeated locations of the three paths are location A and location B. Then, the path from location A to location B can be used as the scheduled path distribution.

[0067] The above is just an example of processing vehicle historical data. Any algorithm in the prior art can be used to calculate the scheduled time distribution and scheduled path distribution of the vehicle to reflect the renting habits of the vehicle, that is, used as a portrait of the vehicle, such as the time periods and paths when the vehicle is frequently used.

[0068] Step 110: Compare the estimated data with the scheduling record.

[0069] Step 111: Determine whether the estimated scheduled time is outside the scheduled time distribution.

[0070] Step 112: If the judgment result of Step 111 is that the estimated scheduled time is not outside the scheduled time distribution, then secondarily display the vehicle identity information on the user side.

[0071] For example, if the estimated scheduled time obtained in Step 106 is 12:00 and the scheduled time distribution obtained in Step 109 is 09:30 - 13:00, then the process of Step 111 is to determine whether the time point 12:00 is outside the time period 09:30 - 13:00. Obviously, the example shows that the time point 12:00 is not outside the time period 09:30 - 13:00. At this time, the judgment result shows that the user's scheduled time is probably within the frequently used time period of the vehicle. Then, for the user, the current vehicle may be in a scheduling conflict state. For the lessor, the willingness of the lessor to rent the current vehicle to the user is relatively low. Therefore, secondarily display the vehicle identity information of the current vehicle on the user side, that is, not display it prominently, reducing the possibility that the customer will finally rent this vehicle to leave it for users with actual scheduling conflicts.

[0072] Step 113: If the judgment result of Step 111 is that the estimated scheduled time is outside the scheduled time distribution, then determine whether the time node obtained by adding the estimated occupancy duration to the estimated scheduled time is outside the scheduled time distribution.

[0073] For example, if the estimated scheduled time obtained in Step 106 is 06:00 and the scheduled time distribution obtained in Step 109 is 09:30 - 13:00, then the process of Step 111 is to determine whether the time point 06:00 is outside the time period 09:30 - 13:00. Obviously, the example shows that the time point 06:00 is outside the time period 09:30 - 13:00, then start the judgment process of Step 113. For example, if the estimated occupancy duration obtained in Step 106 is 4 hours, then 06:00 plus 4 hours is 10:00, that is, the process of Step 113 is to determine whether 10:00 is outside 09:30 - 13:00.

[0074] Step 114: If the judgment result in Step 113 is that the obtained time node after addition is not outside the predetermined time distribution, the vehicle identity information is displayed at an intermediate level on the user side.

[0075] The example given in Step 113 shows that the time point 10:00 is not outside the time period 09:30 - 13:00. At this time, although the user's estimated predetermined time node 06:00 does not fall within the vehicle's frequently used time period 09:30 - 13:00, that is, it may not conflict, but after adding the usage time of 4 hours, the time point 10:00 is within the time period 09:30 - 13:00. Therefore, there is still a certain probability of conflict, but it is lower than the probability of conflict when the predetermined time directly falls within the vehicle's frequently used time period. Therefore, at this time, the vehicle identity information is displayed at an intermediate level on the user side, which is more significant than the secondary display.

[0076] Step 115: If the judgment result in Step 113 is that the obtained time node after addition is outside the predetermined time distribution, it is judged whether the estimated predetermined path is within the predetermined path distribution.

[0077] For example, the estimated predetermined time obtained in Step 106 is 07:00, the estimated occupancy duration is 2 hours, and the predetermined time distribution obtained in Step 109 is 09:30 - 13:00. Then, after adding the estimated occupancy duration of 2 hours to the estimated predetermined time of 07:00, it is 09:00. The time point 09:00 is outside the time period 09:30 - 13:00, indicating that the probability of the current user's car rental time conflicting with the vehicle's frequently used time period is the lowest. At this time, the time conflict problem can be ignored, and the focus is on whether the paths overlap.

[0078] Step 116: If the judgment result in Step 115 is that the estimated predetermined path is within the predetermined path distribution, it indicates that the estimated car rental path for the current user overlaps with the estimated traveling path for the current vehicle. Then, after the current user finishes using the vehicle, the vehicle will probably stop on the route it often travels, that is, it is convenient for the vehicle to be rented out again. Therefore, the lessor's willingness to rent the vehicle to the current user is very strong. At this time, the vehicle identity information can be displayed at a high level on the user side, that is, prominently displayed, to increase the possibility of the user renting the current vehicle.

