Online car-hailing dynamic price adjustment and order sending method and system, and computer equipment

Abstract

The invention provides an online car-hailing dynamic price adjustment and order sending method and system, and computer equipment. The method comprises the steps of obtaining an order receiving mode and driver portrait data set by a driver through a driver end; according to the driver portrait data, the total number of drivers capable of receiving orders in various order receiving modes in the order sending range of the target order is selected; determining an estimated amount type of the target order according to a preset estimated amount type configuration; based on preset price adjustment rules matched with different order receiving time period types, according to the estimated amount type and the total number of drivers capable of receiving orders, determining a final price adjustment multiplying power and a target order sending type of the target order; and sending the target order based on the final price adjustment multiplying power and the target order sending type. According to the invention, the dynamic price adjustment is carried out according to the order receiving mode set by the driver, the problems existing in the peak and the flat period in the prior art are effectively solved by optimizing the order distribution in the peak and setting the price reduction order sending strategy, and the platform operation efficiency, the driver income and the user satisfaction are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of online car-hailing, and particularly to an online car-hailing dynamic price adjustment and order dispatching method, system, and computer device. Background Art

[0002] With the development of mobile Internet technology, all aspects of people's lives have been improved, and online car-hailing has been continuously accepted and used by users. However, during peak taxi-hailing periods: due to a large number of orders and few drivers, the order distribution may be uneven, and some orders may not be processed in a timely manner; high-quality drivers (such as those with good service, high ratings, and fast speeds) may face a large number of orders during peak periods, but lack a selection mechanism, which may cause them to be unable to select the most suitable orders for themselves, thus affecting service quality and income; there is a lack of an effective incentive mechanism, which cannot fully mobilize the enthusiasm of drivers during peak periods and improve the overall transport capacity. During off-peak taxi-hailing periods: there are many drivers and few orders, resulting in long waiting times for drivers and waste of resources; there is a lack of an effective price reduction strategy, which may not be able to attract more users to place orders, resulting in a continuous slump in the order volume; drivers may lose patience during the waiting process and choose to leave the platform, resulting in a loss of platform drivers. In summary, there is a technical problem of imbalance in the matching degree between peak / off-peak transport capacity and orders, which affects the platform operation efficiency, driver income, and user satisfaction. Summary of the Invention

[0003] Therefore, the present invention provides an online car-hailing dynamic price adjustment and order dispatching method, system, and computer device, aiming to solve the technical problem of imbalance in the matching degree between peak / off-peak transport capacity and orders in the prior art.

[0004] To achieve the above objectives, the present invention adopts the following technical solutions:

[0005] According to a first aspect of the present invention, the present invention provides an online car-hailing dynamic price adjustment and order dispatching method, and the method includes:

[0006] Obtain the order-taking mode and driver portrait data set by the driver through the driver terminal; the order-taking mode includes a higher unit price order-taking mode and a multi-stage price reduction order-taking mode;

[0007] According to the driver portrait data, circle the total number of available drivers in various order-taking modes within the first order dispatching range of the target order;

[0008] According to the preset estimated amount type configuration, determine the estimated amount type of the target order;

[0009] Based on the preset price adjustment rules matching different order-taking time periods, according to the estimated amount type and the total number of available drivers, determine the final price adjustment multiple and the target order dispatching type of the target order;

[0010] Dispatch the target order based on the final price adjustment multiple and the target order type;

[0011] Among them, the order receiving time period types include peak periods and off-peak periods.

[0012] Further, before obtaining the order receiving mode and driver portrait data set by the driver through the driver terminal, the method further includes:

[0013] Configure operation-related indicators, including order receiving time period types, estimated amount types, and / or order receiving mode response times;

[0014] Among them, the estimated amount types include small orders, large orders, and general orders;

[0015] The order receiving mode response time is the order receiving response time corresponding to each order receiving mode, including the high-price order receiving response time and the multi-stage price reduction order receiving response time;

[0016] The multi-stage price reduction order receiving mode includes the first-stage price reduction order receiving mode, the second-stage price reduction order receiving mode, and the third-stage price reduction order receiving mode; the multi-stage price reduction order receiving response time includes the first-stage price reduction order receiving response time, the second-stage price reduction order receiving response time, and the third-stage price reduction order receiving response time.

[0017] Further, the driver portrait data includes at least one of the last order completion time, the last departure time, the last return time, the last peak period start time, the last time of setting the peak period high-price order receiving mode, the last time of setting the peak period multi-stage price reduction order receiving mode, the time of setting the high-price order receiving mode to be enabled during the peak period, the time of setting the multi-stage price reduction order receiving mode to be enabled during the peak period, the last off-peak period start time, the last time of setting the off-peak period high-price order receiving mode, the last time of setting the off-peak period multi-stage price reduction order receiving mode, the time of setting the high-price order receiving mode to be enabled during the off-peak period, the time of setting the multi-stage price reduction order receiving mode to be enabled during the off-peak period, and the number of recent small orders.

[0018] Further, within the first dispatch range of the target order selected according to the driver portrait data, the total number of available drivers for each order receiving mode includes:

[0019] Obtain the driver portrait data of all dispatched drivers within the first dispatch range of the target order;

[0020] According to the driver portrait data, determine whether the order receiving mode of each dispatched driver is valid, including:

[0021] In the peak period, the mathematical expression for determining that the high-price order receiving mode is valid is:

[0022] Tcurrent -Max(T last_out , T last_finish , T last_peak_start , T set_higher_price )≤T high_price_order ;

[0023] Among them, T current is the current time; T last_out The last time of departure; T last_finish The last order completion time; T last_peak_start is the start time of the last peak period; T set_higher_price Set the time to open the higher-price order mode for peak periods; T high_price_order Response time for high-priced orders;

[0024] and / or,

[0025] During peak periods, the mathematical expression for determining whether the multi-stage price reduction order acceptance mode is effective is:

[0026] T current -Max(T last_out , T last_finish , T last_flat_start , T set_more_orders_peak )>T discount_order ;

[0027] Among them, T current is the current time; T last_out The last time of departure; T last_finish The last order completion time; T last_peak_start is the start time of the last peak period; T set_more_orders_peak Set the time to start the multi-level price reduction order mode during peak period; T discount_order Response time for accepting orders with multiple price reductions;

[0028] and / or,

[0029] During the off-peak period, the mathematical expression for determining whether the higher-price order-taking mode is effective is:

