Travel activity recommendation method, device and equipment, vehicle and storage medium

Abstract

The invention provides a travel activity recommendation method, device and equipment, a vehicle and a storage medium, and relates to the technical field of automobiles. The method comprises the following steps: acquiring activity related information of a plurality of travel activities; wherein the activity related information is used for guiding a plurality of users to go out at the same time; based on the activity related information, selecting at least one travel activity from the plurality of travel activities as a target travel activity; and recommending at least one target travel activity. According to the method, various travel activities can be provided for the user, the vehicle travel scene of the user is widened, and the travel experience of the user is improved.

Description

Technical Field

[0001] This application relates to the field of automotive technology, and more particularly to a method, apparatus, device, vehicle, and storage medium for recommending mobility activities. Background Technology

[0002] With the increasing popularity of vehicles, many users choose to travel by car during their rest time, making it convenient for them to stop at any time to enjoy the scenery along the way.

[0003] The existing travel methods mainly involve users setting their own destination (or setting both the starting point and the destination), and then planning corresponding routes for users based on the locations set by the users to meet their travel needs.

[0004] However, this mode of travel is not suitable for scenarios where users do not have specific travel route requirements, thus limiting the applicable scenarios for vehicle travel and resulting in a relatively limited range of vehicle travel options, failing to provide users with a better vehicle travel experience. Summary of the Invention

[0005] This application provides a method, apparatus, device, vehicle, and storage medium for recommending travel activities, in order to solve the technical problem that existing vehicle travel modes have limited applicability and cannot improve the user's travel experience.

[0006] Firstly, this application provides a method for recommending travel activities, applied to a target device, comprising:

[0007] Obtain activity-related information for multiple travel activities; wherein, the activity-related information is used to guide multiple users to travel simultaneously;

[0008] Based on the activity-related information, at least one of the multiple travel activities is selected as the target travel activity;

[0009] Recommend at least one of the aforementioned target travel activities.

[0010] In one possible implementation, selecting at least one of the multiple travel activities as the target travel activity based on the activity-related information includes:

[0011] Based on the activity-related information, determine the activity score corresponding to each of the travel activities;

[0012] Based on the activity score, at least one of the multiple travel activities is selected as the target travel activity.

[0013] In one possible implementation, the target travel activity satisfies at least one of the following:

[0014] The activity score corresponding to any of the target travel activities is greater than a preset threshold;

[0015] Alternatively, the activity score corresponding to any of the target travel activities shall rank among the top N in the activity scores corresponding to the plurality of travel activities, where N is a preset integer greater than or equal to 1.

[0016] In one possible implementation, selecting at least one of the multiple travel activities as the target travel activity based on the activity-related information includes:

[0017] Based on the activity-related information, determine the activity type corresponding to each of the travel activities;

[0018] Based on the activity type corresponding to each of the aforementioned travel activities, the multiple travel activities are classified to obtain multiple activity groups; wherein each activity group includes at least one travel activity;

[0019] Select at least one of the travel activities included in each of the activity groups as the target travel activity.

[0020] In one possible implementation, recommending at least one of the target travel activities includes:

[0021] Recommend at least some of the activity groups described, as well as the target travel activities included in the recommended activity groups.

[0022] In one possible implementation, the target travel activity satisfies at least one of the following:

[0023] The activity score corresponding to any of the target travel activities is greater than a preset threshold;

[0024] Alternatively, the activity score corresponding to the target travel activity ranks among the top M travel activities in the activity group to which it belongs, where M is a preset integer greater than or equal to 1.

[0025] In one possible implementation, the activity-related information indicates the activity details of the travel activity; determining the activity type corresponding to each travel activity based on the activity-related information includes:

[0026] Based on at least one of the activity details indicated by the activity-related information, the activity type corresponding to each of the travel activities is determined.

[0027] In one possible implementation, the activity-related information includes at least travel route information; the travel route information is used to determine the route type corresponding to the travel activity; the method further includes:

[0028] Obtain the driving style of the target user;

[0029] Based on the preset correspondence between driving style and route type, determine the target route type corresponding to the driving style of the target user;

[0030] Selecting at least one of the multiple travel activities as the target travel activity includes:

[0031] Based on the travel route information and the target route type, at least one of the multiple travel activities is selected as the target travel activity; wherein the route type of the travel route corresponding to the target travel activity matches the target route type.

[0032] In one possible implementation, the target travel activity satisfies at least one of the following:

[0033] The distance between the current location of the target device and the route location of the target travel activity is less than a preset distance;

[0034] Alternatively, the weather conditions in the region where the target travel activity is located meet the preset weather requirements at the travel time corresponding to the target travel activity;

[0035] Alternatively, the road conditions between the current location of the target device and the starting point of the route for the target travel activity meet the preset road condition requirements.

[0036] In one possible implementation, the activity-related information includes at least travel route information; the travel route information includes at least a route origin and a route destination; different target travel activities satisfy the condition that at least one of the route origin and the route destination is different.

[0037] In one possible implementation, recommending at least one of the target travel activities includes:

[0038] Based on the activity-related information of each of the aforementioned target travel activities, activity recommendation information is determined;

[0039] Send activity recommendation information for at least one of the target travel activities; or display activity recommendation information for at least one of the target travel activities.

[0040] In one possible implementation, the activity rating is determined based on at least one of a first rating, a second rating, and a third rating; wherein the first rating indicates a travel route rating; the second rating indicates a travel time rating; and the third rating indicates a travel distance rating.

[0041] In one possible implementation, the travel route score is determined according to the following steps:

[0042] The system obtains the target user's driving style and route-related information for the travel activity; wherein the route-related information is used to indicate information around the travel route corresponding to the travel activity.

[0043] Based on the activity-related information and the route-related information, determine the calculated values ​​corresponding to each preset information;

[0044] Based on the driving style of the target user, determine the calculation weight corresponding to each of the preset information;

[0045] The travel route score is determined based on the preset information, the calculated values, and the calculated weights.

[0046] Secondly, this application provides a travel activity recommendation device, including:

[0047] An acquisition unit is used to acquire activity-related information for multiple travel activities; wherein, the activity-related information is used to guide multiple users to travel simultaneously;

[0048] A determining unit is configured to select at least one of the multiple travel activities as the target travel activity based on the activity-related information.

[0049] A recommendation unit is used to recommend at least one of the target travel activities.

[0050] In one possible implementation, the determining unit is used for:

[0051] Based on the activity-related information, determine the activity score corresponding to each of the travel activities;

[0052] Based on the activity score, at least one of the multiple travel activities is selected as the target travel activity.

