Recommendation method, device and equipment for online car-hailing, medium and product

Abstract

The invention discloses an online car-hailing recommendation method, device and equipment, a medium and a product. The method comprises the following steps: if an online car-hailing starting point and an online car-hailing ending point are both located in a target area, determining a get-on point set and a get-off point set from unmanned online car-hailing stations in the target area; if the getting-on point set and the getting-off point set are both non-empty sets, determining a getting-on section walking path set and a getting-off section walking path set; and determining an online car-hailing recommendation result according to the walking mileage of each walking path in the get-on section walking path set and the get-off section walking path set. According to the technical scheme, the problems of low online car-hailing matching efficiency, poor user experience and low resource utilization rate are solved, mixed calling of unmanned online car-hailing and manned online car-hailing is realized by performing station screening and path screening in the operation area of the unmanned online car-hailing, the car-hailing experience of the user is improved, and the user experience is improved. The online car-hailing matching efficiency is improved, and the resource waste of an online car-hailing scheduling platform is avoided.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a method, device, equipment, medium and product for recommending online car-hailing services. Background Art

[0002] With the continuous development of driverless technology, more and more driverless online ride-hailing vehicles are being demonstrated in specific areas. Due to different management models, driverless online ride-hailing vehicles and manned online ride-hailing vehicles usually belong to different dispatching platforms, which respond to users' ride-hailing requests separately. It is impossible to call the two types of online ride-hailing vehicles at the same time, which makes it difficult to meet the diverse needs of users and easily leads to a poor user experience. At the same time, the dispatching method of online ride-hailing vehicles dispatched by two dispatching platforms separately leads to low matching efficiency of online ride-hailing vehicles on the one hand, and on the other hand, each dispatching platform needs to occupy transportation capacity, resulting in a waste of hardware resources. Summary of the invention

[0003] The present invention provides a method, device, equipment, medium and product for recommending online taxis to solve the problems of low matching efficiency, poor user experience and low resource utilization of online taxis. By performing site screening and path screening in the operating area of ​​unmanned online taxis, mixed calls of unmanned online taxis and manned online taxis are realized, which is beneficial to improving the user's taxi-hailing experience, increasing the matching efficiency of online taxis, and avoiding resource waste of the online taxi dispatching platform.

[0004] According to one aspect of the present invention, a method for recommending online car-hailing services is provided. The method is executed by an online car-hailing service dispatching platform, and the method comprises:

[0005] If a ride-hailing request is received from a user terminal, determining the starting point and the end point of the online ride-hailing service according to the ride-hailing request;

[0006] If the online car-hailing starting point and the online car-hailing end point are both located in the target area, a set of pick-up points is determined from the driverless online car-hailing stations in the target area according to the online car-hailing starting point, and a set of drop-off points is determined from the driverless online car-hailing stations in the target area according to the online car-hailing end point; wherein the target area is the operating area of ​​the driverless online car-hailing;

[0007] If both the pickup point set and the alighting point set are non-empty sets, then the starting point of the online car-hailing vehicle is taken as the path starting point, and each pickup point in the pickup point set is taken as the path end point to determine the pickup segment walking path set, and, each alighting point in the alighting point set is taken as the path starting point, and the online car-hailing vehicle end point is taken as the path end point to determine the alighting segment walking path set;

[0008] The online car-hailing recommendation result is determined based on the walking mileage of each walking path in the boarding section walking path set and the walking mileage of each walking path in the alighting section walking path set; wherein the online car-hailing recommendation result includes the type of online car-hailing, and the type of online car-hailing includes manned online car-hailing and unmanned online car-hailing.

[0009] According to another aspect of the present invention, a device for recommending online car-hailing vehicles is provided, wherein the device is configured on an online car-hailing vehicle dispatching platform, and the device comprises:

[0010] A starting and ending point determination module, for determining the starting point and the ending point of the online car-hailing service according to the car-hailing request if a car-hailing request is received from a user terminal;

[0011] A point set determination module, for determining a pickup point set from driverless online ride-hailing stations in the target area according to the online ride-hailing starting point, and determining a drop-off point set from driverless online ride-hailing stations in the target area according to the online ride-hailing terminal if both the online ride-hailing starting point and the online ride-hailing terminal are located in a target area; wherein the target area is an operating area of ​​driverless online ride-hailing stations;

[0012] A path set determination module, for determining a set of walking paths for the boarding section by taking the starting point of the online car-hailing vehicle as the path starting point and each boarding point in the boarding point set as the path end point, if both the boarding point set and the boarding point set are non-empty sets, and for determining a set of walking paths for the boarding section by taking each boarding point in the boarding point set as the path starting point and the boarding point of the online car-hailing vehicle as the path end point;

[0013] The first recommendation result determination module is used to determine the online car-hailing recommendation result based on the walking mileage of each walking path in the boarding section walking path set and the walking mileage of each walking path in the alighting section walking path set; wherein the online car-hailing recommendation result includes the type of online car-hailing, and the type of online car-hailing includes manned online car-hailing and unmanned online car-hailing.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the online car-hailing recommendation method described in any embodiment of the present invention.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the online car-hailing recommendation method described in any embodiment of the present invention when executed.

