Task processing method and device, electronic equipment and computer readable storage medium

Abstract

The embodiment of the invention discloses a task processing method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining task information of a target task, and determining a task execution attribute of an automatic driving vehicle according to a task starting point and a task terminal point in the task information, and in response to the fact that the task execution attribute of the autonomous vehicle is executable, displaying an autonomous driving option and a manual driving option on the vehicle using request page. Therefore, by displaying the automatic driving option on the vehicle using request page when the automatic driving vehicle can execute the task, the travel option can be adaptively recommended to the user.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a task processing method, device, electronic device and computer-readable storage medium. Background Art

[0002] With the development of autonomous driving technology, applying autonomous driving vehicles to online ride-hailing scenarios is of great significance to the development of online ride-hailing services and further improving the convenience of people's travel.

[0003] However, due to the limited autonomous driving capacity currently in operation, it is still unable to provide users with stable expected travel services. Therefore, it is necessary to adaptively recommend travel options to users while meeting the expectations of users and passengers. Summary of the invention

[0004] In view of this, an object of embodiments of the present invention is to provide a task processing method, device, electronic device and computer-readable storage medium to adaptively recommend travel options to users.

[0005] In a first aspect, an embodiment of the present invention is to provide a task processing method, the method comprising:

[0006] Obtaining task information of the target task, wherein the task information includes a task start point and a task end point;

[0007] Determining a task execution attribute of the autonomous driving vehicle according to the task starting point and the task end point;

[0008] In response to the task execution attribute of the autonomous driving vehicle being executable, an autonomous driving option and a manual driving option are displayed on the vehicle request page.

[0009] Furthermore, determining the task execution attribute of the autonomous driving vehicle according to the task starting point and the task end point includes:

[0010] Performing a path check according to the task starting point and the task end point;

[0011] Performing site matching on the task starting point and the task end point respectively;

[0012] In response to the results of the route verification and the site matching satisfying preset conditions, it is determined that the task execution attribute of the autonomous driving vehicle is executable.

[0013] Furthermore, determining the task execution attribute of the autonomous driving vehicle according to the task starting point and the task end point also includes:

[0014] Determining whether the task start point and the task end point are within the autonomous driving restriction domain;

[0015] In response to the result of the route verification and the site matching satisfying a preset condition, determining that the task execution attribute of the autonomous driving vehicle is executable includes:

[0016] In response to the fact that both the task start point and the task end point are within the autonomous driving restriction domain and the results of the path verification and the site matching meet preset conditions, it is determined that the task execution attribute of the autonomous driving vehicle is executable.

[0017] Furthermore, the preset condition is that there is a valid path between the task starting point and the task end point, and there are corresponding available sites at both the task starting point and the task end point.

[0018] Further, the performing of the path verification according to the task starting point and the task end point includes:

[0019] Perform path planning according to the task starting point and the task end point, and determine the path planning result;

[0020] A path verification is performed based on the existence status of a valid path in the path planning result, where the valid path is a path on which the autonomous driving vehicle can travel.

[0021] Furthermore, the performing site matching on the task starting point and the task end point respectively includes:

[0022] Site matching is performed according to the existence status of available sites within a preset range respectively corresponding to the task starting point and the task end point, and the available sites are autonomous driving sites.

[0023] Furthermore, the method further comprises:

[0024] In response to the task execution attribute being unexecutable, a manual driving option is displayed on the vehicle request page.

[0025] Furthermore, performing site matching according to the existence status of available sites within a preset range corresponding to the task starting point and the task end point respectively includes:

[0026] Determine a set of candidate sites within a preset range corresponding to the starting point of the task;

[0027] Determine an available site within a preset range corresponding to the task starting point according to the arrival attribute of each candidate site in the candidate site set, wherein the arrival attribute includes the arrival distance between the candidate site and the task starting point and / or the arrival difficulty of the autonomous driving vehicle to reach the candidate site;

[0028] Site matching is performed according to the existence status of available sites within a preset range corresponding to the task starting point.

[0029] Furthermore, performing site matching according to the existence status of available sites within a preset range corresponding to the task starting point and the task end point respectively includes:

[0030] Determine an initial range corresponding to the starting point of the task;

[0031] The initial range is adjusted according to the location attribute of the task starting point and / or the site matching result within the initial range to determine a preset range corresponding to the task starting point;

[0032] Site matching is performed according to the existence status of available sites within a preset range corresponding to the task starting point.

[0033] In a second aspect, an embodiment of the present invention is to provide a task processing device, the device comprising:

[0034] An information acquisition unit, used to acquire task information of a target task, wherein the task information includes a task start point and a task end point;

[0035] An information processing unit, configured to determine a task execution attribute of the autonomous driving vehicle according to the task starting point and the task end point;

[0036] The option recommendation unit is used to display the autonomous driving option and the manual driving option on the vehicle request page in response to the task execution attribute of the autonomous driving vehicle being executable.

[0037] In a third aspect, an embodiment of the present invention aims to provide a computer program product, wherein the computer program product comprises a computer program / instructions, and when the computer program / instructions are executed by a processor, the method as described in any one of the above items is implemented.

[0038] In a fourth aspect, an embodiment of the present invention aims to provide an electronic device, comprising a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement a method as described in any one of the above items.

[0039] In a fifth aspect, an embodiment of the present invention aims to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps as described in any one of the above items are implemented.

