CN115841344A - Taxi taking hotspot area guide network taxi appointment method, system, equipment and storage medium - Google Patents
Taxi taking hotspot area guide network taxi appointment method, system, equipment and storage medium Download PDFInfo
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Abstract
The application relates to a taxi booking method, system, device and storage medium for a taxi taking hotspot area guide network. The method comprises the following steps: calculating and acquiring a pre-generated taxi-taking hot spot area by combining historical data with current environmental influence factors; determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking number of the taxi taking hot spot area and the required network car booking number; and pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area. By adopting the method, the idle network around the taxi taking hot spot area is guided to be contracted to the taxi taking hot spot area in advance in a mode of adjusting the price dynamic adjustment coefficient aiming at the pre-generated taxi taking hot spot area in a mode of being higher than the price of the common area, so that the average taxi taking time of passengers is reduced, the income of a driver is ensured, and meanwhile, the passengers are not required to bear excessive extra cost.
Description
Technical Field
The application relates to the technical field of taxi appointment of guide networks, in particular to a taxi appointment method, a taxi appointment system, computer equipment and a storage medium for a taxi taking hotspot area guide network.
Background
The current situation of network appointment vehicles is accompanied by arrival of peak periods, and some thermal areas are also generated, and the thermal areas mainly comprise places with intensive personnel, such as factories, enterprises, units, schools, residential areas and the like. Peak periods are periods where taxi demand is higher than the average taxi per minute (total taxi per day/total minutes per day), such as: morning hours (8. The number of taxi taking people in the current area at the same time is larger than a certain threshold value, and the average taxi taking duration is longer than a certain time, and the area is judged to be a taxi taking hot spot area. In normal conditions, the waiting time of the user in the rush hour is longer than that in the flat hour, but the difference is multiplied for the heating power area.
In order to improve the matching efficiency and solve the problem of large imbalance of supply and demand in a thermal area, two methods exist currently. One is remote pricing scheduling, which schedules drivers in non-thermal zones to thermal zones remotely by pricing, with additional costs borne by the passengers. The other is that the platform issues subsidies to promise drivers to go to the heating power area to receive orders, and the system can guarantee that the drivers finish orders. If the order is not enough, the system gives it compensation. However, a negative problem with remote premium scheduling is long passenger waiting times. Too much additional price is not accepted by passengers, and if too little additional price is added, the driver has no past power, and the effect is not good. The platform adopts a subsidy distribution mode, the load on the platform is too large, the mode is too simple and violent, and the driver can easily grab a hole to pull wool.
Disclosure of Invention
In view of the above, it is necessary to provide a taxi-taking hot spot area guidance network taxi appointment method, system, computer device and storage medium capable of solving the problem of large imbalance between supply and demand in a thermal area.
In one aspect, a taxi taking hotspot area guidance network taxi appointment method is provided, and the method comprises the following steps:
calculating and acquiring a pre-generated taxi-taking hot spot area by combining historical data with current environmental influence factors;
determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking number of the taxi taking hot spot area and the required network car booking number;
and pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area.
In one embodiment, the step of obtaining the pre-generated taxi-taking hotspot region through calculation of historical data and current environmental influence factors includes: acquiring the number of taxi taking persons at the same time and the taxi taking time of each time in a target area; counting the average taxi taking time; and when the number of taxi taking people at the same time in the target area is more than a certain threshold value and the average taxi taking time length is more than a time length threshold value, judging that the target area is a taxi taking hot spot area.
In one embodiment, the step of determining a price dynamic dispatching coefficient according to the difference between the real-time idle network taxi booking quantity of the taxi-taking hot spot area and the required network taxi booking quantity comprises:
acquiring the required network car booking quantity corresponding to the taxi taking hot spot area in historical data;
acquiring the real-time idle network taxi booking number in the taxi-taking hotspot area;
acquiring the difference value between the number of required network car reservations and the number of real-time idle network car reservations in the taxi taking hotspot area;
and when the difference is larger than a first threshold value, determining the price dynamic adjustment coefficient according to an algorithm model by combining the historical invoice sending data of the taxi-taking hot spot area.
In one embodiment, the step of determining the price momentum according to an algorithm model by combining the historical invoice data of the taxi-taking hot spot region comprises the following steps:
dividing the existing time period of the taxi-taking hot spot area into a plurality of continuous price adjusting time periods;
the price dynamic adjusting coefficient set in each price adjusting time period is unchanged;
before each adjusting time period, the price dynamic adjusting coefficient is recalculated.