[0030] T current -Max(T last_out , T last_finish , T last_flat_start , T set_higher_price_flat )≤T high_price_order_flat ;

[0031] Among them, T current is the current time; T last_out The last time of departure; T last_finish The last order completion time; T last_flat_start is the start time of the last off-peak period; Tset_higher_price_flat Set the time for enabling the higher unit price order receiving mode during the off-peak period; T high_price_order_flat The response time for receiving orders at a high price during the off-peak period;

[0032] And / or,

[0033] During the off-peak period, the mathematical expression for determining the effectiveness of the multi-level price reduction order receiving mode is:

[0034] T current -Max(T last_out ,T last_finish ,T last_flat_start ,T set_more_orders_flat )>T discount_order_flat ;

[0035] Wherein, T current Is the current time; T last_out Is the last departure time; T last_finish Is the last order completion time; T last_flat_start Is the last off-peak period start time; T set_flatr_price Is the time for enabling the multi-level price reduction order receiving mode during the off-peak period; T set_more_orders_flat Is the response time for multi-level price reduction order receiving during the off-peak period;

[0036] Statistically count the total number of available drivers who can receive orders effectively under each of the order receiving modes.

[0037] Furthermore, the determining the estimated amount type of the target order according to the preset estimated amount type configuration includes:

[0038] Obtain the order information of the target order, and determine the small order amount and the large order amount corresponding to the target order according to the order information; wherein, the order information includes the order estimated amount, the city, the channel, and / or the order receiving time period type;

[0039] Determine the estimated amount type of the target order according to the small order amount, the large order amount, and the order estimated amount, including:

[0040] If the order estimated amount ≤ the small order amount, then the target order is a small order; if the order estimated amount > the large order amount, then the target order is a large order; if the small order amount < the order estimated amount < the large order amount, determine whether the order coefficient of the target order meets the high-price order multiple; if the order coefficient ≥ the high-price order multiple, then the target order is a large order; if the order coefficient < the high-price order multiple, then the target order is a general order; the calculation formula of the high-price order multiple is:

[0041]

[0042] Wherein, x is the estimated order amount, and y is the high-price order multiple.

[0043] Further, based on the preset price adjustment rules matching different order-receiving time period types, according to the estimated amount type and the total number of available drivers, determining the final price adjustment multiple and the target order assignment type of the target order includes:

[0044] In the peak period, determine whether the number of available drivers in the order-receiving mode with a higher unit price is greater than 0. When the number of available drivers in the order-receiving mode with a higher unit price is greater than 0, determine whether the estimated amount type is a large order; if the estimated amount type is a large order, determine that the final price adjustment multiple of the target order is 1 and perform normal order assignment; if the estimated amount type is not a large order, determine whether the total number of available drivers is equal to the number of available drivers in the order-receiving mode with a higher unit price.

[0045] If the total number of available drivers is equal to the number of available drivers in the order-receiving mode with a higher unit price, determine whether the estimated amount type is not a small order; if the estimated amount type is not a small order, determine that the final price adjustment multiple of the target order is the high-price order multiple and perform normal order assignment; if the estimated amount type is a small order, determine that the final price adjustment multiple of the target order is 1 and perform small order assignment.

[0046] If the total number of available drivers is not equal to the number of available drivers in the order-receiving mode with a higher unit price, calculate the first proportion of the actual number of available drivers corresponding to the three-step price reduction order-receiving mode in the total number of available drivers in the multi-step price reduction order-receiving mode, and determine whether the first proportion exceeds the first preset threshold; if the first proportion exceeds the first preset threshold, determine that the final multiple of the target order is the first price adjustment multiple and perform price reduction order assignment; if the first proportion does not exceed the first preset threshold, calculate the second proportion of the actual number of available drivers corresponding to the three-step price reduction order-receiving mode and the two-step price reduction order-receiving mode in the total number of available drivers in the multi-step price reduction order-receiving mode, and determine whether the second proportion exceeds the second preset threshold; if the second proportion exceeds the second preset threshold, determine that the final multiple of the target order is the second price adjustment multiple and perform price reduction order assignment.

[0047] When the number of available drivers for the higher unit price order acceptance mode is 0, or when the second ratio does not exceed the second preset threshold, determine whether the estimated amount type is not a small order; if the estimated amount type is not a small order, determine whether the estimated amount type is a large order; if the estimated amount type is a large order, the final price adjustment multiple of the target order is 1, and normal order dispatching is performed; if the estimated amount type is not a large order, the final price adjustment multiple of the target order is 1, and non-high price order dispatching is performed; if the estimated amount type is a small order, the final price adjustment multiple of the target order is 1, and small order dispatching is performed.

[0048] Among them, the first price adjustment multiple is lower than the second price adjustment multiple.

[0049] Furthermore, based on the preset price adjustment rules matching different order acceptance time periods, according to the estimated amount type and the total number of available drivers, determine the final price adjustment multiple and the target order dispatching type of the target order, including:

[0050] During the off-peak period, determine whether the total number of available drivers is equal to the number of available drivers for the higher unit price order acceptance mode.

[0051] If the total number of available drivers is equal to the number of available drivers for the higher unit price order acceptance mode, determine whether the estimated amount type is not a small order; if the estimated amount type is not a small order, determine the final price adjustment multiple of the target order as the high price order multiple, and perform normal order dispatching; if the estimated amount type is a small order, determine the final price adjustment multiple of the target order as 1, and perform small order dispatching.

[0052] If the total number of drivers available for accepting orders is not equal to the number of drivers available for accepting orders in the order-accepting mode with a higher unit price, calculate the first proportion of the actual number of available orders corresponding to the three-stage price reduction order-accepting mode to the total number of available drivers available for accepting orders in the multi-stage price reduction order-accepting mode, and determine whether the first proportion exceeds the first preset threshold; if the first proportion exceeds the first preset threshold, determine the final multiplier of the target order to be the first price adjustment multiplier, and perform price reduction dispatching; if the first proportion does not exceed the first preset threshold, calculate the actual number of available orders corresponding to the three-stage price reduction order-accepting mode and the second-stage price reduction order-accepting mode to the total number of available orders in the multi-stage price reduction order-accepting mode. The second proportion of the total number of drivers is used to determine whether the second proportion exceeds a second preset threshold; if the second proportion exceeds the second preset threshold, the final price adjustment ratio of the target order is determined to be the second price adjustment ratio, and the order is dispatched at a reduced price; if the second proportion does not exceed the second preset threshold, it is determined whether the estimated amount type is a non-small order; if the estimated amount type is not a small order, the final price adjustment ratio of the target order is determined to be a high-price order ratio, and the order is dispatched normally; if the estimated amount type is a small order, the final price adjustment ratio of the target order is determined to be 1, and the order is dispatched as a small order;

[0053] Among them, the first price adjustment ratio is lower than the second price adjustment ratio.