[0040] The technical solution of the embodiment of the present invention obtains the task information of the target task, determines the task execution attribute of the autonomous driving vehicle according to the task starting point and task end point in the task information, and displays the autonomous driving option and the manual driving option on the vehicle request page in response to the task execution attribute of the autonomous driving vehicle being executable. In this way, the autonomous driving option can be displayed on the vehicle request page when the autonomous driving vehicle can execute the task, thereby adaptively recommending travel options to users. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0042] Figure 1 is a schematic diagram of a task processing system according to an embodiment of the present invention;

[0043] Figure 2 is a flowchart of a task processing method according to an embodiment of the present invention;

[0044] Figure 3 is a flow chart of determining task execution attributes according to an embodiment of the present invention;

[0045] Figure 4 is a schematic diagram of a task processing process of an embodiment of the present invention;

[0046] Figure 5 is a schematic diagram of a car request page according to an embodiment of the present invention;

[0047] Figure 6 is another schematic diagram of a car request page according to an embodiment of the present invention;

[0048] Figure 7 is a schematic diagram of a task processing device according to an embodiment of the present invention;

[0049] Figure 8 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The present application is described below based on embodiments, but the present application is not limited to these embodiments. In the detailed description of the present application below, some specific details are described in detail. It is possible for those skilled in the art to fully understand the present application without the description of these details. In order to avoid confusing the essence of the present application, known methods, processes, flows, components and circuits are not described in detail.

[0051] In addition, persons of ordinary skill in the art will appreciate that the drawings provided herein are for illustration purposes and are not necessarily drawn to scale.

[0052] Unless the context clearly requires otherwise, the words "include", "comprising" and similar words throughout the application should be interpreted as including rather than exclusive or exhaustive; that is, the meaning is "including but not limited to".

[0053] In the description of this application, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" is two or more.

[0054] The solutions described in this specification and in the examples, if they involve the processing of personal information, will be processed on the premise of having a legal basis (such as obtaining the consent of the subject of personal information, or being necessary for the performance of a contract, etc.), and will only be processed within the scope of regulations or agreements. If a user refuses to process personal information other than the necessary information for basic functions, it will not affect the user's use of basic functions.

[0055] Figure 1 Schematic diagram of a task processing system according to an embodiment of the present invention. Figure 1 As shown, the task system of this embodiment includes a first terminal 10, a server 20 and a second terminal 30. The first terminal 10 is a user terminal that initiates a task, which can be a smart phone, a computer, a wearable device, etc. The second terminal 30 is a terminal device corresponding to the vehicle that performs the task, which can be a terminal device on an autonomous driving vehicle, such as a central control device, etc., or a terminal device on a manually driven vehicle or a terminal device corresponding to the driver (such as a smart phone, etc.). The first terminal 10 and the second terminal 30 communicate with the server 20 via a network connection. The server 20 can be a single server, or a server cluster consisting of multiple servers, etc.

[0056] When processing a task, the user sends a car request to the server through the client, applet or other means on the first terminal. After receiving the user's car request, the server recommends available travel options to the user based on the car request, including but not limited to manually driven express, carpooling, taxi, automatic driving and other options, so as to facilitate the user to select travel options. After the user selects at least one travel option, the server dispatches an order to the second terminal corresponding to the selected travel option according to the user's selection, and after the second terminal accepts the order, the second terminal that accepts the order executes the task, so as to facilitate the user's travel.

[0057] However, due to the small amount of autonomous driving capacity currently in operation, it is still unable to provide users with stable expected travel services. Therefore, it is necessary to adaptively recommend travel options to users while meeting their expectations for using the vehicle. In view of this, an embodiment of the present invention aims to provide a task processing method to adaptively recommend travel options to users.

[0058] Figure 2 FIG. 1 is a flowchart of a task processing method according to an embodiment of the present invention. Figure 2 As shown, the task processing method in this embodiment includes the following steps.

[0059] In step S210, task information of the target task is obtained, and the task information includes a task start point and a task end point.

[0060] In this embodiment, the target task is a pending task corresponding to a task request initiated by a user. The task starting point is the starting point entered by the user when initiating the task request or a point of interest around the starting point recommended to the user based on the starting point entered by the user, for example, a point of interest such as a bus stop within 30 meters of the user. The task end point is the end point entered by the user when initiating the task request or a point of interest around the end point recommended to the user based on the end point entered by the user.

[0061] In step S220, the task execution attributes of the autonomous driving vehicle are determined based on the task start point and the task end point.

[0062] In this embodiment, the task execution attribute of the autonomous driving vehicle is used to characterize the processing capability of the autonomous driving vehicle for the target task. When the task execution attribute characterizes that the autonomous driving vehicle has the processing capability to process the target task, the task execution attribute of the autonomous driving vehicle is determined to be executable. When the task execution attribute characterizes that the autonomous driving vehicle does not have the processing capability to process the target task, the task execution attribute of the autonomous driving vehicle is determined to be non-executable.

[0063] Optionally, because different users may have different levels of acceptance and respect for autonomous vehicles, in this embodiment, before determining the task execution attributes of the autonomous vehicle based on the task starting point and task end point, the users are first screened to select target users with higher acceptance and respect for the autonomous vehicle, and then the task execution attributes of the autonomous vehicle are determined based on the task starting point and task end point to recommend the autonomous vehicle to the target users.

