A method and device for calculating order matching degree

Abstract

This invention relates to a method and apparatus for calculating order route matching. The method obtains real-time vehicle driving information of ride-hailing drivers, enabling faster and more efficient acquisition of passenger-posted order information. This ensures that ride-hailing drivers receive more convenient ride-hailing orders in a timely manner, meeting passenger needs and improving the passenger experience. Furthermore, by combining ride-hailing drivers' order-accepting profiles, the method can predict the driver's current driving behavior, preventing direct order assignments that could disrupt safe driving. Finally, by integrating the order information selected by ride-hailing drivers and optimizing and updating the order route matching rules, the method can obtain ride-hailing drivers' order-accepting profiles from multiple angles, aspects, and scenarios. These profiles can be further subdivided into more detailed scenario-based categories, allowing for the allocation of more suitable order information to ride-hailing drivers in different scenarios.

Description

Technical Field

[0001] The present invention relates to the field of transportation technology, and in particular to a method and device for calculating the degree of order en-route matching. Background Art

[0002] The development of online ride-hailing has become an emerging mode of transportation. Online ride-hailing is usually based on the current location information of the online ride-hailing owner, the location information of the owner's destination, the starting location information of the passenger, the destination location information of the passenger and the time period of the passenger's use of the vehicle. Because the driving information of the online ride-hailing owner is similar to the order information published by the passenger, a travel matching mechanism for multiple people sharing the ride is generated. Online ride-hailing has the beneficial effects of saving energy, alleviating traffic congestion, reducing air pollution and low-carbon travel.

[0003] In actual scenarios, online car-hailing car owners hope to find passengers with similar current locations, destination locations, and travel time periods. However, the existing online car-hailing dispatching methods have the following drawbacks: First, in the existing technology, usually only the current location of the online car-hailing car owner is considered to be unchanged, and the order matching degree between the online car-hailing car owner and the passenger is calculated. However, in actual situations, the online car-hailing car owner is not always in a static state, that is, the current location information of the online car-hailing car owner may be constantly changing. In other words, in actual life scenarios, the destination location information and travel time information of the online car-hailing car owner can be uniquely determined, but the current location information of the online car-hailing car owner is constantly changing as the vehicle travels. Second, in the existing technology, when the system assigns orders to online car-hailing owners, the system does not consider the driving time period information of the online car-hailing owners; that is, online car-hailing owners will have different order-taking portraits at different times of the day. Directly assigning the passenger's order information to the online car-hailing owner without considering the order-taking portrait of the online car-hailing owner will not only cause trouble to the online car-hailing owner, but also delay the passenger's travel.

[0004] Therefore, there is an urgent need to propose an order en-route matching degree calculation method and device that can effectively predict the order en-route matching degree between the vehicle driving information of the online car-hailing owner and the order information posted by the passenger. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method and device for calculating the order en route matching degree, which can predict the order en route matching degree, meet the order acceptance needs of online car-hailing owners, and meet the taxi-hailing needs of passengers.

[0006] To achieve the above purpose, the present application proposes a first technical solution: a method for calculating the order en-route matching degree, comprising the following steps: obtaining the vehicle driving information of the online car-hailing owner and the order-receiving portrait of the online car-hailing owner; obtaining the order information posted by the passenger, and based on the vehicle driving information and the order-receiving portrait, calculating the order en-route matching degree of the order information and the vehicle driving information according to the preset order en-route matching rules; wherein the vehicle driving information of the online car-hailing owner includes but is not limited to: the owner's current location information, the owner's destination location information, the owner's travel mileage and the owner's travel time period information; the order information may include but is not limited to: the passenger's starting location information, the passenger's destination location information and the passenger's travel mileage. The order information may also include: the order price, that is, the online car-hailing owner receives compensation for sending the passenger from the passenger's starting location to the passenger's destination location. It should be understood that the owner's travel mileage described in this application means the mileage required to travel from the current location to the destination location.

[0007] In one embodiment of the present invention, the preset order en route matching rules specifically include: taking the current location information of the vehicle owner as the center point, obtaining the passenger starting location information within a first threshold, and / or, taking the destination location information of the vehicle owner as the center point, obtaining the passenger destination location information within a third threshold; based on the mileage of the vehicle owner's travel and the mileage of the passenger's travel, calculating the coverage of the order information and the vehicle driving information; based on the current location information of the vehicle owner and the starting location information of the passenger, obtaining the current location distance between the online car-hailing vehicle owner and the passenger; based on the destination location information of the vehicle owner and the passenger's destination location information, the destination location distance between the online car-hailing vehicle owner and the passenger; based on the current location distance, the destination location distance, the passenger mileage and the vehicle owner's travel mileage, calculating the deviation between the order information and the vehicle driving information; based on the order acceptance portrait, correspondingly calculating the first weight of the deviation and the second weight of the coverage; based on the deviation, the coverage, the first weight and the second weight, calculating the order en route matching degree between the order information and the vehicle driving information.