[0079] Step 117: If the judgment result in Step 115 is that the estimated predetermined path is not within the predetermined path distribution, the vehicle identity information is displayed at an intermediate level on the user side. When starting to consider whether the paths overlap, if the estimated car rental path for the current user does not overlap with the estimated traveling path for the current vehicle, it indicates that after the current user finishes using the vehicle, the probability of the vehicle stopping on the route it often travels is relatively low. Therefore, the vehicle identity information is displayed at an intermediate level on the user side.

[0080] The secondary display, intermediate display, and advanced display of the present invention are hierarchical classifications of the prominence of vehicle information display. For example, the advanced display means that the position of the vehicle information display is arranged relatively forward, and the secondary display means that the position of the vehicle information display is arranged relatively backward. It can also be classified by color. The advanced display means that the vehicle information is displayed in red font, and the secondary display means that the vehicle information is displayed in black font. Obviously, the red font is more likely to attract the attention of users.

[0081] The present invention obtains user identity information and vehicle identity information, and then obtains estimated data that can reflect the user's car rental habits and scheduling records of the vehicle's usage habits. It rationally utilizes data related to the occupation and release of the vehicle, and finally recommends vehicle information to the user side in a hierarchical manner, avoiding the situation where some vehicles cannot be rented out for a long time or are rarely rented out, while some other vehicles are always rented frequently, resulting in a large update rate, making the vehicle allocation more reasonable and improving the vehicle utilization rate and adaptability.

[0082] As Figure 2 shown, the present invention also provides a device for vehicle scheduling management, which includes: a query module, a new module, an update module, a user-side data retrieval module, a user-side estimation and determination module, a rental-side data retrieval module, a rental-side estimation and determination module, and a discrimination and display module.

[0083] The query module is used to obtain the login data of the user side and determine whether there is user identity information in the user identity database. The user identity database stores the user identity information of all registered car rental users, where the user identity information includes: name, phone number, and common address.

[0084] When the user needs to rent a car again, the query module obtains the user's login data, extracts the user's name and phone number from the login data, finds the user identity information corresponding to the current user based on the phone number, and verifies whether the search result is correct based on the name.

[0085] The new module is used to create new user identity information and generate initial user historical data when the judgment result of the query module is that it does not exist.

[0086] The update module is used to update the new user identity information created by the new module to the user identity database and store the initial user historical data in the historical database.

[0087] The user-side data retrieval module is used to obtain user identity information from the user identity database and retrieve user historical data matching the user identity information from the historical database.

[0088] The historical database stores data of all users who have registered as car rental users and have completed car rental operations. User historical data refers to the recorded data generated during the user's car rental process, such as the reserved time point of car rental, the rental duration, the rental path, the number of car rentals, vehicle usage characteristic information, etc. Vehicle usage characteristic information includes: vehicle model, number of vehicle seats, vehicle color, etc.

[0089] When the user-side data retrieval module obtains the user identity information, it can search in the historical database based on the obtained user identity information and retrieve the user historical data corresponding to the user identity information, thereby obtaining relevant data reflecting the current user's car rental habits for subsequent analysis.

[0090] The user-side estimation and determination module is used to obtain estimation data based on the user historical data. The estimation data includes: estimated reservation time, estimated occupancy duration, estimated reservation path.

[0091] The user-side estimation and determination module includes: an estimated reservation time calculation unit, an estimated occupancy duration calculation unit, and an estimated reservation path calculation unit.

[0092] The estimated reservation time calculation unit is used to obtain each reservation time in the user historical data, calculate each reservation time according to a preset algorithm, and obtain the estimated reservation time. For example, the reserved time points of car rental recorded in the user historical data are 15:00, 15:30, and 16:00. The estimated reservation time calculated according to the preset algorithm is 15:30. The obtained estimated reservation time can indicate that the user is likely to rent a car around 15:30. Among them, any existing algorithm can be used for the preset algorithm, as long as an average value-close time point is calculated by integrating all time nodes.

