CN116227889B

CN116227889B - Vehicle moving method and device for sharing vehicle, computer equipment and storage medium

Info

Publication number: CN116227889B
Application number: CN202310492248.3A
Authority: CN
Inventors: 金德才; 刘永威; 刘思喆
Original assignee: Beijing Apoco Blue Technology Co ltd
Current assignee: Beijing Apoco Blue Technology Co ltd
Priority date: 2023-05-05
Filing date: 2023-05-05
Publication date: 2023-07-25
Anticipated expiration: 2043-05-05
Also published as: CN116227889A

Abstract

The application relates to a vehicle moving method, device, computer equipment and storage medium of a shared vehicle. The method comprises the following steps: determining candidate stations corresponding to the shared vehicles to be moved; aiming at each candidate station, determining the station estimated demand of the candidate station according to a preset station estimated demand calculation model, the vehicle-on time of the candidate station and the target outflow resource quantity; according to a preset station fusion demand calculation model, a station estimated demand of a candidate station and a target outflow resource quantity, determining a station fusion demand of the candidate station; determining the number of gap vehicles of the candidate station according to a preset vehicle gap calculation model, the station fusion demand of the candidate station, the target inflow resource quantity and the number of existing vehicles in the station; identifying target stations meeting preset vehicle moving conditions in each candidate station according to the number of gap vehicles of each candidate station; the target station is a station into which the shared vehicle to be moved is moved. By adopting the method, the vehicle moving efficiency of the shared vehicle can be improved.

Description

Vehicle moving method and device for sharing vehicle, computer equipment and storage medium

Technical Field

The present application relates to the field of artificial intelligence, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for moving a shared vehicle.

Background

As sharing economies develop, sharing vehicles are entering more and more cities. After the shared vehicle is put in, the shared vehicle is often required to be moved to ensure that the shared vehicle can meet the vehicle requirements of all stations.

In the conventional vehicle moving method of the shared vehicle, the target station for moving the vehicle is determined mainly by personal observation and personal experience of a worker. Therefore, the conventional vehicle moving method of the shared vehicle needs to consume a lot of time and has low efficiency.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a vehicle moving method, apparatus, computer device, computer-readable storage medium, and computer program product for a shared vehicle that can improve efficiency.

In a first aspect, the present application provides a method for moving a shared vehicle. The method comprises the following steps:

determining candidate stations corresponding to the shared vehicles to be moved;

aiming at each candidate station, determining the station estimated demand of the candidate station according to a preset station estimated demand calculation model, the vehicle-on time of the candidate station and the target outflow resource quantity;

Determining the station fusion demand of the candidate station according to a preset station fusion demand calculation model, the station estimated demand of the candidate station and the target outflow resource quantity;

determining the number of gap vehicles of the candidate station according to a preset vehicle gap calculation model, the station fusion demand of the candidate station, the target inflow resource quantity and the number of existing vehicles in the station;

identifying target stations meeting preset vehicle moving conditions in the candidate stations according to the number of gap vehicles of the candidate stations; the target station is a station into which the shared vehicle to be moved is moved.

In one embodiment, the determining the estimated station demand of the candidate station according to the preset estimated station demand calculation model, the available time of the candidate station and the target outflow resource amount includes:

determining the ratio of the time of the bus having the candidate station according to the time of the bus having the candidate station and the reference total time;

and determining the station estimated demand of the candidate station according to the ratio of the target outflow resource quantity of the candidate station to the ratio of the vehicle-mounted time of the candidate station.

In one embodiment, the determining the station fusion demand of the candidate station according to the preset station fusion demand calculation model, the station estimated demand of the candidate station, and the target outflow resource amount includes:

Determining a second weight corresponding to the estimated required quantity of the station according to the first weight corresponding to the target outflow resource quantity;

and determining the station fusion demand of the candidate station according to the first weight, the second weight, the station estimated demand of the candidate station and the target outflow resource quantity.

In one embodiment, the method further comprises:

determining the cumulative resource duty ratio of each station according to a preset cumulative resource duty ratio calculation model, the target outflow resource amount and the target inflow resource amount of each station;

and determining candidate stations in the stations according to the accumulated resource duty ratio of the stations and a preset duty ratio threshold value.

In one embodiment, the determining the cumulative resource duty ratio of each station according to the preset cumulative resource duty ratio calculation model, the target outflow resource amount and the target inflow resource amount of each station includes:

determining the total amount of outflow resources according to the target outflow resource amount of each station;

sequencing the stations according to a first sequence of the target outflow resource quantity from large to small to obtain a first station sequence;

if stations with the same target outflow resource amount exist in the first station sequence, sequencing the stations with the same target outflow resource amount in the first station sequence according to a second sequence from small target inflow resource amount to large target inflow resource amount to obtain a second station sequence;

For each station in the second station sequence, calculating an accumulated resource amount of the station according to a target outflow resource amount of the station and a target outflow resource amount of a front-row station preceding the station in the second station sequence;

and calculating the cumulative resource duty ratio of the station according to the cumulative resource amount of the station and the total outflow resource amount.

In one embodiment, the determining the candidate station in each station according to the cumulative resource duty ratio of each station and the preset duty ratio threshold value includes:

for each station, if the accumulated resource duty ratio of the station is smaller than a preset duty ratio threshold, determining that the station is a hot station;

and if the number of the existing vehicles in the station of the hot station is smaller than or equal to a preset remaining vehicle threshold value, determining the hot station as a candidate station.