[0008] In one embodiment of the present invention, the order acceptance portrait of the online car-hailing owner specifically includes: the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing owner in historical scenarios consistent with the vehicle driving information.

[0009] In one embodiment of the present invention, the determination of the first threshold value specifically includes: based on the characteristics of the online car-hailing owner's behavior of accepting orders and rejecting orders, calculating the maximum value of the distance between the passenger's starting position information and the center point, and defining the maximum value as the first threshold value; the determination of the third threshold value specifically includes: based on the characteristics of the online car-hailing owner's behavior of accepting orders and rejecting orders, calculating the maximum value of the distance between the passenger's destination position information and the center point, and defining the maximum value as the third threshold value.

[0010] In one embodiment of the present invention, the coverage of the order information and the vehicle driving information is calculated based on the following formula:

[0011]

[0012] Based on the following formula, the deviation between the order information and the vehicle driving information is calculated:

[0013]

[0014] In one embodiment of the present invention, the method also includes: obtaining the order en-route matching degree, and sending the order en-route matching degree and the order information corresponding to the order en-route matching degree to the online car-hailing owner, and the online car-hailing owner makes a selection based on the order information; based on the order information selected by the online car-hailing owner, optimizing and updating the order en-route matching rules.

[0015] In one embodiment of the present invention, obtaining the order en-route matching degree, and sending the order en-route matching degree and order information corresponding to the order en-route matching degree to the online car-hailing vehicle owner specifically includes:

[0016] Obtain order information whose order en route matching degree is higher than a second threshold; generate an order sequence list based on the order of the order en route matching degree; based on the order sequence list, push the order en route matching degree and the order information corresponding to the order en route matching degree to the online car-hailing vehicle owner one by one.

[0017] In one embodiment of the present invention, the optimization and updating of the order en route matching rules specifically includes: regularly integrating the order information selected by the online car-hailing owner; and optimizing and updating the order en route matching rules based on the order information selected by the online car-hailing owner.

[0018] To achieve the above purpose, the present application also proposes a second technical solution:

[0019] A device for calculating the degree of matching of an order along the way, the device comprising: an information acquisition unit for acquiring vehicle driving information of an online car-hailing owner and an order acceptance portrait of the online car-hailing owner, wherein the vehicle driving information of the online car-hailing owner comprises: the owner's current location information, the owner's destination location information and the owner's travel mileage; an order matching degree calculation unit, wherein the order matching degree calculation unit is communicatively connected to the information acquisition unit; the order matching degree calculation unit is used to acquire order information posted by a passenger, and based on the vehicle driving information and the order acceptance portrait, calculate the order matching degree of the order information and the vehicle driving information in accordance with a preset order matching rule, wherein the order information comprises: the passenger's starting location information, the passenger's destination location information and the passenger's travel mileage.

[0020] In one embodiment of the present invention, the device also includes: an order information selection unit, which is communicatively connected to the order en-route matching degree calculation unit; the order information selection unit obtains the order en-route matching degree, and sends the order en-route matching degree and the order information corresponding to the order en-route matching degree to the online car-hailing owner, so as to enable the online car-hailing owner to make a selection based on the order information; an optimization and update unit, which is communicatively connected to the order information selection unit, and the optimization and update unit is used to optimize and update the order en-route matching rules based on the order information selected by the online car-hailing owner.