[0093] The estimated occupancy duration calculation unit is used to obtain each car rental duration in the user historical data, calculate the average car rental duration, and use the average car rental duration as the estimated occupancy duration. For example, the car rental durations recorded in the user historical data are 4 hours, 5 hours, and 9 hours. The average of the three durations is taken to get 6 hours. Then 6 hours is used as the current user's average car rental duration, that is, further used as the estimated occupancy duration of the vehicle.

[0094] The estimated reservation path calculation unit is used to obtain each reservation path in the user historical data and use the reservation path with the most repetitions as the estimated reservation path.

[0095] The path can be pre-divided. The following takes long-distance vehicle use as an example for illustration:

[0096] For example, taking a city as a unit, a user's car rental journey once passed through City A, City B, and City C in sequence; another car rental journey passed through City A, City B, and City D in sequence; and yet another car rental journey passed through City A, City B, and City E in sequence.

[0097] Pre-mark the code number of City A as 01, the code number of City B as 02, the code number of City C as 03, the code number of City D as 04, and the code number of City E as 05. The marking method is preset, as long as the codes of each city are different. For short-distance car use, code marking can be carried out for each district and county within the city, or for the intersection posts of the roads.

[0098] The sequences of the three journeys are 010203, 010204, and 010205 respectively. By comparison, the most repeated is 0102, so the path from City A to City B is taken as the estimated reservation path of the vehicle.

[0099] The three elements of estimated reservation time, estimated occupancy duration, and estimated reservation path can reflect the car rental habits of users and can be used as user portraits. When the above three factors that can reflect users' car rental habits are obtained, it is possible to more accurately and quickly predict the current user's car rental needs based on the user's historical data.

[0100] The rental-side data retrieval module is used to obtain vehicle identity information from the vehicle identity library and obtain vehicle historical data matching the vehicle identity information from the vehicle usage database.

[0101] The vehicle identity library stores the vehicle identity information of all vehicles. Among them, the vehicle identity information includes: vehicle number, vehicle model, color, placement location, etc. When the rental-side data retrieval module receives a car rental browsing request sent by the user side, it extracts any unrented vehicle from the vehicle identity library and obtains the vehicle identity information of the current vehicle.

[0102] The vehicle usage database stores the usage records of all vehicles. Vehicle historical data refers to the usage records generated during the rental process of each vehicle. Each time a vehicle is rented, a usage record file will be generated, which records, for example, the rental duration of the vehicle, the rental time period of the vehicle, and the route passed by the vehicle when it is rented. When the rental-side data retrieval module obtains the vehicle identity information, it can search in the vehicle usage database based on the vehicle identity information, for example, search in the vehicle usage database based on the vehicle number, and retrieve the vehicle historical data corresponding to the vehicle identity information.

[0103] The rental-side estimated judgment module is used to obtain the scheduling record according to the vehicle historical data. The scheduling record includes: reservation time distribution and reservation path distribution.

[0104] For example, in the vehicle historical data, the reserved time periods of the vehicle are 09:00 - 12:00, 11:00 - 15:00, 10:00 - 16:00, and 09:00 - 13:00. The overlapping time period of the four time periods is 11:00 - 12:00, and the occurrence frequency of the time point 09:00 is higher than that of other time points. Then, the start time point 11:00 of the overlapping time period is extended forward by one and a half hours to 09:30. The end time point 12:00 of the overlapping time period is extended backward by one hour to 13:00. Finally, 09:30 - 13:00 can be used as the reserved time distribution.

[0105] For example, in the vehicle historical data, the reserved path of the vehicle for a certain time is passing through location A, location B, and location C in sequence; the reserved path for another time is passing through location A, location B, and location D in sequence; the reserved path for yet another time is passing through location A, location B, and location E in sequence. The overlapping locations of the three paths are location A and location B. Then, the path from location A to location B can be used as the reserved path distribution.

[0106] The above is only an example of the processing of vehicle historical data. Any algorithm in the prior art can be used to calculate the reserved time distribution and reserved path distribution of the vehicle to reflect the rental habit of the vehicle, that is, used as the portrait of the vehicle, such as the time period and path when the vehicle is frequently used.