In one embodiment, the method further comprises:

inquiring a target acquisition period corresponding to a target date type in a mapping relation between the date type and the acquisition period according to the target date type of the predicted time;

acquiring the time of arrival, the amount of outflow resources and the amount of inflow resources corresponding to each target day in the target acquisition period, and calculating the average time of arrival, the average amount of outflow resources and the average amount of inflow resources in the target acquisition period according to the time of arrival, the amount of outflow resources and the amount of inflow resources corresponding to each target day in the target acquisition period;

And taking the average time, the average outflow resource amount and the average inflow resource amount in the target acquisition period as the target time, the target outflow resource amount and the target inflow resource amount corresponding to the predicted time respectively.

In a second aspect, the present application further provides a vehicle moving device for a shared vehicle. The device comprises:

the first determining module is used for determining candidate stations corresponding to the shared vehicles to be moved;

the second determining module is used for determining the station estimated demand of each candidate station according to a preset station estimated demand calculation model, the available time of the candidate station and the target outflow resource quantity;

the third determining module is used for determining the station fusion demand of the candidate station according to a preset station fusion demand calculation model, the station estimated demand of the candidate station and the target outflow resource quantity;

a fourth determining module, configured to determine, according to a preset vehicle gap calculation model, a station fusion demand of the candidate station, a target inflow resource amount, and an existing number of vehicles in the station, a number of gap vehicles of the candidate station;

the identification module is used for identifying target stations meeting preset vehicle moving conditions in the candidate stations according to the number of the gap vehicles of the candidate stations; the target station is a station into which the shared vehicle to be moved is moved.

In one embodiment, the second determining module is specifically configured to:

In one embodiment, the third determining module is specifically configured to:

In one embodiment, the apparatus further comprises:

a fifth determining module, configured to determine an accumulated resource duty ratio of each station according to a preset accumulated resource duty ratio calculation model, a target outflow resource amount and a target inflow resource amount of each station;

and a sixth determining module, configured to determine candidate stations in each station according to the cumulative resource duty ratio of each station and a preset duty ratio threshold.

In one embodiment, the fifth determining module is specifically configured to:

In one embodiment, the sixth determining module is specifically configured to:

In one embodiment, the apparatus further comprises:

the query module is used for querying a target acquisition period corresponding to the target date type in the mapping relation between the date type and the acquisition period according to the target date type of the predicted time;

the calculation module is used for acquiring the on-vehicle time, the outflow resource quantity and the inflow resource quantity corresponding to each target day in the target acquisition period, and calculating the average on-vehicle time, the average outflow resource quantity and the average inflow resource quantity in the target acquisition period according to the on-vehicle time, the outflow resource quantity and the inflow resource quantity corresponding to each target day in the target acquisition period;

and a seventh determining module, configured to respectively use the average vehicle-mounted time, the average outflow resource amount and the average inflow resource amount in the target acquisition period as the target vehicle-mounted time, the target outflow resource amount and the target inflow resource amount corresponding to the predicted time.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the steps of the first aspect described above when the processor executes the computer program.

In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the first aspect described above.

In a fifth aspect, the present application also provides a computer program product. The computer program product comprising a computer program which, when executed by a processor, carries out the steps of the first aspect described above.

The vehicle moving method, the vehicle moving device, the computer equipment, the storage medium and the computer program product of the shared vehicle determine candidate stations corresponding to the shared vehicle to be moved; aiming at each candidate station, determining the station estimated demand of the candidate station according to a preset station estimated demand calculation model, the vehicle-on time of the candidate station and the target outflow resource quantity; determining the station fusion demand of the candidate station according to a preset station fusion demand calculation model, the station estimated demand of the candidate station and the target outflow resource quantity; determining the number of gap vehicles of the candidate station according to a preset vehicle gap calculation model, the station fusion demand of the candidate station, the target inflow resource quantity and the number of existing vehicles in the station; identifying target stations meeting preset vehicle moving conditions in the candidate stations according to the number of gap vehicles of the candidate stations; the target station is a station into which the shared vehicle to be moved is moved. In this way, the station estimated demand of the candidate station is predicted according to the vehicle-presence time and the target outflow resource quantity of the candidate station, the station fusion demand of the candidate station is predicted according to the station estimated demand and the target outflow resource quantity of the candidate station, the actual gap vehicle number of the candidate station is predicted according to the station fusion demand, the target inflow resource quantity and the existing vehicle number in the station of the candidate station, in each candidate station, the target station of which the gap vehicle number meets the preset vehicle moving condition is identified, the target station of which the shared vehicle is moved is automatically determined, the personal observation and the personal experience of workers are not needed, the time consumption is short, and the vehicle moving efficiency can be improved.

Drawings

FIG. 1 is a flow chart of a method for moving a shared vehicle in one embodiment;

FIG. 2 is a flowchart illustrating a step of determining a predicted station demand for a candidate station in one embodiment;

FIG. 3 is a flow diagram of a step of determining station fusion demand for a candidate station in one embodiment;

FIG. 4 is a flow chart of a method for moving a shared vehicle in another embodiment;

FIG. 5 is a flowchart illustrating steps for determining the cumulative resource occupancy of each station in one embodiment;

FIG. 6 is a flow diagram of a step of determining candidate stops in one embodiment;

FIG. 7 is a flow diagram of determining a target departure time, a target amount of outbound resources, and a target amount of inbound resources in one embodiment;

FIG. 8 is a block diagram of a shared vehicle moving apparatus in one embodiment;

fig. 9 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

In one embodiment, as shown in fig. 1, a vehicle moving method of a shared vehicle is provided, and this embodiment is illustrated by applying the method to a terminal, it is understood that the method may also be applied to a server, and may also be applied to a system including the terminal and the server, and implemented through interaction between the terminal and the server. The terminal can be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things equipment and portable wearable equipment, and the internet of things equipment can be smart speakers, smart televisions, smart air conditioners, smart vehicle-mounted equipment and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers. In this embodiment, the method includes the steps of:

step 101, determining a candidate station corresponding to the shared vehicle to be moved.