[0021] The above-mentioned technical scheme of the present invention has the following advantages compared with the prior art: the method and device for calculating the order en-route matching degree described in the present invention, the method comprises the following steps: obtaining the vehicle driving information of the online car-hailing owner and the order acceptance portrait of the online car-hailing owner; obtaining the order information posted by the passenger, and based on the vehicle driving information and the order acceptance portrait, calculating the order en-route matching degree of the order information and the vehicle driving information according to the preset order en-route matching rules; obtaining the order en-route matching degree, and sending the order en-route matching degree and the order information corresponding to the order en-route matching degree to the online car-hailing owner, and the online car-hailing owner makes a selection based on the order information; optimizing and updating the order en-route matching rules based on the order information selected by the online car-hailing owner. By obtaining the vehicle driving information of online car-hailing owners in real time, the order information posted by passengers can be obtained quickly, efficiently and economically. On the one hand, it can ensure that online car-hailing owners receive online car-hailing orders in a timely manner. On the other hand, it can meet the passengers' car needs in a timely manner without wasting too much of the passengers' taxi-hailing time and waiting time, thereby improving the passengers' car-using experience. Combined with the online car-hailing owner's order-taking portrait, the online car-hailing owner's vehicle driving behavior in the current scene can be predicted without directly assigning orders to the online car-hailing owner to disrupt the online car-hailing owner's safe driving. Finally, by integrating the order information selected by the online car-hailing owner and optimizing and updating the order matching rules, the online car-hailing owner's order-taking portrait can be obtained from multiple angles, aspects and scenarios, and the online car-hailing owner's order-taking portrait can be divided into more detailed scenario-based categories to achieve more adaptable order information for the online car-hailing owner in different scenarios. To sum up, the order smooth matching degree calculation method and device described in this application realizes the prediction of the order along the way matching degree by calculating the deviation and coverage between the order information released by the online car-hailing owner and the passenger. It can meet the order acceptance needs of the online car-hailing owner and the taxi-hailing needs of the passengers. It has the beneficial effect of improving the passenger's car-using experience and happiness and increasing the income of the online car-hailing owner. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 is a flow chart of the method of the present invention;

[0024] Figure 2 is a schematic diagram of the range of the first threshold value and the third threshold value of the present invention;

[0025] Figure 3 It is a structural diagram of the device of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] Embodiment 1:

[0028] Reference Figure 1 As shown, Figure 1 This is a flow chart of the method of embodiment 1.

[0029] The method of this embodiment includes the following steps: Step S1, obtaining the vehicle driving information of the online car-hailing car owner and the order acceptance portrait of the online car-hailing car owner.

[0030] In one embodiment, the vehicle driving information of the online car-hailing owner includes: the owner's current location information, the owner's destination location information and the owner's travel mileage; the vehicle mileage indicates the distance that the online car-hailing owner needs to travel from the owner's current location to the owner's destination location. Among them, the owner's current location can be variable, that is, the owner's current location is determined according to the current location of the online car-hailing vehicle. For example: the online car-hailing owner needs to drive from the owner's current location point A to the owner's destination location point E. In the process of driving the online car-hailing car from point A to point E, the online car-hailing owner will pass through intermediate points such as point B, point C, and point D. Then, when the online car-hailing owner drives the online car to point B, the owner's current location information is point B at this time. As long as the online car-hailing owner does not change the pre-set owner's destination location information point E, the owner's destination location information is still point E. The online car-hailing owner's order acceptance portrait specifically includes: the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing owner in the historical scene consistent with the vehicle driving information. It should be understood that the historical scenarios consistent with the vehicle driving information include: at least one of the following: consistent driving period information of the owner, consistent current location information of the owner, consistent destination location information of the owner, and consistent mileage of the owner.

[0031] Step S2: Obtain the order information posted by the passenger, and based on the vehicle driving information and the order acceptance portrait, calculate the order en route matching degree between the order information and the vehicle driving information in accordance with the preset order en route matching rules.

[0032] In one embodiment, the order information published by the passenger includes: the passenger's starting location information, the passenger's destination location information and the passenger's travel mileage. The passenger's travel mileage is the distance the passenger needs to travel from the passenger's current location to the passenger's destination location.

[0033] In one embodiment, the preset order en route matching rules specifically include: step S21, taking the current location information of the vehicle owner as the center point, determining a first threshold based on the center point and the order acceptance portrait of the online car-hailing vehicle owner, and obtaining the starting location information of the passenger within the first threshold; step S22, based on the mileage of the vehicle owner and the mileage of the passenger, calculating the coverage of the order information and the vehicle driving information; step S23, based on the current location information of the vehicle owner and the starting location information of the passenger, obtaining the current location distance between the online car-hailing vehicle owner and the passenger; step S24, based on the The owner's destination location information and the passenger's destination location information, and the destination location distance between the online car-hailing owner and the passenger; step S25, based on the current location distance, the destination location distance, the passenger's mileage and the owner's mileage, calculate the deviation between the order information and the vehicle's driving information; step S26, based on the order-taking portrait, calculate the first weight of the deviation and the second weight of the coverage; step S27, based on the deviation, the coverage, the first weight and the second weight, calculate the order en route matching degree between the order information and the vehicle's driving information.

