User interaction method and device

Abstract

The embodiment of the invention discloses a user interaction method and device. The specific implementation mode of the method comprises the steps that in response to detection that current driving data of a user meets preset safety conditions and triggering conditions, a target space-time virtual cloned body is determined from a space-time virtual cloned body set based on the current driving data, and the space-time virtual cloned body set comprises driving data of different users; initiating a request to invite the user to participate in an interactive activity related to a target spatio-temporal virtual avatar; in response to detecting that the user accepts the request, recording interactive driving data of the user during the interactive activity; and performing comparative analysis on the interactive driving data and the driving data of the target space-time virtual branch, and outputting a comparison result. According to the embodiment, the driving pleasure and the interaction experience of the user can be improved.

Description

Technical Field

[0001] The embodiments disclosed herein relate to the field of computer technology, and more specifically to methods and apparatus for user interaction. Background Technology

[0002] With the development of internet and artificial intelligence technologies, cars are becoming increasingly functional, and intelligent control is gradually becoming a standard feature.

[0003] In related technologies, virtual humans are used to achieve a human-like interactive experience, enhancing the interactive experience through preset expressions, actions, and following. However, this primarily relies on preset trigger points for feedback, lacking a personalized user experience. Furthermore, existing interactive experiences are mostly voice, text, and video-based, lacking action-based interaction methods.

[0004] In related technologies, vehicle control and racing games are often achieved by combining navigation information. However, the preset racing schemes are not very relevant to the current user, lack a sense of real-person interaction, and cannot update racing content in real time or enable real-time multiplayer racing.

[0005] In related technologies, user driving data mainly serves new car development and user profile analysis, with little attention paid to or organization of users' social activities based on driving habits, and a lack of emotional guidance for users driving new cars. Summary of the Invention

[0006] Embodiments of this disclosure provide methods and apparatus for user interaction.

[0007] In a first aspect, embodiments of this disclosure provide a user interaction method, comprising: responding to detecting that a user's current driving data meets preset safety conditions and triggering conditions, determining a target spatiotemporal virtual clone from a set of spatiotemporal virtual clones based on the current driving data, wherein the set of spatiotemporal virtual clones includes driving data of different users; initiating a request to invite the user to participate in an interactive activity related to the target spatiotemporal virtual clone; responding to detecting that the user accepts the request, recording the user's interactive driving data during the interactive activity; comparing and analyzing the interactive driving data with the driving data of the target spatiotemporal virtual clone, and outputting a comparison result.

[0008] In some embodiments, the spatiotemporal virtual clone includes feature tags; and determining the target spatiotemporal virtual clone from the set of spatiotemporal virtual clones based on the current driving data includes: extracting the user's driving characteristics based on at least one of the following in the current driving data: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening; matching the driving characteristics with feature tags in the set of spatiotemporal virtual clones, and using the successfully matched spatiotemporal virtual clone as the target spatiotemporal virtual clone.

[0009] In some embodiments, initiating a request to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar includes: inviting the user to participate in interactive activities related to the target spatiotemporal virtual avatar by playing voice or displaying text through a predetermined device, wherein the predetermined device includes at least one of the following: a vehicle infotainment screen, a head-up display system, or an augmented reality device.

[0010] In some embodiments, the method further includes: in response to detecting that the user accepts the request, in response to receiving user voice, understanding the user voice through a large language model to obtain limiting conditions for the request; and reselecting a target spatiotemporal virtual clone that matches the current driving data according to the limiting conditions.

[0011] In some embodiments, the method further includes: in response to the user participating in the interactive activity more than a predetermined threshold, initiating a request to invite multiple other users to participate in the interactive activity.

[0012] In some embodiments, determining the target spatiotemporal virtual clone from the spatiotemporal virtual clone set based on the current driving data includes: receiving a search request input by a user, wherein the search request includes: time and location; searching for a candidate spatiotemporal virtual clone set in the spatiotemporal virtual clone set according to the search request; and determining the target spatiotemporal virtual clone from the candidate spatiotemporal virtual clone set based on the current driving data.