[0064] Among them, since the user's acceptance and respect for the autonomous driving vehicle can be represented by the user's attribute information, the attribute information may include the number of types of vehicle options that appear in the historical vehicle use records, the number of times different vehicle options are used, the replacement cycle of vehicle options, the user's credit level on the vehicle use service platform, etc. In addition, the more the number of types of vehicle options that appear in the historical vehicle use records in the user's attribute information, the more times different vehicle options are used, the shorter the replacement cycle of vehicle options, and the higher the user's credit level on the vehicle use service platform, the greater the probability that the corresponding user is the target user.

[0065] Furthermore, considering that the user's attribute information has a unique correspondence with the user ID (i.e., the ID registered by the user on the car service platform, such as the user name), in this embodiment, when obtaining the task information, the task information also includes the user ID. When determining the task execution attributes of the autonomous driving vehicle based on the task start point and the task end point, in this embodiment, the user attribute information of the corresponding user is first determined based on the user ID, and then whether the user is the target user is determined based on the user attribute information.

[0066] Optionally, in this embodiment, a prediction model can be pre-trained based on the car usage data of different users or the same user in different time periods, and the user's attribute information can be input into the trained prediction model for matching to determine whether the corresponding user is the target user; or, matching rules can be pre-set to determine whether the corresponding user belongs to the target user by judging whether the user's attribute information meets the matching rules. For example, assuming that the matching condition is that the number of types of car usage options appearing in the user's historical car usage record reaches half of the number of car usage types provided by the car usage service platform, the number of car usage types provided by the car usage service platform is 6, the number of types of car usage options appearing in user A's historical car usage record is 4, and the number of types of car usage options appearing in user B's historical car usage record is 1, it can be determined that user A is the target user and user B is not the target user.

[0067] Furthermore, the task execution attributes in this embodiment are determined based on relevant attribute information of the task starting point and the task end point, so as to determine whether the autonomous driving vehicle has the processing capability to process the target task through the relevant attribute information of the task starting point and the task end point.

[0068] Optionally, the attribute information related to the task start point and the task end point in this embodiment includes whether there is a valid path between the task start point and the task end point, and whether there are corresponding available sites between the task start point and the task end point. Figure 3 The method shown in determines the task execution attributes of the autonomous driving vehicle, and specifically includes the following steps.

[0069] In step S310, a path check is performed based on the task starting point and the task end point.

[0070] Since the normal driving of autonomous vehicles has specific requirements for the road environment, autonomous vehicles cannot be used on all roads that can be driven by manually driven vehicles, or there are sections of road that can be driven by manually driven vehicles but not autonomous vehicles. Therefore, the driving of autonomous vehicles needs to meet certain specified conditions, such as driving in the restricted area where autonomous driving can be driven, driving along the designated sections of road where autonomous driving can be driven, and stopping at designated autonomous driving stations.

[0071] To ensure that the autonomous driving option is available, this embodiment will use a route verification to determine whether there is a valid path between the mission start point and the mission end point. A valid path is a path that the autonomous driving vehicle can drive, or a path with a road complexity lower than the preset complexity among the paths that the autonomous driving vehicle can drive. The road complexity is related to the road parameters that affect the driving of the autonomous driving vehicle, such as the number of intersections along the way and the detour distance.

[0072] Optionally, in order to increase the number of autonomous driving vehicles put into use and meet the travel needs of more users, the effective path in this embodiment is a path that the autonomous driving vehicle can drive. In this embodiment, when performing a path verification based on the task starting point and the task end point, a path is first planned based on the task starting point and the task end point to determine the path planning result; then a path verification is performed based on the existence status of the effective path in the path planning result to determine whether there is a path between the task starting point and the task end point that the autonomous driving vehicle can drive.

[0073] In step S320, site matching is performed on the task start point and the task end point respectively.

[0074] Considering that the autonomous driving vehicle needs to stop at the designated autonomous driving station after being put into operation to facilitate users to get on and off the vehicle, in this embodiment, the station matching will be performed for the task starting point and the task end point respectively.

[0075] Optionally, in this embodiment, site matching is performed based on the existence status of available sites within a preset range (e.g., 50 meters) corresponding to the task starting point and the task end point, respectively, to determine whether there are available sites within the preset range corresponding to the task starting point and the task end point. Among them, the available sites are pre-set autonomous driving sites that allow autonomous driving vehicles to stop, and the available sites within the preset range of the task starting point can be used as the user's actual boarding point, and the available sites within the preset range of the task end point can be used as the user's actual alighting point. Therefore, in this embodiment, the available sites within the preset range of the task starting point and the task end point are determined by site matching, so that while meeting the travel needs of users, the use of autonomous driving vehicles can be facilitated, which is conducive to improving the task processing efficiency of autonomous driving vehicles.

[0076] Furthermore, in this embodiment, the available stations within the preset range corresponding to the mission start point and the mission end point may be all the autonomous driving stations within the preset range, or may be some autonomous driving stations determined after screening all the autonomous driving stations within the preset range. At the same time, in this embodiment, the same or different methods may be used to determine the available stations within the preset range corresponding to the mission start point and the mission end point, respectively.

[0077] Optionally, in order to enhance the user experience of the autonomous driving option, the same method is used in this embodiment to determine the available sites within the preset range corresponding to the task starting point and the task end point respectively. The available sites within the preset range corresponding to the task starting point and the task end point are all partial autonomous driving sites determined after screening all autonomous driving sites within the corresponding preset range. The screening conditions can be determined according to the arrival attributes of each autonomous driving site. The arrival attributes include the arrival attributes on the user side and / or the arrival attributes on the autonomous driving vehicle side. The arrival attributes on the user side include walking distance, number of uses in user history records, etc. The arrival attributes on the autonomous driving vehicle side include the difficulty of the autonomous driving vehicle reaching the candidate site, etc.