In the embodiment of the application, the terminal determines a candidate station corresponding to the shared vehicle to be moved. The shared vehicle to be moved is a shared vehicle which needs to be moved between stations, namely, the shared vehicle which needs to be moved from one station to another station. The shared vehicle to be moved is a released vehicle. The shared vehicle is a vehicle sharing economy, and can be a shared bicycle, a shared electric bicycle and a shared automobile. The station is an area where vehicles are put in. The station includes a plurality of launched shared vehicles. The candidate station is a station where the candidate shared vehicle to be moved is moved in.

In one example, the terminal takes all stations as candidate stations.

In another example, the terminal identifies, among stations, candidate stations satisfying preset candidate conditions. The candidate condition is used for measuring whether the station is a candidate station or not. The candidate condition may be a station within a preset area, or a station established within a preset establishment period.

In one example, the terminal identifies, among the released shared vehicles, a shared vehicle to be moved that satisfies a preset condition to be moved. The condition to be moved is used for measuring whether the released shared vehicle is the shared vehicle to be moved or not. The condition to be moved may be that a time when no order is generated exceeds a preset first time threshold, a time when no movement is generated exceeds a preset second time threshold, and the area is at least one of a stacking area or an inefficient area. The first time threshold may be the same as or different from the second time threshold. For example, the first time threshold and the second time threshold may each be 3 days. The accumulation area is an area where vehicles are shared to accumulate, for example, university. The inefficiency region is a region where the frequency of use of the shared vehicle is lower than a preset frequency threshold, for example, a remote region.

Step 102, for each candidate station, determining the station estimated demand of the candidate station according to a preset station estimated demand calculation model, the vehicle-on time of the candidate station and the target outflow resource quantity.

In the embodiment of the application, for each candidate station, the terminal determines the station estimated demand of the candidate station according to a preset station estimated demand calculation model, the vehicle-mounted time of the candidate station and the target outflow resource quantity. The station estimated demand calculation model is a model for calculating the estimated demand of the station, and can be a model comprising a calculation formula, a machine learning model and a neural network model. If all the shared vehicles in the station at a certain moment exit the station and no shared vehicles enter the station, the moment is the moment when no shared vehicles exist in the station. If not all the shared vehicles in the station exit the station at a certain moment or the shared vehicles enter the station, the moment is the moment when the shared vehicles exist in the station. The available time is the duration of the shared vehicle in the station, i.e., the sum of the moments when the shared vehicle exists in the station. The on-vehicle time may be a duration in which the shared vehicle exists in the station for the reference total time. The reference total time is a time period of one day, for example, the reference total time is 7 to 21 points per day, and the vehicle-on time is a time period in which a shared vehicle exists in a station within 7 to 21 points per day. There is a correspondence between the on-coming time and the reference total time. The target outflow resource amount is a target value of the resource amount that exits from the station. The resource may be an order, i.e. the target outflow resource amount is a target value for which the order is an amount that is driven out from the station. The target value may be a predicted value. The station pre-estimated demand is a pre-estimated value of the station demand according to the vehicle-lack time or the vehicle-presence time of the station.

In one example, for each candidate station, the terminal inputs the arrival time and the target outflow resource amount of the candidate station to a preset station estimated demand calculation model to obtain the station estimated demand of the candidate station.

Step 103, determining the station fusion demand of the candidate station according to a preset station fusion demand calculation model, the station estimated demand of the candidate station and the target outflow resource quantity.

In the embodiment of the application, the terminal determines the station fusion demand of the candidate station according to a preset station fusion demand calculation model, the station estimated demand of the candidate station and the target outflow resource quantity. The station fusion demand calculation model is a model for calculating the station fusion demand, and can be a model comprising a calculation formula, a machine learning model and a neural network model. The station fusion demand is a predicted value of the actual demand of the station according to the station predicted demand and the target outflow resource of the station.

In one example, the terminal inputs the station estimated demand and the target outflow resource amount of the candidate station to a preset station fusion demand calculation model to obtain the station fusion demand of the candidate station.

Step 104, determining the number of gap vehicles of the candidate station according to a preset vehicle gap calculation model, the station fusion demand of the candidate station, the target inflow resource quantity and the number of existing vehicles in the station.

In the embodiment of the application, the terminal determines the number of gap vehicles of the candidate station according to a preset vehicle gap calculation model, the station fusion demand of the candidate station, the target inflow resource quantity and the number of existing vehicles in the station. The vehicle gap calculation model is a model for calculating the number of gap vehicles at a station, and can be a model comprising a calculation formula, a machine learning model and a neural network model. The number of the gap vehicles is the number of shared vehicles which are missing in the station to meet the resource demand. The target inflow resource amount is a target value of the resource amount of the entering station. The resource may be an order, i.e. the target inflow resource amount is a target value for the amount of the order to drive into the station. The number of existing vehicles in the station is the number of shared vehicles in the station at present.

In one example, the terminal obtains the number of shared vehicles within a range with a preset radius as a radius from a station at the current moment, and obtains the number of existing vehicles in the station. Wherein the preset radius may be 25m.

In one example, the terminal inputs the station fusion demand, the target inflow resource amount and the number of existing vehicles in the station of the candidate station to a preset vehicle gap calculation model to obtain the number of gap vehicles of the candidate station.

