Online car-hailing order processing method, device, server and storage medium

Abstract

The present invention provides a method, device, server and storage medium for processing online car-hailing orders, and relates to the technical field of online car-hailing. The method comprises: after receiving an order request sent by an online car-hailing user, if the online car-hailing user has target authority, then determining the probability of the online car-hailing user using the target authority this time based on at least one influencing factor of the online car-hailing user using the target authority; if the probability of the online car-hailing user using the target authority this time is greater than a preset probability, and the remaining number of uses of the online car-hailing user's target authority is greater than a preset number, then queuing the online car-hailing user in a fast dispatch channel; if the online car-hailing user determines to use the target authority, then dispatching the online car-hailing user using the queue order in the fast dispatch channel. When the embodiment of the present invention determines that the use probability is relatively high, it will queue the online car-hailing user in advance, thereby improving the success rate of fast dispatching.

Description

Technical Field

[0001] The present invention relates to the field of online car-hailing technology, and in particular to an online car-hailing order processing method, device, server and storage medium. Background Art

[0002] For online ride-hailing users, some users may be more concerned about matching time. For these online ride-hailing users, the quick order dispatch benefit can be activated. When the online ride-hailing user initiates an order and indicates that he or she needs to use the quick order dispatch benefit, the online ride-hailing order platform can quickly dispatch the order for the online ride-hailing user.

[0003] However, when there are fewer vehicles available due to extreme weather or other extreme conditions, the user may not enjoy the quick dispatch benefit because the quick dispatch benefit is only triggered after the user initiates the order, thereby reducing the success rate of quick dispatch. Summary of the Invention

[0004] The present invention provides a method, device, server and storage medium for processing online car-hailing orders. After receiving an order request, the method can determine the probability of an online car-hailing user using the target authority. When the usage probability is relatively high, the online car-hailing user will be queued in advance. After determining that the user uses the target authority, the pre-queuing result will be used to dispatch the order, thereby improving the success rate of fast dispatching.

[0005] In a first aspect, an embodiment of the present invention provides a method for processing an online car-hailing order, comprising:

[0006] After receiving the order request sent by the online car-hailing user, determine whether the online car-hailing user has the target permission;

[0007] If the online car-hailing user has the target permission, determining the probability that the online car-hailing user will use the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission;

[0008] If the probability of the online car-hailing user using the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is greater than the preset number, the online car-hailing user will be queued in the fast dispatch channel;

[0009] If within a preset time after receiving an order request sent by an online car-hailing user, the online car-hailing user confirms to use the target authority, the order will be dispatched for the online car-hailing user in the queue order in the quick dispatch channel.

[0010] The above method can, after receiving an order request from an online car-hailing user, determine whether the online car-hailing user has the target authority, and then judge the probability of the online car-hailing user using the target authority this time. When the probability is greater than the preset probability, it means that the user is more likely to use the target authority. In this case, the user will be pre-queued in the quick order dispatch channel. After determining that the user uses the target authority, the result of pre-queuing the user in the quick order dispatch channel will be used to dispatch the order for the online car-hailing user, thereby improving the success rate of quick order dispatch.

[0011] In one possible implementation, the influencing factors include some or all of the following: the weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the month when the order request is received, and the use of the target permissions by users around the online car-hailing user.

[0012] Since users are more likely to use the vehicle quickly when the weather is bad, users are more likely to use the vehicle quickly when the destination is special, such as a train station or airport, users are more likely to use the vehicle quickly when the start time of the ride is later than the start time of the previous order, users are more likely to use the target authority when the remaining number of target permissions is relatively large, users are more likely to use the target authority at the beginning of the month, and users around them have all used the target authority, etc. In summary, the above method can determine whether the online car-hailing user uses the target authority based on multiple factors such as weather conditions, destination, start time of the ride, remaining number of target permissions, time of the month, and use of target permissions by surrounding users, thereby improving the accuracy.

[0013] In one possible implementation, determining the probability of the online car-hailing user using the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission includes:

[0014] For each of the influencing factors, if the influencing factor satisfies a preset condition corresponding to the influencing factor, determining the probability corresponding to the influencing factor to be a first preset value;

[0015] If the influencing factor does not meet the preset condition corresponding to the influencing factor, determining the probability corresponding to the influencing factor to be a second preset value; wherein the first preset value is greater than the second preset value;

[0016] Determining the probability of the online car-hailing user using the target permission this time based on the probability corresponding to each of the influencing factors;

[0017] or

[0018] If the number of the influencing factors that meet the preset conditions corresponding to the influencing factors exceeds a preset number, it is determined that the probability of the online car-hailing user using the target authority this time is a third preset value; and the third preset value is greater than the preset probability;

[0019] or

[0020] According to the correspondence between the range of influencing factors and the probability, the probability corresponding to the range of influencing factors to which each influencing factor belongs is determined, and the probability corresponding to the range of influencing factors to which each influencing factor belongs is used as the probability corresponding to each influencing factor; according to the probability corresponding to each influencing factor, the probability of the online car-hailing user using the target authority this time is determined.