[0054] Furthermore, the order type includes at least one of a normal order, a non-high-price order, a price-reduction order, and a small order;

[0055] The normal dispatching is to dispatch all drivers who can accept orders in the order acceptance mode within the first dispatching range of the target order as candidates for selection;

[0056] The non-high-price dispatching is to dispatch the order to drivers who can accept the order after filtering out the order modes with higher unit prices within the first dispatching range of the target order as the candidate drivers;

[0057] The price reduction dispatching is to dispatch the drivers who are available to accept orders in the multi-stage price reduction order acceptance mode within the second dispatching range of the target order as the drivers to be selected;

[0058] The small order dispatching is to dispatch the drivers who are available to accept orders in the multi-level price reduction order acceptance mode within the first dispatching range of the target order as the drivers to be selected;

[0059] Among them, the second dispatch range is smaller than the first dispatch range.

[0060] According to a second aspect of the present invention, the present invention provides a dynamic price adjustment and dispatching system for online ride-hailing services, the system comprising:

[0061] A data acquisition module for acquiring the order acceptance mode and driver portrait data set by the driver through the driver terminal; the order acceptance mode includes a higher unit price order acceptance mode and a multi-level price reduction order acceptance mode;

[0062] A driver selection module for selecting the total number of available drivers for various order acceptance modes within the first dispatching range of the target order according to the driver portrait data;

[0063] A type determination module for determining the estimated amount type of the target order according to the preset estimated amount type configuration;

[0064] A rate output module for determining the final price adjustment rate and target dispatching type of the target order based on the preset price adjustment rules matching different order acceptance time periods, according to the estimated amount type and the total number of available drivers;

[0065] An order assignment module for dispatching the target order based on the final price adjustment rate and the target dispatching type;

[0066] Wherein, the order acceptance time periods include peak periods and off-peak periods.

[0067] According to a third aspect of the present invention, the present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, it implements the online car-hailing dynamic price adjustment and dispatching method according to any one of the first aspects of the present invention.

[0068] The present invention adopts the above technical solutions and at least has the following beneficial effects:

[0069] Through the solution of the present invention, the order acceptance mode and driver portrait data set by the driver through the driver terminal are acquired; the order acceptance mode includes a higher unit price order acceptance mode and a multi-level price reduction order acceptance mode; according to the driver portrait data, the total number of available drivers for various order acceptance modes within the first dispatching range of the target order is selected; according to the preset estimated amount type configuration, the estimated amount type of the target order is determined; based on the preset price adjustment rules matching different order acceptance time periods, the final price adjustment rate and target dispatching type of the target order are determined according to the estimated amount type and the total number of available drivers; the target order is dispatched based on the final price adjustment rate and the target dispatching type; wherein, the order acceptance time periods include peak periods and off-peak periods. Thus, a dynamic price adjustment strategy is carried out according to the order acceptance mode set by the driver, and by optimizing the order allocation during peak periods and setting a price reduction dispatching strategy, the problems existing in the prior art during peak periods and off-peak periods are effectively solved, and the platform operation efficiency, driver income and user satisfaction are improved.

[0070] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and do not limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0072] Figure 1 FIG. shows a schematic flowchart of a method for dynamic price adjustment and order dispatching of online car-hailing provided by an embodiment of the present invention;

[0073] Figure 2 FIG. shows a schematic flowchart of a preset price adjustment rule during peak hours provided by an embodiment of the present invention;

[0074] Figure 3 FIG. shows a schematic flowchart of a preset price adjustment rule during off-peak hours provided by an embodiment of the present invention;

[0075] Figure 4 FIG. shows a schematic structural diagram of an online car-hailing dynamic price adjustment and order dispatching system provided by an embodiment of the present invention;

[0076] Figure 5 FIG. shows a schematic structural diagram of an online car-hailing dynamic price adjustment and order dispatching system provided by an embodiment of the present invention;

[0077] Figure 6 FIG. shows a schematic physical structure diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0078] The following will describe the exemplary embodiments of the present disclosure in more detail with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0079] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the said element.

[0080] An embodiment of the present invention provides a method for dynamic price adjustment and order assignment of online car-hailing, as Figure 1 shown, which may at least include the following steps S101 to S105:

[0081] Step S101, obtaining the order receiving mode and driver portrait data set by the driver through the driver terminal; the order receiving mode includes the mode of receiving orders with a higher unit price and the mode of multi-level price reduction for receiving orders.

[0082] Before obtaining the order receiving mode and driver portrait data set by the driver through the driver terminal in the embodiment of the present invention, relevant indicators for online car-hailing operation can be configured in the operation background first, which may include the type of order receiving time period, the type of estimated amount, and the response time of the order receiving mode.

[0083] Among them, the type of order receiving time period may include the peak period and the off-peak period. In practical applications, the whole day can be divided into 24 hours, and the peak / off-peak period is divided for different cities. There may be multiple peak period time periods in the same city. It can be understood that generally, the type of order receiving time period of the target order is judged as the peak period or the off-peak period according to the time period hit by the time when the user issues the target order; if the target order is a reserved order, the time period hit by the reserved departure time is used for judgment.

[0084] The type of estimated amount may include small orders, large orders and general orders. In practical applications, for different cities, channels and types of order receiving time periods, two sets of order amounts, namely small order amounts and large order amounts, can be set, and the type of estimated amount of the target order is determined by using these two sets of order amounts.

[0085] The response time of the order receiving mode is the order receiving response time corresponding to each order receiving mode. In the embodiments of the present invention, the order receiving modes that a driver can set through the driver-side APP include the higher unit price order receiving mode and the multi-level price reduction order receiving mode, where the multi-level price reduction order receiving mode includes the first-level price reduction order receiving mode, the second-level price reduction order receiving mode, and the third-level price reduction order receiving mode. Therefore, the order receiving mode response time can include the high-price order receiving response time and the multi-level price reduction order receiving response time; the multi-level price reduction order receiving response time includes the first-level price reduction order receiving response time, the second-level price reduction order receiving response time, and the third-level price reduction order receiving response time.

