Social interaction method and system, storage medium and vehicle

Abstract

The invention provides a social interaction method and system, a storage medium and a vehicle, and belongs to the technical field of vehicles, and the social interaction method comprises the steps: obtaining first interaction information between a first vehicle and a first user in a driving cycle in which an intelligent driving system is started; determining a social label of the first user based on the first interaction information; and executing a social action associated with the first user based on the social tag of the first user. According to the method, the social preference of the first user is speculated through the first interaction information between the first user and the first vehicle, so that the social tag capable of representing the social preference of the first user is determined, the executed social action is ensured to conform to the social preference of the first user, and the user experience is improved. Therefore, the first user can carry out social contact conforming to the social contact preference of the first user without paying energy except for driving the vehicle, and the social contact interaction convenience of the vehicle user is finally improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and more specifically, to a social interaction method, system, storage medium, and vehicle. Background Art

[0002] With the development of vehicles, people's living radius has also expanded. The expanded urban living radius has further spawned new social modes such as cross-city gatherings and self-driving tours. The emergence of these new social modes has made vehicles a complex life carrier that combines tool attributes with social value.

[0003] However, current social platforms do not take into account the impact of vehicles on people's social lives, and therefore lack a method for social interaction that is convenient for vehicle users. Summary of the Invention

[0004] Based on this, the present application provides a social interaction method, system, storage medium and vehicle to solve the problem of how to improve the convenience of social interaction for vehicle users.

[0005] According to a first aspect of an embodiment of the present application, a social interaction method is provided. The method is applied to a first vehicle, wherein the first vehicle is provided with an intelligent driving system. The method includes: Obtaining first interaction information between the first vehicle and a first user within a driving cycle in which the intelligent driving system is enabled; Determining a social tag of the first user based on the first interaction information; Based on the social tag of the first user, a social action associated with the first user is performed.

[0006] Optionally, the first interaction information includes at least one of an intervention frequency, a takeover duration, a driving control duration of the intelligent driving system at a target confidence level, and an activation frequency of the intelligent driving system in a target environment type; Among them, the intervention frequency is the frequency of the first user intervening in the driving control behavior of the intelligent driving system, and the takeover duration is the time it takes the first user to respond to the takeover request issued by the first vehicle.

[0007] Optionally, the step of obtaining the driving control time of the intelligent driving system at a target confidence level includes: Obtaining the confidence of the intelligent driving system at multiple moments; Based on the confidence levels at the multiple moments, a driving control duration of the intelligent driving system at a target confidence level is determined.

[0008] Optionally, determining the social tag of the first user based on the first interaction information includes: Determining a target condition that the first interaction information meets from a plurality of preset conditions, wherein the plurality of preset conditions respectively correspond to at least one preset tag; The preset tag corresponding to the target condition is determined as the social tag of the first user.

[0009] Optionally, before determining the target condition that the first interaction information meets from a plurality of preset conditions, the method further includes: Acquire second interaction information between a plurality of second vehicles and corresponding second users, where the second vehicles are other vehicles than the first vehicle; Based on the second interaction information, a plurality of the preset conditions are determined.

[0010] Optionally, the first interaction information includes sub-interaction information generated by the first vehicle in different environment types, and determining the social tag of the first user based on the first interaction information includes: Clustering the plurality of sub-interaction information according to different types of environments in which the first vehicle is located when each piece of the sub-interaction information is generated, to obtain a plurality of information sets corresponding to different types of environments, each of the information sets including at least one piece of the sub-interaction information; Determining, based on the plurality of information sets, social tags corresponding to the first user and the different environment types; The performing a social action associated with the first user based on the social tag of the first user includes: Based on the social tags of the first user corresponding to the different environment types, a social action associated with the first user is performed.

[0011] Optionally, the social action includes matching a target social object for the first user, and performing the social action associated with the first user based on the social tag of the first user includes: Acquire multiple social objects to be matched, each of the multiple social objects to be matched corresponding to at least one social tag; Based on the social tag of the social object to be matched and the social tag of the first user, a target social object that matches the first user is determined from the plurality of social objects to be matched.

[0012] According to a second aspect of an embodiment of the present application, a social interaction system is provided. The social interaction system is applied to a first vehicle, the first vehicle being provided with an intelligent driving system, and the social interaction system includes: an acquisition module, configured to acquire first interaction information between the first vehicle and a first user within a driving cycle in which the intelligent driving system is enabled; a determination module, configured to determine a social tag of the first user based on the first interaction information; An execution module is configured to execute a social action associated with the first user based on the social tag of the first user.