In one embodiment, after the step of obtaining the difference between the required number of taxi reservations in the taxi-taking hot spot area and the real-time idle taxi reservation number, the method further includes:
calculating according to the mileage unit price, the distance length and the time length of taxi taking to obtain an original pre-estimation value;
and when the difference is less than or equal to the first threshold, keeping the original pre-valuation unchanged.
In one embodiment, the step of determining the price volatility includes:
when the difference value is larger than a first threshold value, setting values of the price dynamic dispatching coefficient to include a first multiple, a second multiple, a third multiple, a fourth multiple and a fifth multiple;
when the difference value is larger than a first threshold value and smaller than or equal to a second threshold value, the value of the price dynamic dispatching coefficient is a first multiple;
when the difference value is larger than a second threshold value and smaller than or equal to a third threshold value, the price dynamic dispatching coefficient takes a second multiple;
when the difference value is larger than a third threshold value and smaller than or equal to a fourth threshold value, the price dynamic dispatching coefficient value is a third multiple;
when the difference value is larger than a fourth threshold value and smaller than or equal to a fifth threshold value, the price dynamic dispatching coefficient value is a fourth multiple;
and when the difference value is larger than a fifth threshold value, the price dynamic adjustment coefficient takes the value of a fifth multiple.
In one embodiment, the method further comprises:
when the idle network appointment vehicle receives the order information, the dynamic transfer fee information added corresponding to the price dynamic transfer coefficient is sent to the idle network appointment vehicle; wherein the dynamic tuning cost = original pre-valuation (price dynamic tuning coefficient-1); when the dynamic transfer fee of the target order exceeds the upper limit value, the dynamic transfer fee is used for taking the upper limit value;
when the idle network taxi appointment receives orders to execute target orders, sending actually generated price dynamic adjustment coefficient information to passengers; when the dynamic dispatching fee of the target order exceeds the upper limit value, calculating an actually generated price dynamic dispatching coefficient according to the dynamic dispatching fee, wherein the actually generated price dynamic dispatching coefficient = the upper limit value/the original pre-evaluation +1.
In another aspect, a taxi-taking hotspot area guidance network taxi appointment system is provided, which includes:
the taxi taking hot spot area calculating module is used for calculating and acquiring a pre-generated taxi taking hot spot area by combining historical data with current environmental influence factors;
the price dynamic adjustment coefficient determining module is used for determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking quantity of the taxi taking hot spot area and the required network car booking quantity;
and the guiding message pushing module is used for pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi-taking hot spot area to the idle network taxi appointment around the taxi-taking hot spot area.
In another aspect, a computer device is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the following steps when executing the computer program:
calculating and acquiring a pre-generated taxi-taking hot spot area by combining historical data with current environmental influence factors;
determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking number of the taxi taking hot spot area and the required network car booking number;
and pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area.
In yet another aspect, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, performs the steps of:
calculating and acquiring a pre-generated taxi-taking hot spot area by combining historical data with current environmental influence factors;
determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking number of the taxi taking hot spot area and the required network car booking number;
and pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area.
According to the taxi taking hotspot area guidance network taxi booking method, system, computer equipment and storage medium, aiming at the pre-generated taxi taking hotspot area, the idle network taxi booking around the taxi taking hotspot area is guided to the taxi taking hotspot area in advance in a mode of adjusting the price dynamic adjustment coefficient in a mode higher than that of the common area, so that the average taxi taking duration of passengers is reduced, the benefit of a driver is guaranteed, and the passengers are not required to bear excessive extra cost.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a diagram of an application environment of a taxi appointment method for a guidance network in a taxi taking hotspot area in one embodiment;
FIG. 2 is a schematic flow chart illustrating a taxi appointment method for a taxi taking hotspot area guidance network in one embodiment;
FIG. 3 is a schematic flow chart illustrating the step of determining a price dynamic dispatching coefficient according to the difference between the real-time idle network car booking amount of the taxi taking hot spot area and the required network car booking amount in one embodiment;
FIG. 4 is a schematic flow chart illustrating the step of determining the price volatility factor according to an algorithmic model in combination with historical billing data of the taxi taking hot spot area in another embodiment;
FIG. 5 is a block diagram of a taxi booking system of the taxi taking hotspot area guidance network in one embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed description of the preferred embodiments
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The taxi taking hotspot area guidance network taxi appointment method can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The terminal 102 may be a vehicle-mounted system of a networked car appointment or a personal computer, a notebook computer, a smart phone, a tablet computer and a portable wearable device held by a networked car appointment driver, the terminal 102 may also be a personal computer, a notebook computer, a smart phone, a tablet computer and a portable wearable device held by a passenger, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers. The server 104 provides order service for the network appointment and the passengers, and the server 104 is preferably a network appointment service platform.