[0021] The above method can determine the probability of an influencing factor based on whether the influencing factor meets the corresponding preset conditions, or determine the probability corresponding to the influencing factor based on the corresponding relationship between the value of the influencing factor and the probability, and then determine the probability of the online ride-hailing user using the target permission based on this probability. In this way, the overall probability can be determined based on the probability corresponding to a single influencing factor, thereby improving the accuracy of the probability determination. Alternatively, if the majority of influencing factors meet the corresponding preset conditions, the probability of the user using the target permission is higher. In this way, the probability is determined based on the majority of influencing factors meeting the corresponding preset conditions, thereby improving the accuracy of the probability determination.

[0022] In one possible implementation, determining the probability of the online ride-hailing user using the target permission this time based on the probability corresponding to each of the influencing factors includes:

[0023] The sum of the probabilities corresponding to each of the influencing factors is used as the probability that the online car-hailing user uses the target authority this time; or

[0024] The sum of the preset weight corresponding to each of the influencing factors and the product of the probability corresponding to each of the influencing factors is used as the probability that the online car-hailing user uses the target authority this time.

[0025] The above method can use the sum of the probabilities corresponding to each influencing factor as the probability of the target authority or the sum of the products of the preset weights and probabilities corresponding to each influencing factor as the probability of the target authority. It can comprehensively determine the probability of using the target authority based on each influencing factor, thereby improving the accuracy of the determination.

[0026] In one possible implementation, the method further includes:

[0027] After receiving an order request from an online car-hailing user, queue the online car-hailing user in the ordinary dispatch channel;

[0028] If the probability that the online car-hailing user uses the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is less than the preset number, the queue order in the ordinary dispatch channel will be used to dispatch the order for the online car-hailing user.

[0029] In the above method, when the remaining number of uses of the target permission is relatively small, which means that the online car-hailing user cannot use the target permission, the queuing result of the ordinary dispatching channel can be used to dispatch the order for the online car-hailing user, avoiding the user queuing after determining whether to use the target permission, resulting in a long dispatching time and a poor user experience.

[0030] In one possible implementation, the method further includes:

[0031] If the probability that the online car-hailing user will use the target authority this time is greater than a preset probability, and the remaining number of uses of the target authority of the online car-hailing user is equal to a preset number, then within a preset time after receiving the order request sent by the online car-hailing user, after receiving the online car-hailing user's confirmation to use the target authority, a prompt message is sent to the online car-hailing user to remind the online car-hailing user that the remaining number of uses of the target authority of the online car-hailing user is equal to the preset number, and confirmation information is sent to the online car-hailing user on whether to use the target authority, and the online car-hailing user is queued in the fast order dispatch channel;

[0032] After receiving the feedback information from the online car-hailing user, the order is dispatched for the online car-hailing user using the queue order in the quick dispatch channel; wherein, the feedback information is sent by the online car-hailing user after receiving the confirmation information on whether to use the target authority and confirming that he or she will use the target authority.

[0033] According to the above method, if the remaining number of uses of the target permission is determined to be relatively low, the user needs to confirm twice before it can be determined that the user uses the target permission, thereby queuing the online car-hailing user in the quick dispatch channel and using the queuing order in the quick dispatch channel to dispatch the online car-hailing user, thereby improving the speed of dispatch.

[0034] In a second aspect, an embodiment of the present invention provides a device for processing an online car-hailing order, comprising:

[0035] A judgment module is used to judge whether the online car-hailing user has the target authority after receiving the order request sent by the online car-hailing user;

[0036] a probability determination module for determining, if the online car-hailing user has the target permission, the probability that the online car-hailing user will use the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission;

[0037] A queuing module is configured to queue the online car-hailing user in a fast dispatch channel if the probability that the online car-hailing user uses the target authority this time is greater than a preset probability and the remaining number of uses of the target authority of the online car-hailing user is greater than a preset number;

[0038] The order processing module is used to process the order for the online car-hailing user in the queuing order in the quick order dispatch channel if the online car-hailing user confirms to use the target authority within a preset time after receiving the order request sent by the online car-hailing user.

[0039] In one possible implementation, the influencing factors include some or all of the following: the weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the month when the order request is received, and the use of the target permissions by users around the online car-hailing user.

[0040] In a third aspect, an embodiment of the present invention provides a server for order processing, comprising:

[0041] processor;

[0042] a memory for storing instructions executable by the processor;

[0043] In which, the processor is configured to execute the instructions to implement the online car-hailing order processing method as described in any one of the first aspects.

[0044] In a fourth aspect, an embodiment of the present invention provides a storage medium, which, when the instructions in the storage medium are executed by the processor of the server, enables the server to execute the online car-hailing order processing method as described in any one of the first aspects.

[0045] In addition, the technical effects brought about by any implementation method in the second to fourth aspects can refer to the technical effects brought about by different implementation methods in the first aspect, and will not be repeated here.