[0107] The discrimination display module is used to compare the estimated data with the scheduling record, and display the vehicle identity information on the user side according to the display level based on the comparison result.

[0108] The discrimination display module includes: a first discrimination unit, a second discrimination unit, a third discrimination unit, and a fourth discrimination unit.

[0109] The first discrimination unit is used to determine whether the estimated reserved time is outside the reserved time distribution. If not, the vehicle identity information is sub - displayed on the user side.

[0110] For example, the estimated reservation time obtained by the user-side estimation and determination module is 12:00, and the reservation time distribution obtained by the rental-side estimation and determination module is 09:30 - 13:00. Then, the first discrimination unit is used to determine whether the time point 12:00 is outside the time period 09:30 - 13:00. Obviously, the example shows that the time point 12:00 is not outside the time period 09:30 - 13:00. At this time, the judgment result shows that the user's reservation time is likely to fall within the vehicle's peak usage time period. Then, for the user, the current vehicle may be in a collision situation. For the lessor, the lessor's willingness to rent the current vehicle to the user is relatively low. Therefore, the vehicle identity information of the current vehicle is secondarily displayed on the user side, that is, not prominently displayed, to reduce the possibility that the customer will finally rent the vehicle, so as to leave it for users with actual collisions to use.

[0111] The second discrimination unit is used to, if the judgment result of the first discrimination unit is yes, determine whether the time node obtained by adding the estimated reservation time and the estimated occupancy duration is outside the reservation time distribution. If not, the vehicle identity information is displayed at an intermediate level on the user side.

[0112] For example, the estimated reservation time obtained by the user-side estimation and determination module is 06:00, and the reservation time distribution obtained by the rental-side estimation and determination module is 09:30 - 13:00. Then, the first discrimination unit is used to determine whether the time point 06:00 is outside the time period 09:30 - 13:00. Obviously, the example shows that the time point 06:00 is outside the time period 09:30 - 13:00. Then, the second discrimination unit starts the judgment process after the first discrimination unit determines the result as yes. For example, if the estimated occupancy duration obtained by the user-side estimation and determination module is 4 hours, then 06:00 plus 4 hours is 10:00. That is, the process of the second discrimination unit is to determine whether 10:00 is outside 09:30 - 13:00.

[0113] The example shows that the time point 10:00 is not outside the time period 09:30 - 13:00. At this time, it shows that although the user's estimated reservation time node 06:00 does not fall within the vehicle's peak usage time period 09:30 - 13:00, that is, it may not be in a collision situation, but after adding the usage time of 4 hours, the time point 10:00 is within the time period 09:30 - 13:00. Therefore, there is still a certain probability of collision, but it is lower than the probability of collision when the reservation time directly falls within the vehicle's peak usage time period. Therefore, at this time, the vehicle identity information is displayed at an intermediate level on the user side, which is more prominent than the secondary display.

[0114] The third discrimination unit is used to, if the judgment result of the second discrimination unit is yes, determine whether the estimated reservation path is within the reservation path distribution. If not, the vehicle identity information is displayed at an intermediate level on the user side.

[0115] A fourth discrimination unit, configured to, if the judgment result of the third discrimination unit is yes, perform high-level display of the vehicle identity information on the user side.

[0116] For example, if the estimated reservation time obtained by the user-side estimation and determination module is 07:00 and the estimated occupancy duration is 2 hours, and the reservation time distribution obtained by the rental-side estimation and determination module is 09:30 - 13:00, then 09:00 is obtained after adding the estimated occupancy duration of 2 hours to the estimated reservation time of 07:00. Since the time point 09:00 is outside the time period 09:30 - 13:00, it indicates that the probability of the current user's car rental time colliding with the vehicle's frequently used time period is the lowest. At this time, the time collision problem can be ignored, and the focus is on whether the paths overlap.

[0117] If the judgment result of the third discrimination unit is that the estimated reservation path is within the reservation path distribution, it indicates that the estimated car rental path for the current user overlaps with the estimated traveling path for the current vehicle. Then, after the current user finishes using the vehicle, the vehicle is likely to stop on the route it often travels, that is, it is convenient for the vehicle to be rented out again. Therefore, the lessor's willingness to rent this vehicle to the current user is very strong. At this time, the fourth discrimination unit can perform high-level display of the vehicle identity information on the user side, that is, perform significant display, to increase the possibility of the user renting the current vehicle.