[0013] According to a third aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the steps of the social interaction method described in the second aspect of the present application are implemented.

[0014] In a fourth aspect of an embodiment of the present application, a vehicle is provided, comprising the social interaction system described in the second aspect of the embodiment of the present application, or comprising a control module, wherein the control module is used to implement the steps of the social interaction method described in the first aspect of the embodiment of the application.

[0015] The present application provides a social interaction method, system, storage medium and vehicle, the method comprising: obtaining first interaction information between the first vehicle and a first user within a driving cycle in which the intelligent driving system is enabled; determining a social tag of the first user based on the first interaction information; and performing a social action associated with the first user based on the social tag of the first user.

[0016] This application is directed to a first vehicle equipped with an intelligent driving system. The application determines a social tag based on first interaction information between the first vehicle and a first user during a driving cycle in which the intelligent driving system is enabled, and then executes a social action associated with the first user based on the first user's social tag. This application infers the first user's social preferences based on the first interaction information between the first user and the first vehicle, thereby determining a social tag that can characterize the first user's social preferences to ensure that the executed social action is consistent with the first user's social preferences. This allows the first user to engage in social interactions consistent with their social preferences without having to expend any effort other than driving the vehicle, ultimately improving the convenience of social interaction for vehicle users. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 This is a step diagram of a social interaction method provided by an embodiment of the present application; Figure 2 This is a step diagram of a method for determining driving control time provided by an embodiment of the present application; Figure 3 This is a step diagram of a method for determining social tags provided by an embodiment of the present application; Figure 4 This is a step diagram of a method for determining a preset condition provided in an embodiment of the present application; Figure 5 This is another step diagram of a method for determining social tags provided by an embodiment of the present application; Figure 6 This is a step diagram of a method for performing a social action provided by an embodiment of the present application; Figure 7 This is a flow chart of a social interaction method provided by an embodiment of the present application; Figure 8 It is a structural diagram of a social interaction system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0020] With the development of vehicles, people's living radius has also expanded. The expanded urban living radius has further spawned new social modes such as cross-city gatherings and self-driving tours. The emergence of these new social modes has made vehicles a complex life carrier that combines tool attributes with social value.

[0021] However, current social platforms do not take into account the impact of vehicles on people's social lives, and therefore lack a method for social interaction that is convenient for vehicle users.

[0022] Based on this, in order to solve the problem of how to improve the convenience of social interaction for vehicle users, the present application provides a social interaction method, system, storage medium and vehicle. For a first vehicle equipped with an intelligent driving system, the social tag is determined through the first interaction information between the first vehicle and the first user within the driving cycle in which the intelligent driving system is enabled, and then the social action associated with the first user is performed based on the social tag of the first user. The present application infers the social preferences of the first user through the first interaction information between the first user and the first vehicle, thereby determining the social tags that can characterize the social preferences of the first user, so as to ensure that the executed social actions are consistent with the social preferences of the first user, so that the first user can engage in social activities consistent with his social preferences without having to spend any energy other than driving the vehicle, and ultimately achieve an improvement in the convenience of social interaction for vehicle users. The specific method is as follows: The first aspect of this application proposes an embodiment, such as Figure 1 As shown in the step diagram of a social interaction method, the method is applied to a first vehicle, which is provided with an intelligent driving system. The main steps include: Step S101: Acquire first interaction information between the first vehicle and a first user within a driving cycle in which the intelligent driving system is enabled.

[0023] An intelligent driving system uses sensors, controllers, actuators, and communication modules to assist the driver in controlling the vehicle, or to drive the vehicle on their behalf. Common intelligent driving systems include adaptive cruise control, automated parking systems, and autonomous driving systems.

[0024] A drive cycle is a repetitive sequence of various driving conditions over a specific time or distance, describing the vehicle's actual operating state. Whether a drive cycle is defined as a specific time or distance can be calibrated by technicians at the factory.

[0025] The first interaction information between the first vehicle and the first user includes information sent by the first vehicle to the first user for the purpose of interaction, as well as information sent by the first user to the first vehicle for the purpose of interaction. Specifically, it may include various warning messages or prompts sent by the first vehicle to the first user, as well as operations performed by the first user on the first vehicle, such as stepping on the brake pedal or turning the steering wheel. In an optional embodiment, the information can be collected using sensors such as a steering wheel angle sensor and a brake pedal opening sensor on the first vehicle.

[0026] In an optional embodiment, the first interaction information may be the number of times the first user takes over the first vehicle from the intelligent driving system, or the frequency with which the first user pays attention to the vehicle's driving dynamics and warning information. The frequency with which the first user pays attention to the vehicle's driving dynamics and warning information may be obtained by detecting the frequency with which the first user gazes at the instrument panel.