[0078] Specifically, when performing site matching according to the existence status of available sites within the preset range corresponding to the task starting point and the task end point, taking the site matching of the task starting point as an example, first determine the candidate site set within the preset range corresponding to the task starting point, then determine the available sites within the preset range corresponding to the task starting point according to the arrival attributes of each candidate site in the candidate site set, and finally, perform site matching according to the existence status of available sites within the preset range corresponding to the task starting point. Among them, the candidate site set includes all autonomous driving sites within the preset range. The arrival attributes of the candidate site include representing the arrival distance between the candidate site and the task starting point and / or the arrival difficulty of the autonomous driving vehicle to reach the candidate site. The arrival distance can be the navigation distance from the task starting point to the candidate site. The arrival difficulty can be determined according to the road conditions of the section where the candidate site is located (such as congestion coefficient, road flatness, etc.), the number of road connections, and other factors that affect the autonomous driving vehicle to reach the candidate site. The worse the road conditions and the more road connections, the greater the corresponding arrival difficulty.

[0079] Furthermore, when determining the available sites within a preset range corresponding to the task starting point based on the arrival attributes of each candidate site in the candidate site set, in this embodiment, at least one candidate site in the candidate site set whose arrival distance is less than a predetermined threshold and / or whose arrival difficulty is less than a predetermined difficulty threshold can be determined as an available site within the corresponding preset range; the candidate site in the candidate site set with the shortest arrival distance or the shortest arrival difficulty can also be determined as an available site within the corresponding preset range.

[0080] Therefore, in this embodiment, by screening candidate sites within a preset range based on the arrival attributes to determine available sites within the preset range, and performing site matching according to the existence status of the available sites determined by the screening, the site matching process can be optimized, the quality of the self-driving options can be improved, and the user's use needs for high-quality self-driving travel options can be met. In addition, in this embodiment, the available sites determined based on the above process can be recommended to the user in the future, which can facilitate the user to select an available site as a boarding point or alighting point, and then control the self-driving vehicle to perform the task according to the boarding point or alighting point selected by the user, reducing the operation process of re-determining the boarding point or alighting point, which is conducive to improving the task execution efficiency of the self-driving vehicle.

[0081] Optionally, in order to better recommend autonomous driving travel options to users, the preset ranges corresponding to the task start point and the task end point in this embodiment may be a fixed-size area range pre-set based on experience, or may be an area range dynamically set based on actual usage scenarios. At the same time, the preset range corresponding to the task start point and the preset range corresponding to the task end point in this embodiment may be determined by the same method or by different methods.

[0082] Further, in this embodiment, the same method is used to determine the preset range corresponding to the task starting point and the task end point. Taking the determination of the preset range corresponding to the task starting point as an example, in an optional implementation method, in this embodiment, when performing site matching according to the existence status of the available sites within the preset range corresponding to the task starting point and the task end point, the initial range corresponding to the task starting point can be determined first; then the initial range is adjusted according to the location attribute of the task starting point to determine the preset range corresponding to the task starting point; finally, the site matching is performed according to the existence status of the available sites within the preset range. Among them, the initial range is a regional range pre-set according to experience. The location attribute can be determined according to relevant parameters such as the type, heat value, and frequency of use of the task starting point, and the adjustment method of the initial range includes expanding the initial range and reducing the initial range. Therefore, by selecting the matching preset range according to the location attributes corresponding to the task starting point and the task end point, the determination of the preset range and the site matching process based on the matching preset range can be made more practical, thereby improving the effectiveness of site matching.

[0083] Specifically, assuming that the initial range in this embodiment is an area within 50 meters from the starting point of the task, when the initial range is adjusted according to the location attributes of the task starting point, if the type of the task starting point is a railway station or airport, the heat value of the task starting point is greater than a predetermined heat threshold, or the frequency of use of the task starting point in a certain period (such as within one year) is greater than a predetermined number of times, the initial range is adjusted from the area within 50 meters from the starting point of the task to the area within 200 meters from the starting point of the task, and the adjusted area is used as the preset range corresponding to the starting point of the task.

[0084] In another optional implementation, the preset range corresponding to the task starting point can also be determined according to the site matching result within the initial range corresponding to the task starting point in this embodiment. Specifically, when performing site matching according to the existence status of available sites within the preset ranges corresponding to the task starting point and the task end point, the initial range corresponding to the task starting point and the existence status of available sites within the initial range are first determined, and then the initial range is adjusted according to the existence status of available sites within the initial range, and the adjusted initial range is determined as the preset range of the task starting point, and finally the site matching is performed according to the existence status of available sites within the preset range.

[0085] Furthermore, in this embodiment, the available sites within the initial range of the task starting point can be determined according to the arrival attributes of the candidate sites within the initial range, and when the initial range is adjusted according to the existence status of the available sites within the initial range, the initial range is adjusted according to the number of available sites within the initial range, and then the preset range corresponding to the task starting point is determined. Therefore, in this embodiment, the initial range is adjusted and the preset range is determined by the number of available sites within the initial range, which makes the determination of the preset range more flexible. At the same time, by using the existence status of the available sites within the preset range determined based on the above method to perform site matching, the site matching process can be further optimized, the number of times and the quality of the automatic driving options are improved, and the user's use requirements for automatic driving travel options are met.