In one embodiment, as shown in fig. 2, a taxi taking hotspot area guidance network taxi appointment method is provided, which is described by taking the method as an example applied to the server 104 in fig. 1, and includes the following steps:
step S1, calculating and acquiring a pre-generated taxi-taking hot spot area by combining historical data with current environmental influence factors;
s2, determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking quantity of the taxi taking hot spot area and the required network car booking quantity;
and S3, pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area.
The environmental influence factors include weather, holidays, large activities and other external influence factors. Step S1 is to frame the thermal area of a later period of time after the current time by combining historical data with external influences such as weather, holidays, large activities and the like. And predicting and processing a pre-generated taxi-taking hot spot area in advance.
In this embodiment, the step of calculating and acquiring a pre-generated taxi-taking hotspot region by combining historical data with the current environmental influence factors includes: acquiring the number of taxi taking persons at the same time and the taxi taking time of each time in a target area; counting the average taxi taking time; and when the number of taxi taking people at the same time in the target area is more than a certain threshold value and the average taxi taking time length is more than a time length threshold value, judging that the target area is a taxi taking hot spot area. The target area is composed of a grid, the size of which is configurable.
As shown in fig. 3, in this embodiment, the step of determining the price dynamic adjustment coefficient according to the difference between the real-time idle network car booking amount of the taxi taking hot spot area and the required network car booking amount includes:
s21, acquiring the required network car booking quantity corresponding to the taxi taking hot spot area in historical data;
step S22, acquiring the number of real-time idle network car appointments in the taxi taking hotspot area;
step S23, obtaining the difference value between the required network taxi booking quantity of the taxi taking hot spot area and the real-time idle network taxi booking quantity;
and S24, when the difference is larger than a first threshold value, determining the price dynamic dispatching coefficient according to an algorithm model by combining the historical invoice sending data of the taxi taking hot spot area.
It can be understood that the price momentum is based on the historical supply and demand conditions of the heating power area, and the multiple of price adjustment is determined according to an algorithm model by combining the historical invoice of the area, and the multiple is used for pushing the driver-side message and calculating the price.
As shown in fig. 4, in this embodiment, the step of determining the price transfer coefficient according to an algorithm model by combining the historical issue data of the taxi-taking hotspot area includes:
step S241, dividing the existing time period of the taxi-taking hot spot area into a plurality of continuous price adjusting time periods;
step S242, setting the price dynamic adjustment coefficient in each price adjustment time period to be unchanged;
in step S243, the price volatility is recalculated before each price adjustment time period.
The steps S241 to S243 can ensure that the price dynamic adjustment coefficients in the same starting point and close time are consistent, when there is a dynamic adjustment situation in an order in an area, the dynamic adjustment multiplying power in the area is not changed in each price adjustment time period, and the algorithm is requested to calculate the price dynamic adjustment coefficient again after the price adjustment time period is exceeded, wherein the time length of the price adjustment time period is configurable.
In this embodiment, after the step of obtaining the difference between the required number of taxi appointments in the taxi taking hotspot area and the real-time idle number of taxi appointments, the method further includes:
calculating according to the mileage unit price, the distance length and the time length of taxi taking to obtain an original pre-estimation value;
and when the difference is less than or equal to the first threshold, keeping the original pre-valuation unchanged.
In this embodiment, the step of determining the price dynamic adjustment coefficient includes:
when the difference value is larger than a first threshold value, setting values of the price dynamic dispatching coefficient to include a first multiple, a second multiple, a third multiple, a fourth multiple and a fifth multiple;
when the difference value is larger than a first threshold value and smaller than or equal to a second threshold value, the value of the price dynamic dispatching coefficient is a first multiple;
when the difference value is larger than a second threshold value and smaller than or equal to a third threshold value, the price dynamic dispatching coefficient takes a second multiple;
when the difference value is larger than a third threshold value and smaller than or equal to a fourth threshold value, the price dynamic dispatching coefficient value is a third multiple;
when the difference value is larger than a fourth threshold value and smaller than or equal to a fifth threshold value, the price dynamic dispatching coefficient value is a fourth multiple;
and when the difference value is larger than a fifth threshold value, the price dynamic adjustment coefficient takes the value of a fifth multiple.