[0034] In one embodiment, the preset order matching rules also include: based on the current location information and destination location information of the online car-hailing owner and the starting location information and destination location information of the passenger, the value score of the online car-hailing owner is obtained with the online car-hailing owner's revenue as the guide, that is, when the requirements of the degree of convenience are met, the order or order combination that is more conducive to increasing the income of the online car-hailing owner is pushed to the online car-hailing owner. Specifically, assuming that the current location information of the online car-hailing owner is A, the location information of the destination is B, and the location of the online car-hailing owner is E, that is, there is a point E between A and B, that is, when the online car-hailing owner reaches the destination location B from the current location A, he must pass through location E. Assume that passenger 1's starting location information is A, and his destination information is C (the mileage between B and C is within the third threshold); there are passengers 2 and 3 at the same time, passenger 2's starting location is A and his destination location is E, and passenger 3's starting location is E and his destination location is B. If the online car-hailing owner obtains greater revenue from receiving orders from passengers 2 and 3 than from receiving orders from passenger 1, the orders of passengers 2 and 3 will be given priority in being delivered to the online car-hailing owner.

[0035] In one embodiment, the determination of the first threshold specifically includes: based on the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing owner, calculating and obtaining the maximum value of the distance between the passenger's current position and the center point, and defining the maximum value as the first threshold, such as Figure 2 As shown. The characteristics of the online car-hailing owner's order acceptance behavior and order rejection behavior are determined by the online car-hailing owner's historical behavior in historical scenarios that are consistent with the vehicle driving information. For example: in historical scenarios where the owner's current location information, the owner's destination location information, and the owner's driving time period information are all consistent, with the owner's current location as the center point, the owner will receive order information posted by passengers within a radius of 5 kilometers, and the online car-hailing owner will basically refuse to accept orders from passengers who are more than 5 kilometers away. So when dispatching orders to online car-hailing owners, the owner's current location information can be used as the center point to collect order information posted by passengers within a radius of 5 kilometers from the online car-hailing owner, that is, the first threshold is 5 kilometers. It should be understood that in actual application scenarios, the third threshold can be based on the owner's destination location information as the center point, and the passenger's destination location information within the third threshold is obtained, wherein the determination of the third threshold is consistent with the determination method of the first threshold, that is, based on the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing owner, the maximum value of the distance between the passenger's destination location information and the center point is calculated, and the maximum value is defined as the third threshold. For example: in a historical scenario where the owner's current location information, the owner's destination location information, and the owner's driving time period information are all consistent, with the owner's destination location information as the center point, the owner will receive order information posted by passengers within a radius of 5 kilometers, and the online car-hailing owner will basically refuse to accept the order information posted by passengers over 5 kilometers. Then, when dispatching orders to online car-hailing owners, the owner's destination location can be used as the center point to collect order information posted by passengers within a radius of 5 kilometers from the online car-hailing owner, that is, the third threshold is 5 kilometers. In actual application scenarios, the online car-hailing dispatching system can choose to consider either the passenger location information within the first threshold or the passenger destination location information within the third threshold; or it can simultaneously obtain the passenger location information within the first threshold and the passenger destination location information within the third threshold.

[0036] In one implementation manner, the coverage of the order information and the vehicle driving information is calculated based on the following formula:

[0037]

[0038] The coverage is positively correlated with the vehicle driving information of the online car-hailing owner, that is, the larger the coverage value, the higher the overlap between the order information posted by the current passenger and the vehicle driving information of the online car-hailing owner, and the greater the profit of a single order.

[0039] Based on the following formula, the deviation between the order information and the vehicle driving information is calculated:

[0040]

[0041] The deviation is negatively correlated with the vehicle driving information of the online car-hailing owner, that is, the larger the deviation value, the lower the overlap between the order information posted by the current passenger and the vehicle driving information of the online car-hailing owner, and the lower the profit of a single order.

[0042] In one embodiment, based on the order acceptance portrait, the corresponding calculation to obtain the first weight of the deviation and the second weight of the coverage specifically includes: the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing owner in the historical scenes consistent with the vehicle driving information. For example: when the vehicle driving information of at least one of the online car-hailing owner's current location information, the vehicle owner's destination location information and the vehicle owner's driving time period information is consistent, when accepting an order, does the online car-hailing owner pay more attention to the deviation or the coverage, that is, the degree of guidance that the deviation and coverage have for the online car-hailing owner when accepting an order.