[0086] Specifically, when there is no available site within the initial range or the number of available sites is less than a predetermined number, the initial range is expanded, and the expanded initial range is determined as the preset range corresponding to the task starting point. When the number of available sites within the initial range is greater than a predetermined number, the initial range is reduced, and the reduced initial range is determined as the preset range corresponding to the task starting point.

[0087] In another optional implementation, in this embodiment, the preset range corresponding to the task starting point can also be determined based on the location attribute of the task starting point and the site matching result within the initial range corresponding to the task starting point. Specifically, when performing site matching based on the existence status of available sites within the preset ranges corresponding to the task starting point and the task end point, first, based on the initial range corresponding to the task starting point, the initial range is adjusted based on the location attribute of the task starting point, and site matching is performed based on the existence status of available sites within the adjusted initial range, and the adjusted initial range is adjusted again based on the site matching, and finally, site matching is performed based on the existence status of available sites within the adjusted initial range. Among them, the method for adjusting the initial range and the method for re-adjusting the adjusted initial range can adopt the method described above, which will not be repeated here.

[0088] In step S330, in response to the results of the route verification and the site matching satisfying the preset conditions, the task execution attribute of the autonomous driving vehicle is determined to be executable.

[0089] In this embodiment, after performing route verification and site matching according to the task starting point and the task end point respectively, the task execution attribute of the autonomous driving vehicle is determined by judging whether the results of the route verification and the site matching meet the preset conditions, and when the results of the route verification and the site matching meet the preset conditions, the task execution attribute of the autonomous driving vehicle is determined to be executable, or when the results of the route verification and the site matching do not meet the preset conditions, the task execution attribute of the autonomous driving vehicle is determined to be non-executable.

[0090] Further, the preset conditions in this embodiment are that there is a valid path between the task starting point and the task end point, and there are corresponding available sites at both the task starting point and the task end point. Correspondingly, when it is determined that there is a valid path between the task starting point and the task end point, there is a corresponding available site at the task starting point, and there is a corresponding available site at the task end point, it is determined that the results of the path verification and site matching meet the preset conditions. When it is determined that there is a valid path between the task starting point and the task end point, there is a corresponding available site at the task starting point, and there is a corresponding available site at the task end point, at least one of which does not meet the requirements, it is determined that the results of the path verification and site matching do not meet the preset conditions.

[0091] In addition, there is no restriction on the execution order of step S310 and step S320 in this embodiment. Step S310 may be executed first and then step S320, or step S320 may be executed first and then step S310, or step S310 and step S320 may be executed simultaneously.

[0092] Optionally, when executing step S320 first and then executing step S310, in this embodiment, site matching can be performed on the preset range of the locations of the task starting point and the task end point respectively, and when there are corresponding available sites at both the task starting point and the task end point, a path verification is performed based on the available sites corresponding to the task starting point and the available sites corresponding to the task end point, that is, it is determined whether there is a valid path between the available site corresponding to the task starting point and the available site corresponding to the task end point, and when there is a valid path, the execution attribute of the autonomous driving vehicle is determined to be executable.

[0093] Optionally, in this embodiment, when determining the task execution attribute of the autonomous driving vehicle, it also includes determining whether the task start point and the task end point are within the autonomous driving restricted domain. The autonomous driving restricted domain is the allowed activity area of ​​the autonomous driving vehicle. The task execution attribute of the autonomous driving vehicle is determined by judging whether the task start point and the task end point are both within the autonomous driving restricted domain and whether the results of the path verification and the site matching meet the preset conditions, and in response to the task start point and the task end point being both within the autonomous driving restricted domain and the results of the path verification and the site matching meet the preset conditions, the task execution attribute of the autonomous driving vehicle is determined to be executable.

[0094] Furthermore, in this embodiment, the operations of determining whether the task start point and end point are within the automatic restriction domain, path verification and site matching are not restricted in the execution order and can be executed separately or simultaneously.

[0095] In step S230, in response to the task execution attribute of the autonomous driving vehicle being executable, an autonomous driving option and a manual driving option are displayed on the vehicle request page.

[0096] In this embodiment, when it is determined that the task execution attribute of the autonomous driving vehicle is executable, it indicates that the autonomous driving has the ability to handle the task. At this time, the autonomous driving option and the manual driving option will be displayed on the vehicle use request page to facilitate users to select the vehicle use option according to their needs, thereby increasing the participation of automatic assistive vehicles in processing tasks, and thereby improving the use efficiency of autonomous driving vehicles.

[0097] Optionally, in this embodiment, when it is determined that the task execution attribute of the autonomous driving vehicle is not executable, it indicates that the autonomous driving does not have the ability to handle the task. At this time, the manual driving option will be displayed when the user requests it, but the autonomous driving option will not be displayed; or the manual driving option and the unselectable autonomous driving option will be displayed on the vehicle request page, so that the user can only perform the task through the vehicle corresponding to the manual driving option to meet the user's travel needs.

[0098] It should be understood that the task processing method in this embodiment can be implemented by executing on the server side, can be implemented by executing on the first terminal, and can also be partially implemented by executing on the server and the first terminal together (e.g., steps S210-S220 are executed on the server, and step S230 is executed on the first terminal). This embodiment does not limit the execution subject of the method.