[0053] In one possible implementation, the target travel activity satisfies at least one of the following:

[0054] The activity score corresponding to any of the target travel activities is greater than a preset threshold;

[0055] Alternatively, the activity score corresponding to any of the target travel activities shall rank among the top N in the activity scores corresponding to the plurality of travel activities, where N is a preset integer greater than or equal to 1.

[0056] In one possible implementation, the determining unit is used for:

[0057] Based on the activity-related information, determine the activity type corresponding to each of the travel activities;

[0058] Based on the activity type corresponding to each of the aforementioned travel activities, the multiple travel activities are classified to obtain multiple activity groups; wherein each activity group includes at least one travel activity;

[0059] Select at least one of the travel activities included in each of the activity groups as the target travel activity.

[0060] In one possible implementation, recommending at least one of the target travel activities includes:

[0061] Recommend at least some of the activity groups described, as well as the target travel activities included in the recommended activity groups.

[0062] In one possible implementation, the target travel activity satisfies at least one of the following:

[0063] The activity score corresponding to any of the target travel activities is greater than a preset threshold;

[0064] Alternatively, the activity score corresponding to the target travel activity ranks among the top M travel activities in the activity group to which it belongs, where M is a preset integer greater than or equal to 1.

[0065] In one possible implementation, the activity-related information indicates the activity details of the travel activity; the determining unit is configured to:

[0066] Based on at least one of the activity details indicated by the activity-related information, the activity type corresponding to each of the travel activities is determined.

[0067] In one possible implementation, the activity-related information includes at least travel route information; the travel route information is used to determine the route type corresponding to the travel activity; the device is further used to:

[0068] Obtain the driving style of the target user;

[0069] Based on the preset correspondence between driving style and route type, determine the target route type corresponding to the driving style of the target user;

[0070] Based on the travel route information and the target route type, at least one of the multiple travel activities is selected as the target travel activity; wherein the route type of the travel route corresponding to the target travel activity matches the target route type.

[0071] In one possible implementation, the target travel activity satisfies at least one of the following:

[0072] The distance between the current location of the target device and the route location of the target travel activity is less than a preset distance;

[0073] Alternatively, the weather conditions in the region where the target travel activity is located meet the preset weather requirements at the travel time corresponding to the target travel activity;

[0074] Alternatively, the road conditions between the current location of the target device and the starting point of the route for the target travel activity meet the preset road condition requirements.

[0075] In one possible implementation, the activity-related information includes at least travel route information; the travel route information includes at least a route origin and a route destination; different target travel activities satisfy the condition that at least one of the route origin and the route destination is different.

[0076] In one possible implementation, the recommendation unit is used for:

[0077] Based on the activity-related information of each of the aforementioned target travel activities, activity recommendation information is determined;

[0078] Send activity recommendation information for at least one of the target travel activities; or display activity recommendation information for at least one of the target travel activities.

[0079] In one possible implementation, the activity rating is determined based on at least one of a first rating, a second rating, and a third rating; wherein the first rating indicates a travel route rating; the second rating indicates a travel time rating; and the third rating indicates a travel distance rating.

[0080] In one possible implementation, the device further includes a scoring unit for determining a travel route score based on the following steps:

[0081] The system obtains the target user's driving style and route-related information for the travel activity; wherein the route-related information is used to indicate information around the travel route corresponding to the travel activity.

[0082] Based on the activity-related information and the route-related information, determine the calculated values ​​corresponding to each preset information;

[0083] Based on the driving style of the target user, determine the calculation weight corresponding to each of the preset information;

[0084] The travel route score is determined based on the preset information, the calculated values, and the calculated weights.

[0085] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0086] The memory stores computer-executed instructions;

[0087] The processor executes computer execution instructions stored in the memory to implement the method described in any one of the first aspects.

[0088] Fourthly, this application provides a vehicle that includes the electronic equipment described in the third aspect.

[0089] Fifthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in any one of the first aspects.

[0090] Sixthly, this application provides a computer program product comprising: computer execution instructions stored in a readable storage medium, wherein at least one processor of an electronic device can read the computer execution instructions from the readable storage medium, and the at least one processor executes the computer execution instructions to cause the electronic device to perform the method described in any one of the first aspects.

[0091] The travel activity recommendation method, apparatus, device, vehicle, and storage medium provided in this application can, when it is determined that a user has a need for driving travel, obtain activity-related information for multiple travel activities. This activity-related information guides multiple users to travel simultaneously, enabling users to complete their travel activities based on this information, avoiding the limitation of being restricted to user-defined destinations and thus increasing the diversity of user travel options. Then, based on the activity-related information, at least one travel activity is selected as a target travel activity from among the multiple travel activities, and at least one target travel activity is recommended. This allows for the recommendation of matching target travel activities from multiple travel activities to the user, better meeting the user's travel needs and improving the user's travel experience. Furthermore, this implementation method also allows multiple users to travel simultaneously based on the activity-related information of a target travel activity, increasing the enjoyment of the user's travel experience. Attached Figure Description

[0092] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0093] Figure 1 A flowchart illustrating a travel activity recommendation method provided in an embodiment of this application;

[0094] Figure 2 A flowchart illustrating another travel activity recommendation method provided in this application embodiment;

[0095] Figure 3 This application provides an embodiment of a diagram illustrating the recommendation of at least one target travel activity.

[0096] Figure 4 This is a schematic diagram illustrating another recommended target travel activity provided in an embodiment of this application;

[0097] Figure 5 This is a schematic diagram of the structure of a travel activity recommendation device provided in an embodiment of this application;

[0098] Figure 6 A schematic diagram of another travel activity recommendation device provided in this application embodiment;

[0099] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0100] Figure 8 This is a structural schematic diagram of a vehicle provided in an embodiment of this application.

[0101] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0102] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0103] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0104] Current user travel methods primarily involve users setting their own destination, or specifying both the origin and destination, to receive one or more recommended routes. In this case, the recommended routes tend to focus on saving users travel time, distance, or tolls.

[0105] This implementation method not only fails to provide users with more diverse and interesting travel routes, but is also unsuitable for travel scenarios without a clear destination, thus limiting the applicable scenarios for vehicle travel and resulting in a relatively limited mode of vehicle travel, failing to provide users with a better vehicle travel experience.

[0106] The travel activity recommendation method provided in this application aims to provide users with a variety of travel activities to choose from by recommending one or more pre-created travel activities, thereby solving the aforementioned technical problems of the prior art.

[0107] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0108] Figure 1 This is a flowchart illustrating a travel activity recommendation method provided in an embodiment of this application, such as... Figure 1 As shown, the recommended method for this travel activity includes the following steps:

[0109] S101. Obtain activity-related information for multiple travel activities; among which, the activity-related information is used to guide multiple users to travel at the same time.