[0013] In some embodiments, the method further includes: determining the characteristics of a user's spatiotemporal virtual avatar based on the interactive driving data; selecting candidate spatiotemporal virtual avatars that match the characteristics from the set of spatiotemporal virtual avatars; and recommending real users corresponding to the candidate spatiotemporal virtual avatars to the user for social activities.

[0014] In some embodiments, the method further includes: accumulating points based on the number of interactive activities the user participates in; and setting corresponding permissions for the user according to predetermined point rules.

[0015] In some embodiments, the method further includes: cleaning the user's driving data and generating a spatiotemporal virtual clone; inputting the spatiotemporal virtual clone into a pre-trained quality evaluation model and outputting a quality score for the spatiotemporal virtual clone; and storing the spatiotemporal virtual clone in a database in response to determining that the quality score is greater than a predetermined threshold.

[0016] Secondly, embodiments of this disclosure provide a user interaction device, comprising: a determining unit configured to, in response to detecting that a user's current driving data meets preset safety conditions and triggering conditions, determine a target spatiotemporal virtual clone from a set of spatiotemporal virtual clones based on the current driving data, wherein the set of spatiotemporal virtual clones includes driving data from different users; an initiating unit configured to initiate a request to invite the user to participate in an interactive activity related to the target spatiotemporal virtual clone; a recording unit configured to, in response to detecting that the user accepts the request, record the user's interactive driving data during the interactive activity; and an analysis unit configured to compare and analyze the interactive driving data with the driving data of the target spatiotemporal virtual clone, and output a comparison result.

[0017] In some embodiments, the spatiotemporal virtual clone includes feature tags; and the determining unit is further configured to: extract the user's driving characteristics based on at least one of the following in the current driving data: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening; match the driving characteristics with feature tags in the spatiotemporal virtual clone set, and use the successfully matched spatiotemporal virtual clone as the target spatiotemporal virtual clone.

[0018] In some embodiments, the initiating unit is further configured to: invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar by playing voice or displaying text through a predetermined device, wherein the predetermined device includes at least one of the following: a vehicle infotainment screen, a head-up display system, or an augmented reality device.

[0019] In some embodiments, the apparatus further includes a reselection unit configured to: in response to detecting that the user accepts the request, in response to receiving user voice, understand the user voice through a large language model to obtain limiting conditions for the request; and reselect a target spatiotemporal virtual clone that matches the current driving data according to the limiting conditions.

[0020] In some embodiments, the initiating unit is further configured to: in response to the user participating in the interactive activity more than a predetermined threshold, initiate a request to invite multiple other users to participate in the interactive activity.

[0021] In some embodiments, the determining unit is further configured to: receive a search request input by a user, wherein the search request includes: time and location; search for a candidate set of spatiotemporal virtual avatars in the set of spatiotemporal virtual avatars according to the search request; and determine a target spatiotemporal virtual avatar from the candidate set of spatiotemporal virtual avatars based on the current driving data.

[0022] In some embodiments, the device further includes a recommendation unit configured to: determine the characteristics of a user's spatiotemporal virtual avatar based on the interactive driving data; filter candidate spatiotemporal virtual avatars that match the characteristics from the set of spatiotemporal virtual avatars; and recommend real users corresponding to the candidate spatiotemporal virtual avatars to the user for social activities.

[0023] In some embodiments, the device further includes a permission unit configured to: accumulate points based on the number of interactive activities the user participates in; and set corresponding permissions for the user according to predetermined point rules.

[0024] In some embodiments, the apparatus further includes a construction unit configured to: clean the user's driving data and generate a spatiotemporal virtual clone; input the spatiotemporal virtual clone into a pre-trained quality evaluation model and output a quality score for the spatiotemporal virtual clone; and, in response to determining that the quality score is greater than a predetermined threshold, store the spatiotemporal virtual clone in a database.

