CN115731009A - Car renting implementation scheme - Google Patents
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Abstract
The invention relates to the technical field of car rental management, and particularly discloses a car rental realization scheme, which comprises the following steps: s1, obtaining position information of a vehicle using place of a user, and sequencing vehicle returning network points according to a sequence of arrival vehicle using places from near to far; s2, acquiring corresponding vehicle taking network points according to the vehicle returning network points selected by the user, and pushing the vehicle taking network points to the user from near to far according to the vehicle using fixed point distance of the user; each car returning network point at least corresponds to 2 car taking network points; and the number of vehicles of each vehicle taking network point is dynamically adjusted. This scheme can reduce the car taking site for lease part parking stall through the quantity of dynamic adjustment car taking site, reduces and sets up the site cost, satisfies the actual demand of taking the car simultaneously, and then has reduced the holistic operation cost of car hiring company, has guaranteed simultaneously that the user can get the car in comparatively convenient position, has guaranteed again that the in-process vehicle of returning the car gets the judgement that the state obtained the accuracy around returning.
Description
Technical Field
The invention relates to the technical field of car renting management, in particular to a car renting implementation scheme.
Background
Along with the continuous development of 'sharing economy', more and more people choose to use the mode of hiring a car to go on a journey, and the motorcycle type that this kind of mode can the flexible selection needs also can fully improve its fund utilization ratio to the crowd that uses the vehicle low frequency of use to the vexation of having avoided except that vehicle maintenance, annual check.
In the process of car rental of the existing car rental companies, car taking points need to be distributed at a plurality of positions for convenience of using by users, so that car rental service can be selected conveniently by using low time and distance cost; meanwhile, in order to reduce the tedious processes and labor input cost in the car handing over and returning processes, some car renting companies select the technology of the internet of things and realize the convenience of car renting in the form of automatic car returning and automatic car taking.
However, the existing car renting technology has the following problems that firstly, for the mode of unmanned car taking and returning, car losses before and after the car taking and returning cannot be controlled, and the maintenance probability and the maintenance cost are easily improved; the vehicle preparation time after returning is greatly increased, and a specially-assigned person needs to be sent to the returning place to do the returning operation, wash the vehicle, prepare vehicle necessities and the like, so that the personnel cost investment is high; secondly, the choice of the car renting field is limited, the car renting and returning needs to be carried out in a place which is hot or convenient to transport, and the cost for setting up the operation network point is high.
Disclosure of Invention
The invention aims to provide a car renting implementation scheme, which solves the following technical problems:
how to facilitate the operation cost of a car rental company and reduce the cost at the same time of a user.
The purpose of the invention can be realized by the following technical scheme:
a rental car implementation, the scheme comprising:
s1, obtaining position information of a vehicle taking place of a user, and sequencing vehicle returning network points according to the sequence of the vehicle taking place from near to far;
s2, acquiring corresponding vehicle taking network points according to the vehicle returning network points selected by the user, and pushing the vehicle taking network points to the user from near to far according to the vehicle using fixed point distance of the user;
each car returning network point at least corresponds to 2 car taking network points;
and the number of vehicles of each vehicle taking network point is dynamically adjusted.
In an embodiment, the process of dynamically adjusting the number of vehicles at the vehicle pickup point comprises:
acquiring historical vehicle taking data of each vehicle taking network point;
acquiring current climate state and date information;
by the formula
Obtaining the predicted number N of the vehicles for ；
wherein ,Nsub For reserving the number of cars to be picked up, t 2 For the current point in time, t 2 -t 1 = Δ t, Δ t is a preset time period, N (t) is [ t [ [ t ] 1 ，t 2 ]A non-scheduled vehicle taking quantity curve of a time period; gamma (t) is a periodic function, C w Is a climate coefficient, the climate coefficient C w And obtaining according to the environmental parameters.
In one embodiment, the climate coefficient C w The acquisition steps are as follows:
the climate coefficient C w By the formula
Obtaining;
wherein w represents whether the temperature exceeds a preset interval, if yes, w =1, and otherwise, w =0; r represents whether raining occurs, if so, r =1, otherwise, r =0; s represents whether snow falls, if so, s =1, otherwise s =0; q represents whether abnormal weather conditions exist, if so, q =1, otherwise, q =0; alpha (alpha) ("alpha") 1 、α 2 、α 3 And alpha 4 Is a preset weight coefficient; τ is a correction coefficient.