[0046] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A flowchart of a method for processing an online ride-hailing order provided by an embodiment of the present invention;

[0048] Figure 2 A schematic diagram of a user-side order request initiation page provided by an embodiment of the present invention;

[0049] Figure 3A schematic diagram of a user-side target benefit usage provided by an embodiment of the present invention;

[0050] Figure 4 A schematic diagram of another method for processing online ride-hailing orders provided by an embodiment of the present invention;

[0051] Figure 5 A schematic diagram of another method for processing an online ride-hailing order provided by an embodiment of the present invention;

[0052] Figure 6 A schematic diagram of the structure of an online car-hailing order processing device provided by an embodiment of the present invention;

[0053] Figure 7 A schematic diagram of the structure of a server provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] To make the objectives, technical solutions, and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings. It is apparent that the embodiments described are only some, not all, of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0055] The present invention is described in detail below with reference to the accompanying drawings:

[0056] Combine Figure 1 As shown, an embodiment of the present invention provides a method for processing an online car-hailing order, comprising:

[0057] S100: After receiving an order request from an online car-hailing user, determining whether the online car-hailing user has target authority;

[0058] Combine Figure 2 As shown in the figure, when an online car-hailing user makes an online car-hailing reservation, the user fills in the starting address, destination, and starting time of the ride, and then sends this information to the server used for order processing after completing the filling. This is the order request. After the order request is issued, the server receives the order request and determines whether the online car-hailing user has the target permission.

[0059] Combine Figure 3As shown, the user-side page includes: T-coin doubling, birthday gift package, free cancellation, priority dispatch (the priority dispatch here means quick dispatch, which are just two different terms. The following explanation uses quick dispatch), credit improvement, member price and other rights. Among them, the target permission can be the quick dispatch right. In order to make the use of the quick dispatch right more obvious, the 5 times written above the quick dispatch right means that users at this level have 5 opportunities to use the quick dispatch right every month. After placing an order, the user can click the button to use the quick dispatch. The server will perform quick dispatch for this user. Users who do not select the button will be assigned ordinary orders.

[0060] The server will record the remaining usage times of each user who has the right to quick dispatch and the remaining usage times of each user who has the right to quick dispatch. Of course, for users who meet the right to quick dispatch, the remaining usage times of their right to quick dispatch will be updated every month. For example, if there are 5 usage times of the right to quick dispatch each month, then the usage times will be updated on the first day of the month. If user A used the right to quick dispatch 4 times last month, then the usage times will be updated to 5 times on the first day of this month. For example, as shown in Table 1:

[0061] user Remaining usage times this month User A 5 User B 4 User C 5 User D 2

[0062] In step 100, the server can determine whether the online car-hailing user who initiated the order request is in the above table by checking the data of users with quick order dispatch rights, as shown in Table 1. For example, if the online car-hailing user who initiated the order request is user A, then in the above table, it is determined that the online car-hailing user has the target authority.

[0063] S101: If the online car-hailing user has the target permission, determining the probability of the online car-hailing user using the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission;

[0064] Because users are more likely to use the vehicle quickly when the weather is bad, such as rainy, snowy, and windy days; users are more likely to use the vehicle quickly when the destination is special, such as a train station or airport; users are more likely to use the vehicle quickly when the start time of the ride is later than the start time of the previous order. For example, the online car-hailing user's historical ride time is 8:00 to 8:10, and the current online car-hailing user's ride start time is 8:30, which is later than the usual historical ride start time, so the online car-hailing user may need to use the vehicle faster this time; the ride start time is the night before the end of the holiday, so the online car-hailing user may need to use the vehicle faster this time; the ride start time is the time when the movie ends, so the online car-hailing user may need to use the vehicle faster this time; the user is more likely to use the target permission when the remaining number of target permissions is relatively large, the user is more likely to use the target permission at the beginning of the month, and the users around the online car-hailing user use the target permission, which will make the online car-hailing user need to use the vehicle faster this time, etc.

[0065] Based on the above content, the influencing factors of the embodiment of the present invention include some or all of the following: the weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the month when the order request is received, and the use of target permissions by users around the online car-hailing user.

[0066] S102: If the probability of the online car-hailing user using the target authority this time is greater than a preset probability, and the remaining number of uses of the target authority of the online car-hailing user is greater than a preset number, the online car-hailing user is queued in the fast dispatch channel;

[0067] Among them, the preset number can be 1. Then, when the remaining number of uses of the target authority of the online car-hailing user is greater than 1, the online car-hailing user can be queued in the quick dispatch channel.

[0068] S103: If the online car-hailing user confirms to use the target authority within the preset time after receiving the order request sent by the online car-hailing user, the online car-hailing user will be dispatched in the queue order in the fast dispatch channel.

[0069] Recombination Figure 2 and Figure 3 As shown, when the user Figure 2 After initiating an order request in Figure 3After the user clicks on the quick dispatch, the server determines whether the time period between receiving the order request sent by the online car-hailing user and receiving the confirmation of the online car-hailing user to use the target authority is less than the preset time. For example, the time period is 20 seconds and the preset time is 30 seconds. If 20 seconds is less than 30 seconds, then the condition is met and it is determined to use the queuing order in the quick dispatch channel to dispatch the order for the online car-hailing user.