[0025] Thirdly, embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more computer programs stored thereon, wherein when the one or more computer programs are executed by the one or more processors, the one or more processors perform the method as described in any one of the first or second aspects.

[0026] Fourthly, embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method as described in any one of the first or second aspects.

[0027] Fifthly, embodiments of this disclosure provide a computer program product including a computer program that, when executed by a processor, implements the method as described in any one of the first or second aspects.

[0028] The user interaction methods and apparatus provided in the embodiments of this disclosure, based on virtual avatars derived from user spatiotemporal data, allow users to experience the feeling of interacting with their past selves, enhancing driving pleasure. By matching and interacting with other virtual avatars, the barriers to social interaction between users are lowered, ultimately increasing user stickiness and brand value for automakers.

[0029] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0030] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0031] Figure 1 This is an exemplary system architecture diagram to which one embodiment of this disclosure can be applied;

[0032] Figure 2 This is a flowchart of an embodiment of a user interaction method according to the present disclosure;

[0033] Figure 3 This is a schematic diagram of an application scenario of the user interaction method according to this disclosure;

[0034] Figure 4 This is a flowchart of yet another embodiment of the user interaction method according to the present disclosure;

[0035] Figure 5 This is a schematic diagram of the structure of an embodiment of a user interaction device according to the present disclosure;

[0036] Figure 6 This is a schematic diagram of the structure of a computer system suitable for implementing embodiments of the present disclosure. Detailed Implementation

[0037] The present disclosure will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0038] It should be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0039] Figure 1 An exemplary system architecture is shown that allows the application of the user interaction methods disclosed herein.

[0040] like Figure 1 As shown, the system architecture may include a dashcam 110, an in-vehicle camera 120, an in-vehicle display screen 130, a touchpad 140, and a cloud server 105. The system architecture may also include an AR HUD (not shown in the figures) and controllers (not shown in the figures) that establish communication connections with the in-vehicle display screen and the AR HUD, respectively. Figure 1 The touchpad 140 shown is just an example of one mounted on the steering wheel; it can also be mounted on other vehicle components such as the dashboard and armrest. The windshield can be used as a projection screen for the AR HUD to display augmented reality information.

[0041] The dashcam 110 is used to record video images and sound of the entire driving process of a car.

[0042] The vehicle-mounted camera 120 can be a roof-mounted panoramic camera or cameras mounted on each side of the vehicle body. In some embodiments, the position and angle of the vehicle-mounted camera 120 can be adjusted as needed, and can be adjusted via voice commands, button commands, touch commands, etc. For example, a user can send a voice command such as "adjust the angle of the front camera upwards by 10 degrees" or "adjust the position of the front camera downwards by 1 centimeter." In other embodiments, such as a roof-mounted panoramic camera, it can acquire panoramic images around the vehicle body, and can crop images within a specific angle range from the panoramic images for image display or corner recognition according to instructions.

[0043] The touchpad 140 can be mounted on vehicle components such as the dashboard or steering wheel, allowing users to input touch commands to adjust the position of calibration points. For example, the touchpad consists of multiple piezoelectric vibrators, which can be mounted on the back of the touchpad. When pressure is applied to the surface of the touchpad, elastic waves are generated. These elastic waves are then transmitted to different piezoelectric vibrators, where corresponding elastic waveforms are picked up. These elastic waveforms have essentially the same shape, differing only in their arrival time and amplitude.

[0044] In some implementations, the touch position can be identified based on the TOF (Time of Flight) principle to obtain the touch command received by the touchpad 140: receiving voltage signals collected by multiple piezoelectric vibrators; determining a characteristic time point corresponding to each voltage signal based on at least one voltage point with similarity among the multiple voltage signals; the characteristic time point being determined based on at least one time point corresponding to the at least one voltage point; determining at least three characteristic time point pairs among the multiple characteristic time points; and determining the touch position information based on the relative time difference corresponding to the at least three characteristic time point pairs and the position information of a pair of piezoelectric vibrators corresponding to each relative time difference.