[0086] After configuring the relevant indicators for online car-hailing operations, the operation background can obtain the order receiving mode set by the driver through the driver side and the driver portrait data. The driver portrait data can include the last order completion time, the last departure time, the last arrival time, the last peak start time, the last time of setting the higher unit price order receiving mode during peak hours, the last time of setting the multi-level price reduction order receiving mode during peak hours, the time of setting the higher unit price order receiving mode to be enabled during peak hours, the time of setting the multi-level price reduction order receiving mode to be enabled during peak hours, the last off-peak start time, the last time of setting the higher unit price order receiving mode during off-peak hours, the last time of setting the multi-level price reduction order receiving mode during off-peak hours, the time of setting the higher unit price order receiving mode to be enabled during off-peak hours, the time of setting the multi-level price reduction order receiving mode to be enabled during off-peak hours, and the number of recent small orders, etc.

[0087] Step S102: According to the driver portrait data, circle the total number of available drivers for each order receiving mode within the first dispatching range of the target order.

[0088] Specifically, the driver portrait data of all dispatched drivers within the first dispatching range of the target order can be obtained; according to the driver portrait data, it is judged whether the order receiving mode of each dispatched driver is valid; the total number of available drivers that are valid under each order receiving mode is counted. In the embodiments of the present invention, for different order receiving modes set for different order receiving time periods, the rules for judging whether they are valid are also different, which are described separately below:

[0089] During peak hours, the mathematical expression for judging that the higher unit price order receiving mode is valid is:

[0090] T current -Max(T last_out ,T last_finish ,T last_peak_start ,T set_higher_price )≤T high_price_order ;

[0091] The mathematical expression for judging that the higher unit price order receiving mode is invalid is:

[0092] T current -Max(Tlast_out , T last_finish , T last_peak_start , T set_higher_price ) > T high_price_order ;

[0093] Among them, T current is the current time; T last_out is the time of the last trip; T last_finish is the time of the last order completion; T last_peak_start is the start time of the last peak period; T set_higher_price is the time when the higher unit price order receiving mode is enabled during the peak period; T high_price_order is the response time for receiving high - price orders.

[0094] That is to say, the higher unit price order receiving mode during the peak period is restricted by the time for receiving higher unit price orders. After the driver sets the higher unit price order receiving mode, according to the maximum time Tmax1 among the time of the last trip / the time of the last order completion / the start time of the last peak period / the time when the higher unit price order receiving mode is enabled during the peak period, it is judged whether the higher unit price order receiving mode set by the driver during the peak period is effective by judging the difference between the current time and Tmax1.

[0095] During the peak period, the mathematical expression for judging the effectiveness of the multi - level price reduction order receiving mode is:

[0096] T current - Max(T last_out , T last_finish , T last_flat_start , T set_more_orders_peak ) > T discount_order ;

[0097] The mathematical expression for judging the ineffectiveness of the multi - level price reduction order receiving mode is:

[0098] T current - Max(T last_out , T last_finish , T last_flat_start , T set_more_orders_peak ) ≤ T discount_order ;

[0099] Among them, T current is the current time; T last_out is the time of the last trip; T last_finish is the time of the last order completion; T last_peak_start is the start time of the last peak period; T set_more_orders_peak is the time when the multi - level price reduction order receiving mode is enabled during the peak period; T discount_order is the response time for the multi - level price reduction order receiving.

[0100] That is to say, the multi-level price cut order receiving mode during peak hours is restricted by the corresponding response time of the multi-level price cut order receiving. After the driver sets the multi-level price cut order receiving mode, according to the maximum time Tmax2 among the last departure time / the last order completion time / the last peak hour start time / the time when the multi-level price cut order receiving mode is set to be enabled during peak hours, the difference between the current time and Tmax2 is used to determine whether the multi-level price cut order receiving mode set by the driver during peak hours is effective.

[0101] During off-peak hours, the mathematical expression for determining the effectiveness of the higher unit price order receiving mode is:

[0102] T current -Max(T last_out ,T last_finish ,T last_flat_start ,T set_higher_price_flat )≤T high_price_order_flat ;

[0103] The mathematical expression for determining the ineffectiveness of the higher unit price order receiving mode is:

[0104] T current -Max(T last_out ,T last_finish ,T last_flat_start ,T set_higher_price_flat )>T high_price_order_flat ;

[0105] Among them, T current is the current time; T last_out is the last departure time; T last_finish is the last order completion time; T last_flat_start is the last off-peak hour start time; T set_higher_price_flat is the time when the higher unit price order receiving mode is set to be enabled during off-peak hours; T high_price_order_flat is the response time for receiving orders at a higher price during off-peak hours.

[0106] That is to say, the higher unit price order receiving mode during off-peak hours is restricted by the order receiving time at a higher unit price. After the driver sets the higher unit price order receiving mode, according to the maximum time Tmax3 among the last departure time / the last order completion time / the last off-peak hour start time / the time when the higher unit price order receiving mode is set to be enabled during off-peak hours, the difference between the current time and Tmax3 is used to determine whether the higher unit price order receiving mode set by the driver during off-peak hours is effective.

[0107] During off-peak hours, the mathematical expression for determining the effectiveness of the multi-level price cut order receiving mode is:

[0108] T current -Max(T last_out ,T last_finish ,T last_flat_start ,Tset_more_orders_flat ) > T discount_order_flat ;

[0109] The mathematical expression for determining the failure of the multi - level price - cut order - receiving mode is:

[0110] T current - Max(T last_out , T last_finish , T last_flat_start , T set_more_orders_flat ) ≤ T discount_order_flat ;

[0111] Wherein, T current is the current time; T last_out is the time of the last vehicle departure; T last_finish is the time of the last order completion; T last_flat_start is the start time of the last off - peak period; T set_flatr_price is the time when the multi - level price - cut order - receiving mode is set to be enabled during the off - peak period; T set_more_orders_flat is the response time of the multi - level price - cut order - receiving during the off - peak period.

[0112] That is to say, the multi - level price - cut order - receiving mode during the off - peak period is restricted by the corresponding response time of the multi - level price - cut order - receiving. After the driver sets the multi - level price - cut order - receiving mode, according to the maximum time Tmax4 among the time of the last vehicle departure / the time of the last order completion / the start time of the last off - peak period / the time when the multi - level price - cut order - receiving mode is set to be enabled during the off - peak period, judge the difference between the current time and Tmax4 to determine whether the multi - level price - cut order - receiving mode set by the driver during the off - peak period is effective.