[0070] If after receiving an order request, the online car-hailing user is queued in the fast dispatch channel, but some online car-hailing users do not consider using the target authority, then after determining that the online car-hailing user has not used the target authority, the online car-hailing user is queued in the common dispatch channel, which will result in a relatively long queue time. Therefore, the present invention proposes that after receiving the order request sent by the online car-hailing user, the method further includes: queuing the online car-hailing user in the common dispatch channel;

[0071] Within a preset time after receiving an order request sent by an online car-hailing user, after receiving the confirmation of the online car-hailing user to use the target authority, the method also includes: canceling the queue in the ordinary order dispatching channel.

[0072] If it is determined within a preset time after receiving an order request sent by an online car-hailing user that the online car-hailing user has not used the target authority, the method further includes: dispatching orders to the online car-hailing user using the queuing order in the ordinary dispatching channel.

[0073] The above solution can avoid the problem of online car-hailing users waiting in long queues after finally determining that they have not used the target authority, thereby improving the user's sense of security.

[0074] For example, after receiving the order request sent by the online car-hailing user, the online car-hailing user has been queued in the general dispatching channel. Therefore, if the probability of the online car-hailing user using the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is less than the preset number, the queueing order in the general dispatching channel will be used to dispatch the order for the online car-hailing user.

[0075] For example, the preset number of times is 1. When the remaining number of uses of the target authority of the online car-hailing user is less than 1, and the remaining number of uses of the target authority of the online car-hailing user is 0, it means that the online car-hailing user does not have the target authority to use. In this case, there is no need for the user to determine whether to use the target authority. The order can be dispatched to the online car-hailing user in the same queuing order as in the ordinary dispatching channel after receiving the order.

[0076] Based on the above content, combined with Figure 4As shown, an embodiment of the present invention provides another method for processing an online car-hailing order, including:

[0077] S400: After receiving an order request from an online car-hailing user, queuing the online car-hailing user in a common dispatching channel and determining whether the online car-hailing user has target authority;

[0078] S401: If the online car-hailing user has the target permission, determining the probability of the online car-hailing user using the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission;

[0079] S402: If the probability of the online car-hailing user using the target authority this time is greater than a preset probability, and the remaining number of uses of the target authority of the online car-hailing user is greater than a preset number, the online car-hailing user is queued in the fast dispatch channel;

[0080] S403: If the probability of the online car-hailing user using the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is less than the preset number, the online car-hailing user is dispatched using the queue order in the ordinary dispatch channel;

[0081] S404: If the online car-hailing user confirms to use the target authority within the preset time after receiving the order request sent by the online car-hailing user, the online car-hailing user will be dispatched in the queue order in the fast dispatch channel.

[0082] Exemplarily, the method further includes: if the probability that the online car-hailing user uses the target authority this time is greater than a preset probability, and the remaining number of uses of the target authority of the online car-hailing user is equal to a preset number, then within a preset time after receiving the order request sent by the online car-hailing user, after receiving the online car-hailing user's confirmation to use the target authority, sending a prompt message to the online car-hailing user to prompt the online car-hailing user that the remaining number of uses of the target authority is equal to the preset number, and sending confirmation information to the online car-hailing user whether to use the target authority, and queuing the online car-hailing user in the fast order dispatch channel;

[0083] After receiving feedback information from the online car-hailing user, the order is dispatched for the online car-hailing user using the queue order in the quick dispatch channel; wherein, the feedback information is sent by the online car-hailing user after receiving confirmation information on whether to use the target authority and confirming that he or she will use the target authority.

[0084] Specifically, when the number of remaining uses of the target permission of the online car-hailing user is 1, and the online car-hailing user triggers Figure 3When a ride-hailing user selects the target privilege for the first time during a quick dispatch, a prompt will be issued to prevent the user from accidentally triggering the privilege. The user will then be queued in the quick dispatch channel. Once the user returns the second confirmation, the user will be dispatched based on their queue order in the quick dispatch channel.

[0085] Based on the above content, combined with Figure 5 As shown, an embodiment of the present invention provides another method for processing an online car-hailing order, including:

[0086] S500: After receiving an order request from an online car-hailing user, determining whether the online car-hailing user has target authority;

[0087] S501: If the online car-hailing user has the target permission, determining the probability of the online car-hailing user using the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission;

[0088] S502: If the probability of the online car-hailing user using the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is greater than the preset number, the online car-hailing user is queued in the fast dispatch channel;

[0089] S503: If the online car-hailing user confirms to use the target authority within the preset time after receiving the order request sent by the online car-hailing user, the online car-hailing user will be dispatched in the queue order in the fast dispatch channel.

[0090] S504: If the probability that the online car-hailing user uses the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is equal to the preset number, then within the preset time after receiving the order request sent by the online car-hailing user, after receiving the online car-hailing user's confirmation to use the target authority, a prompt message is sent to the online car-hailing user to remind the online car-hailing user that the remaining number of uses of the target authority is equal to the preset number, and a confirmation message is sent to the online car-hailing user on whether to use the target authority, and the online car-hailing user is queued in the fast order dispatch channel;

[0091] S505: After receiving feedback information from the online car-hailing user, the order is dispatched for the online car-hailing user using the queue order in the quick dispatch channel; wherein, the feedback information is sent by the online car-hailing user after receiving confirmation information on whether to use the target authority and confirming that he or she uses the target authority.