[0045] In other embodiments, the touch position can be identified and the touch command received by the touchpad 140 can be obtained by geometric calculation based on the relationship between the reciprocal of the detected voltage value and the distance: by receiving electrical signals collected by multiple piezoelectric vibrators respectively, and determining a first electrical signal point corresponding to each of the multiple electrical signals based on at least one electrical signal point with similarity among the multiple electrical signals, the first electrical signal point obtained can characterize the signal value of the touch point at the first time point collected by the piezoelectric vibrator; at the same time, by determining the proportional relationship between multiple first touch distances based on the first electrical signal point corresponding to each of the multiple electrical signals, the first touch distance is the distance between the piezoelectric vibrator and the touch point at the first time point. Based on the position information of multiple piezoelectric vibrators, the position information of the touch point at the first time point is determined. This takes into account the principle that the farther away from the touch point, the greater the attenuation of the mechanical elastic wave, the smaller the pressure sensing of the mechanical elastic wave on the piezoelectric vibrator, and the smaller the corresponding electrical signal output. By combining the position information of each piezoelectric vibrator, the touch point can be located through geometric relationships. At the same time, since the piezoelectric vibrator can be perfectly integrated with the surface material of the vehicle and has the characteristics of sun exposure resistance, it has stable performance when facing the complex usage scenarios of the vehicle. By determining the proportional relationship between the first touch distance through the first electrical signal point, and then combining the position information of the piezoelectric vibrator, the position information of the touch point can be accurately determined.

[0046] The vehicle-mounted display screen 130 can be various types of displays, such as the display screen of a DVR (Digital Video Recorder), or a central control screen, instrument panel screen, or passenger-side screen. It can also be an electronic device display screen that establishes a communication connection with the vehicle. The vehicle-mounted camera 120 and the vehicle-mounted display screen 130 can be connected via wired or wireless communication. For example, images captured by the vehicle-mounted camera 120 can be transmitted to the vehicle-mounted display screen 130 for display via WiFi, Bluetooth, or satellite imagery technology. In some embodiments, the vehicle-mounted display screen 130 can be a touchscreen, used to receive touch events and send adjustment commands to the controller to generate adjustment instructions for the position of calibration points, while simultaneously setting the calibration interface to block or not respond to the touch events.

[0047] AR HUD is configured to project content from in-vehicle displays.

[0048] The controller is configured to receive signals sent by the user via an in-vehicle display, touchpad, microphone, or buttons.

[0049] The controller is also configured to send instructions to the onboard sensors to collect driving data in response to a detected user-initiated interaction request, and to send the collected driving data to a cloud-based server for storage. Users can initiate interaction requests via touchpad 140 or voice.

[0050] The controller is also configured to display the activity content on the in-vehicle display screen 130 in response to the detection of an interactive activity pushed by the server, and to send instructions to the in-vehicle sensors to collect driving data in response to the detection of user confirmation of participation in the activity, and to send the collected driving data to the cloud server for storage. Users can confirm participation in the interactive activity via touchpad 140 or voice.

[0051] It should be noted that the user interaction methods provided in the embodiments of this disclosure are generally executed by the cloud server 105.

[0052] Continue to refer to Figure 2 The flowchart 200 illustrates an embodiment of a user interaction method according to the present disclosure. The user interaction method includes the following steps:

[0053] Step 201: In response to detecting that the user's current driving data meets the preset safety conditions and trigger conditions, determine the target spatiotemporal virtual clone from the spatiotemporal virtual clone set based on the current driving data.

[0054] In this embodiment, the execution body of the user interaction method (e.g. Figure 1 The cloud server shown can receive driving data from the vehicle via wired or wireless connection, and then analyze whether the user's current driving data meets preset safety and trigger conditions. Both safety and trigger conditions can be set by the user in advance, or default values ​​can be set by the server. Safety conditions ensure that pushing interactive activities to the user will not affect driving safety; for example, the vehicle speed should be below 20 km / h. Trigger conditions can be time and / or spatial conditions for participating in activities preset by the user. For example, on a weekday morning between 8:00 and 9:00, on the way from home to work.