[0027] Step S102: Determine a social tag of the first user based on the first interaction information.

[0028] During a driving cycle in which the intelligent driving system is enabled, interactions between the first user and the first vehicle can be considered to be conducted by the first user under the influence of the intelligent driving system. For example, when the first user steps on the accelerator pedal while the intelligent driving system is enabled, this is because they are dissatisfied with the intelligent driving system's control of the first vehicle's speed. The intelligent driving system causing the first user to feel dissatisfied is considered an influence on the first user.

[0029] Therefore, the first interaction information represents the first user's intended control of the first vehicle under the influence of the intelligent driving system. This control intention is determined by factors such as the user's personality or driving habits, which can represent the first user's social preferences. Therefore, the social tag determined based on the first interaction information can represent the first user's social preferences.

[0030] In an optional embodiment, the social tag of the first user may be one or more of cautious supervision type, over-dependence type, risk preference type, scenario-specific dependence type, and extreme challenge type.

[0031] In an optional implementation, the first user's trust level in the intelligent driving system may be determined based on the first interaction information, and then the first user's social tag may be determined based on the first user's trust level in the intelligent driving system.

[0032] In an optional embodiment, the driving habits of the first user can also be identified through a neural network, and the driving behavior of the first user can be bound to the road characteristics to establish an association matrix of "environmental conditions-system status-user behavior" to determine the social tags of the first user.

[0033] Step S103: executing a social action associated with the first user based on the social tag of the first user.

[0034] The social action associated with the first user may be matching a target social object with the first user, or recommending social activities such as car friends gatherings, self-driving tours, etc. to the first user.

[0035] Taking the example of recommending social activities to the first user, step S103 will be described. Assuming that in step S102, the first user's social tag is determined to be risk-prone, then step S103 may recommend car gatherings initiated by other risk-prone users, or areas with challenging roads as destinations for self-driving tours.

[0036] This embodiment, for a first vehicle equipped with an intelligent driving system, determines a social tag based on first interaction information between the first vehicle and a first user during a driving cycle in which the intelligent driving system is enabled. Based on the first user's social tag, a social action associated with the first user is then executed. This embodiment infers the first user's social preferences based on the first interaction information between the first user and the first vehicle, thereby determining a social tag that characterizes the first user's social preferences. This ensures that the executed social action is consistent with the first user's social preferences, allowing the first user to engage in social interactions consistent with their social preferences without having to expend any effort beyond driving the vehicle, ultimately improving the convenience of social interaction for vehicle users.

[0037] In addition, since the first interaction information is the interaction information between the first user and the first vehicle when the intelligent driving system is enabled, the first user's risk preference and technical trust will be directly mapped to the interaction decision. At the same time, when the first user is socializing, it is also a process of interacting with other users. In this process, the first user is also constantly making interactive decisions. Therefore, determining the social tag based on the first interaction information is actually inferring the interaction decision of the first user when socializing with other users through the interaction decision of the first user when "socializing" with the first vehicle. This enables the social tag determined based on the first interaction information to accurately reflect the social preferences of the first user.

[0038] Assuming that the social tags of the first user are determined based on the operating condition information of the first vehicle when the intelligent driving system is not enabled (that is, the control information of the first vehicle when the first user manually drives the first vehicle), then because the operating condition information is only based on the one-way control of the first vehicle by the first user, and there is a lack of interactivity between the first user and the first vehicle, the operating condition information cannot accurately reflect the social preferences of the first user, and thus the social tags determined based on the operating condition information cannot accurately reflect the social preferences of the first user.

[0039] Therefore, the method described in the embodiments of the present application can not only ensure that the executed social actions are consistent with the social preferences of the first user, so that the first user can engage in social activities consistent with his or her social preferences without having to spend any energy other than driving the vehicle, ultimately improving the convenience of social interaction for vehicle users, but also more accurately reflect the user's social preferences and improve the user's social experience.

[0040] In some exemplary embodiments, the first interaction information includes at least one of an intervention frequency, a takeover duration, a driving control duration of the intelligent driving system at a target confidence level, and an activation frequency of the intelligent driving system in a target environment type; Among them, the intervention frequency is the frequency of the first user intervening in the driving control behavior of the intelligent driving system, and the takeover duration is the time it takes the first user to respond to the takeover request issued by the first vehicle.