[0017] According to another aspect of the present invention, a computer program product is provided, including a computer program, which, when executed by a processor, implements the method for recommending an online car-hailing service as described in any embodiment of the present invention.

[0018] The technical solution of the embodiment of the present invention is as follows: when receiving a ride-hailing request from a user terminal, the starting point and the end point of the online ride-hailing vehicle are determined according to the ride-hailing request; if the starting point and the end point of the online ride-hailing vehicle are both located in the target area, a set of pick-up points are determined from the unmanned online ride-hailing vehicle stations in the target area according to the starting point of the online ride-hailing vehicle, and a set of alighting points are determined from the unmanned online ride-hailing vehicle stations in the target area according to the end point of the online ride-hailing vehicle; if the pick-up point set and the alighting point set are both non-empty sets, a set of walking paths for the pick-up section is determined with the starting point of the online ride-hailing vehicle as the starting point of the path and each pick-up point in the pick-up point set as the end point of the path, and a set of walking paths for the alighting section is determined with each alighting point in the alighting point set as the starting point of the path and the end point of the online ride-hailing vehicle as the end point of the path; and a recommendation result for the online ride-hailing vehicle is determined according to the walking mileage of each walking path in the pick-up section walking path set and the walking mileage of each walking path in the alighting section walking path set. This technical solution solves the problems of low efficiency in online ride-hailing matching, poor user experience and low resource utilization. By performing site screening and route screening within the operating area of ​​driverless online ride-hailing vehicles, mixed calls of driverless online ride-hailing vehicles and manned online ride-hailing vehicles can be achieved, which is conducive to improving users' taxi experience, increasing the efficiency of online ride-hailing matching and avoiding waste of resources on the online ride-hailing dispatching platform.

[0019] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0021] Figure 1 is a flow chart of a method for recommending online car-hailing services according to Embodiment 1 of the present invention;

[0022] Figure 2is a flow chart of a method for recommending online car-hailing services according to Embodiment 2 of the present invention;

[0023] Figure 3 is a structural diagram of a device for recommending online car-hailing services provided according to a third embodiment of the present invention;

[0024] Figure 4 It is a schematic diagram of the structure of an electronic device that implements the online car-hailing recommendation method of an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments 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 should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0027] Embodiment 1

[0028] Figure 1 A flowchart of a method for recommending online ride-hailing vehicles is provided for the first embodiment of the present invention. This embodiment is applicable to scenarios where online ride-hailing vehicles are recommended to users by online ride-hailing vehicles applications, especially for driverless online ride-hailing vehicles. The method can be executed by an online ride-hailing vehicle recommendation device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0029] S110. If a ride-hailing request is received from a user terminal, a starting point and a terminal point of the online ride-hailing service are determined according to the ride-hailing request.

[0030] This solution can be executed by an online car-hailing dispatching platform, which can call both manned online car-hailing and unmanned online car-hailing at the same time, realizing two types of online car-hailing dispatching. The online car-hailing dispatching platform can communicate with one or more user terminals, which can be mobile phones, phone watches and other devices installed with car-hailing applications. When a user opens the car-hailing application, the user terminal can use the user's current location as the starting point of the online car-hailing. The user terminal can also obtain the starting address and the end address entered by the user, and then determine the starting point and the end point of the online car-hailing. After obtaining the starting point and the end point of the online car-hailing, the user terminal can initiate a car-hailing request to the online car-hailing dispatching platform. Among them, the car-hailing request may include information such as user identification, car-hailing time, starting point and end point of the online car-hailing. The online car-hailing dispatching platform can parse the car-hailing request and obtain the starting point and the end point of the online car-hailing.

[0031] S120. If the starting point and the end point of the online-hailing vehicle are both located within the target area, a set of boarding points is determined from the driverless online-hailing vehicle stations within the target area according to the starting point of the online-hailing vehicle, and a set of alighting points is determined from the driverless online-hailing vehicle stations within the target area according to the end point of the online-hailing vehicle; wherein the target area is the operating area of ​​the driverless online-hailing vehicle.

[0032] The online car-hailing dispatching platform can obtain the operating area of ​​the driverless online car-hailing vehicle in advance, and use the operating area of ​​the driverless online car-hailing vehicle as the target area. It can compare the location of the starting point of the online car-hailing vehicle with the target area to determine whether the starting point of the online car-hailing vehicle is within the target area. At the same time, it can compare the location of the end point of the online car-hailing vehicle with the target area to determine whether the end point of the online car-hailing vehicle is within the target area.

[0033] If the starting point and the end point of the online car-hailing are both within the target area, it means that the user can take a driverless online car-hailing in the target area. Understandably, in order to ensure the operational safety of driverless online car-hailing and facilitate the management and maintenance of the vehicle, fixed stops are usually set up in the target area to facilitate users to find driverless online car-hailing. Driverless online car-hailing stations can be used as pick-up or drop-off points for users. The online car-hailing dispatching platform can determine whether there is a driverless online car-hailing station in the target area that can be used as a pick-up point based on the starting point of the online car-hailing, and at the same time, determine whether there is a driverless online car-hailing station in the target area that can be used as a drop-off point based on the end point of the online car-hailing.