In one example, the terminal subtracts the target inflow resource amount and the number of existing vehicles in the station from the station fusion demand amount of the candidate station to obtain the number of gap vehicles of the candidate station, which can be expressed as: gap = mix order in num-rake num in station. Wherein gap is the number of gap vehicles, mix_order is the station fusion demand, mean_order_in_num is the target inflow resource amount, and make_num_in_station is the number of existing vehicles in the station.

And 105, identifying target stations meeting preset vehicle moving conditions in each candidate station according to the number of gap vehicles in each candidate station.

The target station is a station into which the shared vehicle to be moved is moved.

In the embodiment of the application, the terminal identifies the target station meeting the preset vehicle moving condition in each candidate station according to the number of the gap vehicles of each candidate station. Specifically, for each candidate station, if the number of the gap vehicles of the candidate station is greater than or equal to the preset minimum vehicle moving number, determining that the candidate station meets the preset vehicle moving condition, and taking the candidate station as a target station. The vehicle moving condition is used for measuring whether the station is a station into which the shared vehicle to be moved is moved or not. The minimum vehicle moving number is the minimum number for moving the shared vehicle to be moved into a station. For example, the minimum number of vehicles moving may be 3.

In the vehicle moving method of the shared vehicle, a candidate station corresponding to the shared vehicle to be moved is determined; aiming at each candidate station, determining the station estimated demand of the candidate station according to a preset station estimated demand calculation model, the vehicle-on time of the candidate station and the target outflow resource quantity; according to a preset station fusion demand calculation model, a station estimated demand of a candidate station and a target outflow resource quantity, determining a station fusion demand of the candidate station; determining the number of gap vehicles of the candidate station according to a preset vehicle gap calculation model, the station fusion demand of the candidate station, the target inflow resource quantity and the number of existing vehicles in the station; identifying target stations meeting preset vehicle moving conditions in each candidate station according to the number of gap vehicles of each candidate station; the target station is a station into which the shared vehicle to be moved is moved. In this way, the station estimated demand of the candidate station is predicted according to the vehicle-presence time and the target outflow resource quantity of the candidate station, the station fusion demand of the candidate station is predicted according to the station estimated demand and the target outflow resource quantity of the candidate station, the actual gap vehicle number of the candidate station is predicted according to the station fusion demand, the target inflow resource quantity and the existing vehicle number in the station of the candidate station, the target station of which the gap vehicle number meets the preset vehicle moving condition is identified in each candidate station, the target station of which the shared vehicle is moved is automatically determined, the personal observation and the personal experience of workers are not needed, the time consumption is short, and the vehicle moving efficiency can be improved. In addition, the method comprehensively considers the predicted demand of the station and the actually generated target resource outflow when the predicted demand of the station is predicted, comprehensively considers the predicted value and the actually generated value, and considers the time when the predicted demand of the station is predicted, so that the method is more in line with the actual situation, the accuracy of the predicted demand of the station can be improved, and the accuracy of the target station determination is further improved.

In one embodiment, as shown in fig. 2, according to a preset station estimated demand calculation model, a vehicle-on time of a candidate station and a target outflow resource amount, a specific process of determining the station estimated demand of the candidate station includes the following steps:

step 201, determining the ratio of the time of the bus having the candidate station according to the time of the bus having the candidate station and the reference total time.

In the embodiment of the application, the terminal uses the ratio of the available time of the candidate station to the reference total time as the available time duty ratio of the candidate station. The ratio of the on-vehicle time to the total time of the shared vehicles in the station can be the ratio of the on-vehicle time to the total time of the shared vehicles in the station in one day, or the ratio of the on-vehicle time to the total reference time in the station in the reference total time in one day.

In one embodiment, the reference total time is 7-21 points per day for 900 minutes. The terminal determines the time-to-live duty ratio of the candidate station, and can be expressed as: have_rake_rate=mean_have_rake_mine/900. Wherein, the wave_rake_rate is the time-to-live duty ratio, and the mean_wave_rake_period is the time-to-live.

Step 202, determining the estimated station demand of the candidate station according to the ratio of the target outflow resource quantity of the candidate station to the ratio of the on-vehicle time of the candidate station.

In the embodiment of the application, the terminal divides the target outflow resource amount of the candidate station by the on-vehicle time duty ratio of the candidate station. And then, the terminal determines the estimated station demand of the candidate station according to the ratio of the obtained target outflow resource quantity of the candidate station to the ratio of the on-vehicle time of the candidate station.

In one example, the terminal uses the ratio of the obtained target outflow resource amount of the candidate station to the vehicle-on time ratio of the candidate station as the station estimated demand of the candidate station.

In one example, for each candidate station, the terminal multiplies the target resource outflow amount of the candidate station by a preset limit number to obtain an estimated upper limit of the demand amount of the candidate station. Then, the terminal judges whether the ratio of the obtained target outflow resource quantity of the candidate station to the vehicle-on time ratio of the candidate station is smaller than or equal to the estimated demand upper limit of the candidate station. If the ratio of the obtained target outflow resource quantity of the candidate station to the ratio of the on-vehicle time of the candidate station is smaller than or equal to the estimated demand upper limit of the candidate station, the terminal uses the obtained ratio as the estimated demand of the station of the candidate station. If the ratio of the obtained target outflow resource quantity of the candidate station to the ratio of the vehicle-on time of the candidate station is greater than the estimated demand upper limit of the candidate station, the terminal takes the estimated demand upper limit of the candidate station as the estimated demand of the station of the candidate station. The limiting number is a multiple of the estimated demand of the limiting station. For example, the limit number is 5. The upper limit of the estimated demand is the maximum value of the estimated demand of the station. Therefore, the upper limit is set for the estimated demand of the station, the estimated demand of the station is prevented from being separated from actual overestimated, the method is more in line with the fact that the shared vehicles in the station are frequently used only in certain time periods in one day, but are not frequently used in other time periods, namely, the actual situation that the use time of the shared vehicles in the station is unbalanced, the accuracy of the estimated demand of the station can be further improved, and the accuracy of the target station determination is further improved.