In one embodiment, the vehicle pickup network point dynamically adjusts the vehicle type pushed to the user;
the dynamic adjustment process of the vehicle type of the push vehicle comprises the following steps:
obtaining historical vehicle taking data of each vehicle taking point, and obtaining vehicle type information and vehicle value information in the historical vehicle taking data;
and dynamically distributing the vehicle type of each vehicle taking point according to the vehicle type information and the vehicle value information in the historical vehicle taking data.
In one embodiment, the process of recommending vehicle types according to historical vehicle pickup data comprises:
dividing the vehicle into value sections X according to the vehicle value information 1 、X 2 、…、X A ；
Classifying vehicles into type Y according to vehicle type information 1 、Y 2 、…、Y B ；
Obtaining a curve M of the change of the vehicle taking amount along with the date of the type Y in the X value interval through historical vehicle taking data jXY (d)；
By the formula
Calculating and obtaining a recommendation coefficient of the type Y of the value interval X of the jth vehicle taking point;
to M jXY Sorting, and recommending vehicle types according to sorting results;
wherein X is ∈ { X 1 ，X 2 ，…，X A }；Y∈{Y 1 、Y 2 、…、Y B }; d is the current date; m is a group of XY The total number of Y-type vehicles in the X value interval; a is the total number of the vehicle taking points, j belongs to [1,A ]]。
In one embodiment, the types classified according to the vehicle type information include, but are not limited to, a car, a SUV, and an MPV.
In one embodiment, the scheme further comprises:
and S3, adjusting the operators dynamically scheduling different returning points according to the predicted number of the vehicles taken at all the vehicle taking points corresponding to each vehicle changing point.
In an embodiment, the scheduling process of the operator is as follows:
grouping the returning points according to the areas;
by the formula
Obtaining the number R of the k-th vehicle returning point in the area k ；
Wherein, P is the total number of the vehicle returning points in the area; k is an element of [1, P ]]；R sum The total number of operators in the region;
and the predicted vehicle taking number of the kth vehicle returning point of the area is obtained. The invention has the beneficial effects that:
(1) The invention can reduce the laying cost of the personnel at the network points by taking the car returning network point as the center and sharing the mode of the operators at the car taking network point; in addition, the number of the car taking points is dynamically adjusted, the car taking points can be reduced to lease part of parking spaces, the cost for setting the points is reduced, the actual car taking requirement is met, the overall operation cost of a car renting company is reduced, the situation that a user can take a car at a convenient position is guaranteed, and the situation before and after the car is taken back in the car returning process is accurately judged.
(2) According to the invention, after the user selects the corresponding car taking point, the car type with higher probability is predicted and selected according to the historical car taking data of the car taking point, and through preferential pushing, the car renting requirement of the user can be more matched with the car type of the pushed car, so that the probability of selecting the component type by the user is improved, and the success rate of renting the car is improved.
(3) According to the invention, the number of operators in the shared area is adjusted and the operators of different returning points are dynamically dispatched according to the predicted number of the car taking points corresponding to each returning point, so that the operators can be more reasonably distributed, and the efficient operation of each car taking and returning point is improved.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a flow chart of the steps of a car rental implementation of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, in an embodiment, a car rental implementation scheme is provided, and the scheme includes:
s1, obtaining position information of a vehicle using place of a user, and sequencing vehicle returning network points according to a sequence of arrival vehicle using places from near to far;
s2, acquiring corresponding vehicle taking network points according to the vehicle returning network points selected by the user, and pushing the vehicle taking network points to the user from near to far according to the vehicle using fixed point distance of the user;
each car returning network point at least corresponds to 2 car taking network points;
and the number of vehicles of each vehicle taking network point is dynamically adjusted according to historical data and environmental data.
Through the technical scheme, the car renting service is realized in a mode that each car returning network corresponds to a plurality of car taking networks, and the number of cars of each car taking network is dynamically adjusted, so that on one hand, an unmanned car taking and manned car returning mode can be realized, and the mode that operators are shared by the car returning networks is used as the center, so that the laying cost of network personnel can be reduced; in addition, the number of the car taking points is dynamically adjusted, the car taking points can be reduced to lease part of parking spaces, the cost for setting the points is reduced, the actual car taking requirement is met, the overall operation cost of a car renting company is reduced, the situation that a user can take a car at a convenient position is guaranteed, and the situation before and after the car is taken back in the car returning process is accurately judged.