The value of the price dynamic adjustment coefficient is larger than 1, so that the price of the taxi-taking hot spot area is higher than that of the ordinary area. The price dynamic adjustment coefficient is the multiple of the price of the taxi-taking hot spot area being the price of the common area, and preferably, the value of the price dynamic adjustment coefficient comprises a first multiple, a second multiple, a third multiple, a fourth multiple and a fifth multiple, and the range is 1.1-1.5.
When the difference value is larger than the first threshold value, a plurality of threshold values can be set to divide the value of the price dynamic adjustment coefficient. For example, the value of the price dynamic adjustment coefficient includes a first multiple, a second multiple, a third multiple, a fourth multiple and a fifth multiple, which are 1.1, 1.2, 1.3, 1.4 and 1.5 respectively, and when the difference is greater than a first threshold and less than or equal to a second threshold, the value of the price dynamic adjustment coefficient is 1.1; when the difference value is larger than a second threshold value and smaller than or equal to a third threshold value, the value of the price dynamic dispatching coefficient is 1.2; when the difference value is larger than a third threshold value and smaller than or equal to a fourth threshold value, the value of the price dynamic dispatching coefficient is 1.3; when the difference value is larger than a fourth threshold value and smaller than or equal to a fifth threshold value, the value of the price dynamic dispatching coefficient is 1.4; and when the difference value is larger than a fifth threshold value, the value of the price dynamic adjustment coefficient is 1.5.
As shown in fig. 2, in this embodiment, the taxi taking hotspot area guidance network taxi appointment method further includes:
s4, when the free network taxi appointment receives the order information, the dynamic dispatching fee information added corresponding to the price dynamic dispatching coefficient is sent to the free network taxi appointment; wherein the dynamic tuning cost = original pre-valuation (price dynamic tuning coefficient-1); when the dynamic transfer fee of the target order exceeds the upper limit value, the dynamic transfer fee is used for taking the upper limit value;
s5, sending actually generated price dynamic adjustment coefficient information to passengers when the idle network taxi appointment order receiving execution target orders; when the dynamic dispatching fee of the target order exceeds the upper limit value, calculating an actually generated price dynamic dispatching coefficient according to the dynamic dispatching fee, wherein the actually generated price dynamic dispatching coefficient = the upper limit value/the original pre-evaluation +1.
The upper limit value of the dynamic dispatching fee can limit the upper limit of the extra fee borne by the passenger, and the situation that the passenger in a long distance needs to bear excessive extra fee is avoided. And the upper limit value is set to be a fixed value, so that the maximum value of the dynamic transfer fee is prevented. Thus, for example, the original estimated taxi taking cost is 20 yuan, the price dynamic adjustment coefficient is 1.1, the dynamic adjustment cost = the original estimated price x (the price dynamic adjustment coefficient-1) =20 x (1.3-1) =6 yuan, and even if the total cost is increased by 6 yuan, the passenger can easily accept the method. When the original estimated taxi taking cost is 120 yuan, the price dynamic dispatching coefficient is 1.3, the dynamic dispatching cost = the original estimated price (price dynamic dispatching coefficient-1) =120 × (1.3-1) =36 yuan, and therefore the total cost is increased by 36 yuan and cannot be accepted by passengers. In order to avoid this, if the upper limit value is limited to 20 yuan, the total cost is 140 yuan, and even if the total cost is increased by 20 yuan, the passenger can easily accept it. And the actually generated price dynamic adjustment coefficient = upper limit value/original pre-estimation +1=20/120+1=1.17 obtained by calculation is lower than the expected price dynamic adjustment coefficient value to be 1.3, and the actually generated price dynamic adjustment coefficient is fed back to the passenger, so that the passenger acceptance can be increased. And the mode supports the configuration of the unified upper limit value, realizes national unification, can carry out unified price adjustment on a plurality of network appointment cars in the taxi-taking hot spot area, and ensures that the price ranking of the tenant in the area is not influenced by the dynamic price adjustment. The network appointment vehicle is a network appointment vehicle service provider and can be regarded as a tenant in the system. Therefore, the dynamic price adjustment method and the dynamic price adjustment device can perform dynamic price adjustment on a plurality of tenants based on supply and demand prediction.
According to the taxi taking hotspot area guiding network taxi booking method, the idle network taxi booking around the taxi taking hotspot area is guided to the taxi taking hotspot area in advance in a mode of adjusting the price dynamic adjustment coefficient aiming at the pre-generated taxi taking hotspot area in a mode of being higher than the price of the common area, the average taxi taking duration of passengers is reduced, the income of a driver is guaranteed, and meanwhile the passengers are not required to bear excessive extra cost.