[0092] Exemplarily, there are multiple ways to determine the probability of an online ride-hailing user using the target permission based on factors influencing at least one online ride-hailing user's use of the target permission. The following are some of the ways described in the embodiments of the present invention:

[0093] Method 1: For each influencing factor, if the influencing factor satisfies the preset condition corresponding to the influencing factor, the probability corresponding to the influencing factor is determined to be a first preset value;

[0094] If the influencing factor does not meet the preset condition corresponding to the influencing factor, determining the probability corresponding to the influencing factor to be a second preset value; wherein the first preset value is greater than the second preset value;

[0095] Based on the probability corresponding to each influencing factor, determine the probability of the online ride-hailing user using the target permission this time;

[0096] Among them, the influencing factors include some or all of the following: the weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the month when the order request is received, and the use of target permissions by users around the online car-hailing user.

[0097] When the influencing factor is the weather condition when the order request is received, the preset condition corresponding to the weather condition when the order request is received is: the weather is rainy, snowy, or windy.

[0098] When the influencing factor is the destination in the order request, the preset conditions corresponding to the destination in the order request are: train station, airport, etc.

[0099] When the influencing factor is the ride start time in the order request, the preset condition corresponding to the ride start time in the order request is: the ride start time in the order request exceeds the maximum time in the ride start time period in the historical orders of the online car-hailing user that is closest to the ride start time in the order request.

[0100] For example, the ride start times collected from the online ride-hailing user's historical orders are 6:00 PM, 6:01 PM, 6:05 PM, 8:00 AM, 8:01 AM, and 8:10 AM. It can be determined that the ride start time periods in the user's historical orders include two: 5:50 PM to 6:10 PM and 7:50 AM to 8:10 AM. The ride start time in the current order request is 8:30 AM. Compared to the most recent historical ride start time period of 7:50 AM to 8:10 AM, the maximum time is 8:10 AM. Therefore, the 8:30 AM ride time is later than the maximum time of the ride start time period in the historical orders, which is 8:10 AM.

[0101] Alternatively, the preset condition corresponding to the ride start time in the order request is: the ride start time is from 7 p.m. the day before the holiday to 7 a.m. the next day. Of course, this time period is only exemplary and can be set arbitrarily as needed.

[0102] For example, the starting time of the ride for the online car-hailing user is 8 pm, and it is the last day of the May Day holiday, so the starting time of the ride meets the corresponding preset conditions.

[0103] Alternatively, the preset condition corresponding to the ride start time in the order request is: the ride start time falls within the time range of the movie ending.

[0104] The time range of the movie ending is the time period that includes the movie ending. For example, if the movie ends at 8:30 pm, then the time range of the movie ending is from 8:20 pm to 9 pm. Specifically, if the ride start time of the online ride-hailing user is 8:35 pm, then the ride start time meets the corresponding preset conditions.

[0105] The influencing factor is the remaining number of target permissions of the online car-hailing user. The preset condition corresponding to the remaining number of target permissions of the online car-hailing user is: the remaining number of target permissions of the online car-hailing user is greater than 3 times.

[0106] The influencing factor is the time of the month when the order request is received. The preset condition corresponding to the time of the month when the order request is received is: the time of the month when the order request is received is the beginning of the month, that is, the beginning of the month is from the 1st to the 10th of the month.

[0107] The influencing factor is the situation in which users around the online car-hailing user use the target authority. The preset condition corresponding to the situation in which users around the online car-hailing user use the target authority is: most users around the online car-hailing user use the target authority.

[0108] Users around the online ride-hailing user can be those who are less than 500 meters away from the online ride-hailing user. Of course, 500 meters is only an example.

[0109] The majority of users around a ride-hailing user can be determined based on the total number of users around the ride-hailing user. For example, if the total number of users around the ride-hailing user is 10, then the majority of users around the ride-hailing user is 8; if the total number of users around the ride-hailing user is 3, then the majority of users around the ride-hailing user is 2; if the total number of users around the ride-hailing user is 2, then the majority of users around the ride-hailing user is 1.

[0110] The first preset value is determined according to the number of influencing factors, and the second preset value is 0. For example, if there are 6 influencing factors, then the first preset value can be 1 divided by 6, which is equal to 16%. Then if one influencing factor is satisfied, it is 16%. When the influencing factors are the weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the received order request in the current month, and the use of target permissions by users around the online car-hailing user, and all of the above meet the corresponding preset conditions, then the probability corresponding to each influencing factor is 16%.

[0111] Alternatively, the first preset value is 70%, and the second preset value is 30%, that is, if the corresponding preset conditions are met, then the probability corresponding to the influencing factor is 70%.

[0112] In this regard, the above is only exemplary and can be set according to user needs.

[0113] Among them, the probability corresponding to the influencing factor is the probability that the influencing factor affects the online car-hailing user's use of the target permission this time.

[0114] Method 2: If the number of influencing factors that satisfy the preset conditions corresponding to the influencing factors exceeds a preset number, then the probability that the online car-hailing user uses the target authority this time is determined to be a third preset value; and the third preset value is greater than the preset probability;

[0115] The preset number can be determined according to the number of influencing factors. For example, if there are 5 influencing factors and the preset number needs to be smaller than 5, it can be set to 3. The preset conditions corresponding to the influencing factors are the same as those in Method 1. For details, please refer to Method 1.