[0118] If the judgment result of the third discrimination unit is that the estimated reservation path is not within the reservation path distribution, the vehicle identity information is displayed at the intermediate level on the user side. When starting to consider whether the paths overlap, if the estimated car rental path for the current user does not overlap with the estimated traveling path for the current vehicle, it indicates that after the current user finishes using the vehicle, the probability of the vehicle stopping on the route it often travels is relatively low. Therefore, the third discrimination unit displays the vehicle identity information at the intermediate level on the user side.

[0119] The device of this embodiment can be used to execute the technical solutions of the method embodiment shown above. The implementation principle and technical effects are similar and will not be elaborated here.

[0120] Figure 3 It is a schematic structural diagram of an embodiment of an electronic device of the present invention, which can implement the process of the embodiment shown in the above method for vehicle scheduling management of the present invention, as Figure 3As shown in the figure, the above-mentioned electronic device may include: a housing 51, a processor 52, a memory 53, a circuit board 54, and a power supply circuit 55. Among them, the circuit board 54 is arranged inside the space surrounded by the housing 51, and the processor 52 and the memory 53 are provided on the circuit board 54; the power supply circuit 55 is used to supply power to each circuit or device of the above-mentioned electronic device; the memory 53 is used to store executable program codes; the processor 52 runs a program corresponding to the executable program code by reading the executable program code stored in the memory 53, and is used to execute the method for vehicle scheduling management described in any one of the foregoing embodiments.

[0121] For the specific execution process of the above steps by the processor 52 and the further steps executed by the processor 52 by running the executable program code, reference may be made to the description of the embodiments shown in the present invention Figure 1 and will not be elaborated herein.

[0122] The electronic device exists in various forms, including but not limited to:

[0123] (1) Mobile communication device: The characteristic of this type of device is that it has mobile communication functions and mainly aims to provide voice and data communication. This type of terminal includes: smart phones (such as iPhone), multimedia phones, functional phones, and low-end phones, etc.

[0124] (2) Mobile personal computer device: This type of device belongs to the category of personal computers, has computing and processing functions, and generally also has the characteristic of mobile Internet access. This type of terminal includes: PDA, MID, and UMPC devices, etc., such as iPad.

[0125] (3) Portable entertainment device: This type of device can display and play multimedia content. This type of device includes: audio and video players (such as iPod), handheld game consoles, e-books, and smart toys and portable vehicle navigation devices.

[0126] (4) Server: A device that provides computing services. The composition of the server includes a processor, a hard disk, a memory, a system bus, etc. The server is similar to a general computer architecture, but due to the need to provide highly reliable services, it has higher requirements in terms of processing power, stability, reliability, security, scalability, manageability, etc.

[0127] (5) Other electronic devices with data interaction functions.

[0128] Fourthly, an embodiment of the present invention further provides a computer-readable storage medium, and the computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the method for vehicle scheduling management described in any one of the foregoing embodiments.

[0129] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the said element.

[0130] Each embodiment in this specification is described in a related manner. For the same or similar parts among the embodiments, reference can be made to each other, and each embodiment focuses on the differences from other embodiments.

[0131] In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the method embodiments.

[0132] For the convenience of description, the above device is described by dividing it into various units / modules according to functions. Of course, when implementing the present invention, the functions of each unit / module can be realized in the same or multiple software and / or hardware.