In addition, the vehicle returning points are screened and sequenced according to the vehicle using place position information of the user based on the vehicle returning points, and the number of the vehicle returning points is far lower than that of the vehicle taking points, so that the query efficiency of the user is higher.
It should be noted that, the specific implementation process of the solutions in steps S1 and S2 is implemented based on a positioning module configured by the mobile terminal, and both the specific path determination and the distance analysis process can be implemented by connecting to a map API interface, which is not described in this embodiment again.
As an implementation manner of the present invention, the process of dynamically adjusting the number of vehicles at the vehicle pick-up point is as follows:
acquiring historical vehicle taking data of each vehicle taking network point;
acquiring current climate state and date information;
by the formula
Obtaining the predicted number N of the vehicles for ；
wherein ,Nsub For reserving the number of cars to be picked up, t 2 For the current point in time, t 2 -t 1 = Δ t, Δ t is a preset time period, N (t) is [ t [ [ t ] 1 ，t 2 ]A curve of the quantity of non-scheduled vehicle taking in time periods; gamma (t) is a periodic function, C w Is the climate coefficient, climate coefficient C w Obtained according to the environmental parameters.
Through the technical scheme, the embodiment provides the method for predicting the vehicle taking quantity of each vehicle taking point, and specifically, the vehicle taking quantity N is reserved on the current day of the vehicle taking point according to the system sub Then obtaining the climate coefficient C based on the environmental parameters w Obtaining [ t ] based on historical data 1 ，t 2 ]The curve of the quantity of the vehicles taken in the period without reservation is finally obtained by a formula
Obtaining the predicted vehicle taking quantity N for, wherein ,
reaction at [ t 1 ，t 2 ]The average condition of non-reserved vehicles in a time period is comprehensively judged by combining the change rule of the demand quantity of the taxi renting period and the climate condition, so that the predicted number of the vehicles at the vehicle taking points can be more accurately predicted, the number of the vehicles is distributed to each vehicle taking network point based on the predicted number of the vehicles, the demands of users can be met adaptively, meanwhile, the vehicles can be rented by using the idle parking spaces, and the network point establishing cost is further reduced.
It should be noted that, different weight values are set for the periodic function γ (t) according to the working day and the rest day, the size of the weight value is determined according to the historical data and by combining data fitting, and according to the day of the week on the current date, whether the current date is a holiday or not is judged at the same time, so as to determine a unique periodic function value, and the specific data determination process is within the scope understood by those skilled in the art, which is not described in detail herein.
As an embodiment of the invention, the climate coefficient C w The acquisition steps are as follows:
climate coefficient C w By the formula
Obtaining;
wherein w represents whether the temperature exceeds a preset interval, if so, w =1, otherwise, w =0; r represents whether raining occurs, if so, r =1, otherwise, r =0; s represents whether snow falls, if so, s =1, otherwise, s =0; q represents whether abnormal weather conditions exist, if so, q =1, otherwise, q =0; alpha (alpha) ("alpha") 1 、α 2 、α 3 And alpha 4 Is a preset weight coefficient; τ is a correction coefficient.
Through the technical scheme, the embodiment provides a method for acquiring the climate coefficient C w The method of (1) is specifically determined according to data such as whether it is raining, whether it is snowing, whether abnormal weather occurs, whether the temperature is too high and the like in the weather parameters, and the data is processed by a formula
Determining the influence of environmental factors on car rental selection, obviously, the more conditions unsuitable for travelingThe greater the degree of influence on travel, the positive correlation between the degree of influence and the predicted vehicle taking quantity, and therefore the climate coefficient C is used w The calculation process can judge the influence of the environmental factors on the predicted vehicle taking quantity, so that operators can conveniently take the parking spaces with the corresponding quantity according to the predicted vehicle taking quantity in a reasonable distribution mode, the adaptability meets the requirements of users, and the overall operation cost is reduced.
It should be noted that the preset interval for judging whether the temperature is too high is set according to the routine selection in the field; the preset weight coefficient alpha in the scheme 1 、α 2 、α 3 、α 4 And the correction coefficient tau is selectively obtained after fitting according to historical data, which is not detailed here.