[0034] Among them, the pick-up point can be an unmanned online car-hailing station whose distance from the starting point of the online car-hailing is less than a preset distance threshold, and the drop-off point can be an unmanned online car-hailing station whose distance from the end point of the online car-hailing is less than a preset distance threshold. The online car-hailing dispatching platform can select the pick-up points that meet the distance requirements in the target area to form a pick-up point set, and at the same time, the online car-hailing dispatching platform can select the drop-off points that meet the distance requirements in the target area to form a drop-off point set.

[0035] S130. If both the boarding point set and the alighting point set are non-empty sets, then the starting point of the online-hailing vehicle is taken as the starting point of the path, and each boarding point in the boarding point set is taken as the end point of the path to determine the walking path set of the boarding section, and, further, each alighting point in the alighting point set is taken as the starting point of the path, and the end point of the online-hailing vehicle is taken as the end point of the path to determine the walking path set of the alighting section.

[0036] If the pickup point set is an empty set, it means that there is no pickup point that meets the distance requirement in the target area. If the drop-off point set is an empty set, it means that there is no drop-off point that meets the distance requirement in the target area. If at least one of the pickup point set and the drop-off point set is an empty set, the driverless online ride-hailing vehicle cannot meet the user's transportation task. Therefore, the online ride-hailing vehicle type fed back to the user terminal does not include driverless online ride-hailing vehicles. If both the pickup point set and the drop-off point set are non-empty sets, it means that there are both pickup points that meet the distance requirement and drop-off points that meet the distance requirement in the target area, and the driverless online ride-hailing vehicle can complete the user's transportation task.

[0037] It is understandable that the starting point of the online car-hailing vehicle and the pick-up point of the driverless online car-hailing vehicle may not be at the same location, and the end point of the online car-hailing vehicle and the drop-off point of the driverless online car-hailing vehicle may not be at the same location. Assuming that the user chooses to take an unmanned online car-hailing vehicle, the path between the pick-up point and the drop-off point is completed by the driverless online car-hailing vehicle, and the path from the starting point of the online car-hailing vehicle to the pick-up point and the path from the drop-off point to the end point of the online car-hailing vehicle need to be completed by the user on foot. The online car-hailing vehicle dispatching platform can take the starting point of the online car-hailing vehicle as the starting point of the path, take each pick-up point in the pick-up point set as the end point of the path, plan the user's walking path from the starting point of the online car-hailing vehicle to the pick-up point, and generate a set of walking paths for the pick-up section. Similarly, the online car-hailing vehicle dispatching platform can take each drop-off point in the drop-off point set as the starting point of the path, take the end point of the online car-hailing vehicle as the end point of the path, plan the user's walking path from the drop-off point to the end point of the online car-hailing vehicle, and generate a set of walking paths for the drop-off section.

[0038] S140. Determine the online car-hailing recommendation result based on the walking mileage of each walking path in the boarding section walking path set and the walking mileage of each walking path in the alighting section walking path set; wherein the online car-hailing recommendation result includes the type of online car-hailing, and the type of online car-hailing includes manned online car-hailing and unmanned online car-hailing.

[0039] The online car-hailing dispatching platform can determine whether to recommend a driverless online car-hailing vehicle to the user based on the distance the user needs to walk when the user chooses to take a driverless online car-hailing vehicle, so as to provide the user with a good taxi-hailing experience. The online car-hailing vehicle recommendation results can include information such as the type of online car-hailing vehicle, the number of online car-hailing vehicles, and the current location of the online car-hailing vehicle. It should be noted that the types of online car-hailing vehicles include manned online car-hailing vehicles and driverless online car-hailing vehicles. The types of online car-hailing vehicles in the online car-hailing vehicle recommendation results can be manned online car-hailing vehicles, driverless online car-hailing vehicles, or both manned online car-hailing vehicles and driverless online car-hailing vehicles.

[0040] The technical solution of the embodiment of the present invention is as follows: when receiving a ride-hailing request from a user terminal, the starting point and the end point of the online ride-hailing vehicle are determined according to the ride-hailing request; if the starting point and the end point of the online ride-hailing vehicle are both located in the target area, a set of pick-up points are determined from the unmanned online ride-hailing vehicle stations in the target area according to the starting point of the online ride-hailing vehicle, and a set of alighting points are determined from the unmanned online ride-hailing vehicle stations in the target area according to the end point of the online ride-hailing vehicle; if the pick-up point set and the alighting point set are both non-empty sets, a set of walking paths for the pick-up section is determined with the starting point of the online ride-hailing vehicle as the starting point of the path and each pick-up point in the pick-up point set as the end point of the path, and a set of walking paths for the alighting section is determined with each alighting point in the alighting point set as the starting point of the path and the end point of the online ride-hailing vehicle as the end point of the path; and a recommendation result for the online ride-hailing vehicle is determined according to the walking mileage of each walking path in the pick-up section walking path set and the walking mileage of each walking path in the alighting section walking path set. This technical solution solves the problems of low efficiency in online ride-hailing matching, poor user experience and low resource utilization. By performing site screening and route screening within the operating area of ​​driverless online ride-hailing vehicles, mixed calls of driverless online ride-hailing vehicles and manned online ride-hailing vehicles can be achieved, which is conducive to improving users' taxi experience, increasing the efficiency of online ride-hailing matching and avoiding waste of resources on the online ride-hailing dispatching platform.