[0043] In one embodiment, the determination of the first weight and the second weight can be achieved based on the following steps: regularly obtain the total number of orders received by the online car-hailing owner within the fifth threshold, the first number of orders guided by the degree of deviation in the total number of orders, and the second number of orders guided by the degree of coverage in the total number of orders; determine the first weight based on the first number of orders and the total number of orders, and determine the second weight based on the second number of orders and the total number of orders. Among them, the first weight is determined based on the following formula: the first weight = the first number of orders / the total number of orders; the second weight is determined based on the following formula: the second weight = the second number of orders / the total number of orders. It should be understood that the fifth threshold described in this application is the period of time before the online car-hailing owner has the last order-taking behavior characteristics. Specifically, in this application, the fifth threshold is 15 days, that is, the online car-hailing owner is obtained every 15 days within the last 15 days. For example: the total number of orders received by an online car-hailing driver within 15 days is 20, among which the first number of orders guided by deviation is 5, and the second number of orders guided by coverage is 15; then the first weight is 0.25, and the second weight is 0.75.

[0044] In one embodiment, the first weight and the second weight may also be determined based on the vehicle owner's destination location information and the vehicle owner's driving time period information set by the online car-hailing vehicle owner. That is, guided by the vehicle owner's driving time period information and the vehicle owner's destination location information, the total number of orders received by the vehicle owner within the fifth threshold, the first number of orders received guided by the degree of deviation in the total number of orders received, and the second number of orders received guided by the degree of coverage in the total number of orders received are regularly obtained; based on the first number of orders received and the total number of orders received, the first weight is determined, and based on the second number of orders received and the total number of orders received, the second weight is determined. For example, if the online car-hailing owner has received orders in the last 15 days, and the destination location set by the online car-hailing owner is a residential area and the owner's driving time information is night, and the number of second orders oriented to coverage exceeds 2 / 3 of the total number of orders, it can be determined that the online car-hailing owner wants to take the car home as soon as possible. Therefore, if the owner's driving time information is night and the owner's destination location is a residential area, the first weight can be defined as 0.2 and the second weight can be defined as 0.8 to obtain the calculation result of the order matching degree, and then the order information with the highest order matching degree can be pushed to the online car-hailing owner. Based on the online car-hailing owner's order-taking portrait, the online car-hailing owner's order-taking behavior can be predicted. On the one hand, it can help passengers find suitable online car-hailing cars more quickly. On the other hand, while ensuring that the online car-hailing owner can smoothly reach the owner's destination location, it can also increase the online car-hailing owner's additional income.

[0045] Step S3, obtaining the order's en-route matching degree, and sending the order's en-route matching degree and the order information corresponding to the order's en-route matching degree to the online car-hailing vehicle owner, and the online car-hailing vehicle owner makes a selection based on the order information;

[0046] In one embodiment, the order en-route matching degree is obtained, and the order en-route matching degree and the order information corresponding to the order en-route matching degree are sent to the online car-hailing car owner, and the online car-hailing car owner makes a selection based on the order information, specifically including: obtaining the order en-route matching degree between the order information and the vehicle driving information, and generating an order sequence table based on the order of the order en-route matching degree; if the order en-route matching degree in the order sequence table is not higher than the second threshold, then the order information corresponding to the order en-route matching degree is eliminated, and the order sequence table is updated and generated; based on the order sequence table, the order en-route matching degree and the order information corresponding to the order en-route matching degree are pushed one by one to the online car-hailing car owner. There is no provision for the generation order of the order sequence table. The technicians in this field can generate the order sequence table in the order of the order en-route matching degree from high to low or in the order of the matching degree from low to high according to the actual situation. The order sequence table may include but is not limited to the following contents: passenger starting position information, passenger destination position information and order en-route matching degree.

[0047] In one of the embodiments, the order en-route matching degree of the order information and the vehicle driving information is obtained, and the order en-route matching degree is generated into an order sequence table in descending order; if there is an order en-route matching degree not higher than 0.8 in the order sequence table, the order information corresponding to the order en-route matching degree is eliminated, and the order sequence table is updated and generated; based on the order sequence table, the order en-route matching degree and the order information corresponding to the order en-route matching degree are pushed one by one to the online car-hailing owner, that is, the order information with a higher en-route matching degree is pushed to the online car-hailing owner first, so as to ensure that the online car-hailing owner can choose the appropriate order more efficiently. It should be understood that the present application does not restrict the size of the second threshold value, and technicians in this field can select the size of the second threshold value according to actual conditions. The order information whose order en route matching degree is not higher than the second threshold is eliminated, and the order sequence table is updated and generated; based on the order sequence table, the order en route matching degree and the order information corresponding to the order en route matching degree are pushed to the online car-hailing vehicle owner one by one. By pushing the order to the online car-hailing vehicle owner, on the one hand, it ensures that the online car-hailing vehicle owner does not waste too much time in processing the delivery order, and ensures that the online car-hailing vehicle owner can drive safely; on the other hand, it ensures that the order information posted by the passenger can be delivered to a more suitable online car-hailing vehicle owner, and ensures that the passenger can choose a more suitable online car-hailing vehicle faster; in addition, it can also achieve the beneficial effect of protecting the passenger's privacy.