As an embodiment of the invention, the vehicle type pushed to the user is dynamically adjusted by the vehicle pickup network;
the process of pushing the vehicle type dynamic adjustment comprises the following steps:
obtaining historical vehicle taking data of each vehicle taking point, and obtaining vehicle type information and vehicle value information in the historical vehicle taking data;
and dynamically distributing the vehicle type of each vehicle taking point according to the vehicle type information and the vehicle value information in the historical vehicle taking data.
Through the technical scheme, after the user selects the corresponding car taking point, the car renting scheme in the implementation can predict and select the car type with higher probability according to the pushing to the car taking point corresponding to the historical car taking data of the car taking point, and through preferential pushing, the car renting requirement of the user can be matched with the car type of the pushed car more probability, so that the probability of selecting the component type by the user is improved, and the success rate of renting the car is improved.
As an embodiment of the present invention, the process of recommending a vehicle type according to historical vehicle pickup data is:
dividing the vehicle into value sections X according to the vehicle value information 1 、X 2 、…、X A ；
Classifying vehicles into types Y according to vehicle type information 1 、Y 2 、…、Y B ；
Obtaining a curve M of the change of the vehicle taking amount of the Y type in the X value interval along with the date through historical vehicle taking data jXY (d)；
By the formula
Calculating and obtaining a recommendation coefficient of the type Y of the value interval X of the jth vehicle taking point;
to M jXY Sorting, and recommending vehicle types according to sorting results;
wherein X is ∈ { X 1 ，X 2 ，…，X A }；Y∈{Y 1 、Y 2 、…、Y B }; d is the current date; m XY The total number of Y-type vehicles in the X value interval; a is the total number of the vehicle taking points, j belongs to [1,A ]]。
Through the technical scheme, the embodiment provides a specific method for sharply reducing vehicle types, specifically, the value interval X is divided according to all vehicle types 1 、X 2 、…、X A E.g., 1-10 ten thousand vehicle types, 10-20 ten thousand vehicle types, etc., and further classified into type Y according to the type of vehicle 1 、Y 2 、…、Y B Including but not limited to cars, SUVs and MPVs, and then obtaining different types of curves M of the vehicle taking quantity along with the date in different value intervals based on historical data jXY (d) Then through the formula
Calculating to obtain a recommendation coefficient of the type Y of the value interval X of the jth vehicle taking point, wherein M is jXY (d-1)+M′ jXY (d-1) the predicted value of the Y type vehicle in the value interval X of the jth vehicle taking point on the current date is superposed, so that the vehicle types which meet the requirements of users can be pushed to different vehicle taking points more reasonably, and the success rate is improved; meanwhile, vehicles of various types can be comprehensively guaranteed to be recommended in a balanced mode.
As an embodiment of the present invention, the scheme further includes:
and S3, adjusting the operators dynamically scheduling different returning points according to the predicted number of the vehicles taken at all the vehicle taking points corresponding to each vehicle changing point.
Through the technical scheme, the number of the operators in the shared area is used in the car renting scheme in the embodiment, and the operators in different car returning points are dynamically dispatched according to the predicted car taking number of all the car taking points corresponding to each car returning point, so that the operators can be more reasonably distributed, and the efficient operation of each car taking and returning point is improved.
As an embodiment of the present invention, the scheduling process of the operator is as follows:
grouping the returning points according to areas;
by the formula
Obtaining the number R of the k-th vehicle returning point in the area k ；
Wherein, P is the total number of the returning points of the area; k is an element of [1, P ]]；R sum The total number of operators in the region;
and the predicted vehicle taking number of the kth vehicle returning point of the area is obtained.
Through the technical scheme, the embodiment provides a method for scheduling operators, and specifically, returning points are grouped according to regions; then through the formula
Obtaining the number R of the k-th vehicle returning point in the area k (ii) a Wherein, P is the total number of the returning points of the area; k is an element of [1, P ]]；R sum The total number of operators in the region;
the predicted number of vehicles to be picked up for the kth returning point of the area, and therefore R is obtained through a formula k The operation personnel can be allocated in advance in a prediction mode, so that the actual requirements of different vehicle taking points and vehicle returning points can be met adaptively, and the overall operation efficiency are improvedThe rationality of the work allocation.