In one embodiment, the terminal determines the estimated station demand of the candidate station, which may be expressed as: the prediction_order_num=mean_order_out_num/have_rake_rate, and the prediction_order_num is equal to or less than 5 x mean_order_out_num. The prediction_order_num is a station estimated demand, the mean_order_out_num is a target outflow resource amount, and the wave_make_rate is an available time duty ratio.

In the vehicle moving method of the shared vehicle, the ratio of the available time of the candidate station is determined according to the available time of the candidate station and the reference total time; and determining the estimated station demand of the candidate station according to the ratio of the target outflow resource quantity of the candidate station to the ratio of the on-vehicle time of the candidate station. The conventional method determines the station demand according to the inflow and outflow orders which actually occur, when the supply is insufficient, the actual demand of the station tends to be underestimated, and the method predicts the station estimated demand by using the time when the vehicle is in existence, considers the vehicle shortage time length, considers the possible resource loss caused by the vehicle shortage, can avoid the underestimation of the station estimated demand caused by the insufficient supply, accords with the actual situation better, can further improve the accuracy of the station estimated demand, and further improves the accuracy of the target station determination.

In one embodiment, as shown in fig. 3, according to a preset station fusion demand calculation model, a station estimated demand of a candidate station, and a target outflow resource amount, a specific process of determining the station fusion demand of the candidate station includes the following steps:

step 301, determining a second weight corresponding to the estimated required quantity of the station according to the first weight corresponding to the target outflow resource quantity.

In the embodiment of the application, the terminal presets a first weight corresponding to the target outflow resource amount. Then, the terminal subtracts the first weight corresponding to the target outflow resource amount from 1 to obtain the second weight corresponding to the station estimated demand amount. Wherein the sum of the first weight and the second weight is 1.

Step 302, determining the station fusion demand of the candidate station according to the first weight, the second weight, the station estimated demand of the candidate station and the target outflow resource.

In the embodiment of the application, the terminal multiplies the first weight and the target outflow resource amount. Meanwhile, the terminal multiplies the second weight and the estimated station demand of the candidate station. And then, the terminal adds the obtained two products to obtain the station fusion demand of the candidate station.

In one embodiment, the terminal determines the station fusion demand of the candidate station, which may be expressed as: mix_order=mix_rate. Mean_order_out_num+ (1-mix_rate) ×predict_order_num. The mix_order is a station fusion demand, the mix_rate is a first weight, (1-mix_rate) is a second weight, the mean_order_out_num is a target outflow resource amount, and the prediction_order_num is a station estimated demand.

In the vehicle moving method of the shared vehicle, a second weight corresponding to the estimated required quantity of the station is determined according to the first weight corresponding to the target outflow resource quantity; and determining the station fusion demand of the candidate station according to the first weight, the second weight, the station estimated demand of the candidate station and the target outflow resource. In this way, weights are set for the predicted demand of the station and the target outflow resource, the fusion demand of the station is calculated by weighting and summing, the resource demand actually occurring and the predicted resource demand are balanced through parameters, the accuracy and the stability of the predicted demand of the station can be further improved, and the accuracy of the determination of the target station is further improved.

In one embodiment, as shown in fig. 4, the vehicle moving method of the shared vehicle further includes the steps of:

step 401, determining the cumulative resource duty ratio of each station according to a preset cumulative resource duty ratio calculation model, the target outflow resource amount and the target inflow resource amount of each station.

In the embodiment of the application, the terminal determines the cumulative resource ratio of each station according to a preset cumulative resource ratio calculation model, the target outflow resource amount and the target inflow resource amount of each station. The accumulated resource duty ratio calculation model is a model for calculating the accumulated resource duty ratio of the station, and can be a model comprising a calculation formula, a machine learning model and a neural network model. The cumulative resource ratio is the ratio of the cumulative outflow resource amount to the total outflow resource amount of all stations when the station is reached.

In one example, the terminal inputs the target outflow resource amount and the target inflow resource amount of each station to a preset cumulative resource duty ratio calculation model to obtain a cumulative resource duty ratio of each station.

And step 402, determining candidate stations in the stations according to the accumulated resource duty ratio of the stations and a preset duty ratio threshold value.

In the embodiment of the present application, for each station, if the station cumulative resource duty ratio is smaller than the preset duty ratio threshold, the terminal takes the station as a hot station. Then, the terminal determines candidate stations among the hot stations. The duty ratio threshold is used for measuring whether the station is a hot station or not. For example, the duty cycle threshold may be 0.3.

In one example, the terminal takes a hot station as a candidate station.