[0041] Embodiment 2

[0042] Figure 2 This is a flow chart of a method for recommending online car-hailing services provided in Embodiment 2 of the present invention. This embodiment is based on the above embodiment and is refined. Figure 2 As shown, the method includes:

[0043] S210. If a ride-hailing request is received from a user terminal, determine the starting point and the end point of the online ride-hailing service based on the ride-hailing request.

[0044] S220: Determine whether the starting point and the end point of the online car-hailing service are both located within the target area.

[0045] In this solution, the online car-hailing dispatching platform can determine whether the starting point and the end point of the online car-hailing are located in the target area based on the area judgment method, the ray judgment method, etc. In a feasible solution, the online car-hailing dispatching platform can use polygons to represent the target area, obtain the coordinates of each vertex of the polygon in turn, use the starting point of the online car-hailing as the starting point of the ray, extend the ray along the preset direction, count the number of intersection points between the ray and the edge of the polygon, and determine whether the starting point of the online car-hailing is within the target area based on the odd or even number of intersection points. Similarly, the online car-hailing dispatching platform can determine whether the end point of the online car-hailing is within the target area based on the above method.

[0046] If both the starting point and the end point of the online-hailing vehicle are located within the target area, continue to execute S230. If at least one of the starting point and the end point of the online-hailing vehicle is not located within the target area, execute S280.

[0047] S230. Determine a set of boarding points from the driverless online taxi stations in the target area according to the starting point of the online taxi, and determine a set of alighting points from the driverless online taxi stations in the target area according to the destination of the online taxi.

[0048] The step of determining a set of pick-up points from driverless online car-hailing stations in a target area according to the online car-hailing starting point includes:

[0049] Taking the starting point of the online car-hailing vehicle as the center, obtaining driverless online car-hailing vehicle stations within a preset radius to form a set of boarding points;

[0050] The step of determining a set of drop-off points from driverless online car-hailing stations in a target area according to the online car-hailing destination includes:

[0051] Taking the online car-hailing terminal as the center, obtain the driverless online car-hailing stations within a preset radius to form a set of get-off points.

[0052] In this embodiment, the online car-hailing dispatching platform can set a radius range based on the distance statistics results of the user questionnaire, and use the radius range as a distance condition to filter the boarding point set and the alighting point set. The online car-hailing dispatching platform can also construct a multivariate linear regression model based on statistics to determine the impact of factors such as online car-hailing supply and demand, weather, temperature, user age, and user gender on travel volume, and then adjust the radius range according to the travel volume. Specifically, the online car-hailing dispatching platform can predict the travel volume based on factors such as user age, user gender, the time when the user orders a car, and the place where the car is ordered based on a multivariate linear regression model, and adaptively adjust the current radius range based on the mapping relationship between travel volume and radius range to adapt to environmental changes and provide users with personalized taxi services.

[0053] Optionally, after determining a set of pick-up points from driverless online ride-hailing stations in the target area according to the online ride-hailing starting point, and determining a set of drop-off points from driverless online ride-hailing stations in the target area according to the online ride-hailing destination, the method further includes:

[0054] Determine a provider of each pick-up point in the pick-up point set and a provider of each alighting point in the alighting point set;

[0055] Taking each boarding point in the boarding point set as a target boarding point in turn, and determining a target alighting point in the alighting point set that matches a provider of the target boarding point;

[0056] If there is no target drop-off point in the drop-off point set that matches the provider of the target pickup point, deleting the target pickup point from the pickup point set;

[0057] Taking each alighting point in the alighting point set as a target alighting point in turn, and determining a target boarding point in the boarding point set that matches a provider of the target alighting point;

[0058] If there is no target pick-up point in the pick-up point set that matches the provider of the target drop-off point, the target drop-off point is deleted from the drop-off point set.

[0059] Multiple driverless online ride-hailing service providers may be allowed to operate online ride-hailing services in the target area, and the management modes of driverless online ride-hailing services provided by each provider may differ. Therefore, it is necessary to screen the driverless online ride-hailing service stations in the pick-up point set and the alighting point set to ensure that both the pick-up point set and the alighting point set include driverless online ride-hailing service stations provided by the same provider, so as to realize the effective operation of driverless online ride-hailing services.

[0060] The online car-hailing dispatching platform can determine the providers of each pickup point in the pickup point set and the providers of each drop-off point in the drop-off point set based on the attribute information of the driverless online car-hailing station. Each pickup point in the pickup point set is taken as the target pickup point in turn, and a target drop-off point with the same provider as the target pickup point is determined in the drop-off point set. If there is no target drop-off point with the same provider as the target pickup point in the drop-off point set, the target pickup point is deleted from the pickup point set to ensure that each pickup point in the pickup point set can find a drop-off point with the same provider in the drop-off point set.

[0061] Each drop-off point in the drop-off point set is taken as the target drop-off point in turn, and a target pickup point with the same provider as the target drop-off point is determined in the pickup point set. If there is no target pickup point in the pickup point set that matches the provider of the target drop-off point, the target drop-off point is deleted from the drop-off point set to ensure that each drop-off point in the drop-off point set can find a pickup point with the same provider in the pickup point set.