[0110] In one example, the travel activity recommendation method provided in this application embodiment can be applied to a target device, wherein the target device can instruct a server or an in-vehicle terminal. In this case, the travel activity recommendation method can be executed in at least some of the servers or at least some of the in-vehicle terminals.

[0111] In one example, the multiple travel activities retrieved can be officially created activities or user-created activities, etc., without restriction on the creator of the travel activities. Among them, user-created travel activities can be submitted to the official platform for review after creation, and distributed after approval. At this time, after the travel activity is published, the activity-related information of the travel activity can be obtained.

[0112] In one example, when retrieving activity-related information for multiple travel activities, one can retrieve activity-related information for all created travel activities, or activity-related information for travel activities whose travel time is within a preset time range from the current time, or activity-related information for travel activities with a large number of favorites, or activity-related information for travel activities with high activity ratings, or activity-related information for multiple travel activities based on their creation time, etc. Here, the method for determining multiple travel activities for retrieving activity-related information is not limited, and the method that can be implemented is the standard.

[0113] S102. Based on activity-related information, select at least one travel activity from among multiple travel activities as the target travel activity.

[0114] In one example, activity-related information can indicate the activity details of a travel activity. In this case, based on the activity details of the travel activity, at least one target travel activity that matches a domain user can be selected from multiple travel activities as the target travel activity.

[0115] S103. Recommend at least one target travel activity.

[0116] In one example, when recommending at least one target travel activity, the system can support users in sorting or filtering the target travel activities before recommending / displaying them. For example, users can sort the target travel activities based on their travel time, total length, travel duration, and distance from the user's location; or they can filter based on the location information of the target travel activities (e.g., the city where the target travel activity is located, the altitude of the target travel activity, etc.); or they can filter based on the creator of the travel activity. The sorting / filtering method for the target travel activities is not limited here.

[0117] As described above, this embodiment of the application can obtain activity-related information for multiple travel activities when it is determined that a user has a need for driving. This activity-related information guides multiple users to travel simultaneously, enabling users to complete their travel activities based on this information, avoiding the limitation of only being able to travel to a destination set by the user themselves, thereby increasing the diversity of user travel. Then, based on the activity-related information, at least one travel activity is selected as the target travel activity from among the multiple travel activities, and at least one target travel activity is recommended. This allows for the recommendation of matching target travel activities for the user from multiple travel activities, thus better meeting the user's travel needs and improving the user's travel experience. Simultaneously, this implementation also allows multiple users to travel simultaneously based on the activity-related information of the target travel activity, increasing the enjoyment of the user's travel experience.

[0118] Figure 2 A flowchart illustrating another travel activity recommendation method provided in this application embodiment is shown below. Figure 2 As shown, the recommended method for this travel activity includes the following steps:

[0119] S201. Obtain activity-related information for multiple travel activities; whereby the activity-related information is used to guide multiple users to travel simultaneously.

[0120] In one example, this step can be referred to the content described in S101 above, and will not be repeated in detail here.

[0121] S202. Based on activity-related information, select at least one travel activity as the target travel activity from among multiple travel activities.

[0122] In one example, the process of determining the target travel activity can be described in Implementation Method 1 and Implementation Method 2 below, where Implementation Method 1 represents the method of determining the target travel activity individually, and Implementation Method 2 represents the method of determining the target travel activity in groups.

[0123] Implementation Method 1

[0124] In this embodiment, an activity score can be determined for each travel activity based on activity-related information. Then, based on the activity score, at least one travel activity can be selected as the target travel activity from among multiple travel activities.

[0125] In one example, the activity rating can be a star rating, such as 5 stars, 4 stars, 4.5 stars, etc., or the activity rating can be a numerical rating, such as 10 points, 9 points, etc., or the activity rating can be a level rating, such as level 1, level 2, level 3, etc. There is no limitation on the form of the activity rating.

[0126] At this point, the identified target travel activity satisfies at least one of the following: the activity score corresponding to any target travel activity is greater than a preset threshold, or the activity score corresponding to any target travel activity ranks in the top N among the activity scores corresponding to multiple travel activities, where N is a preset integer greater than or equal to 1.

[0127] In one example, the preset threshold can be a value pre-set according to the representation of the activity rating. For example, if the activity rating is a star rating, the preset threshold can be set to 4 stars or 4.5 stars, etc. If the activity rating is a numerical rating, the preset threshold can be set to 8 points or 9 points, etc. There is no limitation on the preset threshold here, and it is based on meeting the actual needs.

[0128] This implementation method can determine the target travel activity based on the activity rating of each travel activity, thereby prioritizing the recommendation of travel activities with higher activity ratings to users, thus increasing user satisfaction with the recommended target travel activities and increasing the probability that users will travel based on the recommended target travel activities.

[0129] Implementation Method 2

[0130] In this embodiment, the activity type corresponding to each travel activity can be determined first based on activity-related information; then, based on the activity type corresponding to each travel activity, multiple travel activities can be classified to obtain multiple activity groups, wherein each activity group includes at least one travel activity; finally, at least one travel activity can be selected as the target travel activity from the at least one travel activity included in each activity group.

[0131] In one example, the activity type can indicate the theme of the trip. For example, the theme of the trip can indicate season, location, charity, tourism, activity rating, route type, etc. The theme of the trip is not limited here, but should be based on actual needs. For example, the activity type can be "Ice and Snow Experience", "Desert Trip", "Meet at the Summit of Mountains and Seas", "Highly Recommended", "Off-Road Trip", etc. The specific content of the activity type is not limited here.

[0132] In one example, activity-related information can indicate the activity details of a travel activity. In this case, when determining the activity type corresponding to each travel activity based on the activity-related information, the activity type corresponding to each travel activity can be determined based on at least one activity detail indicated by the activity-related information.

[0133] In one example, the activity details may include, but are not limited to, the following: travel time, route type, route origin, route destination, location information of the activity, travel duration, total length of the activity, distance from the route origin, creator, activity rating, etc.

[0134] In this implementation, the target travel activity satisfies at least one of the following: the activity score corresponding to any target travel activity is greater than a preset threshold; or, the activity score corresponding to the target travel activity ranks among the top M travel activities in the activity group, where M is a preset integer greater than or equal to 1. Here, the value of M can be the same as or different from the value of N mentioned above.

[0135] In this embodiment, after determining the target travel activity, when recommending at least one target travel activity, at least a partial group of activities and the target travel activities included in the recommended group of activities can be recommended.

[0136] This implementation method categorizes multiple travel activities based on the activity types determined by activity-related information, resulting in multiple activity groups. It then identifies the target travel activity based on the activities included in each group. This allows users to gain an initial understanding of the theme of the target travel activity through the activity type, thus assisting them in determining their desired travel activity. Furthermore, it can recommend more target travel activities to users by suggesting activity groups and target travel activities within those groups, providing them with more choices.