[0116] Method 3: According to the correspondence between the influencing factor range and the probability, determine the probability corresponding to the influencing factor range of each influencing factor, and use the probability corresponding to the influencing factor range of each influencing factor as the probability corresponding to each influencing factor; according to the probability corresponding to each influencing factor, determine the probability that the online car-hailing user will use the target authority this time.

[0117] The correspondence between the range of influencing factors and the probability can be pre-set, taking the following influencing factors as an example: the weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the received order request in the current month, and the use of target permissions by users around the online car-hailing user.

[0118] When the influencing factor is the weather conditions when the order request is received, as shown in Table 2:

[0119] Range of influencing factors Probability Heavy rain, snow, strong winds 70％ other 30％

[0120] When the influencing factor is the destination in the order request, combined with Table 3:

[0121] Range of influencing factors Probability Railway stations, airports, and subway stations 70％ other 30％

[0122] When the influencing factor is the ride start time in the order request (here we take the historical ride start time as an example, the other two preset conditions are similar to this situation, all with different degrees and different probabilities), combined with Table 4:

[0123] Range of influencing factors Probability 8:30 (Historical ride start time 8:00) 60％ 8:40 (historical ride start time 8:00) 70％ 9:00 (historical ride start time 8:00) 80％ 8:00 (Historical ride start time 8:00) 10％

[0124] When the influencing factor is the remaining number of target permissions of the online car-hailing user, combined with Table 5:

[0125] Range of influencing factors Probability 5 (the default number is 3 times) 80％ 4 70％ 3 60％

[0126] When the influencing factor is the time of the month when the order request is received, combined with Table 6:

[0127] Range of influencing factors Probability 1st to 9th 70％ other 30％

[0128] When the influencing factor is the use of the target permission by users around the online car-hailing user, assuming that the total number of users around the online car-hailing user is 5 and the number of the majority of users around is 4, combined with Table 7:

[0129] Influencing factors Probability 5 90％ 4 70％

[0130] In combination with the above content, for example, if the weather condition when the order request is received is heavy rain, then in combination with Table 2, the probability corresponding to the weather condition when the order request is received is 70%;

[0131] If the destination in the order request is Office Building B in City Q, combined with Table 3, the probability corresponding to the weather conditions when the order request is received is 30%;

[0132] If the ride start time in the order request is 8:00 a.m., combined with Table 4, the probability corresponding to the ride start time in the order request is 10%;

[0133] If the remaining number of times the online car-hailing user uses the target permission is 4, combined with Table 5, the probability corresponding to the remaining number of times the online car-hailing user uses the target permission is 70%;

[0134] If the order request is received on the 11th of the month, according to Table 6, the probability of the ride start time in the order request being 30% is 30%.

[0135] If the situation in which the users around the online car-hailing user use the target authority is that all four users around the online car-hailing user use the target authority, combined with Table 7, the probability that the users around the online car-hailing user use the target authority is 70%.

[0136] The method of determining the probability of the online car-hailing user using the target permission this time based on the probability corresponding to each influencing factor includes:

[0137] The sum of the probabilities corresponding to each influencing factor is used as the probability that the online car-hailing user uses the target permission this time; or

[0138] The sum of the preset weight corresponding to each influencing factor and the product of the probability corresponding to each influencing factor is taken as the probability that the online car-hailing user uses the target permission this time.

[0139] Taking the above example, the probability corresponding to the weather conditions when the order request is received is 70%, the probability corresponding to the weather conditions when the order request is received is 30%, the probability corresponding to the starting time of the ride in the order request is 10%, the probability corresponding to the remaining number of times the online car-hailing user uses the target authority is 70%, the probability corresponding to the starting time of the ride in the order request is 30%, and the probability corresponding to the users around the online car-hailing user using the target authority is 70%, then 70% + 30% + 10% + 70% + 30% + 70% = 280%, 2.8 is the probability that the online car-hailing user uses the target authority this time.

[0140] Alternatively, according to the actual situation, a preset weight is set for each influencing factor. For example, the preset weight corresponding to the weather conditions when the order request is received is 25%, the preset weight corresponding to the destination in the order request is 15%, the preset weight corresponding to the start time of the ride in the order request is 15%, the preset weight corresponding to the remaining number of target permissions of the online car-hailing user is 15%, the preset weight corresponding to the time of the received order request in the current month is 20%, and the preset weight corresponding to the situation in which users around the online car-hailing user use the target permissions is 10%.

[0141] 70%*25%+30%*15%+10%*15%+70%*15%+30%*20%+70%*10%=47%, so 0.47 is the probability that the ride-hailing user uses the target permission this time.