[0062] This solution can be applied to situations where there are multiple driverless online ride-hailing service providers in the target area. While improving the user's taxi experience, it can also standardize the operation of driverless online ride-hailing services and avoid invalid orders.

[0063] S240: Determine whether the boarding point set and the alighting point set are both non-empty sets.

[0064] If both the boarding point set and the alighting point set are non-empty sets, S250 is executed. If at least one of the boarding point set and the alighting point set is an empty set, S280 is executed.

[0065] S250, taking the starting point of the online-hailing vehicle as the starting point of the path and each boarding point in the boarding point set as the end point of the path, determine a set of walking paths for the boarding section; and, taking each alighting point in the alighting point set as the starting point of the path and the end point of the online-hailing vehicle as the end point of the path, determine a set of walking paths for the alighting section.

[0066] S260: Determine whether the walking mileage of a walking path that does not exist in the walking path set for the boarding section is less than a pre-acquired mileage threshold, or whether the walking mileage of a walking path that does not exist in the walking path set for the alighting section is less than a pre-acquired mileage threshold.

[0067] It is understandable that the online car-hailing dispatching platform can obtain the historical order information of driverless online car-hailing vehicles in advance, extract the user's walking distance information from the historical order information, and set the mileage threshold based on the statistical results of the user's walking distance information.

[0068] If at least one walking path in the set of walking paths for boarding has a walking mileage less than a pre-acquired mileage threshold, it means that there is a walking path for boarding that satisfies the user's walking distance tolerance. If at least one walking path in the set of walking paths for disembarking has a walking mileage less than a pre-acquired mileage threshold, it means that there is a walking path for disembarking that satisfies the user's walking distance tolerance. If there are both walking paths for boarding that satisfy the user's walking distance tolerance and walking paths for disembarking that satisfy the user's walking distance tolerance, the online car-hailing dispatching platform can determine that the type of online car-hailing in the online car-hailing recommendation results is an unmanned online car-hailing, or can determine that the types of online car-hailing in the online car-hailing recommendation results include both unmanned online car-hailing and manned online car-hailing.

[0069] There is no walking path in the set of walking paths for the boarding section whose walking mileage is less than the pre-acquired mileage threshold, indicating that there is no walking path for boarding that satisfies the user's walking distance tolerance. There is no walking path in the set of walking paths for the alighting section whose walking mileage is less than the pre-acquired mileage threshold, indicating that there is no walking path for alighting that satisfies the user's walking distance tolerance. The online car-hailing dispatching platform can determine that the online car-hailing type in the online car-hailing recommendation results is a manned online car-hailing.

[0070] S270. Determine that the types of online-hailing vehicles in the online-hailing vehicle recommendation results include driverless online-hailing vehicles and manned online-hailing vehicles.

[0071] S280: Determine that the type of online-hailing vehicle in the online-hailing vehicle recommendation result is a manned online-hailing vehicle.

[0072] On the basis of the above scheme, after determining the online car-hailing recommendation result, the method further includes:

[0073] If the types of online-hailing vehicles in the online-hailing vehicle recommendation result include driverless online-hailing vehicles and manned online-hailing vehicles, feeding back the online-hailing vehicle recommendation result to the user terminal;

[0074] The type of online car-hailing vehicle determined by the user terminal is obtained, and a group of online car-hailing vehicles matching the type of online car-hailing vehicle is called.

[0075] After the online car-hailing dispatching platform determines the online car-hailing recommendation results, if the online car-hailing types in the online car-hailing recommendation results include both unmanned online car-hailing and manned online car-hailing, the online car-hailing dispatching platform can feedback the online car-hailing recommendation results to the user for the user to choose. According to the online car-hailing type determined by the user, the online car-hailing dispatching platform can call the online car-hailing group corresponding to the online car-hailing type to provide transportation services for the user.

[0076] When the types of online ride-hailing vehicles include both driverless and manned ones, this solution can call the online ride-hailing vehicle group based on the type of online ride-hailing vehicle selected by the user, fully respecting the user's preferences. While bringing a good car-using experience to the user, it is helpful to narrow the calling scope and save dispatch resources.

[0077] In a preferred solution, if the historical orders of driverless online ride-hailing vehicles are sufficient, the online ride-hailing dispatching platform can obtain the user's evaluation information on the historical orders in advance, and extract the user's rating information on the driverless online ride-hailing stations from the evaluation information. Based on the user's rating information on the driverless online ride-hailing stations, the similarity between every two users is calculated. Specifically, the calculation formula for user similarity can be expressed as:

[0078] Among them, u and v represent user indexes, I uvrepresents the set of driverless online car-hailing stations that have been evaluated by both user u and user v, i represents the index of the driverless online car-hailing station, r u,i represents the rating of user u on driverless online car-hailing station i, r v,i represents the rating of user v on driverless online car-hailing station i, I u represents the set of driverless online ride-hailing stations evaluated by user u, I v Represents the set of driverless online car-hailing stations evaluated by user v.