[0113] It should be noted that in practical applications, the response time of the multi - level price - cut order - receiving is replaced with the response time of the price - cut order - receiving for the specific level according to the multi - level price - cut order - receiving mode set by the driver. For example, if the driver sets it to the first - level price - cut order - receiving mode, the corresponding response time of the price - cut order - receiving is the response time of the first - level price - cut order - receiving, and so on.

[0114] Step S103, determine the estimated amount type of the target order according to the preset estimated amount type configuration.

[0115] First, the order information of the target order can be obtained, and the small - order amount and large - order amount corresponding to the target order are determined according to the order information. Among them, the order information includes the estimated order amount, city, channel, and / or order - receiving time period type;

[0116] Specifically, to judge the estimated amount type of the target order according to the small - order amount, large - order amount, and estimated order amount, the following rules can be used for judgment:

[0117] If the estimated order amount ≤ small order amount, then the target order is a small order; if the estimated order amount > large order amount, then the target order is a large order; if the small order amount < estimated order amount < large order amount, determine whether the order coefficient of the target order meets the high-price order multiple; if the order coefficient ≥ high-price order multiple, then the target order is a large order; if the order coefficient < high-price order multiple, then the target order is a general order; the calculation formula for the high-price order multiple is:

[0118]

[0119] where x is the estimated order amount and y is the high-price order multiple.

[0120] It should be noted that in actual applications, x can be set to the evidence of the estimated order amount, discarding the amount after the decimal point for easier multiple calculation.

[0121] Step S104: Based on the preset price adjustment rules matching different order receiving time period types, determine the final price adjustment multiple and the target dispatching type of the target order according to the estimated amount type and the total number of available drivers.

[0122] The preset price adjustment rules for peak hours and off-peak hours are described as follows:

[0123] Such as Figure 2As shown, under peak hours, it is determined whether the number of available drivers for the order-taking mode with a higher unit price is greater than 0. When the number of available drivers for the order-taking mode with a higher unit price is greater than 0, it is determined whether the estimated amount type of the target order is a large-order; if the estimated amount type is a large-order, the final price adjustment multiple of the target order is determined to be 1, and normal order assignment is performed; if the estimated amount type is not a large-order, it is determined whether the total number of available drivers is equal to the number of available drivers set for the order-taking mode with a higher unit price. If the total number of available drivers is equal to the number of available drivers set for the order-taking mode with a higher unit price, it is determined whether the estimated amount type is not a small-order; if the estimated amount type is not a small-order, the final price adjustment multiple of the target order is determined to be the high-order order multiple, and normal order assignment is performed; if the estimated amount type is a small-order, the final price adjustment multiple of the target order is determined to be 1, and small-order assignment is performed; if the total number of available drivers is not equal to the number of available drivers set for the order-taking mode with a higher unit price, calculate the first proportion of the actual number of available drivers corresponding to the three-step price reduction order-taking mode in the total number of available drivers for the multi-step price reduction order-taking mode, and determine whether the first proportion exceeds the first preset threshold; if the first proportion exceeds the first preset threshold, the final multiple of the target order is determined to be the first price adjustment multiple, and price reduction order assignment is performed; if the first proportion does not exceed the first preset threshold, calculate the second proportion of the actual number of available drivers corresponding to the three-step price reduction order-taking mode and the two-step price reduction order-taking mode in the total number of available drivers for the multi-step price reduction order-taking mode, and determine whether the second proportion exceeds the second preset threshold; if the second proportion exceeds the second preset threshold, the final multiple of the target order is determined to be the second price adjustment multiple, and price reduction order assignment is performed; when the number of available drivers for the order-taking mode with a higher unit price is 0, or, the second proportion does not exceed the second preset threshold, it is determined whether the estimated amount type is not a small-order; if the estimated amount type is not a small-order, it is determined whether the estimated amount type is a large-order; if the estimated amount type is a large-order, the final price adjustment multiple of the target order is 1, and normal order assignment is performed; if the estimated amount type is not a large-order, the final price adjustment multiple of the target order is 1, and non-high-price order assignment is performed; if the estimated amount type is a small-order, the final price adjustment multiple of the target order is 1, and small-order assignment is performed.

[0124] As Figure 3As shown, during the off-peak period, it is determined whether the total number of available drivers for receiving orders is equal to the number of available drivers for the order-receiving mode with a higher set price. If the total number of available drivers for receiving orders is equal to the number of available drivers for the order-receiving mode with a higher set price, it is determined whether the estimated amount type is not a small order; if the estimated amount type is not a small order, the final price adjustment multiple of the target order is determined to be the high-price order multiple, and normal order dispatching is performed; if the estimated amount type is a small order, the final price adjustment multiple of the target order is determined to be 1, and small order dispatching is performed; if the total number of available drivers for receiving orders is not equal to the number of available drivers for the order-receiving mode with a higher set price, calculate the first proportion of the actual number of available drivers corresponding to the three-stage price reduction order-receiving mode in the total number of available drivers for the multi-stage price reduction order-receiving mode, and determine whether the first proportion exceeds the first preset threshold; if the first proportion exceeds the first preset threshold, the final multiple of the target order is determined to be the first price adjustment multiple, and price reduction order dispatching is performed; if the first proportion does not exceed the first preset threshold, calculate the second proportion of the actual number of available drivers corresponding to the three-stage price reduction order-receiving mode and the two-stage price reduction order-receiving mode in the total number of available drivers for the multi-stage price reduction order-receiving mode, and determine whether the second proportion exceeds the second preset threshold; if the second proportion exceeds the second preset threshold, the final multiple of the target order is determined to be the second price adjustment multiple, and price reduction order dispatching is performed; if the second proportion does not exceed the second preset threshold, determine whether the estimated amount type is not a small order; if the estimated amount type is not a small order, the final price adjustment multiple of the target order is determined to be the high-price order multiple, and normal order dispatching is performed; if the estimated amount type is a small order, the final price adjustment multiple of the target order is determined to be 1, and small order dispatching is performed.