[0142] like Figure 6 As shown, the present invention also provides an online car-hailing order processing device, comprising:

[0143] The judgment module 600 is used to judge whether the online car-hailing user has the target authority after receiving the order request sent by the online car-hailing user;

[0144] The probability determination module 601 is configured to determine, if the online car-hailing user has the target permission, the probability that the online car-hailing user will use the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission;

[0145] The queuing module 602 is configured to queue the online car-hailing user in the fast dispatch channel if the probability of the online car-hailing user using the target authority this time is greater than a preset probability and the remaining number of uses of the target authority of the online car-hailing user is greater than a preset number;

[0146] The order processing module 603 is used to process the order for the online car-hailing user in the queue order in the quick order dispatch channel if the online car-hailing user confirms to use the target authority within a preset time after receiving the order request sent by the online car-hailing user.

[0147] Optionally, the influencing factors include some or all of the following: weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the month when the order request is received, and the use of the target permissions by users around the online car-hailing user.

[0148] Optionally, the probability determination module 601 is specifically configured to:

[0149] For each of the influencing factors, if the influencing factor satisfies a preset condition corresponding to the influencing factor, determining the probability corresponding to the influencing factor to be a first preset value;

[0150] If the influencing factor does not meet the preset condition corresponding to the influencing factor, determining the probability corresponding to the influencing factor to be a second preset value; wherein the first preset value is greater than the second preset value;

[0151] Determining the probability of the online car-hailing user using the target permission this time based on the probability corresponding to each of the influencing factors;

[0152] or

[0153] If the number of the influencing factors that meet the preset conditions corresponding to the influencing factors exceeds a preset number, it is determined that the probability of the online car-hailing user using the target authority this time is a third preset value; and the third preset value is greater than the preset probability;

[0154] or

[0155] According to the correspondence between the range of influencing factors and the probability, the probability corresponding to the range of influencing factors to which each influencing factor belongs is determined, and the probability corresponding to the range of influencing factors to which each influencing factor belongs is used as the probability corresponding to each influencing factor; according to the probability corresponding to each influencing factor, the probability of the online car-hailing user using the target authority this time is determined.

[0156] Optionally, the probability determination module 601 is further configured to:

[0157] The sum of the probabilities corresponding to each of the influencing factors is used as the probability that the online car-hailing user uses the target authority this time; or

[0158] The sum of the preset weight corresponding to each of the influencing factors and the product of the probability corresponding to each of the influencing factors is used as the probability that the online car-hailing user uses the target authority this time.

[0159] Optionally, the queuing module 602 is further configured to:

[0160] After receiving an order request from an online car-hailing user, queue the online car-hailing user in the ordinary dispatch channel;

[0161] If the probability that the online car-hailing user uses the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is less than the preset number, the queue order in the ordinary dispatch channel will be used to dispatch the order for the online car-hailing user.

[0162] Optionally, the queuing module 602 is configured to:

[0163] If the probability that the online car-hailing user will use the target authority this time is greater than a preset probability, and the remaining number of uses of the target authority of the online car-hailing user is equal to a preset number, then within a preset time after receiving the order request sent by the online car-hailing user, after receiving the online car-hailing user's confirmation to use the target authority, a prompt message is sent to the online car-hailing user to remind the online car-hailing user that the remaining number of uses of the target authority of the online car-hailing user is equal to the preset number, and confirmation information is sent to the online car-hailing user on whether to use the target authority, and the online car-hailing user is queued in the fast order dispatch channel;

[0164] After receiving the feedback information from the online car-hailing user, the order is dispatched for the online car-hailing user using the queue order in the quick dispatch channel; wherein, the feedback information is sent by the online car-hailing user after receiving the confirmation information on whether to use the target authority and confirming that he or she will use the target authority.

[0165] In addition, combined Figures 1-6 The knowledge graph generation method and device described in the embodiments of the present invention can be implemented by a server.

[0166] The server for order processing includes: a processor;

[0167] a memory for storing instructions executable by the processor;

[0168] Wherein, the processor is configured to execute the instructions to implement the online car-hailing order processing method as described in any one of the above-mentioned methods.

[0169] Based on the above introduction, for example, Figure 7 server structure.

[0170] The server may include a processor 710 and a memory 720 storing computer program instructions.

[0171] Specifically, the processor 710 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiment of the present invention.

[0172] The memory 720 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 720 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 720 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 720 may be inside or outside the data processing device. In a specific embodiment, the memory 720 is a non-volatile solid-state memory. In a specific embodiment, the memory 720 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0173] The processor 710 implements any one of the task execution methods in the above embodiments by reading and executing computer program instructions stored in the memory 720 .

[0174] In one example, the server may further include a communication interface 730 and a bus 740. Figure 7 As shown, the processor 710 , the memory 720 , and the communication interface 730 are connected via a bus 740 and communicate with each other.

[0175] The communication interface 730 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present invention.

[0176] Bus 740 includes hardware, software or both, and the components of server are coupled to each other. For example, and not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnect (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 740 may include one or more buses. Although the embodiment of the present invention describes and shows a specific bus, the present invention considers any suitable bus or interconnection.

[0177] The server can execute the task execution method in the embodiment of the present invention based on the received task, thereby realizing the combination Figures 1-6 Described is a method and device for processing online ride-hailing orders.

[0178] In addition, in combination with the server in the above embodiments, an embodiment of the present invention may provide a storage medium, which, when the instructions in the storage medium are executed by the processor of the server, enables the server to execute the online car-hailing order processing method as described in any one of the above items.