[0137] In this embodiment, in addition to determining and recommending the target travel activity according to the two implementation methods described above, the target travel activity can also be determined from multiple travel activities based on the degree of matching between the travel activity and the current user's driving style. For details, please refer to the description of the third implementation method below.

[0138] Implementation Method 3

[0139] In this embodiment, the driving style of the target user can be obtained first, and then the target route type corresponding to the driving style of the target user can be determined according to the preset correspondence between driving style and route type.

[0140] Therefore, when selecting at least one activity as the target activity from multiple travel activities, the selection can be based on the travel route information and target route type included in the activity-related information. Specifically, the route type of the travel route corresponding to the target activity matches the target route type.

[0141] In one example, a target user's driving style can be determined based on their historical driving data. This historical driving data may include, but is not limited to, the following first parameters: accelerator pedal opening, brake pedal depth, lateral acceleration G-value, longitudinal acceleration G-value, straight-line speed, steering angle change, corner exit speed, and corner entry speed. After obtaining the target user's historical driving data, the average value (μ) and standard deviation (σ) of each historical driving data point can be determined. Then, the historical driving data is filtered using the z-score method to remove outliers, resulting in processed historical driving data. Outliers in the historical driving data can be understood as data at extreme points. For example, the data distribution range can be determined based on the normal distribution of the historical driving data, and data outside this range can be identified as outliers.

[0142] After obtaining the processed historical driving data, a threshold can be set, and the processed historical driving data can be used to make a bias judgment based on the set threshold. In this way, the driving style of the target user can be determined based on the degree of bias judged.

[0143] The threshold values ​​can be determined based on the mean μ and standard deviation σ. For example, if the data distribution range of the processed historical driving data is a certain range, each first parameter can be divided into multiple levels to determine the degree of tendency corresponding to each first parameter. The multiple levels can include: high tendency, relatively high tendency, moderate tendency, relatively low tendency, low tendency, etc. The number of levels is not limited here, but only if feasible.

[0144] Assuming the mean is μ and the standard deviation is σ, if the final data processing result's data distribution ranges from μ-3σ to μ+3σ, then the threshold can be determined based on the required stratification. For example, if the stratification includes high propensity, relatively high propensity, moderate propensity, relatively low propensity, and low propensity, then the threshold can include μ+2σ, μ+σ, μ-σ, and μ-2σ. In this case, historical driving data greater than μ+2σ can be classified as high propensity; historical driving data greater than μ+σ and less than or equal to μ+2σ can be classified as relatively high propensity; historical driving data greater than or equal to μ-σ and less than or equal to μ+σ can be classified as moderate propensity; historical driving data greater than or equal to μ-2σ and less than μ-σ can be classified as relatively low propensity; and historical driving data less than μ-2σ can be classified as low propensity. Alternatively, the set threshold can be determined by jointly using the adjustment parameter k, the average value μ, and the standard deviation σ. In this case, the set threshold can include μ+2kσ, μ+kσ, μ-kσ, and μ-2kσ. Then, if the historical driving data is greater than μ+2kσ, it can be determined as a high propensity; if the historical driving data is greater than μ+kσ and less than or equal to μ+2kσ, it can be determined as a relatively high propensity; if the historical driving data is greater than or equal to μ-kσ and less than or equal to μ+kσ, it can be determined as a moderate propensity; if the historical driving data is greater than or equal to μ-2kσ and less than μ-kσ, it can be determined as a relatively low propensity; and if the historical driving data is less than μ-2kσ, it can be determined as a low propensity. Here, k is a value between 1 and 2.

[0145] Then, the driving style of the target user can be determined based on the processed historical driving data. For example, the driving style that matches the processed historical driving data among several preset driving styles can be identified as the target user's driving style.

[0146] The preset driving styles can include, but are not limited to: Dynamic Driving Style, Balanced Driving Style, and Curve Driving Style. The Dynamic Driving Style indicates a preference for straight lines and good speed continuity, reducing turns and lane changes; the Balanced Driving Style indicates a preference for smooth, comfortable, and fluid driving lines, reducing congestion and intersections; and the Curve Driving Style indicates a preference for curves, experiencing lateral forces, and driving pleasure.

[0147] At this point, the target user's driving style can be determined by judging the degree of matching between the target user's historical driving data and the style characteristics of each preset driving style.

[0148] The characteristics of dynamic driving style are: high accelerator pedal opening, high longitudinal acceleration G-value, high straight-line speed, high brake pedal depth, and low steering angle change.

[0149] The characteristics of a balanced driving style are: lower accelerator pedal opening, lower brake pedal depth, lower lateral acceleration G-force, lower longitudinal acceleration G-force, moderate straight-line speed, and moderate steering angle variation.

[0150] The characteristics of the curve driving style are: medium accelerator pedal opening, medium brake pedal depth, large lateral acceleration G-value, medium longitudinal acceleration G-value, large steering angle change, large exit speed, and large entry speed.

[0151] At this point, if it is determined that the target user's historical driving data meets any one of the following first conditions, then it indicates that the target user's driving style is dynamic driving style.

[0152] The first condition is: the tendency of the accelerator pedal opening, brake pedal depth, longitudinal acceleration G-value, and straight-line speed is high or high; or, the first condition is: the tendency of the accelerator pedal opening, brake pedal depth, longitudinal acceleration G-value, and straight-line speed is high or medium, and the tendency of the exit speed and entry speed is low or low; or, the first condition is: the tendency of the accelerator pedal opening, brake pedal depth, longitudinal acceleration G-value, and straight-line speed is high or medium, and the change in steering angle is low or low.

[0153] If it is determined whether the target user's historical driving data meets all of the following second conditions, then the target user's driving style is a balanced driving style.

[0154] The second condition is: the tendency to accelerate, brake, longitudinal acceleration (G-value), and straight-line speed are all relatively high or high; or, the second condition is: the tendency to accelerate, brake, longitudinal acceleration (G-value), and straight-line speed are relatively high or medium, and the tendency to exit and enter corners is relatively low or low; or, the second condition is: the tendency to accelerate, brake, longitudinal acceleration (G-value), and straight-line speed are relatively high or medium, and the tendency to change steering angle is relatively low or low; or... The second condition is: the tendency corresponding to the changes in lateral acceleration G-value, corner exit speed, corner entry speed, and steering angle is high or high; or, the second condition is: the tendency corresponding to the changes in lateral acceleration G-value, corner exit speed, corner entry speed, and steering angle is high or medium, and the tendency corresponding to longitudinal acceleration G-value and straight-line speed is low or medium; or, the second condition is: the tendency corresponding to the changes in lateral acceleration G-value, corner exit speed, corner entry speed, and steering angle is high or high, and the tendency corresponding to accelerator pedal opening and brake pedal depth is low or medium.