[0125] It should be noted that the first price adjustment multiple is lower than the second price adjustment multiple. Preferably, the first price adjustment multiple can be 0.9, and the second price adjustment multiple can be 0.95. In practical applications, the first price adjustment multiple and the second price adjustment multiple can be set according to actual needs, and the present invention does not limit this.

[0126] Step S105, dispatch the target order based on the final price adjustment multiple and the target order dispatching type.

[0127] The dispatch types in the embodiments of the present invention include normal dispatch, non-high-price dispatch, price reduction dispatch, small order dispatch, etc. Among them, normal dispatch is to dispatch the target order to the eligible drivers by taking all the eligible drivers with all order-taking modes within the first dispatch range of the target order as the candidate drivers; non-high-price dispatch is to dispatch the target order to the eligible drivers by taking the eligible drivers after filtering out the order-taking modes with higher unit prices within the first dispatch range of the target order as the candidate drivers; price reduction dispatch is to dispatch the target order to the eligible drivers with multi-level price reduction order-taking modes within the second dispatch range of the target order as the candidate drivers; small order dispatch is to dispatch the target order to the eligible drivers with multi-level price reduction order-taking modes within the first dispatch range of the target order as the candidate drivers. Furthermore, in combination with the final price adjustment multiple given by the preset price adjustment rule in step S104 and the target dispatch type, the target order is assigned to the eligible drivers.

[0128] It should be noted that the second dispatch range is smaller than the first dispatch range. Preferably, the second dispatch range can be 2KM, and the second price adjustment multiple can be 5KM. In practical applications, the first dispatch range and the second dispatch range can be set according to actual needs, and the present invention does not make any limitations thereto.

[0129] The embodiments of the present invention provide a method for dynamic price adjustment and order dispatch of online car-hailing, and present an innovative dynamic order allocation algorithm. This algorithm can be adjusted in real time according to the number of orders, the number of drivers, the quality of drivers (such as service score, speed, etc.), and the characteristics of orders (such as urgency, destination, etc.) to ensure that orders are more evenly and reasonably distributed during peak periods. Specifically, a setting can be provided for high-quality drivers to select higher-price orders. This mechanism allows drivers to select those orders with higher prices and more in line with their own needs during peak periods according to their own situations and preferences, thereby improving their service quality and income level. In addition, an intelligent price reduction dispatch algorithm is also presented. This algorithm can automatically adjust the order price according to factors such as the waiting time of drivers, the order volume, and the market competition situation, so as to attract more users to place orders, thereby reducing the waiting time of drivers and improving the resource utilization rate. Specifically, price reduction strategies and other incentive measures (such as coupons, point rewards, etc.) can also be adopted to attract more users to place orders during off-peak periods. This incentive mechanism not only helps to increase the order volume, but also reduces the loss of drivers and improves the overall operation efficiency of the platform. Through the present invention, the status of orders and drivers can be monitored in real time, and real-time adjustment can be made according to the above dynamic price adjustment strategy, with a high level of automation and intelligence, to ensure the accuracy and timeliness of price adjustment, and greatly improve the user experience and usability.

[0130] Furthermore, as Figure 1 a specific implementation of, the embodiments of the present invention provide a system for dynamic price adjustment and order dispatch of online car-hailing, such as Figure 4As shown, the system may include: a data acquisition module 410, a driver selection module 420, a type determination module 430, a rate output module 440, and an order assignment module 450.

[0131] The data acquisition module 410 can be used to acquire the order acceptance mode and driver portrait data set by the driver through the driver terminal; the order acceptance mode includes a higher unit price order acceptance mode and a multi-stage price reduction order acceptance mode.

[0132] The driver selection module 420 can be used to select the total number of available drivers for various order acceptance modes within the first dispatching range of the target order according to the driver portrait data.

[0133] The type determination module 430 can be used to determine the estimated amount type of the target order according to the preset estimated amount type configuration.

[0134] The rate output module 440 can be used to determine the final price adjustment rate and the target dispatching type of the target order based on the preset price adjustment rules matching different order acceptance time periods, according to the estimated amount type and the total number of available drivers.

[0135] The order assignment module 450 can be used to dispatch the target order based on the final price adjustment rate and the target dispatching type.

[0136] Among them, the order acceptance time periods include peak periods and off-peak periods.

[0137] Optionally, as Figure 4 shown, the online car-hailing dynamic price adjustment and dispatching system provided by another embodiment of the present invention further includes: an index configuration module 460.

[0138] The index configuration module 460 can be used to configure operation-related indexes before acquiring the order acceptance mode and driver portrait data set by the driver through the driver terminal, including order acceptance time periods, estimated amount types, and / or order acceptance mode response times.

[0139] Among them, the estimated amount types include small orders, large orders, and general orders.

[0140] The order acceptance mode response time is the order acceptance response time corresponding to each order acceptance mode, including the high-price order acceptance response time and the multi-stage price reduction order acceptance response time.

[0141] The multi-stage price reduction order acceptance mode includes a first-stage price reduction order acceptance mode, a second-stage price reduction order acceptance mode, and a third-stage price reduction order acceptance mode; the multi-stage price reduction order acceptance response time includes a first-stage price reduction order acceptance response time, a second-stage price reduction order acceptance response time, and a third-stage price reduction order acceptance response time.

[0142] It should be noted that for other corresponding descriptions of the functional modules involved in the online car-hailing dynamic price adjustment and order dispatching system provided in the embodiments of the present invention, reference can be made to Figure 1 the corresponding descriptions of the methods shown, which will not be elaborated here.

[0143] Based on the above as Figure 1 shown in the method, correspondingly, the embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the online car-hailing dynamic price adjustment and order dispatching method in any of the above embodiments are implemented.

[0144] Based on the above as Figure 1 shown in the method and the embodiments of the system as Figure 5 shown, the embodiments of the present invention also provide an entity structure diagram of a computer device, as Figure 6 shown. The computer device may include a communication bus, a processor, a memory, and a communication interface, and may also include an input / output interface and a display device. Among them, each functional unit can complete mutual communication through the bus. The memory stores a computer program, and the processor is used to execute the program stored on the memory and execute the steps of the online car-hailing dynamic price adjustment and order dispatching method in the above embodiments.

[0145] Those skilled in the art can clearly understand that the specific working processes of the above-described system, device, module, and unit can refer to the corresponding processes in the foregoing method embodiments. For the sake of brevity, they will not be elaborated here.