[0041] Intervention frequency refers to the frequency with which the first user intervenes in the driving control behavior of the intelligent driving system. For example, if the first user steps on the brake pedal while the first vehicle is under the driving control of the intelligent driving system, it can be considered that the first user has intervened in the driving control behavior of the intelligent driving system. Similarly, if the user turns the steering wheel once, activates the turn signal once, or takes over manual driving, it can also be considered an intervention.

[0042] The intervention frequency can be characterized by the number of interventions performed by the first user per unit time. A higher intervention frequency indicates that the first user is less satisfied with the driving behavior of the intelligent driving system and has a more cautious social preference. Conversely, a lower intervention frequency indicates a more casual social preference.

[0043] The takeover duration is the time it takes the first user to respond to a takeover request from the first vehicle. A takeover request is a request sent by the first vehicle to the first user to take over control of the first vehicle while the first vehicle is under the control of the intelligent driving system. In actual measurement, the takeover duration can be the time from the moment the takeover request is sent to the moment the first user actually takes over.

[0044] The target confidence is the target value of the confidence of the intelligent driving system. Among them, the confidence of the intelligent driving system refers to the deterministic quantitative evaluation of the perception, decision-making or control results by its algorithm, which reflects the system's internal judgment on the reliability of its own behavior. The higher the confidence, the better the control of the vehicle by the intelligent driving system and the safer the driving state of the vehicle; otherwise, the more dangerous it is. In an optional embodiment, the target confidence may be below 0.6, and the driving control time of the intelligent driving system at the target confidence is the driving control time of the intelligent driving system at a confidence level below 0.6. If the driving control time of the intelligent driving system at a confidence level below 0.6 is greater than 30 seconds, it can be determined that the social tag of the first user is risk-preferring; otherwise, it can be determined that the social tag of the first user is ordinary.

[0045] The environment type refers to the type of environment in which the first vehicle is located. The environment type can be different according to different classification criteria. For example, according to weather conditions, the environment type can be a sunny environment, a rainy environment, and a snowy environment; according to the different roads traveled, the environment type can be a highway environment, an urban road environment, and a rural road environment. The target environment type can be any one of a variety of environment types. In addition, in addition to classifying environment types according to weather conditions and road types, it can also be classified according to traffic signs, slope information, etc., which will not be elaborated in this application.

[0046] In an optional embodiment, the first interaction information may be the intervention frequency and takeover duration, or the driving control duration of the intelligent driving system at the target confidence level and the activation frequency of the intelligent driving system in the target environment type, or simply the intervention frequency.

[0047] In an optional implementation, the first interaction information may further include a following distance setting preference or a speed limit setting set by the first user on the first vehicle.

[0048] This embodiment determines the first user's social tag by using intervention frequency or takeover duration. This removes external interference, forms a quantifiable and comparable behavioral baseline, and provides an objective basis for determining social tags. Furthermore, the duration of driving control at the target confidence level or the frequency of activation in the target environment type directly correlates to the first user's risk decision-making pattern. Therefore, by determining a user's social tag using the first interaction information composed of this information, a more comprehensive feature matrix can be constructed, thereby improving the accuracy of social tag determination.

[0049] In some exemplary embodiments, referring to Figure 2 A method for determining a driving control duration is shown in the figure, wherein the steps for obtaining the driving control duration of the intelligent driving system under a target confidence level specifically include the following: Step S11: Obtain the confidence of the intelligent driving system at multiple moments.

[0050] Step S12: determining the driving control duration of the intelligent driving system at a target confidence level based on the confidence levels at the multiple moments.

[0051] First, the intelligent driving system's perception and decision-making modules are used to obtain and record the confidence levels of the intelligent driving system at different moments. Then, at least one target moment with the same confidence level as the target confidence level is selected from these multiple moments. Finally, the distribution of these target moments along the timeline is statistically analyzed. Based on this distribution, the driving control duration of the intelligent driving system at the target confidence level is determined.

[0052] For example, the confidence level of the intelligent driving system at 11:30 is 0.7, the confidence level at 11:40 is 0.7, the confidence level at 11:50 is 0.6, and the confidence level at 11:30 is 0.5. If the target confidence level is 0.7, then among the confidence levels of the intelligent driving system at multiple moments, the moments at which the confidence level and the target confidence level have the same value are 11:30 and 11:40. From this, it can be inferred that the confidence level of the intelligent driving system is 0.7 during the time period between 11:30 and 11:40 on the timeline. Therefore, it can be determined that the driving control time of the intelligent driving system at the target confidence level of 0.7 is 10 minutes.