It should be understood that although the various steps in the flowcharts of fig. 2-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 5, there is provided a taxi hot spot area web-guided taxi appointment system 10, comprising: the system comprises a taxi taking hot spot area calculating module 1, a price dynamic adjustment coefficient determining module 2 and a guiding message pushing module 3.
The taxi taking hot spot area calculating module 1 is used for calculating and acquiring a pre-generated taxi taking hot spot area through historical data and current environment influence factors.
And the module 2 for determining the price dynamic dispatching coefficient is used for determining the price dynamic dispatching coefficient according to the difference value between the real-time idle network car booking quantity of the taxi taking hot spot area and the required network car booking quantity.
The guiding message pushing module 3 is configured to push the existence time period, the position coordinate, and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area.
In this embodiment, the module 1 for calculating a taxi taking hot spot region is configured to, when calculating and acquiring a pre-generated taxi taking hot spot region by combining historical data with a current environmental influence factor,: and when the number of taxi taking people at the same time in the target area is more than a certain threshold value and the average taxi taking time length is more than a time length threshold value, judging that the target area is a taxi taking hot spot area.
In this embodiment, the module for determining a dynamic price adjustment coefficient 2 is configured to, when determining a dynamic price adjustment coefficient according to a difference between the real-time idle network taxi appointment amount of the taxi-taking hotspot area and the required network taxi appointment amount, be configured to:
acquiring the required network car booking quantity corresponding to the taxi taking hot spot area in historical data;
acquiring the real-time idle network car booking quantity in the taxi taking hotspot area;
acquiring the difference value between the number of required network car reservations and the number of real-time idle network car reservations in the taxi taking hotspot area;
and when the difference is larger than a first threshold value, determining the price dynamic adjustment coefficient according to an algorithm model by combining the historical invoice data of the taxi taking hot spot area.
In this embodiment, the step of determining the price dynamic dispatching coefficient according to an algorithm model by combining the historical invoice data of the taxi-taking hotspot area includes:
dividing the existing time period of the taxi-taking hot spot area into a plurality of continuous price adjusting time periods;
the price dynamic adjustment coefficient set in each price adjustment time period is unchanged;
and recalculating the price dynamic adjustment coefficient before each price adjustment time period.
In this embodiment, after the step of obtaining the difference between the required number of taxi appointments in the taxi taking hotspot area and the real-time idle number of taxi appointments, the method further includes:
calculating according to the mileage unit price, the distance length and the time length of taxi taking to obtain an original pre-estimation value;
and when the difference is less than or equal to the first threshold, keeping the original pre-valuation unchanged.
In this embodiment, the step of determining the price dynamic adjustment coefficient includes:
when the difference value is larger than a first threshold value, setting values of the price dynamic dispatching coefficient to include a first multiple, a second multiple, a third multiple, a fourth multiple and a fifth multiple;
when the difference value is larger than a first threshold value and smaller than or equal to a second threshold value, the value of the price dynamic dispatching coefficient is a first multiple;
when the difference value is larger than a second threshold value and smaller than or equal to a third threshold value, the price dynamic dispatching coefficient takes a second multiple;
when the difference value is larger than a third threshold value and smaller than or equal to a fourth threshold value, the value of the price dynamic dispatching coefficient is a third multiple;
when the difference value is larger than a fourth threshold value and smaller than or equal to a fifth threshold value, the price dynamic dispatching coefficient value is a fourth multiple;
and when the difference value is larger than a fifth threshold value, the price dynamic adjustment coefficient takes the value of a fifth multiple.
As shown in fig. 5, in this embodiment, the taxi taking hotspot area guidance network booking system 10 further includes a dynamic pricing information pushing module 4 and an actual price dynamic pricing coefficient pushing module 5.
The dynamic transfer fee information pushing module 4 is used for sending dynamic transfer fee information increased corresponding to the price dynamic transfer coefficient to an idle network appointment vehicle when the idle network appointment vehicle receives order information; wherein the dynamic tuning cost = original pre-valuation (price dynamic tuning coefficient-1); and when the dynamic transfer fee of the target order exceeds the upper limit value, the dynamic transfer fee is taken as the upper limit value.
The actual price dynamic dispatching coefficient pushing module 5 is used for sending the actually generated price dynamic dispatching coefficient information to the passengers when the idle network appointment receives orders to execute the target orders; when the dynamic dispatching fee of the target order exceeds the upper limit value, calculating an actually generated price dynamic dispatching coefficient according to the dynamic dispatching fee, wherein the actually generated price dynamic dispatching coefficient = the upper limit value/the original pre-evaluation +1.