[0146] In addition, in each embodiment of the present invention, each functional unit may be physically independent, or two or more functional units may be integrated together, or all functional units may be integrated in a processing unit. The above-mentioned integrated functional units can be implemented in the form of hardware, or in the form of software or firmware.

[0147] Those of ordinary skill in the art can understand that if the above-mentioned integrated functional units are implemented in the form of software and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, which includes several instructions for causing a computing device (such as a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present invention when running the instructions. The foregoing storage media include: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, etc., which can store program codes.

[0148] Alternatively, all or part of the steps of implementing the foregoing method embodiments may be completed by hardware related to program instructions (such as computing devices such as personal computers, servers, or network devices), and the program instructions may be stored in a computer-readable storage medium. When the program instructions are executed by the processor of the computing device, the computing device executes all or part of the steps of the methods described in the embodiments of the present invention.

[0149] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: within the spirit and principle of the present invention, it is still possible to modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the corresponding technical solutions to deviate from the protection scope of the present invention.

Claims

1. A method for dynamic price adjustment and order dispatching of online car-hailing, characterized in that, The method includes: Obtaining the order receiving mode and driver portrait data set by the driver through the driver terminal; the order receiving mode includes a higher unit price order receiving mode and a multi-level price reduction order receiving mode; According to the driver portrait data, selecting the total number of available drivers for various order receiving modes within the first dispatching range of the target order; Determining the estimated amount type of the target order according to the preset estimated amount type configuration; Based on the preset price adjustment rules matching different order receiving time periods, determining the final price adjustment multiple and target dispatching type of the target order according to the estimated amount type and the total number of available drivers; Dispatching the target order based on the final price adjustment multiple and the target dispatching type; Wherein, the order receiving time period types include peak periods and off-peak periods.

2. The method according to claim 1, characterized in that, Before obtaining the order receiving mode and driver portrait data set by the driver through the driver terminal, the method further includes: Configuring operation-related indicators, including order receiving time period types, estimated amount types, and / or order receiving mode response times; Wherein, the estimated amount types include small order orders, large order orders, and general orders; The order receiving mode response time is the order receiving response time corresponding to each order receiving mode, including the high-price order receiving response time and the multi-level price reduction order receiving response time; The multi-level price reduction order receiving mode includes a first-level price reduction order receiving mode, a second-level price reduction order receiving mode, and a third-level price reduction order receiving mode; the multi-level price reduction order receiving response time includes a first-level price reduction order receiving response time, a second-level price reduction order receiving response time, and a third-level price reduction order receiving response time.

3. The method according to claim 1, characterized in that The driver portrait data includes at least one of the last order completion time, the last departure time, the last return time, the last peak period start time, the last time of setting the higher unit price order receiving mode during the peak period, the last time of setting the multi-level price reduction order receiving mode during the peak period, the time of setting the higher unit price order receiving mode to be enabled during the peak period, the time of setting the multi-level price reduction order receiving mode to be enabled during the peak period, the last off-peak period start time, the last time of setting the higher unit price order receiving mode during the off-peak period, the last time of setting the multi-level price reduction order receiving mode during the off-peak period, the time of setting the higher unit price order receiving mode to be enabled during the off-peak period, the time of setting the multi-level price reduction order receiving mode to be enabled during the off-peak period, and the number of recent small order orders.

4. The method according to claim 3, wherein The selecting the total number of available drivers for various order receiving modes within the first dispatching range of the target order according to the driver portrait data includes: Obtaining the driver portrait data of all dispatched drivers within the first dispatching range of the target order; According to the driver portrait data, judging whether the order receiving mode of each dispatched driver is valid, including: Under the peak period, the mathematical expression for judging that the higher unit price order receiving mode is valid is: T current -Max(T last_out ,T last_finish ,T last_peak_start ,T set_higher_price )≤T high_price_order ; Among them, T current is the current time; T last_out is the time of the last vehicle departure; T last_finish is the time of the last order completion; T last_peak_start is the start time of the last peak period; T set_higher_price is the time to set a higher unit price for order acceptance in the peak period; T high_price_order is the response time for high-price order acceptance; And / or, Under the peak period, the mathematical expression for judging that the multi-level price reduction order receiving mode is valid is: T current -Max(T last_out ,T last_finish ,T last_flat_start ,T set_more_orders_peak )>T discount_order ; Among them, T current is the current time; T last_out is the last departure time; T last_finish is the last order completion time; T last_peak_start is the start time of the last peak period; T set_more_orders_peak is the time when the multi-level price reduction order receiving mode is enabled during the peak period; T discount_order is the multi-level price reduction order receiving response time; And / or, Under the off-peak period, the mathematical expression for judging that the higher unit price order receiving mode is valid is: T current -Max(T last_out ,T last_finish ,T last_flat_start ,T set_higher_price_flat )≤T high_price_order_flat ; Among them, T current is the current time; T last_out is the time of the last vehicle departure; T last_finish is the time of the last order completion; T last_flat_start is the start time of the last off-peak period; T set_higher_price_flat is the time to set the higher acceptance price mode during the off-peak period; T high_price_order_flat is the response time for accepting high-price orders during the off-peak period; And / or, Under the off-peak period, the mathematical expression for judging that the multi-level price reduction order receiving mode is valid is: T current -Max(T last_out ,T last_finish ,T last_flat_start ,T set_more_orders_flat )>T discount_order_flat ; Among them, T current is the current time; T last_out is the time of the last vehicle departure; T last_finish is the time of the last order completion; T last_flat_start is the start time of the last off-peak period; T set_flatr_price is the time when the multi-level price reduction order receiving mode is enabled during the off-peak period; T set_more_orders_flat is the response time of the multi-level price reduction order receiving during the off-peak period; Counting the total number of available drivers who are valid under each order receiving mode.

5. The method according to claim 1, wherein Determining the estimated amount type of the target order according to the preset estimated amount type configuration includes: Obtaining the order information of the target order, and determining the small order amount and large order amount corresponding to the target order according to the order information; wherein, the order information includes order estimated amount, city, channel, and / or order receiving time period type; Judging the estimated amount type of the target order according to the small order amount, the large order amount, and the order estimated amount, including: If the order estimated amount ≤ the small order amount, the target order is a small order; if the order estimated amount > the large order amount, the target order is a large order; if the small order amount < the order estimated amount < the large order amount, judge whether the order coefficient of the target order meets the high-price order multiple; if the order coefficient ≥ the high-price order multiple, the target order is a large order; if the order coefficient < the high-price order multiple, the target order is a general order; the calculation formula of the high-price order multiple is: Where x is the order estimated amount and y is the high-price order multiple.