[0053] This embodiment determines the driving control time of the intelligent driving system at the target execution degree through the confidence of the intelligent driving system at multiple moments, which can reduce the monitoring frequency of the confidence level, thereby reducing the vehicle resources required to obtain the driving control time and improving the vehicle's resource utilization.

[0054] In some exemplary embodiments, referring to Figure 3 The method for determining social tags is shown in the step diagram. In step S102, the social tags of the first user are determined based on the first interaction information. Specifically, the following steps may be included: Step S21: Determine a target condition that the first interaction information meets from a plurality of preset conditions.

[0055] The plurality of preset conditions respectively correspond to at least one preset label.

[0056] Step S22: determining the preset tag corresponding to the target condition as the social tag of the first user.

[0057] When the first interactive information is at least one of the intervention frequency, the takeover duration, the driving control duration of the intelligent driving system at the target confidence level, and the activation frequency of the intelligent driving system in the target environment type, the preset condition can specifically be a preset numerical range.

[0058] Taking the takeover duration as the first interaction information as an example, assuming that multiple preset numerical intervals are (0s, 1s], (1s, 3s], (3s, +∞), among which the preset label corresponding to (0s, 1s] is cautious supervision type, the preset label corresponding to (1s, 3s] is ordinary type, and the preset label corresponding to (3s, +∞) is over-dependence type. If it is detected that the takeover duration of the first user is 2s, then since the takeover duration is within the preset interval (1s, 3s], it can be considered that the target condition met by the first interaction information is (1s, 3s]. In this case, the preset label corresponding to (1s, 3s] is ordinary type, so the social label of the first user is determined to be ordinary type.

[0059] This embodiment determines the social tag of the first user based on the target condition met by the first interaction information, so that the social tag of the first user can be determined in a quantitative manner, thereby improving the standardization of the social tag determination process.

[0060] In some exemplary embodiments, referring to Figure 4 The diagram shows a method for determining a preset condition. Before determining, in step S21, a target condition that the first interaction information meets from a plurality of preset conditions, the method further includes the following steps: Step S23: obtaining second interaction information between the plurality of second vehicles and the corresponding second users.

[0061] The second vehicle is a vehicle different from the first vehicle.

[0062] Step S24: determining a plurality of preset conditions based on the second interaction information.

[0063] The second vehicle is a different vehicle than the first vehicle, and the second vehicle may also be equipped with an intelligent driving system. The second interaction information may specifically be interaction information between the second vehicle and the second user during a driving cycle in which the intelligent driving system is enabled. The second interaction information may include at least one of the frequency with which the second user intervenes in the driving control behavior of the intelligent driving system, the duration of the second user's response to a takeover request from the second vehicle, the duration of driving control of the second vehicle's intelligent driving system at a target confidence level, and the activation frequency of the second vehicle's intelligent driving system in a target environment type.

[0064] The second interaction information between multiple second vehicles and their corresponding second users can be considered a criterion for evaluating the first user's social preferences. For example, if the second interaction information shows that 90% of the second users' takeovers lasted less than 2 seconds, then if the first user's takeovers lasted longer than 2 seconds, then the user might be considered overly dependent. If the second interaction information shows that 90% of the second users' takeovers lasted less than 1 second, then if the first user's takeovers lasted longer than 1 second, then the user might be considered overly dependent.

[0065] Based on the above analysis, it can be seen that this embodiment determines the preset conditions through the second interaction information between multiple second vehicles and the corresponding second users, which can make the setting of the preset conditions more reasonable, thereby improving the accuracy of determining the social tags of the first user.

[0066] In some exemplary embodiments, referring to Figure 5In another method for determining social tags, the first interaction information includes sub-interaction information generated by the first vehicle in different environment types. Step S102, determining the social tag of the first user based on the first interaction information, may further include the following steps: Step S31 : clustering the plurality of sub-interaction information according to the different types of environments in which the first vehicle is located when each piece of the sub-interaction information is generated, to obtain a plurality of information sets corresponding to different types of environments.

[0067] The information set includes at least one piece of sub-interaction information.

[0068] Step S32: determining, based on the plurality of information sets, social tags of the first user corresponding to the different environment types.

[0069] Step S103 may specifically be: executing a social action associated with the first user based on the social tags corresponding to the first user and the different environment types.

[0070] The first interaction information may include sub-interaction information generated by the first vehicle in different environment types. For example, the first interaction information may include sub-interaction information A generated by the first vehicle in a highway environment, sub-interaction information B generated in an urban road environment, and sub-interaction information C generated in a rural road environment.