In the taxi taking hotspot area guiding network taxi booking system, the idle networks around the taxi taking hotspot area are guided to book taxi to the taxi taking hotspot area in advance in a mode of adjusting the price dynamic adjustment coefficient aiming at the pre-generated taxi taking hotspot area in a mode of being higher than the price of the common area, the average taxi taking duration of passengers is reduced, the benefit of a driver is guaranteed, and meanwhile the passengers are not required to bear excessive extra cost.
For specific limitations of the taxi taking hotspot area guidance network taxi appointment system, reference may be made to the above limitations on the taxi taking hotspot area guidance network taxi appointment method, and details are not described herein again. All or part of each module in the taxi taking hotspot area guiding network taxi booking system can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing taxi taking hot spot area guidance network taxi appointment data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize a taxi taking hotspot area guidance network taxi appointment method.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
calculating and acquiring a pre-generated taxi-taking hot spot area by combining historical data with current environmental influence factors;
determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking number of the taxi taking hot spot area and the required network car booking number;
and pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area.
In one embodiment, the processor when executing the computer program further performs the steps of:
the step of calculating and acquiring the pre-generated taxi-taking hot spot area by combining historical data with the current environmental influence factors comprises the following steps: and when the number of taxi taking people at the same time in the target area is more than a certain threshold value and the average taxi taking time length is more than a time length threshold value, judging that the target area is a taxi taking hot spot area.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the step of determining the price dynamic dispatching coefficient according to the difference value between the real-time idle network taxi booking quantity of the taxi taking hot spot area and the required network taxi booking quantity comprises the following steps:
acquiring the required network car booking quantity corresponding to the taxi taking hot spot area in historical data;
acquiring the real-time idle network car booking quantity in the taxi taking hotspot area;
acquiring the difference value between the number of required network car reservations and the number of real-time idle network car reservations in the taxi taking hotspot area;
and when the difference is larger than a first threshold value, determining the price dynamic adjustment coefficient according to an algorithm model by combining the historical invoice data of the taxi taking hot spot area.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the step of determining the price dynamic dispatching coefficient by combining the historical invoice sending data of the taxi-taking hot spot area according to an algorithm model comprises the following steps:
dividing the existing time period of the taxi-taking hot spot area into a plurality of continuous price adjusting time periods;
the price dynamic adjustment coefficient set in each price adjustment time period is unchanged;
before each adjusting time period, the price dynamic adjusting coefficient is recalculated.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
after the step of obtaining the difference value between the required network taxi booking number of the taxi taking hot spot area and the real-time idle network taxi booking number, the method further comprises the following steps:
calculating according to the mileage unit price, the distance length and the time length of taxi taking to obtain an original pre-estimation value;
and when the difference is less than or equal to the first threshold, keeping the original pre-valuation unchanged.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
in the step of determining the price transfer coefficient, the method comprises the following steps:
when the difference value is larger than a first threshold value, setting values of the price dynamic dispatching coefficient to include a first multiple, a second multiple, a third multiple, a fourth multiple and a fifth multiple;
when the difference value is larger than a first threshold value and smaller than or equal to a second threshold value, the value of the price dynamic dispatching coefficient is a first multiple;
when the difference value is larger than a second threshold value and smaller than or equal to a third threshold value, the price dynamic dispatching coefficient takes a second multiple;
when the difference value is larger than a third threshold value and smaller than or equal to a fourth threshold value, the price dynamic dispatching coefficient value is a third multiple;
when the difference value is larger than a fourth threshold value and smaller than or equal to a fifth threshold value, the value of the price dynamic adjusting coefficient is a fourth multiple;
and when the difference value is larger than a fifth threshold value, the price dynamic adjustment coefficient takes the value of a fifth multiple.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the method further comprises the following steps:
when the idle network appointment vehicle receives the order information, the dynamic transfer fee information added corresponding to the price dynamic transfer coefficient is sent to the idle network appointment vehicle; wherein the dynamic tuning cost = original pre-valuation (price dynamic tuning coefficient-1); when the dynamic transfer fee of the target order exceeds the upper limit value, the dynamic transfer fee is used for taking the upper limit value;
when the idle network taxi appointment receives orders to execute target orders, sending actually generated price dynamic adjustment coefficient information to passengers; when the dynamic dispatching fee of the target order exceeds the upper limit value, calculating an actually generated price dynamic dispatching coefficient according to the dynamic dispatching fee, wherein the actually generated price dynamic dispatching coefficient = the upper limit value/the original pre-evaluation +1.