Although one embodiment of the present invention has been described in detail, the description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (8)
1. A car rental implementation scheme, comprising:
s1, obtaining position information of a vehicle taking place of a user, and sequencing vehicle returning network points according to the sequence of the vehicle taking place from near to far;
s2, acquiring corresponding vehicle taking network points according to the vehicle returning network points selected by the user, and pushing the vehicle taking network points to the user from near to far according to the vehicle using fixed point distance of the user;
each car returning network point at least corresponds to 2 car taking network points;
and the number of vehicles of each vehicle taking network point is dynamically adjusted.
2. The car renting implementation scheme is characterized in that the dynamic adjustment process of the number of vehicles at the car taking site is as follows:
acquiring historical vehicle taking data of each vehicle taking network point;
acquiring current climate state and date information;
by the formula
Obtaining the predicted number N of the vehicles for ；
wherein ,Nsub For reserving the number of vehicles to be picked up, t 2 For the current time point, t 2 -t 1 = Δ t, Δ t is a preset time period, N (t) is [ t [ [ t ] 1 ，t 2 ]A non-scheduled vehicle taking quantity curve of a time period; gamma (t) is a periodic function, C w Is a climate coefficient, the climate coefficient C w And obtaining according to the environmental parameters.
3. The renting implementation scheme of claim 2, wherein the climate coefficient C is w The acquisition steps are as follows:
the climate coefficient C w By the formula
Obtaining;
wherein w represents whether the temperature exceeds a preset interval, if yes, w =1, and otherwise, w =0; r represents whether raining occurs, if so, r =1, otherwise, r =0; s represents whether snow falls, if so, s =1, otherwise s =0; q represents whether abnormal weather conditions exist, if so, q =1, otherwise, q =0; alpha (alpha) ("alpha") 1 、α 2 、α 3 And alpha 4 Is a preset weight coefficient; τ is a correction coefficient.
4. The car renting implementation scheme is characterized in that the car taking network point dynamically adjusts the types of the cars pushed to the user;
the dynamic adjustment process of the vehicle type of the push vehicle comprises the following steps:
obtaining historical vehicle taking data of each vehicle taking point, and obtaining vehicle type information and vehicle value information in the historical vehicle taking data;
and dynamically distributing the vehicle type of each vehicle taking point according to the vehicle type information and the vehicle value information in the historical vehicle taking data.
5. The car renting implementation scheme is characterized in that the process of recommending the car type according to the historical car fetching data is as follows:
dividing the vehicle into value sections X according to the vehicle value information 1 、X 2 、…、X A ；
Classifying vehicles into type Y according to vehicle type information 1 、Y 2 、…、Y B ；
Obtaining a curve M of the change of the vehicle taking amount of the Y type in the X value interval along with the date through historical vehicle taking data jXY (d)；
By the formula
Calculating and obtaining a recommendation coefficient of the type Y of the value interval X of the jth vehicle taking point;
to M jXY Sorting, and recommending vehicle types according to sorting results;
wherein X is ∈ { X 1 ，X 2 ，…，X A }；Y∈{Y 1 、Y 2 、…、Y B }; d is the current date; m XY The total number of Y-type vehicles in the X value interval; a is the total number of the vehicle taking points, j belongs to [1,A ]]。
6. The car renting implementation scheme is characterized in that the types divided according to the car type information comprise but are not limited to cars, SUVs and MPVs.
7. The car rental implementation scheme of claim 3, further comprising:
and S3, adjusting the operators dynamically scheduling different returning points according to the predicted number of the vehicles taken at all the vehicle taking points corresponding to each vehicle changing point.
8. The car renting implementation scheme is characterized in that the scheduling process of the operator is as follows:
grouping the returning points according to areas;
by the formula
Obtaining the number R of the k-th vehicle returning point in the area k ；
Wherein, P is the total number of the vehicle returning points in the area; k is an element of [1, P ]]；R sum The total number of operators in the region;
and the predicted vehicle taking number of the kth vehicle returning point of the area is obtained.
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Denomination of invention: A method for implementing car rental Granted publication date: 20230609 Pledgee: Bank of Hangzhou Limited by Share Ltd. science and Technology Branch Pledgor: Hangzhou Aoyou Technology Co.,Ltd. Registration number: Y2024980009650 |
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