[0155] If the target user's historical driving data is determined to satisfy any one of the following third conditions, then the target user's driving style is a curve driving style.

[0156] The third condition is: the tendency corresponding to changes in lateral acceleration G-value, corner exit speed, corner entry speed, and steering angle is high or high; or, the third condition is: the tendency corresponding to changes in lateral acceleration G-value, corner exit speed, corner entry speed, and steering angle is high or medium, and the tendency corresponding to changes in straight-line speed and longitudinal acceleration G-value is medium or low; or, the third condition is: the tendency corresponding to changes in lateral acceleration G-value, corner exit speed, corner entry speed, and steering angle is low or medium, and the tendency corresponding to changes in accelerator pedal opening and brake pedal depth is low or medium.

[0157] In one example, the route types involved in this application embodiment may include, but are not limited to, the following types: relaxation cruise type, city exploration type, mountain running hobby type, adventure journey type, etc. The specific names of each route type are not limited here, and the implementation shall prevail.

[0158] The characteristics of routes in the Relaxed Cruise type are: avoiding highways and busy city streets, and choosing routes that are more scenic, such as rural roads, riverside routes, or other natural landscapes, providing smooth and fluid route planning, and avoiding frequent sharp turns or high-speed driving. Therefore, the Relaxed Cruise type corresponds to the Balanced driving style and is suitable for drivers who seek calm and tranquility.

[0159] The road conditions for city exploration routes are characterized by: route planning that considers distinctive urban neighborhoods, cultural landmarks, and popular attractions; careful selection of unique city streets and well-known landmarks; consideration of urban traffic flow; and provision of optimal driving time to avoid peak-hour congestion. Therefore, city exploration routes correspond to a balanced driving style and are suitable for drivers who want to explore the cityscape and culture.

[0160] The road conditions for mountain driving enthusiasts are characterized by carefully selected mountain routes, taking into account road conditions and safety, and incorporating data such as altitude changes and route curvature to recommend exciting yet safe mountain roads. Therefore, mountain driving enthusiasts are suited to a winding driving style, ideal for drivers who want to explore the scenery of mountain roads.

[0161] Adventure journey routes are characterized by: remote natural beauty, little-known adventure locations, and challenging terrain; numerous straight-line acceleration sections; high average speeds; smooth traffic flow; and strict speed limits. Therefore, adventure journeys correspond to a dynamic driving style and are suitable for drivers who enjoy exploring remote, natural, and off-the-beaten-path destinations.

[0162] Then, based on the aforementioned pre-defined correspondence between driving style and route type, the target route type corresponding to the target user's driving style can be determined. After determining the route type of each travel activity based on the activity-related information of each travel activity, the travel activity whose route type is the same as the target route type can be selected from multiple travel activities as the target travel activity.

[0163] In one example, the process for determining the route type based on activity-related information can be described below. Since the activity-related information includes at least travel route information, the location of the travel route can be determined based on this information. After collecting information about the surrounding environment of the travel route, the route type corresponding to the travel activity can be determined.

[0164] In one example, route information and surrounding environment information can indicate real-world information regarding the driving pleasure, safety, and surrounding amenities of the route. This information may include, but is not limited to, the following: the number of curves, gradient changes, elevation gain, route curvature, route length, terrain changes, road conditions, number and quality of tourist attractions, historical or cultural landmarks, natural landscapes and biodiversity, road width, roadside warning signs, clarity of roadside warning signs, availability of emergency lanes, street lighting conditions, nighttime visibility, route maintenance (e.g., whether the road surface is regularly maintained, whether it is an open road, whether there is a risk of rockfalls), signal coverage, accessibility and remoteness (indicating the distance of the route from the nearest major city or main transportation line, vehicle range and refueling capabilities, etc.), adaptability (indicating the adaptability of the route under different weather conditions, such as whether the route is prone to landslides or flooding during the rainy season, and whether there is snow or ice in winter), traffic flow (indicating whether the route is prone to congestion), hotel facilities, dining options, and entertainment options.

[0165] After determining the collected field information, a second parameter can be determined based on this information. This second parameter can be used to determine the route type. The second parameter may include, but is not limited to, the following information: route length, route curvature, total number of curves, length of curves, total number of consecutive curves, elevation difference, scenic spots (including the number of natural landscapes, historical and cultural sites, etc.), route maintainability, route adaptability, traffic flow, and terrain changes (e.g., terrain can be mountains, plains, hills, etc.).

[0166] Before determining the route type based on the second parameter, the second parameter can be processed in a hierarchical manner. For example, the route length can be divided into short, medium-short, medium-long, and long (e.g., 0-20KM is short; 20-100KM is medium-short; 100-300KM is medium-long; and over 300KM is long). The route curvature can be divided into low, medium, and high (e.g., average radius of curvature greater than 500m is low; average radius of curvature 200-500m is medium; and average radius of curvature less than 200m is high). The total number of curves can be divided into few, medium, and many (e.g., 0-20 curves is few; and 20-100 curves is medium). The route is categorized as follows: Total number of curves greater than 100 (high); Curve length categorized as short, medium, and long (e.g., curves less than 100m are short; 100-300m are medium; curves greater than 300m are long); Number of consecutive curves categorized as few, medium, and many (e.g., 0-5 consecutive curves are few; 5-20 consecutive curves are medium; more than 20 consecutive curves are high); Elevation difference categorized as small, medium, and large (e.g., 0-100m difference is small; 100-500m difference is medium; more than 500m difference is large); Natural scenery... The number of natural landscapes is categorized as low, medium, and high (indicating the number of natural landscapes per kilometer; less than 3 natural landscapes per 10 kilometers is considered low; 3-10 natural landscapes per 10 kilometers is considered medium; and more than 10 natural landscapes per 10 kilometers is considered high). The number of historical and cultural landscapes is also categorized as low, medium, and high (indicating the number of historical and cultural landscapes per kilometer; less than 1 historical and cultural landscape per 10 kilometers is considered low; 1-3 historical and cultural landscapes per 10 kilometers is considered medium; and more than 3 historical and cultural landscapes per 10 kilometers is considered high). Route maintainability is categorized as poor, medium, and excellent (e.g., if the road surface has many potholes, is unpaved, or is severely aged). The road surface is classified as follows: Heavy damage is considered poor; occasional road surface damage is considered medium; smooth and regularly maintained road surface is considered excellent. Route adaptability is classified as low, medium, and high (e.g., if suitable for specific vehicles and less than 100 days of travel per year, it is low; if suitable for most vehicles and 100-200 days of travel per year, it is medium; if suitable for all vehicles and more than 200 days of travel per year, it is high). Route traffic flow is classified as low, medium, and high (e.g., if less than 50 vehicles per hour, it is low; if 50-200 vehicles per hour, it is medium; if more than 200 vehicles per hour, it is high). Terrain variation is classified as low, medium, and high (e.g., if the terrain includes plains, hills, and mountains, it is low).If the terrain includes two of the following: plains, hills, and mountains, it is classified as medium; if the terrain includes more than two of the following: plains, hills, and mountains, it is classified as high. It should be noted that the values ​​used to classify the second parameter here are only illustrative and not fixed. These values ​​can be adjusted according to the actual application scenario, and will not be listed in detail here.