[0179] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0180] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0181] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0182] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0183] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for processing online car-hailing orders, characterized in that: include: After receiving the order request sent by the online car-hailing user, determine whether the online car-hailing user has the target permission; If the online car-hailing user has the target permission, determining the probability that the online car-hailing user will use the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission; If the probability of the online car-hailing user using the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is greater than the preset number, the online car-hailing user will be queued in the fast dispatch channel; If within a preset time after receiving an order request sent by an online car-hailing user, the online car-hailing user confirms to use the target authority, the order will be dispatched for the online car-hailing user in the queue order in the quick dispatch channel.

2. The method for processing online car-hailing orders according to claim 1, characterized in that: The influencing factors include some or all of the following: the weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the month when the order request is received, and the use of the target permissions by users around the online car-hailing user.

3. The method for processing online car-hailing orders according to claim 1 or 2, characterized in that: Determining the probability that the online car-hailing user uses the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission includes: For each of the influencing factors, if the influencing factor satisfies a preset condition corresponding to the influencing factor, determining the probability corresponding to the influencing factor to be a first preset value; If the influencing factor does not meet the preset condition corresponding to the influencing factor, determining the probability corresponding to the influencing factor to be a second preset value; wherein the first preset value is greater than the second preset value; Determining the probability of the online car-hailing user using the target permission this time based on the probability corresponding to each of the influencing factors; or According to the correspondence between the range of influencing factors and the probability, the probability corresponding to the range of influencing factors to which each influencing factor belongs is determined, and the probability corresponding to the range of influencing factors to which each influencing factor belongs is used as the probability corresponding to each influencing factor; according to the probability corresponding to each influencing factor, the probability of the online car-hailing user using the target authority this time is determined.

4. The method for processing online car-hailing orders according to claim 3, characterized in that: Determining the probability of the online car-hailing user using the target permission this time based on the probability corresponding to each of the influencing factors includes: The sum of the probabilities corresponding to each of the influencing factors is used as the probability that the online car-hailing user uses the target authority this time; or The sum of the preset weight corresponding to each of the influencing factors and the product of the probability corresponding to each of the influencing factors is used as the probability that the online car-hailing user uses the target authority this time.

5. The method for processing online car-hailing orders according to claim 1, wherein: The method further comprises: After receiving an order request from an online car-hailing user, queue the online car-hailing user in the ordinary dispatch channel; If the probability that the online car-hailing user uses the target authority this time is greater than the preset probability, and the remaining number of uses of the target authority of the online car-hailing user is less than the preset number, the queue order in the ordinary dispatch channel will be used to dispatch the order for the online car-hailing user.

6. The method for processing online car-hailing orders according to claim 1, characterized in that: The method further comprises: If the probability that the online car-hailing user will use the target authority this time is greater than a preset probability, and the remaining number of uses of the target authority of the online car-hailing user is equal to a preset number, then within a preset time after receiving the order request sent by the online car-hailing user, after receiving the online car-hailing user's confirmation to use the target authority, a prompt message is sent to the online car-hailing user to remind the online car-hailing user that the remaining number of uses of the target authority of the online car-hailing user is equal to the preset number, and confirmation information is sent to the online car-hailing user on whether to use the target authority, and the online car-hailing user is queued in the fast order dispatch channel; After receiving the feedback information from the online car-hailing user, the order is dispatched for the online car-hailing user using the queue order in the quick dispatch channel; wherein, the feedback information is sent by the online car-hailing user after receiving the confirmation information on whether to use the target authority and confirming that he or she will use the target authority.

7. A device for processing online car-hailing orders, characterized in that: include: A judgment module is used to judge whether the online car-hailing user has the target authority after receiving the order request sent by the online car-hailing user; a probability determination module for determining, if the online car-hailing user has the target permission, the probability that the online car-hailing user will use the target permission this time based on at least one influencing factor of the online car-hailing user using the target permission; A queuing module is configured to queue the online car-hailing user in a fast dispatch channel if the probability that the online car-hailing user uses the target authority this time is greater than a preset probability and the remaining number of uses of the target authority of the online car-hailing user is greater than a preset number; The order processing module is used to process the order for the online car-hailing user in the queuing order in the quick order dispatch channel if the online car-hailing user confirms to use the target authority within a preset time after receiving the order request sent by the online car-hailing user.

8. The online car-hailing order processing device according to claim 7, characterized in that: The influencing factors include some or all of the following: the weather conditions when the order request is received, the destination in the order request, the starting time of the ride in the order request, the remaining number of target permissions of the online car-hailing user, the time of the month when the order request is received, and the use of the target permissions by users around the online car-hailing user.

9. A server for order processing, characterized in that: include: processor; a memory for storing instructions executable by the processor; Wherein, the processor is configured to execute the instructions to implement the online car-hailing order processing method as described in any one of claims 1 to claim 6.

10. A storage medium, characterized in that: When the instructions in the storage medium are executed by the processor of the server, the server is enabled to execute the online car-hailing order processing method as described in any one of claims 1 to 6.

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