[0079] After receiving the ride-hailing request from the user terminal, the online ride-hailing dispatching platform can determine the target user based on the user identifier in the ride-hailing request, and select a preset number of reference users with the highest similarity to the target user from the historical users. Based on the similarity between the target user and each reference user, and the rating information of each reference user on the driverless online ride-hailing station, the target user's rating for each pick-up point in the pick-up point set and the rating for each drop-off point in the drop-off point set are predicted. Specifically, the target user's rating prediction result for the driverless online ride-hailing station can be expressed as:

[0080] Where u represents the target user ID, N(u) represents the reference user set consisting of the K reference users with the highest similarity to user u, v represents the reference user index, j represents the driverless online car-hailing station index, sim(u,v) represents the similarity between the target user u and the reference user v, and r v,j represents the rating of the reference user v on the driverless online car-hailing station j, represents the target user u’s rating prediction result for the driverless online car-hailing station j. It should be noted that if the reference user v has not evaluated the driverless online car-hailing station j, the online car-hailing dispatching platform can use r v,j Set to a preset value, such as 0.

[0081] The online car-hailing dispatching platform can determine the target pickup point based on the walking distance of each walking path in the pickup segment walking path set and the target user's rating of each pickup point in the pickup point set. Similarly, the online car-hailing dispatching platform can determine the target drop-off point based on the walking distance of each walking path in the drop-off segment walking path set and the target user's rating of each drop-off point in the drop-off point set.

[0082] The target boarding point and target alighting point determined in the above manner can be more in line with user habits and facilitate user travel.

[0083] The technical solution of the embodiment of the present invention is as follows: when receiving a ride-hailing request from a user terminal, the starting point and the end point of the online ride-hailing vehicle are determined according to the ride-hailing request; if the starting point and the end point of the online ride-hailing vehicle are both located in the target area, a set of pick-up points are determined from the unmanned online ride-hailing vehicle stations in the target area according to the starting point of the online ride-hailing vehicle, and a set of alighting points are determined from the unmanned online ride-hailing vehicle stations in the target area according to the end point of the online ride-hailing vehicle; if the pick-up point set and the alighting point set are both non-empty sets, a set of walking paths for the pick-up section is determined with the starting point of the online ride-hailing vehicle as the starting point of the path and each pick-up point in the pick-up point set as the end point of the path, and a set of walking paths for the alighting section is determined with each alighting point in the alighting point set as the starting point of the path and the end point of the online ride-hailing vehicle as the end point of the path; and a recommendation result for the online ride-hailing vehicle is determined according to the walking mileage of each walking path in the pick-up section walking path set and the walking mileage of each walking path in the alighting section walking path set. This technical solution solves the problems of low efficiency in online ride-hailing matching, poor user experience and low resource utilization. By performing site screening and route screening within the operating area of ​​driverless online ride-hailing vehicles, mixed calls of driverless online ride-hailing vehicles and manned online ride-hailing vehicles can be achieved, which is conducive to improving users' taxi experience, increasing the efficiency of online ride-hailing matching and avoiding waste of resources on the online ride-hailing dispatching platform.

[0084] Embodiment 3

[0085] Figure 3 This is a schematic diagram of the structure of a network car-hailing recommendation device provided in Embodiment 3 of the present invention. The device is configured on a network car-hailing dispatching platform, such as Figure 3 As shown, the device comprises:

[0086] The starting and ending point determination module 310 is used to determine the starting point and the ending point of the online car-hailing service according to the car-hailing request if a car-hailing request is received from a user terminal;

[0087] The point set determination module 320 is used to determine a pickup point set from the driverless online car-hailing stations in the target area according to the online car-hailing starting point if the online car-hailing starting point and the online car-hailing terminal are both located in the target area, and to determine a drop-off point set from the driverless online car-hailing stations in the target area according to the online car-hailing terminal; wherein the target area is the operating area of ​​the driverless online car-hailing;

[0088] The path set determination module 330 is used for determining a walking path set for the boarding section by taking the starting point of the online car-hailing vehicle as the path starting point and each boarding point in the boarding point set as the path end point if both the boarding point set and the boarding point set are non-empty sets, and determining a walking path set for the boarding section by taking each boarding point in the boarding point set as the path starting point and the boarding point of the online car-hailing vehicle as the path end point;

[0089] The first recommendation result determination module 340 is used to determine the online car-hailing recommendation result based on the walking mileage of each walking path in the boarding section walking path set and the walking mileage of each walking path in the alighting section walking path set; wherein the online car-hailing recommendation result includes the type of online car-hailing, and the type of online car-hailing includes manned online car-hailing and unmanned online car-hailing.

[0090] In this solution, the point set determination module 320 is specifically used to:

[0091] Taking the starting point of the online car-hailing vehicle as the center, obtaining driverless online car-hailing vehicle stations within a preset radius to form a set of boarding points;

[0092] The step of determining a set of drop-off points from driverless online car-hailing stations in a target area according to the online car-hailing destination includes:

[0093] Taking the online car-hailing terminal as the center, obtain the driverless online car-hailing stations within a preset radius to form a set of get-off points.

[0094] In a feasible solution, the first recommendation result determination module 340 is specifically used to:

[0095] If the walking mileage of at least one walking path in the set of walking paths for the boarding section is less than the pre-acquired mileage threshold, and the walking mileage of at least one walking path in the set of walking paths for the alighting section is less than the pre-acquired mileage threshold, it is determined that the types of online-hailing vehicles in the online-hailing vehicle recommendation results include driverless online-hailing vehicles and manned online-hailing vehicles;

[0096] If there is no walking path in the walking path set of the boarding section and the walking mileage is less than the pre-acquired mileage threshold, or there is no walking path in the walking path set of the alighting section and the walking mileage is less than the pre-acquired mileage threshold, then the type of online car-hailing vehicle in the online car-hailing vehicle recommendation result is determined to be a manned online car-hailing vehicle.