[0167] After determining the second parameter and the multiple levels corresponding to each second parameter, parameter scores can be preset for each level corresponding to each second parameter. For example, for the multiple levels corresponding to route length: short, medium-short, medium-long, and long, the parameter score corresponding to short route length can be preset to 3; the parameter score corresponding to medium-short route length to 5; the parameter score corresponding to medium-long route length to 7; and the parameter score corresponding to long route length to 10, etc. Here, the preset scores for each level corresponding to each second parameter are not limited, as long as they are feasible.

[0168] Then, based on the road condition characteristics of each route type, the parameter weights corresponding to the second parameter under each route type can be set. At this time, higher parameter weights can be set for the critical second parameter that affects the route type, and lower parameter weights can be set for the non-critical second parameter, thereby improving the accuracy of the determined route type. For example, for the relaxed cruising type, based on road conditions, the number of natural landscapes, route maintainability, route adaptability, and route traffic flow in the second parameter can be assigned higher weights, while the other second parameters have lower weights. For the urban exploration type, based on road conditions, the number of historical and cultural landscapes, route traffic flow, route adaptability, and route maintainability in the second parameter can be assigned higher weights, while the other second parameters have lower weights. For the mountain running type, based on road conditions, the route curvature, total number of curves, route curve length, number of consecutive curves, route elevation difference, and terrain changes in the second parameter can be assigned higher weights, while the other second parameters have lower weights. For the adventure journey type, based on road conditions, the route length, number of natural landscapes, and terrain changes in the second parameter can be assigned higher weights, while the other second parameters have lower weights, and so on. Here, the number and type of key parameters affecting the route type are not limited, nor are the weights of each second parameter specifically limited, but are determined based on actual needs.

[0169] After determining the parameter scores and weights of each second parameter, the route type score of each travel activity can be determined under each preset route type based on the activity-related information of each travel activity. At this point, the preset route type corresponding to the highest route type score can be determined as the route type of the travel route corresponding to the travel activity.

[0170] This implementation method, after determining the target user's driving style based on the user's historical driving data, can identify the target route type corresponding to the target user's driving style from the preset driving styles. Thus, based on the route type corresponding to the travel activity, the target travel activity can be determined, thereby identifying a target travel interaction that is more compatible with the user's driving style. This not only improves the user's travel comfort but also enhances the user's travel safety.

[0171] In one possible implementation, the activity score involved in any of the above implementations is determined based on at least one of a first score, a second score, and a third score. The first score indicates a travel route score; the second score indicates a travel time score; and the third score indicates a travel distance score.

[0172] In one example, the activity score can be determined by weighted summation of the first, second, and third scores.

[0173] In another example, the activity score can be determined by weighting and summing at least one of the first, second, and third scores based on the user's actual needs. For instance, if the user does not consider the distance between their current location and the starting point of their travel route, the activity score can be determined based on the first and second scores.

[0174] In this implementation, activity scores can be determined from multiple aspects, making the determined activity scores more comprehensive and accurate, thereby improving the reliability and credibility of the activity scores and better assisting users in determining their desired travel activities.

[0175] In one example, the travel route score indicated by the first score can be determined according to the following steps: First, obtain the target user's driving style and obtain route-related information for the travel activity, wherein the route-related information is used to indicate the information around the travel route corresponding to the travel activity; then, determine the calculated value corresponding to each preset information based on the activity-related information and the route-related information; next, determine the calculated weight corresponding to each preset information based on the target user's driving style; finally, determine the travel route score based on each preset information, the calculated value, and the calculated weight.

[0176] In one example, the preset information can indicate at least part of the second parameter mentioned above, the calculated value can indicate the parameter score mentioned above, the calculated weight can indicate the parameter weight mentioned above, and the travel route score can indicate the route type score mentioned above, which will not be elaborated on here.

[0177] In one example, the travel time score indicated by the second score can be determined according to the following steps: first, determine the difference between the start time of the travel activity and the current time, and then determine the travel time score based on this difference. If the unit of the difference information is seconds, the difference information can be determined using the following formula (1). It should be noted that the unit of the difference information can also be minutes, hours, etc. After changing the unit of the difference information, the size of the divisor in the calculation formula of the difference information can be adaptively adjusted, which will not be described in detail here.

[0178]

[0179] Then, the travel time score can be determined based on the difference information, as shown in formula (2) below.

[0180]

[0181] In one example, the travel distance score indicated by the third rating can be determined by the following steps: first, determining the distance between the user's location (i.e., the location of the target device) and the target location of the travel activity (e.g., the starting point of the route), and then determining the travel distance score based on that distance.

[0182] For example, if the distance between the user's location (i.e. the location of the target device) and the target location of the travel activity (e.g., the starting point of the route) is D, then the travel distance score can be expressed as the following formula (3).

[0183]

[0184] In one possible implementation, the activity score can also indicate the evaluation score of users who have already traveled. The method of determining the activity score is not limited here, but is based on the ability to better identify travel activities that meet the actual needs of users.

[0185] In one possible implementation, the target travel activity determined according to any of the above implementation methods / exemplary methods may also satisfy at least one of the following: the distance between the current location of the target device and the route location of the target travel activity is less than a preset distance; or, the weather conditions in the region where the target travel activity is located meet preset weather requirements at the travel time corresponding to the target travel activity; or, the road conditions between the current location of the target device and the starting point of the route of the target travel activity meet preset road condition requirements.

[0186] In one example, the route location can indicate the starting point of the route, the ending point of the route, or any location between the starting point and the ending point of the route; no specific limitation is made here.

[0187] In one example, the preset weather requirement can indicate the pre-set weather conditions, such as sunny, cloudy, light rain, light wind, etc., or the preset weather requirement can also indicate the temperature, such as the temperature being between 15 and 25 degrees Celsius, or the preset weather requirement can also indicate that the weather is not extreme, such as heavy rain or heavy snow. There are no limitations on the preset weather requirement here.