[0099] The technical solution of the embodiment of the present invention obtains the task information of the target task, determines the task execution attribute of the autonomous driving vehicle according to the task start point and task end point in the task information, and displays the autonomous driving option and the manual driving option on the car use request page when the task execution attribute of the autonomous driving vehicle is executable; or displays the manual driving option on the car use request page when the task execution attribute of the autonomous driving vehicle is not executable. In this way, a backup plan is provided for users' travel by displaying the manual driving option, which can meet the travel needs of users, and can adaptively display or not display the autonomous driving option on the car use request page according to the task execution attribute of the autonomous driving vehicle, thereby adaptively recommending travel options to users.

[0100] Figure 4 FIG. 1 is a schematic diagram of the task processing process of an embodiment of the present invention. Figure 4 As shown, the task processing method in this embodiment includes the following steps.

[0101] In step S410, a vehicle request is sent.

[0102] In this embodiment, when the user has a travel demand, the first terminal 10 sends a vehicle request to the server 20 based on the user operation. The vehicle request includes task-related information such as user identification, task starting point and task end point.

[0103] In step S420, task information is obtained.

[0104] In this embodiment, after receiving the user request, the server 20 obtains task information based on the user request, and the task information includes a user identifier, a task start point, and a task end point.

[0105] In step S430, the task execution attributes of the autonomous driving vehicle are determined.

[0106] In this embodiment, the server 20 determines the task execution attributes of the autonomous driving vehicle based on the task start point and the task end point.

[0107] In step S440, it is determined whether the task start point and the task end point are within the restricted area.

[0108] In this embodiment, the location area corresponding to the restricted domain is pre-set, and the server 20 determines whether the task start point and the task end point are within the restricted domain by matching the locations of the task start point and the task end point with the location area corresponding to the restricted domain. At the same time, when it is determined that both the task start point and the task end point are within the restricted domain, step S450 is continued to be executed; otherwise, when it is determined that the task start point or the task end point is not within the restricted domain, step S490 is continued to be executed.

[0109] In step S450, it is determined whether there is a valid path between the task start point and the task end point.

[0110] In this embodiment, the server 20 determines whether there is a valid path between the task starting point and the task end point by performing a path check according to the task starting point and the task end point. The specific method of the path check has been introduced in the above content and will not be repeated here. At the same time, when the result of the path check indicates that there is a valid path between the task starting point and the task end point, step S460 is continued to be executed; otherwise, when the result of the path check indicates that there is no valid path between the task starting point and the task end point, step S490 is continued to be executed.

[0111] In step S460, it is determined whether there are available sites at the task start point and the task end point.

[0112] In this embodiment, the server 20 determines whether there are available sites at the task starting point and the task end point by performing site matching on the task starting point and the task end point respectively. The site matching method has been introduced in the above content and will not be repeated here. Further, when the site matching result shows that there are corresponding available sites at both the task starting point and the task end point, step S470 is continued to be executed; otherwise, when the site matching result shows that there is no corresponding available site at the task starting point or the task end point, step S490 is continued to be executed.

[0113] In step S470, the estimated price is determined.

[0114] In this embodiment, when it is determined that the task starting point and task end point corresponding to the task information are both within the restricted domain, there is a valid path between the task starting point and the task end point, and there are corresponding available sites at the task starting point and the task end point, the server 20 determines the estimated price of the corresponding task based on the task starting point and the task end point.

[0115] Optionally, in this embodiment, when determining the estimated price of the corresponding task according to the task starting point and the task end point, the estimated price is determined based on at least one of the driving distance and driving time corresponding to the effective path between the task starting point and the task end point, and other factors that affect the operation of autonomous driving. For example, when determining the estimated price of the corresponding task based on the driving distance and driving time corresponding to the effective path between the task starting point and the task end point, the longer the driving distance and the longer the driving time, the higher the corresponding estimated price.

[0116] It should be understood that the method for determining the estimated price in this embodiment can be set according to the actual usage scenario to adapt to the operating requirements of the autonomous driving vehicle and the travel needs of the user in a specific scenario.

[0117] In step S480, the automatic driving option and the manual driving option are displayed.

[0118] In this embodiment, after determining that the execution attribute of the autonomous driving vehicle is executable and the estimated price of the task corresponding to the vehicle request, in this embodiment, the autonomous driving option and the manual driving option will be displayed on the vehicle request page of the first terminal 10, that is, the autonomous driving option and the manual driving option will be recommended to the user at the same time, so as to facilitate the user to select the appropriate vehicle option from the autonomous driving option and the manual driving option. The vehicle option is adaptively recommended to provide users with more diverse vehicle options, which is conducive to further improving the user's travel experience.

[0119] In step S490, a manual driving option is displayed.

[0120] In this embodiment, when it is determined that the task starting point or task end point in the user's request is not within the restricted domain, there is no valid path between the task starting point and the task end point, or there is no available site at the task starting point or the task end point, it is determined that the task execution attribute of the autonomous driving vehicle for the user is not executable. At this time, the manual driving option is displayed on the vehicle use request page of the first terminal 10, and the autonomous driving option is not displayed, that is, the autonomous driving vehicle option is not recommended to the user.

[0121] Furthermore, in order to facilitate intuitive understanding of the display of car use options after the user initiates a car use request, this embodiment provides a car use request page for different task execution attributes of autonomous driving vehicles.