In the vehicle moving method of the shared vehicle, the cumulative resource duty ratio of each station is determined according to a preset cumulative resource duty ratio calculation model, the target outflow resource amount and the target inflow resource amount of each station; and determining candidate stations in each station according to the accumulated resource duty ratio of each station and a preset duty ratio threshold value. Therefore, the method has the advantages that the hot stations with high service efficiency of the shared vehicles are screened in the stations by calculating the accumulated resource proportion of the stations and comparing the accumulated resource proportion of the stations with the threshold value of the proportion, and then the target stations with high service efficiency of the shared vehicles are screened in the hot stations, so that the target stations to be moved in by the shared vehicles are the stations with high service efficiency of the shared vehicles, a large amount of resource loss and waste caused by the fact that the stations with high vehicle efficiency are not available can be avoided, the hot stations consume the shared vehicles faster, the exposure is higher, a certain brand advertising effect is achieved, the vehicle efficiency can be improved when the method moves to the hot stations, the actual situation is met, the accuracy of the predicted demand quantity of the stations can be further improved while the resources of the shared vehicles are balanced, and the accuracy of the target station determination is further improved.

In one embodiment, as shown in fig. 5, according to a preset cumulative resource duty ratio calculation model, a target outflow resource amount and a target inflow resource amount of each station, a specific process of determining the cumulative resource duty ratio of each station includes the following steps:

step 501, determining the total amount of outflow resources according to the target amount of outflow resources of each station.

In the embodiment of the application, the terminal adds the target outflow resource amounts of the stations to obtain the total outflow resource amount. The total amount of the outflow resources is the sum of the target outflow resource amounts of the stations.

Step 502, sequencing stations according to a first sequence from large to small of the target outflow resource amount to obtain a first station sequence.

In the embodiment of the application, the terminal sorts the stations according to the first order from the large target outflow resource amount to the small target outflow resource amount to obtain a first station sequence. In the sorting process, when the target outflow resource amounts are equal, the terminal randomly arranges the front-back sequence of stations with the equal target outflow resource amounts. The first train station sequence is a sequence representing the sequence of train stations.

In step 503, if stations with the same target outflow resource amount exist in the first station sequence, the stations with the same target outflow resource amount in the first station sequence are ordered according to the second order from the smaller target inflow resource amount to the larger target inflow resource amount, so as to obtain a second station sequence.

In this embodiment of the present application, if stations with the same target outflow resource amount exist in the first station sequence, the terminal orders the stations with the same target outflow resource amount in the first station sequence according to a second order from the smaller target inflow resource amount to the larger target inflow resource amount, so as to obtain a second station sequence. The second train station sequence is a sequence representing the sequence of the train stations.

Step 504, for each station in the second station sequence, calculating an accumulated resource amount of the station according to the target outflow resource amount of the station and the target outflow resource amount of the front-row station before the station in the second station sequence.

In an embodiment of the present application, for each station in the second station sequence, the terminal determines a front-row station preceding the station in the second station sequence. Then, the terminal adds the target outflow resource amount of the station and the target outflow resource amounts of the front-row stations to obtain the accumulated resource amount of the station. The accumulated resource amount is an accumulated outflow resource amount when the station is reached. The front-row station is positioned in front of a certain station in the second sequence.

Step 505, calculating the cumulative resource ratio of the station according to the cumulative resource amount and the total outflow resource amount of the station.

In the embodiment of the application, the terminal calculates the ratio of the accumulated resource amount of the station to the total outflow resource amount. The terminal then takes this ratio as the cumulative resource duty of the station.

In the vehicle moving method of the shared vehicle, the total amount of the outflow resources is determined according to the target outflow resource amount of each station; sequencing stations according to a first sequence of the target outflow resource quantity from large to small to obtain a first station sequence; if stations with the same target outflow resource amount exist in the first station sequence, sequencing the stations with the same target outflow resource amount in the first station sequence according to a second sequence from small target inflow resource amount to large target inflow resource amount to obtain a second station sequence; for each station in the second station sequence, calculating the accumulated resource amount of the station according to the target outflow resource amount of the station and the target outflow resource amount of the front-row station before the station in the second station sequence; and calculating the cumulative resource duty ratio of the station according to the cumulative resource amount and the total outflow resource amount of the station. In this way, each station is ordered according to the first order of the target outflow resource quantity from large to small, when the target outflow resource quantity of the stations is the same, the stations with the same target outflow resource quantity are ordered according to the second order of the target inflow resource quantity from small to large, a second station sequence is obtained, and the cumulative resource occupation ratio of the stations is calculated according to the second station sequence, so that the target stations to be moved in by the shared vehicle are all the stations with the shared vehicle driving out of the stations, and the stations with the small driving in of the stations are all the stations with the shared vehicle driving out of the stations, a large amount of resource loss and waste caused by the fact that the stations with high vehicle effect and unbalanced outflow and inflow of the shared vehicle are not supplied can be avoided, the actual situation is more met, the accuracy of the predicted station demand quantity can be further improved while the shared vehicle resources are balanced, and the accuracy of the determination of the target stations is further improved.

In one embodiment, as shown in fig. 6, the specific process of determining candidate stations in each station according to the cumulative resource duty ratio of each station and the preset duty ratio threshold value includes the following steps:

step 601, for each station, if the cumulative resource duty ratio of the station is smaller than a preset duty ratio threshold, determining that the station is a hot station.

In the embodiment of the present application, for each station, if the cumulative resource occupancy of the station is smaller than the preset occupancy threshold, the terminal determines that the station is a hot station.

Step 602, if the number of existing vehicles in the station of the hot station is less than or equal to the preset remaining vehicle threshold, determining the hot station as a candidate station.

In the embodiment of the application, the terminal acquires the number of existing vehicles in the station of the hot station. If the number of existing vehicles in the station of the hot station is greater than a preset remaining vehicle threshold, the terminal determines that the hot station is a candidate station. The residual vehicle threshold is used for measuring whether the number of the existing shared vehicles in the station is temporarily abundant. For example, the residual threshold may be 10.