[0048] Step S4: Based on the order information selected by the online car-hailing vehicle owner, optimize and update the order en route matching rules.

[0049] In one of the embodiments, the optimization and updating of the order en route matching rules specifically include: regularly integrating the order information selected by the online car-hailing car owner; updating the order en route matching rules based on the order information selected by the online car-hailing car owner. Among them, it should be understood that the regular integration of the order information selected by the online car-hailing car owner not only includes regular integration of the order information selected by the online car-hailing car owner within a certain time period, but also regular integration based on the number of order information selected by the online car-hailing car owner. That is, the regular integration of the order information selected by the online car-hailing car owner can be that the technicians in this field choose to integrate the order information selected by the online car-hailing car owner at intervals of several days according to the actual situation, or it can be that when the number of orders selected by the online car-hailing car owner exceeds a certain number threshold, the order information selected by the online car-hailing car owner is integrated.

[0050] In one embodiment, updating the order en-route matching rule specifically refers to: learning the order-taking portrait of the online car-hailing owner according to the order information selected by the online car-hailing owner that is regularly integrated, that is, realizing the division of more order-taking scenarios, and realizing learning the order-taking behavior characteristics and order-rejecting behavior characteristics of the online car-hailing owner based on the same scenario. In other words, by regularly integrating the order information selected by the online car-hailing owner, the order-taking portrait of the online car-hailing owner can be obtained from multiple angles, multiple aspects, and multiple scenarios. By regularly integrating and obtaining the orders selected by the online car-hailing owner, on the one hand, the order-taking portrait of the online car-hailing owner can be divided into more detailed scenarios, that is, based on different scenarios, the order-taking behavior characteristics and order-rejecting behavior characteristics of the online car-hailing owner can be more accurately obtained to ensure that the online car-hailing owner is assigned more adaptable order information; on the other hand, based on the updated order-taking portrait, the acceptance degree of the online car-hailing owner for the deviation and coverage can be correspondingly updated, that is, the first weight of the deviation and the second weight of the coverage can be correspondingly calculated to obtain the order en-route matching degree of the order information and the vehicle driving information.

[0051] Embodiment 2:

[0052] The method of this embodiment includes the following steps: obtaining the vehicle driving information of the online car-hailing owner and the order acceptance portrait of the online car-hailing owner; obtaining the order information posted by the passenger, and based on the vehicle driving information and the order acceptance portrait, calculating the order en-route matching degree between the order information and the vehicle driving information in accordance with a preset order en-route matching rule; obtaining the order en-route matching degree, and sending the order en-route matching degree and the order information corresponding to the order en-route matching degree to the online car-hailing owner, and the online car-hailing owner makes a selection based on the order information; and optimizing and updating the order en-route matching rules based on the order information selected by the online car-hailing owner.

[0053] In one embodiment, the vehicle driving information of the online car-hailing owner includes: the owner's current location information, the owner's destination location information, the owner's mileage and the owner's driving time period information; the order information includes: the passenger's starting location information, the passenger's destination location information and the passenger's mileage.

[0054] In one embodiment, the preset order en route matching rules specifically include: taking the current location information of the vehicle owner as the center point, determining a first threshold based on the center point and the order acceptance portrait of the online car-hailing vehicle owner, and obtaining the passenger's starting location information within the first threshold, and / or, taking the destination location information of the vehicle owner as the center point, determining a third threshold based on the center point and the order acceptance portrait of the online car-hailing vehicle owner, and obtaining the passenger's destination location information within the third threshold; calculating the coverage of the order information and the vehicle driving information based on the mileage of the vehicle owner and the mileage of the passenger; and calculating the coverage of the order information and the vehicle driving information based on the current location information of the vehicle owner and the The passenger's starting location information is used to obtain the current location distance between the online car-hailing owner and the passenger; the destination location distance between the online car-hailing owner and the passenger is calculated based on the owner's destination location information and the passenger's destination location information; based on the current location distance, the destination location distance, the passenger's mileage and the owner's mileage, the deviation between the order information and the vehicle's driving information is calculated; based on the order-receiving portrait, the first weight of the deviation and the second weight of the coverage are calculated accordingly; based on the deviation, the coverage, the first weight and the second weight, the order en route matching degree between the order information and the vehicle's driving information is calculated.