[0122] Figure 5 FIG. 1 is a schematic diagram of a car request page according to an embodiment of the present invention. Figure 5 As shown, in this embodiment, a schematic diagram of a car request page is given when it is determined that the task execution attribute of the autonomous driving vehicle is executable. In the car request page P1, both the autonomous driving option and the manual driving option are displayed. The manual driving option includes car options such as special carpooling, special express, express, taxi, premium, and private car. In addition, the display controls corresponding to different car options also display the estimated price corresponding to the task (represented by "estimated X yuan" in the figure) and the operation options (represented by "□" in the figure), so that the user can view the car options and the corresponding estimated prices, select one or more car options through the operation controls, and after selecting the car options, click the order control at the bottom of the car request page (the "Confirm Call" control in the figure) to generate the corresponding car order and complete the order.

[0123] Optionally, in this embodiment, the same or different display modes (including display options such as display fonts and rendering effects) can be used to display the automatic driving option and the manual driving option. Furthermore, in this embodiment, the car use options can also be displayed on the car use request page based on a certain priority order, such as displaying the automatic driving option first and then the manual driving option; or displaying the automatic driving option and each manual driving option in order from low to high according to the estimated price, etc.

[0124] Figure 6 FIG. 1 is another schematic diagram of a car request page according to an embodiment of the present invention. Figure 6 As shown, in this embodiment, a schematic diagram of a car request page is given when it is determined that the task execution attribute of the autonomous driving vehicle is not executable. In the car request page P2, only the manual driving option is displayed in the car option, and the autonomous driving option is not displayed. The manual driving option includes car options such as special carpooling, special express, express, taxi, premium, and private car. In addition, the display control where the car option corresponding to each manual driving option is located also displays the estimated price corresponding to the task (indicated by "estimated X yuan" in the figure) and the operation option (indicated by "□" in the figure), so that the user can view the car option and the corresponding estimated price, select one or more car options through the operation control, and after selecting the car option, click the order control at the bottom of the car request page (the "Confirm Call" control in the figure) to generate the corresponding car order and complete the order.

[0125] It should be understood that the display content and the specific display method of the display content (including but not limited to the display position) in the car request page in this embodiment are only examples and can be set according to the actual application scenario, and are not limited here.

[0126] The technical solution of this embodiment is that after the first terminal initiates a request for a vehicle, the server obtains task information according to the user's request, and determines the task execution attribute of the autonomous driving vehicle based on the task start point and task end point in the task information, and recommends the autonomous driving option and the manual driving option to the user when the task execution attribute of the autonomous driving vehicle is executable; at the same time, the manual driving option is recommended to the user corresponding to the task when the task execution attribute of the autonomous driving vehicle is not executable, instead of the autonomous driving option. Therefore, the above method can realize the adaptive recommendation of the autonomous driving vehicle option to users under different tasks, which is conducive to further improving the user's travel experience.

[0127] Figure 7 Schematic diagram of a task processing device according to an embodiment of the present invention. Figure 7As shown, the task processing device in this embodiment includes an information acquisition unit 1, an information processing unit 2 and an option recommendation unit 3. Among them, the information acquisition unit 1 is used to obtain the task information of the target task, and the task information includes the task start point and the task end point. The information processing unit 2 is used to determine the task execution attribute of the autonomous driving vehicle according to the task start point and the task end point. The option recommendation unit 3 is used to display the autonomous driving option and the manual driving option on the vehicle request page in response to the task execution attribute of the autonomous driving vehicle being executable; and to display the manual driving option on the vehicle request page in response to the task execution attribute being unexecutable.

[0128] Optionally, when the information processing unit 2 in this embodiment determines the task execution attribute of the autonomous driving vehicle based on the task starting point and the task end point, it is used to perform a route verification based on the task starting point and the task end point; perform site matching on the task starting point and the task end point respectively; in response to the results of the route verification and the site matching satisfying preset conditions, determine that the task execution attribute of the autonomous driving vehicle is executable.

[0129] Furthermore, the information processing unit 2 in this embodiment is also used to determine whether the task starting point and the task end point are within the autonomous driving restricted domain; in response to the results of the path verification and the site matching satisfying the preset conditions, the task execution attribute of the autonomous driving vehicle is determined to be executable, which is specifically used to respond to the fact that the task starting point and the task end point are both within the autonomous driving restricted domain and the results of the path verification and the site matching satisfy the preset conditions, and determine that the task execution attribute of the autonomous driving vehicle is executable.

[0130] The preset conditions are that there is a valid path between the task starting point and the task end point, and there are corresponding available sites at both the task starting point and the task end point.

[0131] Optionally, when performing route verification based on the task starting point and the task end point, the information processing unit 2 is used to perform path planning based on the task starting point and the task end point, and determine the path planning result; and perform route verification based on the existence status of a valid path in the path planning result, and the valid path is a path on which the autonomous driving vehicle can travel.

[0132] Optionally, when performing site matching for the task starting point and the task end point respectively, the information processing unit 2 is used to perform site matching according to the existence status of available sites within a preset range corresponding to the task starting point and the task end point respectively, and the available sites are autonomous driving sites.

[0133] The technical solution of this embodiment obtains task information of the target task through the information acquisition unit, and the information processing unit determines the task execution attribute of the autonomous driving vehicle according to the task start point and task end point in the task information. The option recommendation unit responds to the task execution attribute of the autonomous driving vehicle being executable and displays the autonomous driving option and the manual driving option on the vehicle request page, or responds to the task execution attribute being unexecutable and displays the manual driving option on the vehicle request page. In this way, the autonomous driving option can be displayed on the vehicle request page when the autonomous driving vehicle can execute the task, thereby adaptively recommending travel options to users.