The specific limitations regarding the steps implemented when the processor executes the computer program may be referred to the above limitations on the method for guiding network appointment in taxi-taking hot spot areas, and will not be described herein again.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
calculating and acquiring a pre-generated taxi-taking hot spot area by combining historical data with current environmental influence factors;
determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking number of the taxi taking hot spot area and the required network car booking number;
and pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi-taking hot spot area to the idle network taxi appointment around the taxi-taking hot spot area.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the step of calculating and acquiring the pre-generated taxi-taking hot spot area by combining historical data with the current environmental influence factors comprises the following steps: and when the number of taxi taking people at the same time in the target area is more than a certain threshold value and the average taxi taking time length is more than a time length threshold value, judging that the target area is a taxi taking hot spot area.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the step of determining the price dynamic dispatching coefficient according to the difference value between the real-time idle network car booking number of the taxi taking hot spot area and the required network car booking number comprises the following steps:
acquiring the required network car booking quantity corresponding to the taxi taking hot spot area in historical data;
acquiring the real-time idle network car booking quantity in the taxi taking hotspot area;
acquiring the difference value between the number of required network car reservations and the number of real-time idle network car reservations in the taxi taking hotspot area;
and when the difference is larger than a first threshold value, determining the price dynamic adjustment coefficient according to an algorithm model by combining the historical invoice data of the taxi taking hot spot area.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the step of determining the price dynamic dispatching coefficient by combining the historical invoice data of the taxi taking hotspot area according to an algorithm model comprises the following steps:
dividing the existing time period of the taxi-taking hot spot area into a plurality of continuous price adjusting time periods;
the price dynamic adjustment coefficient set in each price adjustment time period is unchanged;
and recalculating the price dynamic adjustment coefficient before each price adjustment time period.
In one embodiment, the computer program when executed by the processor further performs the steps of:
after the step of obtaining the difference value between the required network taxi booking number of the taxi taking hot spot area and the real-time idle network taxi booking number, the method further comprises the following steps:
calculating according to the mileage unit price, the distance length and the time length of taxi taking to obtain an original pre-estimation value;
and when the difference is less than or equal to the first threshold, keeping the original pre-valuation unchanged.
In one embodiment, the computer program when executed by the processor further performs the steps of:
in the step of determining the price transfer coefficient, the method comprises the following steps:
when the difference value is larger than a first threshold value, setting values of the price dynamic dispatching coefficient to include a first multiple, a second multiple, a third multiple, a fourth multiple and a fifth multiple;
when the difference value is larger than a first threshold value and smaller than or equal to a second threshold value, the value of the price dynamic dispatching coefficient is a first multiple;
when the difference value is larger than a second threshold value and smaller than or equal to a third threshold value, the price dynamic dispatching coefficient takes a second multiple;
when the difference value is larger than a third threshold value and smaller than or equal to a fourth threshold value, the price dynamic dispatching coefficient value is a third multiple;
when the difference value is larger than a fourth threshold value and smaller than or equal to a fifth threshold value, the price dynamic dispatching coefficient value is a fourth multiple;
and when the difference value is larger than a fifth threshold value, the price dynamic adjustment coefficient takes the value of a fifth multiple.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the method further comprises the following steps:
when the idle network appointment vehicle receives the order information, the dynamic transfer fee information added corresponding to the price dynamic transfer coefficient is sent to the idle network appointment vehicle; wherein the dynamic tuning cost = original pre-valuation (price dynamic tuning coefficient-1); when the dynamic transfer fee of the target order exceeds the upper limit value, the dynamic transfer fee is used for taking the upper limit value;
when the idle network taxi appointment receives orders to execute target orders, sending actually generated price dynamic adjustment coefficient information to passengers; when the dynamic dispatching fee of the target order exceeds the upper limit value, calculating an actually generated price dynamic dispatching coefficient according to the dynamic dispatching fee, wherein the actually generated price dynamic dispatching coefficient = the upper limit value/the original pre-evaluation +1.
For specific limitations of the steps implemented by the computer program when executed by the processor, reference may be made to the above limitations of the method for guiding network appointment in taxi taking hot spot areas, which are not described in detail herein.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A taxi taking hotspot area guidance network taxi booking method is characterized by comprising the following steps:
calculating and acquiring a pre-generated taxi-taking hot spot area by combining historical data with current environmental influence factors;
determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking number of the taxi taking hot spot area and the required network car booking number;
and pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area.