[0097] In this embodiment, the device further includes:

[0098] A second recommendation result determination module is used for, after determining the starting point and the end point of the online car-hailing vehicle according to the car-hailing request, if at least one of the starting point and the end point of the online car-hailing vehicle is not located in the target area, determining the type of the online car-hailing vehicle in the online car-hailing vehicle recommendation result as a manned online car-hailing vehicle;

[0099] The third recommendation result determination module is used to determine a set of pick-up points from unmanned online car-hailing stations in a target area according to the starting point of the online car-hailing vehicle, and determine a set of alighting points from unmanned online car-hailing stations in the target area according to the destination of the online car-hailing vehicle. If at least one of the pick-up point set and the alighting point set is an empty set, then the type of the online car-hailing vehicle in the online car-hailing vehicle recommendation result is determined to be a manned online car-hailing vehicle.

[0100] In a feasible solution, the device further includes a site filtering module, which is used to:

[0101] After determining a set of pick-up points from driverless online ride-hailing stations in a target area according to the online ride-hailing starting point, and determining a set of drop-off points from driverless online ride-hailing stations in the target area according to the online ride-hailing destination, determining a provider of each pick-up point in the set of pick-up points and a provider of each drop-off point in the set of drop-off points;

[0102] Taking each boarding point in the boarding point set as a target boarding point in turn, and determining a target alighting point in the alighting point set that matches a provider of the target boarding point;

[0103] If there is no target drop-off point in the drop-off point set that matches the provider of the target pickup point, deleting the target pickup point from the pickup point set;

[0104] Taking each alighting point in the alighting point set as a target alighting point in turn, and determining a target boarding point in the boarding point set that matches a provider of the target alighting point;

[0105] If there is no target pick-up point in the pick-up point set that matches the provider of the target drop-off point, the target drop-off point is deleted from the drop-off point set.

[0106] On the basis of the above solution, the device further includes an online car-hailing calling module, which is used to:

[0107] After determining the online car-hailing recommendation result, if the online car-hailing types in the online car-hailing recommendation result include driverless online car-hailing vehicles and manned online car-hailing vehicles, feeding back the online car-hailing recommendation result to the user terminal;

[0108] The type of online car-hailing vehicle determined by the user terminal is obtained, and a group of online car-hailing vehicles matching the type of online car-hailing vehicle is called.

[0109] The online car-hailing recommendation device provided in the embodiment of the present invention can execute the online car-hailing recommendation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0110] Embodiment 4

[0111] Figure 4 A schematic diagram of an electronic device 410 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0112] like Figure 4 As shown, the electronic device 410 includes at least one processor 411, and a memory connected to the at least one processor 411 in communication, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 to the random access memory (RAM) 413. In the RAM 413, various programs and data required for the operation of the electronic device 410 can also be stored. The processor 411, the ROM 412, and the RAM 413 are connected to each other via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0113] Multiple components in the electronic device 410 are connected to the I / O interface 415, including: an input unit 416, such as a keyboard, a mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a disk, an optical disk, etc.; and a communication unit 419, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 419 allows the electronic device 410 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0114] Processor 411 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. Processor 411 executes the various methods and processes described above, such as a recommendation method for online car-hailing.

[0115] In some embodiments, the method for recommending online ride-hailing vehicles may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 410 via the ROM 412 and / or the communication unit 419. When the computer program is loaded into the RAM 413 and executed by the processor 411, one or more steps of the method for recommending online ride-hailing vehicles described above may be performed. Alternatively, in other embodiments, the processor 411 may be configured to execute the method for recommending online ride-hailing vehicles in any other appropriate manner (e.g., by means of firmware).

[0116] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0117] The computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable online car-hailing recommendation device, so that when the computer program is executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0118] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0120] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0121] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0122] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0123] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for recommending online car-hailing services, characterized in that: The method is executed by an online car-hailing dispatching platform, and the method includes: If a ride-hailing request is received from a user terminal, determining the starting point and the end point of the online ride-hailing service according to the ride-hailing request; If the online car-hailing starting point and the online car-hailing end point are both located in the target area, a set of pick-up points is determined from the driverless online car-hailing stations in the target area according to the online car-hailing starting point, and a set of drop-off points is determined from the driverless online car-hailing stations in the target area according to the online car-hailing end point; wherein the target area is the operating area of ​​the driverless online car-hailing; If both the pickup point set and the alighting point set are non-empty sets, then the starting point of the online car-hailing vehicle is taken as the path starting point, and each pickup point in the pickup point set is taken as the path end point to determine the pickup segment walking path set, and, each alighting point in the alighting point set is taken as the path starting point, and the online car-hailing vehicle end point is taken as the path end point to determine the alighting segment walking path set; The online car-hailing recommendation result is determined based on the walking mileage of each walking path in the boarding section walking path set and the walking mileage of each walking path in the alighting section walking path set; wherein the online car-hailing recommendation result includes the type of online car-hailing, and the type of online car-hailing includes manned online car-hailing and unmanned online car-hailing.