[0134] Figure 8 Schematic diagram of an electronic device according to an embodiment of the present invention. Figure 8 As shown, Figure 8 The electronic device shown is a general address query device, which includes a general computer hardware structure, which at least includes a processor 81 and a memory 82. The processor 81 and the memory 82 are connected via a bus 83. The memory 82 is suitable for storing instructions or programs executable by the processor 81. The processor 81 can be an independent microprocessor or a collection of one or more microprocessors. Thus, the processor 81 executes the instructions stored in the memory 82, thereby executing the method flow of the embodiment of the present invention as described above to realize the processing of data and the control of other devices. The bus 83 connects the above-mentioned multiple components together, and at the same time connects the above-mentioned components to the display controller 84 and the display device and the input / output (I / O) device 85. The input / output (I / O) device 85 can be a mouse, a keyboard, a modem, a network interface, a touch input device, a somatosensory input device, a printer, and other devices known in the art. Typically, the input / output device 85 is connected to the system via an input / output (I / O) controller 86.

[0135] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, devices (equipment) or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may adopt a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0136] The present application is described with reference to flowcharts of methods, apparatuses (devices) and computer program products according to embodiments of the present application. It should be understood that each process in the flowchart can be implemented by computer program instructions.

[0137] These computer program instructions may be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device that implements the process Figure 1 A function specified in a process or multiple processes.

[0138] These computer program instructions may also be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce the instructions for implementing the process Figure 1 A device that specifies functions in a process or multiple processes.

[0139] Another embodiment of the present invention relates to a non-volatile storage medium for storing a computer-readable program, wherein the computer-readable program is used for a computer to execute part or all of the above method embodiments.

[0140] That is, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by specifying relevant hardware through a program, and the program is stored in a storage medium, including several instructions for a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0141] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A task processing method, characterized in that: The method comprises: Obtaining task information of the target task, wherein the task information includes a task start point and a task end point; Determining a task execution attribute of the autonomous driving vehicle according to the task starting point and the task end point; In response to the task execution attribute of the autonomous driving vehicle being executable, an autonomous driving option and a manual driving option are displayed on the vehicle request page.

2. The method according to claim 1, characterized in that: Determining the task execution attribute of the autonomous driving vehicle according to the task starting point and the task end point includes: Performing a path check according to the task starting point and the task end point; Performing site matching on the task starting point and the task end point respectively; In response to the results of the route verification and the site matching satisfying preset conditions, it is determined that the task execution attribute of the autonomous driving vehicle is executable.

3. The method according to claim 2, characterized in that The determining of the task execution attribute of the autonomous driving vehicle according to the task starting point and the task end point further comprises: Determining whether the task start point and the task end point are within the autonomous driving restriction domain; In response to the result of the route verification and the site matching satisfying a preset condition, determining that the task execution attribute of the autonomous driving vehicle is executable includes: In response to the fact that both the task start point and the task end point are within the autonomous driving restriction domain and the results of the path verification and the site matching meet preset conditions, it is determined that the task execution attribute of the autonomous driving vehicle is executable.

4. The method according to claim 2 or 3, characterized in that: The preset conditions are that there is a valid path between the task starting point and the task end point, and there are corresponding available sites at both the task starting point and the task end point.

5. The method according to claim 2, characterized in that: The path verification according to the task starting point and the task end point includes: Perform path planning according to the task starting point and the task end point, and determine the path planning result; A path verification is performed based on the existence status of a valid path in the path planning result, where the valid path is a path on which the autonomous driving vehicle can travel.

6. The method according to claim 2, characterized in that The performing site matching on the task starting point and the task end point respectively comprises: Site matching is performed according to the existence status of available sites within a preset range respectively corresponding to the task starting point and the task end point, and the available sites are autonomous driving sites.

7. The method according to claim 6, characterized in that The performing site matching according to the existence status of available sites within the preset ranges respectively corresponding to the task starting point and the task end point includes: Determine a set of candidate sites within a preset range corresponding to the starting point of the task; Determine an available site within a preset range corresponding to the task starting point according to the arrival attribute of each candidate site in the candidate site set, wherein the arrival attribute includes the arrival distance between the candidate site and the task starting point and / or the arrival difficulty of the autonomous driving vehicle to reach the candidate site; Site matching is performed according to the existence status of available sites within a preset range corresponding to the task starting point.

8. The method according to claim 6, characterized in that The performing site matching according to the existence status of available sites within the preset ranges respectively corresponding to the task starting point and the task end point includes: Determine an initial range corresponding to the starting point of the task; The initial range is adjusted according to the location attribute of the task starting point and / or the site matching result within the initial range to determine a preset range corresponding to the task starting point; Site matching is performed according to the existence status of available sites within a preset range corresponding to the task starting point.

9. The method according to claim 1, characterized in that: The method further comprises: In response to the task execution attribute being unexecutable, a manual driving option is displayed on the vehicle request page.

10. A task processing device, characterized in that: The device comprises: An information acquisition unit, used to acquire task information of a target task, wherein the task information includes a task start point and a task end point; An information processing unit, configured to determine a task execution attribute of the autonomous driving vehicle according to the task starting point and the task end point; The option recommendation unit is used to display the autonomous driving option and the manual driving option on the vehicle request page in response to the task execution attribute of the autonomous driving vehicle being executable.

11. A computer program product, characterized in that The computer program product comprises a computer program / instructions, and when the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 9 is implemented.

12. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of claims 1 to 9.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps of any one of claims 1 to 9 are implemented.

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