[0071] If sub-interaction information A, sub-interaction information B and sub-interaction information C are clustered according to step S31, then based on the different types of environments in which the first vehicle is located when the three are generated, information set A including sub-interaction information A, information set B including sub-interaction information B and information set C including sub-interaction information C can be obtained.

[0072] Afterwards, based on the sub-interaction information A in the information set A, the social tags corresponding to the first user and the highway environment are determined; based on the sub-interaction information B in the information set B, the social tags corresponding to the first user and the urban road environment are determined; based on the sub-interaction information C in the information set C, the social tags corresponding to the first user and the rural road environment are determined.

[0073] This embodiment clusters sub-interaction information according to different environment types to obtain multiple information sets, and then determines the social tags corresponding to the first user and different environment types based on the different information sets. When performing social actions associated with the first user, different social preferences that may exist in different environment types can be further taken into account, thereby improving the social experience of the first user.

[0074] In some exemplary embodiments, referring to Figure 6A step diagram of a method for performing a social action is shown, wherein the social action includes matching a target social object for the first user, and performing a social action associated with the first user based on the social tag of the first user in step S103. Specifically, the method may include the following steps: Step S41: Acquire multiple social objects to be matched.

[0075] The plurality of objects to be matched respectively correspond to at least one social tag.

[0076] Step S42 : determining a target social object that matches the first user from a plurality of social objects to be matched based on the social tags of the social objects to be matched and the social tags of the first user.

[0077] The social objects to be matched can be users of other vehicles. The first user's social tags represent the first user's social preferences, while the social tags of the social objects to be matched represent the social preferences of the social objects to be matched. Therefore, by matching the first user with a target social object based on the social tags of the social objects to be matched and the social tags of the first user, the social preferences of the target social object can be aligned with those of the first user, thereby ensuring the first user's social experience.

[0078] For example, the multiple social objects to be matched are Object A, Object B, and Object C. Object A has a social tag of Normal, Object B has a social tag of Cautious Supervision, and Object C has a social tag of Over-Dependence. If the first user's social tag is Normal, the target social object can be determined to be Object A, which is also Normal.

[0079] This embodiment matches the target social object for the first user by using the social tag of the social object to be matched and the social tag of the first user, which can simplify the matching process of the target social object and thus improve matching efficiency.

[0080] Based on the above embodiment, refer to Figure 7 A flowchart of a social interaction method is shown below. The social interaction method described in this application is exemplarily described below: The social interaction method described in this application is applied to a first vehicle equipped with an intelligent driving system. Specifically, it includes the following steps: At the beginning of the method, first interaction information between the first vehicle and the first user is obtained within a driving cycle in which the intelligent driving system is enabled. The first interaction information includes sub-interaction information generated by the first vehicle in different environment types. The sub-interaction information includes at least one of the intervention frequency of the first vehicle in different environment types, the takeover duration, the driving control duration of the intelligent driving system at the target confidence level, and the activation frequency of the intelligent driving system in the target environment type. The intervention frequency is the frequency with which the first user intervenes in the driving control behavior of the intelligent driving system, and the takeover duration is the time it takes the first user to respond to the takeover request issued by the first vehicle.

[0081] Afterwards, the plurality of sub-interaction information are clustered according to the different types of environments in which the first vehicle is located when the information is generated, to obtain a plurality of information sets corresponding to different environment types, wherein the information set includes at least one sub-interaction information.

[0082] After obtaining the multiple information sets, second interaction information is obtained between multiple second vehicles and corresponding second users, where the second vehicles are vehicles different from the first vehicle. Based on the second interaction information, multiple preset conditions are determined. Each of the multiple preset conditions corresponds to a preset tag.

[0083] From a plurality of preset conditions, target conditions that the sub-interaction information in the plurality of information sets respectively meets are determined, and then preset tags corresponding to the target conditions of the plurality of information sets are respectively determined as social tags corresponding to the first user and different environment types.

[0084] Finally, when matching target social objects for the first user, multiple social objects to be matched are first obtained, each of which has social tags corresponding to different environment types. Based on the social tags corresponding to the different environment types of the social objects to be matched, and the social tags corresponding to the different environment types of the first user, target social objects that match the first user in each of the different environment types are determined from the multiple social objects to be matched.

[0085] This embodiment is illustrated by taking an engineering application scenario as an example. The details are as follows: The social interaction method described in this application is applied to a first vehicle equipped with an intelligent driving system. Specifically, it includes the following steps: At the outset of the method, first interaction information is obtained between a first vehicle and a first user during a driving cycle in which the intelligent driving system is enabled. The first interaction information includes a takeover duration of 3 seconds for the first vehicle on highways, a takeover duration of 1 second on urban roads, and a takeover duration of 2 seconds on city roads.