6. The method according to claim 2, wherein Based on the preset price adjustment rules matching different order receiving time period types, determining the final price adjustment multiple and the target dispatching type of the target order according to the estimated amount type and the total number of available drivers, including: Under peak hours, judge whether the number of available drivers in the higher unit price receiving mode is greater than 0. When the number of available drivers in the higher unit price receiving mode is greater than 0, judge whether the estimated amount type is a large order; if the estimated amount type is a large order, determine that the final price adjustment multiple of the target order is 1 and perform normal dispatching; if the estimated amount type is not a large order, judge whether the total number of available drivers is equal to the number of available drivers in the higher unit price receiving mode set, If the total number of available drivers is equal to the number of available drivers in the higher unit price receiving mode set, judge whether the estimated amount type is not a small order; if the estimated amount type is not a small order, determine that the final price adjustment multiple of the target order is the high-price order multiple and perform normal dispatching; if the estimated amount type is a small order, determine that the final price adjustment multiple of the target order is 1 and perform small order dispatching; If the total number of available drivers is not equal to the number of available drivers in the higher unit price receiving mode set, calculate the first proportion of the actual number of available drivers corresponding to the three-stage price reduction receiving mode in the total number of available drivers in the multi-stage price reduction receiving mode, and judge whether the first proportion exceeds the first preset threshold; if the first proportion exceeds the first preset threshold, determine that the final multiple of the target order is the first price adjustment multiple and perform price reduction dispatching; if the first proportion does not exceed the first preset threshold, calculate the second proportion of the actual number of available drivers corresponding to the three-stage price reduction receiving mode and the two-stage price reduction receiving mode in the total number of available drivers in the multi-stage price reduction receiving mode, and judge whether the second proportion exceeds the second preset threshold; if the second proportion exceeds the second preset threshold, determine that the final multiple of the target order is the second price adjustment multiple and perform price reduction dispatching; When the number of available drivers for the higher unit price order receiving mode is 0, or when the second ratio does not exceed the second preset threshold, determine whether the estimated amount type is not a small order; if the estimated amount type is not a small order, determine whether the estimated amount type is a large order; if the estimated amount type is a large order, the final price adjustment multiple of the target order is 1, and normal order dispatching is performed; if the estimated amount type is not a large order, the final price adjustment multiple of the target order is 1, and non-high price order dispatching is performed; if the estimated amount type is a small order, the final price adjustment multiple of the target order is 1, and small order dispatching is performed. Among them, the first price adjustment multiple is lower than the second price adjustment multiple.

7. The method according to claim 1, characterized in that, Based on the preset price adjustment rules matching different order receiving time periods, determine the final price adjustment multiple and the target order dispatching type of the target order according to the estimated amount type and the total number of available drivers, including: During the off-peak period, determine whether the total number of available drivers is equal to the number of available drivers for the higher unit price order receiving mode. If the total number of available drivers is equal to the number of available drivers for the higher unit price order receiving mode, determine whether the estimated amount type is not a small order; if the estimated amount type is not a small order, determine the final price adjustment multiple of the target order as the high price order multiple, and perform normal order dispatching; if the estimated amount type is a small order, determine the final price adjustment multiple of the target order as 1, and perform small order dispatching. If the total number of available drivers is not equal to the number of available drivers for the higher unit price order receiving mode, calculate the first ratio of the actual number of available drivers corresponding to the three-stage price reduction order receiving mode to the total number of available drivers for the multi-stage price reduction order receiving mode, and determine whether the first ratio exceeds the first preset threshold; if the first ratio exceeds the first preset threshold, determine the final multiple of the target order as the first price adjustment multiple, and perform price reduction order dispatching; if the first ratio does not exceed the first preset threshold, calculate the second ratio of the actual number of available drivers corresponding to the three-stage price reduction order receiving mode and the two-stage price reduction order receiving mode to the total number of available drivers for the multi-stage price reduction order receiving mode, and determine whether the second ratio exceeds the second preset threshold; if the second ratio exceeds the second preset threshold, determine the final multiple of the target order as the second price adjustment multiple, and perform price reduction order dispatching; if the second ratio does not exceed the second preset threshold, determine whether the estimated amount type is not a small order; if the estimated amount type is not a small order, determine the final price adjustment multiple of the target order as the high price order multiple, and perform normal order dispatching; if the estimated amount type is a small order, determine the final price adjustment multiple of the target order as 1, and perform small order dispatching. Among them, the first price adjustment multiple is lower than the second price adjustment multiple.

8. The method according to any one of claims 6 or 7, characterized in that, The order dispatching type includes at least one of normal order dispatching, non-high price order dispatching, price reduction order dispatching, and small order dispatching. Among them, the normal order dispatching is to use all available drivers in the first order dispatching range of the target order as candidate drivers for order dispatching. The non-high-price order assignment is to assign orders by using the available drivers within the first order assignment range of the target order after filtering out the higher unit price order receiving modes as candidate drivers; The price reduction order assignment is to assign orders by using the available drivers with multi-level price reduction order receiving modes within the second order assignment range of the target order as candidate drivers; The small order assignment is to assign orders by using the available drivers with multi-level price reduction order receiving modes within the first order assignment range of the target order as candidate drivers; Wherein, the second order assignment range is smaller than the first order assignment range.

9. A dynamic price adjustment and order dispatching system for online car-hailing, characterized in that, The system includes: A data acquisition module, configured to acquire the order receiving mode and driver portrait data set by the driver through the driver terminal; the order receiving mode includes the higher unit price order receiving mode and the multi-level price reduction order receiving mode; A driver selection module, configured to select, according to the driver portrait data, the total number of available drivers with various order receiving modes within the first order assignment range of the target order; A type determination module, configured to determine the estimated amount type of the target order according to the preset estimated amount type configuration; A multiplier output module, configured to determine the final price adjustment multiplier and the target order assignment type of the target order based on the preset price adjustment rules matching different order receiving time periods, according to the estimated amount type and the total number of available drivers; An order assignment module, configured to assign the target order based on the final price adjustment multiplier and the target order assignment type; Wherein, the order receiving time periods include peak periods and off-peak periods.

10. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the online car-hailing dynamic price adjustment and order assignment method according to any one of claims 1 to 8.

Images