2. The taxi-taking hotspot area guidance network taxi-taking method according to claim 1, wherein the step of calculating and acquiring the pre-generated taxi-taking hotspot area by combining historical data with current environmental influence factors comprises the following steps:
acquiring the number of taxi taking persons at the same time and the taxi taking time of each time in a target area;
counting the average taxi taking time;
and when the number of taxi taking people at the same time in the target area is more than a certain threshold value and the average taxi taking time is more than a time threshold value, judging that the target area is a taxi taking hot spot area.
3. The taxi-taking hotspot area guidance network taxi appointment method according to claim 1, wherein the step of determining the price dynamic adjustment coefficient according to the difference between the real-time idle network taxi appointment quantity of the taxi-taking hotspot area and the required network taxi appointment quantity comprises the following steps:
acquiring the required network taxi booking quantity corresponding to the taxi-taking hot spot area in historical data;
acquiring the real-time idle network taxi booking number in the taxi-taking hotspot area;
acquiring the difference value between the number of required network car reservations and the number of real-time idle network car reservations in the taxi taking hotspot area;
and when the difference is larger than a first threshold value, determining the price dynamic adjustment coefficient according to an algorithm model by combining the historical invoice sending data of the taxi-taking hot spot area.
4. The taxi-taking hotspot area guide network taxi appointment method according to claim 3, wherein the step of determining the price momentum coefficient according to an algorithm model by combining historical taxi-taking data of the taxi-taking hotspot area comprises the steps of:
dividing the existing time period of the taxi-taking hot spot area into a plurality of continuous price adjusting time periods;
the price dynamic adjustment coefficient set in each price adjustment time period is unchanged;
and recalculating the price dynamic adjustment coefficient before each price adjustment time period.
5. The taxi-taking hotspot area network-guided taxi appointment method according to claim 3, further comprising, after the step of obtaining the difference between the required taxi appointment number and the real-time idle taxi appointment number in the taxi-taking hotspot area:
calculating according to the mileage unit price, the distance length and the time length of taxi taking to obtain an original pre-estimation value;
and when the difference is less than or equal to the first threshold, keeping the original pre-valuation unchanged.
6. The taxi-taking hotspot area guidance network taxi appointment method according to claim 3, wherein the step of determining the price transfer coefficient comprises the following steps:
when the difference value is larger than a first threshold value, setting values of the price dynamic dispatching coefficient to include a first multiple, a second multiple, a third multiple, a fourth multiple and a fifth multiple;
when the difference value is larger than a first threshold value and smaller than or equal to a second threshold value, the value of the price dynamic dispatching coefficient is a first multiple;
when the difference value is larger than a second threshold value and smaller than or equal to a third threshold value, the price dynamic dispatching coefficient takes a second multiple;
when the difference value is larger than a third threshold value and smaller than or equal to a fourth threshold value, the price dynamic dispatching coefficient value is a third multiple;
when the difference value is larger than a fourth threshold value and smaller than or equal to a fifth threshold value, the price dynamic dispatching coefficient value is a fourth multiple;
and when the difference value is larger than a fifth threshold value, the price dynamic adjustment coefficient takes the value of a fifth multiple.
7. The taxi-taking hotspot area guide network taxi appointment method according to claim 1, further comprising:
when the idle network appointment vehicle receives the order information, the dynamic transfer fee information added corresponding to the price dynamic transfer coefficient is sent to the idle network appointment vehicle; wherein the dynamic tuning cost = original pre-valuation (price dynamic tuning coefficient-1); when the dynamic transfer fee of the target order exceeds the upper limit value, the dynamic transfer fee is used for taking the upper limit value;
when the idle network taxi appointment receives orders to execute target orders, sending actually generated price dynamic adjustment coefficient information to passengers; when the dynamic transfer fee of the target order exceeds the upper limit value, calculating an actually generated price dynamic transfer coefficient according to the dynamic transfer fee, wherein the actually generated price dynamic transfer coefficient = the upper limit value/the original pre-evaluation +1.
8. A taxi taking hotspot area guidance network taxi reservation system is characterized by comprising:
the taxi taking hot spot area calculating module is used for calculating and acquiring a pre-generated taxi taking hot spot area by combining historical data with current environmental influence factors;
the price dynamic adjustment coefficient determining module is used for determining a price dynamic adjustment coefficient according to the difference value between the real-time idle network car booking quantity of the taxi taking hot spot area and the required network car booking quantity;
and the guiding message pushing module is used for pushing the existing time period, the position coordinates and the price dynamic adjustment coefficient of the taxi taking hot spot area to the idle network taxi appointment around the taxi taking hot spot area.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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