[0086] Subsequently, based on the different types of environments in which the first vehicle was located when generated, the first interaction information can be clustered into information set A including takeover durations of 1 second and 2 seconds, and information set B including takeover durations of 3 seconds, according to the highway type and urban road type. Information set A corresponds to the urban road type, while information set B corresponds to the highway type.

[0087] After obtaining information sets A and B, second interaction information is obtained between multiple second vehicles and their corresponding second users. The second vehicles are vehicles different from the first vehicle. Based on this second interaction information, preset conditions A and B are determined. Preset condition A is that the takeover duration is greater than or equal to 3 seconds, and the corresponding preset label is "over-dependence". Preset condition B is that the takeover duration is less than 3 seconds, and the corresponding preset label is "normal".

[0088] After determining multiple preset conditions, it can be determined that the target condition met by information set A is preset condition A, and the preset label corresponding to preset condition A is over-dependent. Therefore, it can be determined that the social tags of the first user in the urban road environment are transitionally dependent. At the same time, the target condition met by information set B is preset condition B, and the preset label corresponding to preset condition B is normal. Therefore, it can be determined that the social tags of the first user in the highway environment are normal.

[0089] Finally, when matching target social objects for the first user, multiple social objects to be matched are first obtained, each of which has social tags corresponding to highway and urban road environments, respectively. Based on the social tags corresponding to the different environment types of the social objects to be matched, as well as the social tags corresponding to the different environment types of the first user, target social objects that match the first user in each of the different environment types are determined from the multiple social objects to be matched.

[0090] Based on the same inventive concept, the present application also provides a social interaction system, such as Figure 8 As shown in the structural schematic diagram of a social interaction system, the social interaction system is applied to a first vehicle, the first vehicle is provided with an intelligent driving system, and the social interaction system includes: an acquisition module, configured to acquire first interaction information between the first vehicle and a first user within a driving cycle in which the intelligent driving system is enabled; a determination module, configured to determine a social tag of the first user based on the first interaction information; An execution module is configured to execute a social action associated with the first user based on the social tag of the first user.

[0091] In some exemplary embodiments, the first interaction information includes at least one of an intervention frequency, a takeover duration, a driving control duration of the intelligent driving system at a target confidence level, and an activation frequency of the intelligent driving system in a target environment type; Among them, the intervention frequency is the frequency of the first user intervening in the driving control behavior of the intelligent driving system, and the takeover duration is the time it takes the first user to respond to the takeover request issued by the first vehicle.

[0092] In some exemplary embodiments, the acquisition module is further used to obtain the confidence of the intelligent driving system at multiple moments; based on the confidence at the multiple moments, determine the driving control time of the intelligent driving system at the target confidence.

[0093] In some exemplary embodiments, the determination module is further used to determine a target condition that the first interaction information meets from a plurality of preset conditions, wherein the plurality of preset conditions respectively correspond to at least one preset tag; and the preset tag corresponding to the target condition is determined as the social tag of the first user.

[0094] In some exemplary embodiments, the determination module is further used to obtain second interaction information between multiple second vehicles and corresponding second users, where the second vehicles are other vehicles different from the first vehicle; and based on the second interaction information, determine multiple preset conditions.

[0095] In some exemplary embodiments, the first interaction information includes sub-interaction information generated by the first vehicle in different environment types, and the determining module is further configured to cluster the plurality of sub-interaction information according to the different environment types in which the first vehicle was located when each sub-interaction information was generated, to obtain a plurality of information sets corresponding to different environment types, each of the information sets including at least one sub-interaction information; and determine, based on the plurality of information sets, social tags corresponding to the first user and the different environment types. The execution module is further configured to execute a social action associated with the first user based on the social tags of the first user corresponding to the different environment types.

[0096] In some exemplary embodiments, the social action includes matching a target social object for the first user, and the execution module is further used to obtain multiple social objects to be matched, each of the multiple objects to be matched corresponding to at least one social tag; based on the social tags of the social objects to be matched and the social tags of the first user, determine the target social object that matches the first user from the multiple social objects to be matched.

[0097] An embodiment of the present application also provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, a social interaction method as disclosed in an embodiment of the present application is implemented.

[0098] An embodiment of the present application also provides a vehicle, including a social interaction system provided by the present application, or including a control module, wherein the control module is used to implement the steps of the social interaction method described in the embodiment of the present application.