[0188] In one example, preset road condition requirements could indicate road surface maintainability and / or route traffic flow, etc.

[0189] In this case, the recommended target travel activities can be those that enable timely and efficient travel, thereby improving the accuracy and effectiveness of the recommended target travel activities.

[0190] In one possible implementation, the activity-related information includes at least travel route information; the travel route information includes at least a route start point and a route end point; in this case, the different target travel activities determined according to any of the above implementation methods / exemplary embodiments satisfy the following: at least one of the route start point and the route end point is different.

[0191] This allows different target travel activities to have different route origins and / or route destinations, thereby increasing the richness and diversity of target travel activities.

[0192] S203. Based on the activity-related information for each target travel activity, determine the activity recommendation information.

[0193] In one example, the activity recommendation information may indicate an overall activity information, or an activity summary information, or some activity-related information, etc. In this case, the activity recommendation information may include at least one of the following: activity theme, activity name, activity time, activity location (including at least one of country, province, and city information), activity image, etc.

[0194] S204. Send activity recommendation information for at least one target travel activity; or, display activity recommendation information for at least one target travel activity.

[0195] In one example, activity recommendation information can be sent to the target device via SMS, notification, or other means. Alternatively, activity recommendation information for at least one target travel activity can be displayed directly on the display interface of the target device.

[0196] In one example, when displaying activity recommendations for at least one target travel activity, the activity recommendations for each target travel activity can be directly displayed on the display interface corresponding to the target device. See also Figure 3 , Figure 3This is a schematic diagram illustrating a recommendation of at least one target travel activity, provided as an embodiment of this application. Figure 3 As shown, the main recommendation area in the recommended "Activities" display interface can display activity recommendations for the first target travel activity, and the other recommendation areas below the main recommendation area can display activity recommendations for the second, third, and fourth target travel activities.

[0197] In one example, while displaying activity recommendations for at least one target travel activity, it is also possible to display various activity themes on the display interface corresponding to the target device, and display activity recommendations for one or more target travel activities under each activity theme. See also Figure 4 , Figure 4 This is a schematic diagram illustrating another recommended target travel activity provided in an embodiment of this application. (See diagram below.) Figure 4 As shown, in the main recommendation area of ​​the recommended "Activities" display interface, the first activity theme is displayed, followed by the activity recommendation information for the first target travel activity. After that, in other recommendation areas below the main recommendation area, the activity recommendation information for the second activity theme and the second target travel activity under the second activity theme, the activity recommendation information for the third activity theme and the third target travel activity under the third activity theme, and the activity recommendation information for the fourth target travel activity can be displayed.

[0198] This implementation method allows users to gain an initial understanding of the event content through event recommendation information, while saving browsing time and improving browsing efficiency.

[0199] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0200] Figure 5 This is a schematic diagram of the structure of a travel activity recommendation device provided in an embodiment of this application, as shown below. Figure 5 As shown, the travel activity recommendation device 500 includes:

[0201] The acquisition unit 501 is used to acquire activity-related information for multiple travel activities; wherein, the activity-related information is used to guide multiple users to travel at the same time.

[0202] The determining unit 502 is used to select at least one travel activity as the target travel activity from multiple travel activities based on activity-related information.

[0203] Recommendation unit 503 is used to recommend at least one target travel activity.

[0204] Figure 6 This is a schematic diagram of another travel activity recommendation device provided in an embodiment of this application, as shown below. Figure 6 As shown, the travel activity recommendation device 600 includes:

[0205] The acquisition unit 601 is used to acquire activity-related information for multiple travel activities; wherein, the activity-related information is used to guide multiple users to travel at the same time.

[0206] The determining unit 602 is used to select at least one travel activity as the target travel activity from multiple travel activities based on activity-related information.

[0207] Recommendation unit 603 is used to recommend at least one target travel activity.

[0208] In one possible implementation, the determining unit 602 is configured to:

[0209] Based on activity-related information, determine the activity score corresponding to each travel activity;

[0210] Based on the activity score, at least one travel activity is selected as the target travel activity from multiple travel activities.

[0211] In one possible implementation, the target travel activity satisfies at least one of the following:

[0212] The activity score corresponding to any target travel activity is greater than a preset threshold;

[0213] Alternatively, the activity score corresponding to any target travel activity ranks among the top N in the activity scores corresponding to multiple travel activities, where N is a preset integer greater than or equal to 1.

[0214] In one possible implementation, the determining unit 602 is configured to:

[0215] Based on the relevant information about the activities, determine the activity type corresponding to each travel activity;

[0216] Based on the activity type corresponding to each travel activity, multiple travel activities are classified to obtain multiple activity groups; each activity group includes at least one travel activity.

[0217] Select at least one travel activity from the at least one travel activity included in each activity group as the target travel activity.

[0218] In one possible implementation, at least one target travel activity is recommended, including:

[0219] Recommend at least some of the activity groups, as well as the target travel activities included in the recommended activity groups.

[0220] In one possible implementation, the target travel activity satisfies at least one of the following:

[0221] The activity score corresponding to any target travel activity is greater than a preset threshold;

[0222] Alternatively, the activity score corresponding to the target travel activity ranks among the top M travel activities in the activity group, where M is a preset integer greater than or equal to 1.

[0223] In one possible implementation, the activity-related information indicates the activity details of the travel activity; the determining unit 602 is used for:

[0224] Based on at least one activity detail indicated by the activity-related information, determine the activity type corresponding to each travel activity.

[0225] In one possible implementation, the activity-related information includes at least travel route information; the travel route information is used to determine the route type corresponding to the travel activity; the device is also used to:

[0226] Obtain the driving style of the target user;

[0227] Based on the preset correspondence between driving style and route type, determine the target route type corresponding to the driving style of the target user;

[0228] Based on travel route information and target route type, at least one travel activity is selected as the target travel activity from multiple travel activities; wherein, the route type of the travel route corresponding to the target travel activity matches the target route type.

[0229] In one possible implementation, the target travel activity satisfies at least one of the following:

[0230] The distance between the current location of the target device and the route location of the target travel activity is less than a preset distance;

[0231] Alternatively, the weather conditions in the region where the target travel activity is located meet the preset weather requirements at the travel time corresponding to the target travel activity;

[0232] Alternatively, the road conditions between the current location of the target device and the starting point of the route for the target travel activity meet the preset road condition requirements.

[0233] In one possible implementation, the activity-related information includes at least travel route information; the travel route information includes at least a route origin and a route destination; different target travel activities satisfy the following condition: at least one of the route origin and route destination is different.

[0234] In one possible implementation, the recommending unit 603 is used for:

[0235] Based on the activity-related information for each target travel activity, activity recommendation information is determined;

[0236] Send activity recommendation information for at least one target travel activity; or display activity recommendation information for at least one target travel activity.