[0133] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The said program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the above method embodiments. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0134] As mentioned above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for vehicle scheduling management, characterized in that, It includes the following steps: Obtain user identity information from the user identity database, and retrieve user historical data matching the user identity information from the historical database; Obtain estimated data according to the user historical data, where the estimated data includes: estimated reservation time, estimated occupancy duration, and estimated reservation path; Obtain vehicle identity information from the vehicle identity database, and obtain vehicle historical data matching the vehicle identity information from the vehicle usage database; The process of obtaining the estimated data according to the user historical data includes: obtaining each reservation time in the user historical data, calculating each reservation time according to a preset algorithm to obtain the estimated reservation time; obtaining each car rental duration in the user historical data, and calculating the average car rental duration, and using the average car rental duration as the estimated occupancy duration; obtaining each reservation path in the user historical data, and using the reservation path with the most repetitions as the estimated reservation path; Obtain a scheduling record according to the vehicle historical data, where the scheduling record includes: reservation time distribution and reservation path distribution; Compare the estimated data with the scheduling record, and make the following judgments in sequence: Judge whether the estimated reservation time is outside the reservation time distribution. If not, then secondarily display the vehicle identity information on the user side; If so, then judge whether the time node obtained after adding the estimated occupancy duration to the estimated reservation time is outside the reservation time distribution. If not, then moderately display the vehicle identity information on the user side; If so, then judge whether the estimated reservation path is within the reservation path distribution. If not, then moderately display the vehicle identity information on the user side; If so, then highly display the vehicle identity information on the user side; If when obtaining user identity information from the user identity database, the user identity information does not exist in the user identity database, then create new user identity information and generate initial user historical data, update the new user identity information to the user identity database, and store the initial user historical data in the historical database; The user identity information includes: name, phone number, and common address.

2. A device for vehicle scheduling management, characterized in that, It includes: A user-side data retrieval module, which is used to obtain user identity information from the user identity database and retrieve user historical data matching the user identity information from the historical database; A user-side estimation and determination module, which is used to obtain estimated data according to the user historical data, where the estimated data includes: estimated reservation time, estimated occupancy duration, and estimated reservation path; A rental-side data retrieval module, which is used to obtain vehicle identity information from the vehicle identity database and obtain vehicle historical data matching the vehicle identity information from the vehicle usage database; A rental-side estimation and determination module, which is used to obtain a scheduling record according to the vehicle historical data, where the scheduling record includes: reservation time distribution and reservation path distribution; A discrimination and display module, which is used to compare the estimated data with the scheduling record and display the vehicle identity information on the user side according to the display level based on the comparison result; The discrimination and display module includes: The first discrimination unit is used to determine whether the estimated scheduled time is outside the scheduled time distribution. If not, the vehicle identity information is secondarily displayed on the user side. The second discrimination unit is used to, if the determination result of the first discrimination unit is yes, determine whether the time node obtained by adding the estimated occupancy duration to the estimated scheduled time is outside the scheduled time distribution. If not, the vehicle identity information is moderately displayed on the user side. The third discrimination unit is used to, if the determination result of the second discrimination unit is yes, determine whether the estimated scheduled path is within the scheduled path distribution. If not, the vehicle identity information is moderately displayed on the user side. The fourth discrimination unit is used to, if the determination result of the third discrimination unit is yes, highly display the vehicle identity information on the user side. The query module is used to obtain the login data of the user side and determine whether there is user identity information in the user identity database. The new creation module is used to, when the determination result of the query module is non-existence, create new user identity information and generate initial user historical data. The update module is used to update the new user identity information to the user identity database, and store the initial user historical data in the historical database. The user identity information includes: name, phone number, and common address. The user-side estimated determination module includes: The estimated scheduled time calculation unit is used to obtain each scheduled time in the user historical data, calculate each scheduled time according to a preset algorithm, and obtain the estimated scheduled time. The estimated occupancy duration calculation unit is used to obtain each car rental duration in the user historical data, calculate the average car rental duration, and use the average car rental duration as the estimated occupancy duration. The estimated scheduled path calculation unit is used to obtain each scheduled path in the user historical data, and use the most repeated scheduled path as the estimated scheduled path.

3. An electronic device, characterized in that, The electronic device includes: a housing, a processor, a memory, a circuit board, and a power supply circuit. Among them, the circuit board is arranged inside the space surrounded by the housing, and the processor and the memory are arranged on the circuit board; the power supply circuit is used to supply power to each circuit or device of the above-mentioned electronic device; the memory is used to store executable program codes; the processor runs the program corresponding to the executable program codes by reading the executable program codes stored in the memory, and is used to execute a method for vehicle scheduling management described in the preceding claim 1.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement a method for vehicle scheduling management described in the preceding claim 1.

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