[0055] In one embodiment, the preset order en-route matching rules specifically include: calculating the coverage of the order information and the vehicle driving information based on the mileage of the owner's travel and the mileage of the passenger; obtaining the current location distance between the online car-hailing owner and the passenger based on the owner's current location information and the passenger's starting location information; obtaining the destination location distance between the online car-hailing owner and the passenger based on the owner's destination location information and the passenger's destination location information; calculating the deviation between the order information and the vehicle driving information based on the current location distance, the destination location distance, the passenger's mileage and the owner's mileage; based on the order acceptance portrait, correspondingly calculating the first weight of the deviation and the second weight of the coverage; calculating the order en-route matching degree between the order information and the vehicle driving information based on the deviation, the coverage, the first weight and the second weight.

[0056] In one of the embodiments, the order en-route matching degree is obtained, and the order en-route matching degree and the order information corresponding to the order en-route matching degree are sent to the online car-hailing vehicle owner, and the online car-hailing vehicle owner makes a selection based on the order information, specifically including: obtaining order information whose order en-route matching degree is higher than a second threshold; generating an order sequence table based on the order of the order en-route matching degrees; and based on the order sequence table, pushing the order en-route matching degree and the order information corresponding to the order en-route matching degree to the online car-hailing vehicle owner one by one.

[0057] In one of the embodiments, the optimization and updating of the order en route matching rules specifically includes: regularly integrating the order information selected by the online car-hailing owner; and updating the order en route matching rules based on the order information selected by the online car-hailing owner.

[0058] In one of the embodiments, the order acceptance portrait of the online car-hailing owner specifically includes: the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing owner in historical scenarios consistent with the vehicle driving information.

[0059] In one embodiment, the determination of the first threshold value specifically includes: based on the characteristics of the online car-hailing owner's behavior of accepting orders and rejecting orders, calculating the maximum value of the distance between the passenger's starting location information and the center point, and defining the maximum value as the first threshold value; the determination of the third threshold value specifically includes: based on the characteristics of the online car-hailing owner's behavior of accepting orders and rejecting orders, calculating the maximum value of the distance between the passenger's destination location information and the center point, and defining the maximum value as the third threshold value.

[0060] In one implementation manner, the coverage of the order information and the vehicle driving information is calculated based on the following formula:

[0061]

[0062] Based on the following formula, the deviation between the order information and the vehicle driving information is calculated:

[0063]

[0064] Embodiment three:

[0065] Reference Figure 3 As shown, Figure 3 This is a structural diagram of the device of Embodiment 3.

[0066] The device of this embodiment includes: an information acquisition unit, which is used to obtain the vehicle driving information of the online car-hailing owner and the order acceptance portrait of the online car-hailing owner, the vehicle driving information of the online car-hailing owner includes: the owner's current location information, the owner's destination location information and the owner's mileage, and the order information includes: the passenger's starting location information, the passenger's destination location information and the passenger's mileage; an order en-route matching degree calculation unit, which is communicatively connected to the information acquisition unit; the order en-route matching degree calculation unit is used to obtain the order information posted by the passenger, and based on the vehicle driving information and the order acceptance portrait, calculate the order en-route matching degree between the order information and the vehicle driving information in accordance with the preset order en-route matching rules.

[0067] In one embodiment, the device also includes: an order information selection unit, which is communicatively connected to the order en-route matching degree calculation unit; the order information selection unit obtains the order en-route matching degree, and sends the order en-route matching degree and the order information corresponding to the order en-route matching degree to the online car-hailing owner, so as to enable the online car-hailing owner to make a selection based on the order information; an optimization and update unit, which is communicatively connected to the order information selection unit, and the optimization and update unit is used to optimize and update the order en-route matching rules based on the order information selected by the online car-hailing owner.