[0099] The present application provides a social interaction method, system, storage medium and vehicle, the method comprising: obtaining first interaction information between the first vehicle and a first user within a driving cycle in which the intelligent driving system is enabled; determining a social tag of the first user based on the first interaction information; and performing a social action associated with the first user based on the social tag of the first user.

[0100] This application is directed to a first vehicle equipped with an intelligent driving system. The application determines a social tag based on first interaction information between the first vehicle and a first user during a driving cycle in which the intelligent driving system is enabled, and then executes a social action associated with the first user based on the first user's social tag. This application infers the first user's social preferences based on the first interaction information between the first user and the first vehicle, thereby determining a social tag that can characterize the first user's social preferences to ensure that the executed social action is consistent with the first user's social preferences. This allows the first user to engage in social interactions consistent with their social preferences without having to expend any effort other than driving the vehicle, ultimately improving the convenience of social interaction for vehicle users.

[0101] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0102] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, systems, electronic devices, and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0103] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0104] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0105] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0106] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0107] The above is a detailed introduction to a social interaction method, system, storage medium and vehicle provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for those skilled in the art, according to the ideas of the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A social interaction method, characterized in that: The method is applied to a first vehicle, wherein the first vehicle is provided with an intelligent driving system, and the method includes: Obtaining first interaction information between the first vehicle and a first user within a driving cycle in which the intelligent driving system is enabled; Determining a social tag of the first user based on the first interaction information; Based on the social tag of the first user, a social action associated with the first user is performed.

2. The social interaction method according to claim 1, characterized in that: The first interaction information includes at least one of an intervention frequency, a takeover duration, a driving control duration of the intelligent driving system at a target confidence level, and an activation frequency of the intelligent driving system in a target environment type; Among them, the intervention frequency is the frequency of the first user intervening in the driving control behavior of the intelligent driving system, and the takeover duration is the time it takes the first user to respond to the takeover request issued by the first vehicle.

3. The social interaction method according to claim 2, characterized in that: The step of obtaining the driving control time of the intelligent driving system at a target confidence level includes: Obtaining the confidence of the intelligent driving system at multiple moments; Based on the confidence levels at the multiple moments, a driving control duration of the intelligent driving system at a target confidence level is determined.

4. The social interaction method according to claim 1, wherein: The determining the social tag of the first user based on the first interaction information includes: Determining a target condition that the first interaction information meets from a plurality of preset conditions, wherein the plurality of preset conditions respectively correspond to at least one preset tag; The preset tag corresponding to the target condition is determined as the social tag of the first user.

5. The social interaction method according to claim 4, characterized in that: Before determining, from among a plurality of preset conditions, that the first interaction information satisfies a target condition, the method further includes: Acquire second interaction information between a plurality of second vehicles and corresponding second users, where the second vehicles are other vehicles than the first vehicle; Based on the second interaction information, a plurality of the preset conditions are determined.

6. The social interaction method according to claim 1, characterized in that: The first interaction information includes sub-interaction information generated by the first vehicle in different environment types. Determining the social tag of the first user based on the first interaction information includes: Clustering the plurality of sub-interaction information according to different types of environments in which the first vehicle is located when each piece of the sub-interaction information is generated, to obtain a plurality of information sets corresponding to different types of environments, each of the information sets including at least one piece of the sub-interaction information; Determining, based on the plurality of information sets, social tags corresponding to the first user and the different environment types; The performing a social action associated with the first user based on the social tag of the first user includes: Based on the social tags of the first user corresponding to the different environment types, a social action associated with the first user is performed.

7. The social interaction method according to claim 1, characterized in that: The social action includes matching a target social object for the first user, and performing the social action associated with the first user based on the social tag of the first user includes: Acquire multiple social objects to be matched, each of the multiple social objects to be matched corresponding to at least one social tag; Based on the social tag of the social object to be matched and the social tag of the first user, a target social object that matches the first user is determined from the plurality of social objects to be matched.

8. A social interaction system, characterized in that: The social interaction system is applied to a first vehicle, the first vehicle being provided with an intelligent driving system, and the social interaction system includes: an acquisition module, configured to acquire first interaction information between the first vehicle and a first user within a driving cycle in which the intelligent driving system is enabled; a determination module, configured to determine a social tag of the first user based on the first interaction information; An execution module is configured to execute a social action associated with the first user based on the social tag of the first user.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the social interaction method according to any one of claims 1 to 7 are implemented.

10. A vehicle, characterized in that: The social interaction system comprises the social interaction system as claimed in claim 8, or comprises a control module, wherein the control module is used to implement the steps of the social interaction method as claimed in any one of claims 1 to 7.

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