2. The method according to claim 1, characterized in that The step of determining a set of pick-up points from driverless online car-hailing stations in a target area according to the online car-hailing starting point includes: Taking the starting point of the online car-hailing vehicle as the center, obtaining driverless online car-hailing vehicle stations within a preset radius to form a set of boarding points; The step of determining a set of drop-off points from driverless online car-hailing stations in a target area according to the online car-hailing destination includes: Taking the online car-hailing terminal as the center, obtain the driverless online car-hailing stations within a preset radius to form a set of get-off points.

3. The method according to claim 1, characterized in that The determining of the online car-hailing recommendation result according to the walking mileage of each walking path in the set of walking paths for the boarding section and the walking mileage of each walking path in the set of walking paths for the alighting section includes: If the walking mileage of at least one walking path in the set of walking paths for the boarding section is less than the pre-acquired mileage threshold, and the walking mileage of at least one walking path in the set of walking paths for the alighting section is less than the pre-acquired mileage threshold, it is determined that the types of online-hailing vehicles in the online-hailing vehicle recommendation results include driverless online-hailing vehicles and manned online-hailing vehicles; If there is no walking path in the walking path set of the boarding section and the walking mileage is less than the pre-acquired mileage threshold, or there is no walking path in the walking path set of the alighting section and the walking mileage is less than the pre-acquired mileage threshold, then the type of online car-hailing vehicle in the online car-hailing vehicle recommendation result is determined to be a manned online car-hailing vehicle.

4. The method according to claim 1, characterized in that: After determining the starting point and the end point of the online car-hailing service according to the car-hailing request, the method further includes: If at least one of the online car-hailing starting point and the online car-hailing end point is not located in the target area, determining that the online car-hailing type in the online car-hailing recommendation result is a manned online car-hailing type; After determining a set of pick-up points from driverless online ride-hailing stations in the target area according to the online ride-hailing starting point, and determining a set of drop-off points from driverless online ride-hailing stations in the target area according to the online ride-hailing destination, the method further includes: If at least one of the boarding point set and the alighting point set is an empty set, the type of online-hailing car in the online-hailing car recommendation result is determined to be a manned online-hailing car.

5. The method according to claim 1, characterized in that After determining a set of pick-up points from driverless online ride-hailing stations in the target area according to the online ride-hailing starting point, and determining a set of drop-off points from driverless online ride-hailing stations in the target area according to the online ride-hailing destination, the method further includes: Determine a provider of each pick-up point in the pick-up point set and a provider of each alighting point in the alighting point set; Taking each boarding point in the boarding point set as a target boarding point in turn, and determining a target alighting point in the alighting point set that matches a provider of the target boarding point; If there is no target drop-off point in the drop-off point set that matches the provider of the target pickup point, deleting the target pickup point from the pickup point set; Taking each alighting point in the alighting point set as a target alighting point in turn, and determining a target boarding point in the boarding point set that matches a provider of the target alighting point; If there is no target pick-up point in the pick-up point set that matches the provider of the target drop-off point, the target drop-off point is deleted from the drop-off point set.

6. The method according to claim 3, characterized in that After determining the online car-hailing recommendation result, the method further includes: If the types of online-hailing vehicles in the online-hailing vehicle recommendation result include driverless online-hailing vehicles and manned online-hailing vehicles, feeding back the online-hailing vehicle recommendation result to the user terminal; The type of online car-hailing vehicle determined by the user terminal is obtained, and a group of online car-hailing vehicles matching the type of online car-hailing vehicle is called.

7. A device for recommending online car-hailing services, characterized in that: The device is configured on an online car-hailing dispatching platform, and includes: A starting and ending point determination module, for determining the starting point and the ending point of the online car-hailing service according to the car-hailing request if a car-hailing request is received from a user terminal; A point set determination module, for determining a pickup point set from driverless online ride-hailing stations in the target area according to the online ride-hailing starting point, and determining a drop-off point set from driverless online ride-hailing stations in the target area according to the online ride-hailing terminal if both the online ride-hailing starting point and the online ride-hailing terminal are located in a target area; wherein the target area is an operating area of ​​driverless online ride-hailing stations; A path set determination module, for determining a set of walking paths for the boarding section by taking the starting point of the online car-hailing vehicle as the path starting point and each boarding point in the boarding point set as the path end point, if both the boarding point set and the boarding point set are non-empty sets, and for determining a set of walking paths for the boarding section by taking each boarding point in the boarding point set as the path starting point and the boarding point of the online car-hailing vehicle as the path end point; The first recommendation result determination module is used to determine the online car-hailing recommendation result based on the walking mileage of each walking path in the boarding section walking path set and the walking mileage of each walking path in the alighting section walking path set; wherein the online car-hailing recommendation result includes the type of online car-hailing, and the type of online car-hailing includes manned online car-hailing and unmanned online car-hailing.

8. An electronic device, characterized in that: The electronic device comprises: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the online car-hailing recommendation method described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the online car-hailing recommendation method described in any one of claims 1-6 when executed.

10. A computer program product, comprising a computer program, which, when executed by a processor, implements the online car-hailing recommendation method according to any one of claims 1-6.

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