[0237] In one possible implementation, the activity score is determined based on at least one of a first score, a second score, and a third score; wherein the first score indicates a travel route score; the second score indicates a travel time score; and the third score indicates a travel distance score.

[0238] In one possible implementation, the device further includes a scoring unit 604 for determining a travel route score based on the following steps:

[0239] The system obtains the target user's driving style and route-related information for travel activities; the route-related information is used to indicate the information surrounding the travel route corresponding to the travel activity.

[0240] Based on activity-related information and route-related information, determine the calculated values ​​corresponding to each preset information;

[0241] Based on the driving style of the target user, determine the calculation weight corresponding to each preset information;

[0242] The travel route score is determined based on the preset information, calculated values, and calculated weights.

[0243] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 7 As shown, the electronic device 700 includes: a memory 701 and a processor 702.

[0244] Memory 701; a memory used to store computer-executed instructions in processor 702.

[0245] The processor 702 is configured to perform the method provided in the above embodiments.

[0246] The electronic device also includes a receiver 703 and a transmitter 704. The receiver 703 is used to receive instructions and data sent by an external device, and the transmitter 704 is used to send instructions and data to an external device.

[0247] See Figure 8 , Figure 8 This application provides a schematic diagram of the structure of a vehicle, as shown in the embodiment of the present application. Figure 8 As shown, the vehicle includes Figure 7 The electronic device shown.

[0248] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, perform the steps of the travel activity recommendation method described in the above method embodiments. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0249] This application also provides a computer program product that carries computer execution instructions. The computer execution instructions include instructions that can be used to execute the steps of the travel activity recommendation method in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0250] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0251] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0252] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0253] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0254] When an integrated unit / module is implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0255] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0256] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0257] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0258] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for recommending travel activities, characterized in that, Applied to a target device; the method includes: Obtain activity-related information for multiple travel activities; wherein, the activity-related information is used to guide multiple users to travel simultaneously; Based on the activity-related information, at least one of the multiple travel activities is selected as the target travel activity; Recommend at least one of the aforementioned target travel activities.

2. The method according to claim 1, characterized in that, The step of selecting at least one of the multiple travel activities as the target travel activity based on the activity-related information includes: Based on the activity-related information, determine the activity score corresponding to each of the travel activities; Based on the activity score, at least one of the multiple travel activities is selected as the target travel activity.

3. The method according to claim 2, characterized in that, The target travel activity satisfies at least one of the following: The activity score corresponding to any of the target travel activities is greater than a preset threshold; Alternatively, the activity score corresponding to any of the target travel activities shall rank among the top N in the activity scores corresponding to the plurality of travel activities, where N is a preset integer greater than or equal to 1.

4. The method according to claim 1, characterized in that, The step of selecting at least one of the multiple travel activities as the target travel activity based on the activity-related information includes: Based on the activity-related information, determine the activity type corresponding to each of the travel activities; Based on the activity type corresponding to each of the aforementioned travel activities, the multiple travel activities are classified to obtain multiple activity groups; wherein each activity group includes at least one travel activity; Select at least one of the travel activities included in each of the activity groups as the target travel activity.

5. The method according to claim 4, characterized in that, The recommendation of at least one of the target travel activities includes: Recommend at least some of the activity groups described, as well as the target travel activities included in the recommended activity groups.

6. The method according to claim 4, characterized in that, The target travel activity satisfies at least one of the following: The activity score corresponding to any of the target travel activities is greater than a preset threshold; Alternatively, the activity score corresponding to the target travel activity ranks among the top M travel activities in the activity group to which it belongs, where M is a preset integer greater than or equal to 1.

7. The method according to claim 4, characterized in that, The activity-related information indicates the details of the travel activity; The process of determining the activity type corresponding to each travel activity based on the activity-related information includes: Based on at least one of the activity details indicated by the activity-related information, the activity type corresponding to each of the travel activities is determined.

8. The method according to claim 1, characterized in that, The activity-related information includes at least travel route information; the travel route information is used to determine the route type corresponding to the travel activity. The method further includes: Obtain the driving style of the target user; Based on the preset correspondence between driving style and route type, determine the target route type corresponding to the driving style of the target user; Selecting at least one of the multiple travel activities as the target travel activity includes: Based on the travel route information and the target route type, at least one of the multiple travel activities is selected as the target travel activity; wherein the route type of the travel route corresponding to the target travel activity matches the target route type.

9. The method according to any one of claims 1 to 8, characterized in that, The target travel activity satisfies at least one of the following: The distance between the current location of the target device and the route location of the target travel activity is less than a preset distance; Alternatively, the weather conditions in the region where the target travel activity is located meet the preset weather requirements at the travel time corresponding to the target travel activity; Alternatively, the road conditions between the current location of the target device and the starting point of the route for the target travel activity meet the preset road condition requirements.

10. The method according to any one of claims 1 to 8, characterized in that, The activity-related information includes at least travel route information; the travel route information includes at least a route start point and a route end point; different target travel activities satisfy the following condition: at least one of the route start point and the route end point is different.

11. The method according to claim 1, characterized in that, The recommendation of at least one of the target travel activities includes: Based on the activity-related information of each of the aforementioned target travel activities, activity recommendation information is determined; Send activity recommendation information for at least one of the target travel activities; or display activity recommendation information for at least one of the target travel activities.

12. The method according to any one of claims 2, 3 or 6, characterized in that, The activity rating is determined based on at least one of a first rating, a second rating, and a third rating; wherein the first rating indicates a travel route rating; the second rating indicates a travel time rating; and the third rating indicates a travel distance rating.

13. The method according to claim 12, characterized in that, The travel route score is determined based on the following steps: The system obtains the target user's driving style and route-related information for the travel activity; wherein the route-related information is used to indicate information around the travel route corresponding to the travel activity. Based on the activity-related information and the route-related information, determine the calculated values ​​corresponding to each preset information; Based on the driving style of the target user, determine the calculation weight corresponding to each of the preset information; The travel route score is determined based on the preset information, the calculated values, and the calculated weights.

14. A travel activity recommendation device, characterized in that, include: An acquisition unit is used to acquire activity-related information for multiple travel activities; wherein, the activity-related information is used to guide multiple users to travel simultaneously; A determining unit is configured to select at least one of the multiple travel activities as the target travel activity based on the activity-related information. A recommendation unit is used to recommend at least one of the target travel activities.

15. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the travel activity recommendation method as described in any one of claims 1 to 13.

16. A vehicle, characterized in that, The vehicle includes the electronic equipment as described in claim 15.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the travel activity recommendation method as described in any one of claims 1 to 13.

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