In the vehicle moving method of the shared vehicle, for each station, if the accumulated resource occupancy rate of the station is smaller than a preset occupancy rate threshold value, determining that the station is a hot station; if the number of existing vehicles in the station of the hot station is smaller than or equal to a preset remaining vehicle threshold value, determining the hot station as a candidate station. Therefore, only the hot station with the number of the existing vehicles in the station being smaller than or equal to the preset residual vehicle threshold value is used as the target station, the hot station with the enough idle vehicles and no shortage in a short time is filtered, the actual situation is more met, the waste of the shared vehicles can be avoided, the vehicle efficiency of the shared vehicles is further improved, the accuracy of the estimated demand of the station is further improved, and the accuracy of the determination of the target station is further improved.

In one embodiment, as shown in fig. 7, the vehicle moving method of the shared vehicle further includes the steps of:

in step 701, according to the target date type of the predicted time, a target acquisition period corresponding to the target date type is queried in the mapping relationship between the date type and the acquisition period.

In the embodiment of the application, the terminal stores the mapping relation between the date type and the acquisition period in advance. Then, the terminal inquires a target acquisition period corresponding to the target date type in a mapping relation between the date type and the acquisition period according to the target date type of the predicted time.

Wherein, different prediction time corresponds to different target stations, namely the target stations are determined according to the prediction time. The predicted time may be a time after the vehicle moving operation is performed, for example, a day after the vehicle moving time. The target date type is a date type of the predicted time. The date type includes an internal traffic peak period, an internal traffic stationary period, and an internal and external traffic peak period. The interior traffic peak period is the date of the interior traffic peak by the area. The interior traffic peak period may include a first type and a second type. The first type is rush hour. The second type is rush hour. The internal traffic stationary phase is a date at which the internal traffic of the area tends to be stationary compared to the internal traffic peak phase. The inside and outside traffic peak period is the date when traffic between the inside of the area and the outside of the area is frequent. The interior traffic peak period may be a first day and a last day of a workday, the first type may be the first day of the workday, and the second type may be the last day of the workday. For example, the first type is monday and/or the first day of the festival, and the second type is friday and/or the last day of the festival. The internal traffic stationary phase may be a workday other than the first and last day of the workday. For example, the internal traffic stationary phase may be Tuesday, wednesday, tuesday, and/or weekdays other than the first weekday after the festival and the last weekday before the festival. The peak internal and external traffic periods may be non-weekdays, weekends (i.e., saturday and sunday), and/or holidays. The target acquisition period is an acquisition period corresponding to the predicted time. The date type of the target acquisition period is the same as the date type of the predicted time. The target acquisition period may be a period of time of the same date type as the predicted time within a preset target period of time before the predicted time. For example, the predicted time is Saturday, the target date type is an internal-external traffic peak (weekend), and the target acquisition period is a weekend of the first 2 weeks. The date type and the target time period have a corresponding relation, namely, the target time periods corresponding to different date types are different. For example, the date type is 3 weeks for the target period corresponding to the internal traffic peak period, and the date type is 2 weeks for the target period corresponding to the internal traffic stationary period and the internal and external traffic peak period.

Step 702, obtaining the on-vehicle time, the outflow resource amount and the inflow resource amount corresponding to each target day in the target acquisition period, and calculating the average on-vehicle time, the average outflow resource amount and the average inflow resource amount in the target acquisition period according to the on-vehicle time, the outflow resource amount and the inflow resource amount corresponding to each target day in the target acquisition period.

In the embodiment of the application, the terminal acquires the vehicle-on time corresponding to each target day in the target acquisition period. Then, the terminal calculates the daily drive time in the target acquisition period according to the drive time corresponding to each target day in the target acquisition period and the target acquisition period. Specifically, the terminal calculates a ratio of the on-vehicle time corresponding to each target day in the target acquisition period to the target acquisition period. Then, the terminal takes this ratio as the daily drive time in the target acquisition period. It is understood that the specific process of the terminal calculating the average daily outflow resource amount and average daily inflow resource amount in the target acquisition period is similar to the specific process of the terminal calculating the average daily on-vehicle time in the target acquisition period described above. Wherein the target day is a natural day in the target acquisition period. For example, the target acquisition period is the weekend of the first 1 week, and the target days are the last wednesday and the last sunday.

Step 703, taking the average time of the vehicle, the average outflow resource amount and the average inflow resource amount in the target acquisition period as the target time of the vehicle, the target outflow resource amount and the target inflow resource amount corresponding to the predicted time respectively.

In the embodiment of the application, the terminal takes the daily available time in the target acquisition period as the target available time corresponding to the predicted time. Meanwhile, the terminal takes the daily average outflow resource quantity in the target acquisition period as the target outflow resource quantity corresponding to the prediction time. Meanwhile, the terminal takes the daily average inflow resource quantity in the target acquisition period as the target inflow resource quantity corresponding to the prediction time.

In the vehicle moving method of the shared vehicle, according to the target date type of the predicted time, inquiring a target acquisition period corresponding to the target date type in a mapping relation between the date type and the acquisition period; acquiring the time of arrival, the quantity of outflow resources and the quantity of inflow resources corresponding to each target day in a target acquisition period, and calculating the average time of arrival, the quantity of daily outflow resources and the quantity of daily inflow resources in the target acquisition period according to the time of arrival, the quantity of outflow resources and the quantity of inflow resources corresponding to each target day in the target acquisition period; and taking the average time, the average outflow resource quantity and the average inflow resource quantity in the target acquisition period as the target time, the target outflow resource quantity and the target inflow resource quantity corresponding to the predicted time respectively. In this way, compared with the traditional method that only dates are roughly divided into weekdays and weekends, the method divides a week into three or four categories by finely dividing time, and the time span of each category of use data is different, so that the method is more in line with the actual use condition of the shared vehicle, can improve the accuracy of the estimated use data, further improve the accuracy of the estimated demand of the station, and further improve the accuracy of the determination of the target station. In addition, compared with the traditional method of dividing the date from the precision to the date, the date type has sparse data quantity, the date type obtained by dividing the method has more data quantity, the time span of a target acquisition time period for acquiring the data is small, the data is closer to the predicted time, the timeliness of the data is better, the accuracy of the data used in prediction can be further improved, the accuracy of the predicted demand quantity of the station is further improved, and the accuracy of the determination of the target station is further improved.