[0068] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for calculating the order matching degree, characterized in that: The method comprises the following steps: Obtaining the vehicle driving information of the online car-hailing vehicle owner and the order acceptance portrait of the online car-hailing vehicle owner, wherein the vehicle driving information of the online car-hailing vehicle owner includes: the vehicle owner's current location information, the vehicle owner's destination location information, and the vehicle owner's mileage; Obtaining the order information posted by the passenger, and calculating the order matching degree between the order information and the vehicle driving information based on the vehicle driving information and the order acceptance portrait according to the preset order matching rules, wherein the order information includes: the passenger's starting location information, the passenger's destination location information, and the passenger's travel mileage; The preset order matching rules specifically include: Taking the vehicle owner's current location information as the center point, obtaining the passenger's starting location information within a first threshold, and / or taking the vehicle owner's destination location information as the center point, obtaining the passenger's destination location information within a third threshold; Based on the mileage of the vehicle owner and the mileage of the passenger, calculating and obtaining the coverage of the order information and the vehicle driving information; Based on the current location information of the vehicle owner and the starting location information of the passenger, the current location distance between the vehicle owner and the passenger is obtained; based on the destination location information of the vehicle owner and the destination location information of the passenger, the destination location distance between the vehicle owner and the passenger is obtained; Based on the current location distance, the destination location distance, the passenger travel mileage and the vehicle owner travel mileage, the deviation between the order information and the vehicle driving information is calculated; Based on the order acceptance portrait, a first weight value of the deviation and a second weight value of the coverage are correspondingly calculated and obtained; Based on the deviation, the coverage, the first weight and the second weight, the order en route matching degree between the order information and the vehicle driving information is calculated.

2. The method for calculating order en-route matching degree according to claim 1, characterized in that: The order acceptance portrait of the online car-hailing car owner specifically includes: the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing car owner in historical scenarios consistent with the vehicle driving information.

3. The method for calculating order en-route matching degree according to claim 2, characterized in that: Determining the first threshold specifically includes: based on the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing driver, calculating and obtaining the maximum value of the distance between the passenger's starting position information and the center point, and defining the maximum value as the first threshold; Determination of the third threshold value specifically includes: based on the order acceptance behavior characteristics and order rejection behavior characteristics of the online car-hailing driver, calculating the maximum value of the distance between the passenger destination location information and the center point, and defining the maximum value as the third threshold value.

4. The method for calculating order route matching degree according to claim 1, characterized in that: Based on the following formula, the coverage of the order information and the vehicle driving information is calculated: Based on the following formula, the deviation between the order information and the vehicle driving information is calculated:

5. The method for calculating order route matching degree according to claim 1, characterized in that: The method further comprises: Obtaining the order's en-route matching degree, and sending the order's en-route matching degree and the order information corresponding to the order's en-route matching degree to the online car-hailing vehicle owner one by one, and the online car-hailing vehicle owner makes a selection based on the order information; Based on the order information selected by the online car-hailing car owner, the order en route matching rules are optimized and updated.

6. The method for calculating order en-route matching degree according to claim 5, characterized in that: Obtaining the order en route matching degree, and sending the order en route matching degree and the order information corresponding to the order en route matching degree to the online car-hailing vehicle owner one by one specifically includes: Acquire order information whose order matching degree is higher than a second threshold; Generate an order sequence table based on the order of the order's route matching degree; Based on the order sequence table, the order en route matching degree and the order information corresponding to the order en route matching degree are pushed to the online car-hailing vehicle owner one by one.

7. The method for calculating order en-route matching degree according to claim 5, characterized in that: The optimization and updating of the order en-route matching rules specifically includes: Regularly integrating the order information selected by the online car-hailing car owner; Based on the order information selected by the online car-hailing car owner, the order en route matching rules are optimized and updated.

8. An order en-route matching degree calculation device for implementing the order en-route matching degree calculation method as claimed in claim 1, characterized in that: The device comprises: An information acquisition unit is used to acquire the vehicle driving information of the online car-hailing vehicle owner and the order acceptance portrait of the online car-hailing vehicle owner, wherein the vehicle driving information of the online car-hailing vehicle owner includes: the vehicle owner's current location information, the vehicle owner's destination location information and the vehicle owner's travel mileage; An order en-route matching degree calculation unit, the order en-route matching degree calculation unit is communicatively connected with the information acquisition unit; the order en-route matching degree calculation unit is used to obtain the order information posted by the passenger, and based on the vehicle driving information and the order acceptance portrait, calculate the order en-route matching degree between the order information and the vehicle driving information in accordance with preset order en-route matching rules, wherein the order information includes: passenger starting location information, passenger destination location information and passenger travel mileage.

9. The order route matching degree calculation device according to claim 8, characterized in that: The device also includes: An order information selection unit, the order information selection unit is in communication connection with the order en-route matching degree calculation unit; the order information selection unit obtains the order en-route matching degree, and sends the order en-route matching degree and the order information corresponding to the order en-route matching degree to the online car-hailing vehicle owner, so that the online car-hailing vehicle owner can make a selection based on the order information; An optimization and update unit, wherein the optimization and update unit is communicatively connected to the order information selection unit, and the optimization and update unit is used to optimize and update the order en route matching rules based on the order information selected by the online car-hailing vehicle owner.

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