In one embodiment, the vehicle moving method of the shared vehicle further includes: and the terminal determines the vehicle moving quantity of the vehicle moving to the target station according to the number of the gap vehicles of the target station. In one example, the terminal takes the number of gap vehicles at the target station as the number of vehicles moving toward the target station. Therefore, the method determines the vehicle moving quantity of the vehicle moving to the target station according to the determined number of the notch vehicles of the target vehicle, can help to adjust parameters such as the first weight and the like in the method according to the previous vehicle moving condition and the actual condition of the station, has good timeliness, can further improve the accuracy of the estimated demand of the station, and further improves the accuracy of the determination of the target station.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a vehicle moving device of the shared vehicle for realizing the vehicle moving method of the shared vehicle. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the vehicle moving device for one or more sharing vehicles provided below may refer to the limitation of the vehicle moving method for the sharing vehicle described above, and will not be repeated herein.

In one embodiment, as shown in fig. 8, there is provided a vehicle moving apparatus 800 of a shared vehicle, including: a first determination module 810, a second determination module 820, a third determination module 830, a fourth determination module 840, and an identification module 850, wherein:

a first determining module 810, configured to determine a candidate station corresponding to the shared vehicle to be moved;

a second determining module 820, configured to determine, for each candidate station, a station estimated demand of the candidate station according to a preset station estimated demand calculation model, a time of arrival of the candidate station, and a target outflow resource amount;

a third determining module 830, configured to determine a station fusion demand of the candidate station according to a preset station fusion demand calculation model, a station estimated demand of the candidate station, and a target outflow resource amount;

A fourth determining module 840, configured to determine, according to a preset vehicle gap calculation model, a station fusion demand of the candidate station, a target inflow resource amount, and an existing number of vehicles in the station, a number of gap vehicles of the candidate station;

an identifying module 850, configured to identify, in each of the candidate stations, a target station that meets a preset vehicle moving condition according to the number of notched vehicles in each of the candidate stations; the target station is a station into which the shared vehicle to be moved is moved.

Optionally, the second determining module 820 is specifically configured to:

Optionally, the third determining module 830 is specifically configured to:

Optionally, the apparatus 800 further includes:

Optionally, the fifth determining module is specifically configured to:

Optionally, the sixth determining module is specifically configured to:

Optionally, the apparatus 800 further includes:

The above-described respective modules in the vehicle moving apparatus of the shared vehicle may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 9. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured 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 and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by the processor to implement a method of moving a shared vehicle. The display unit of the computer device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by those skilled in the art that the structure shown in fig. 9 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application applies, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method embodiments described above.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data are required to comply with the related laws and regulations and standards of the related countries and regions.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric RandomAccess Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can take many forms, such as static Random access memory (Static Random Access Memory, SRAM) or Dynamic Random access memory (Dynamic Random AccessMemory, DRAM), among others. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims

1. A method of moving a shared vehicle, the method comprising:

identifying target stations meeting preset vehicle moving conditions in the candidate stations according to the number of gap vehicles of the candidate stations; the target station is a station into which the shared vehicle to be moved is moved;

the determining the candidate station corresponding to the shared vehicle to be moved comprises the following steps: determining the cumulative resource duty ratio of each station according to a preset cumulative resource duty ratio calculation model, the target outflow resource amount and the target inflow resource amount of each station; and determining candidate stations in the stations according to the accumulated resource duty ratio of the stations and a preset duty ratio threshold value.

2. The method according to claim 1, wherein determining the estimated required amount of the station of the candidate station according to the pre-set estimated required amount calculation model of the station, the time of arrival of the candidate station, and the target outflow resource amount comprises:

3. The method according to claim 1, wherein determining the station fusion demand of the candidate station according to the preset station fusion demand calculation model, the station estimated demand of the candidate station, and the target outflow resource amount includes:

4. The method of claim 1, wherein determining the cumulative resource duty cycle for each station based on a predetermined cumulative resource duty cycle calculation model, a target outflow resource amount and a target inflow resource amount for each station comprises:

5. The method of claim 1, wherein determining candidate stops in each of the stops based on the cumulative resource occupancy of each stop and a preset occupancy threshold comprises:

6. The method according to claim 1, wherein the method further comprises:

7. A vehicle moving apparatus for a shared vehicle, the apparatus comprising:

the identification module is used for identifying target stations meeting preset vehicle moving conditions in the candidate stations according to the number of the gap vehicles of the candidate stations; the target station is a station into which the shared vehicle to be moved is moved;

the first determining module is specifically configured to: determining the cumulative resource duty ratio of each station according to a preset cumulative resource duty ratio calculation model, the target outflow resource amount and the target inflow resource amount of each station; and determining candidate stations in the stations according to the accumulated resource duty ratio of the stations and a preset duty ratio threshold value.

8. The apparatus of claim 7, wherein the second determining module is specifically configured to:

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.