[0055] The server pre-stores driving data from different users, and generates spatiotemporal virtual clones after preprocessing. The driving data may include at least one of the following: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening.

[0056] The system can match current driving data with a set of spatiotemporal virtual clones, finding those with a similarity greater than a predetermined threshold. For example, if the driving time and route are exactly the same, or the similarity is greater than 90%, a match is considered successful. If multiple matching spatiotemporal virtual clones exist, the one with the highest matching degree is selected.

[0057] In some embodiments, when a user uses the vehicle for the first time, they register their user information on a cloud server, which may include name, age, occupation, etc. Triggering conditions can also be set. Matching can also refer to user information; for example, matching spatiotemporal virtual clones based on age.

[0058] In some embodiments, when a user uses the vehicle for the first time, the system automatically recommends the highest-ranking spatiotemporal virtual clone in the community and guides the user to use the vehicle.

[0059] In some embodiments, after a user has been driving for a period of time, by matching the spatiotemporal virtual clone trigger rules in real time, and when the mobile device's security settings and trigger conditions are met, the system proactively engages in interactive behaviors such as inviting users to activities through devices such as LLM voice, HUD, or AR.

[0060] Step 202: Initiate a request to invite users to participate in interactive activities related to the target spatiotemporal virtual clone.

[0061] In this embodiment, a request to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar can be output through a large voice model, HUD, or AR device. For example, the voice message "Would you like to participate in a race to get to the office first?" can be output, or the HUD screen can display that other users are also taking the same route, asking if they want to race to see who arrives at the destination first. If the user is wearing AR glasses, the interactive activity information can be displayed on the AR glasses.

[0062] Step 203: In response to detecting that the user accepts the request, record the user's interactive driving data during the interactive activity.

[0063] In this embodiment, the user can accept requests via voice or touchpad. After acceptance, driving data within the specified time and space range of the interactive activity will be recorded as interactive driving data.

[0064] Step 204: Compare and analyze the interactive driving data with the driving data of the target spatiotemporal virtual clone, and output the comparison results.

[0065] In this embodiment, at least one of the following driving data can be compared and analyzed: driving time, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening. Item-by-item comparison results are obtained. For example, the current user's driving time is shorter than other users', but their driving route is longer. The current user's vehicle speed is faster than other users'. The current user's vehicle acceleration is greater than other users'. The current user's steering wheel angle is larger than other users'. The current user's accelerator pedal opening is greater than other users'. The current user's brake pedal opening is greater than other users'. The overall analysis result shows that although the current user drives faster than other users, their driving is unstable, resulting in higher fuel consumption, increased wear and tear on parts, and a poor passenger experience. The advantages and disadvantages of the current user's driving habits can be analyzed, and improvement suggestions can be provided.

[0066] The method provided in the above embodiments of this disclosure generates spatiotemporal virtual avatars from each user's own driving data, interacts with users through a large language model, enhances the user's driving pleasure and interactive experience, and increases the user's acceptance of their private virtual avatar. By interacting with spatiotemporal virtual avatars of different users, interest matching based on driving habits is established in advance among users, thereby guiding users to engage in more extensive real-person social activities and improving community activity.

[0067] In some optional implementations of this embodiment, the target spatiotemporal virtual avatar can be the user's historical driving data. Therefore, the user's current driving data can be compared with historical driving data. For example, comparing the current user's driving data with driving data from a month ago can reveal that the user's commuting time has decreased, indicating improved driving skills. This allows the user to experience the feeling of interacting with their past self, increasing driving enjoyment. It can also encourage users to continuously improve their driving skills.

[0068] In some optional implementations of this embodiment, the target spatiotemporal virtual avatar can be the driving data of multiple users who share the same time and space. Comparison results can be queried. For example, one can query the comparison results between oneself and other users of the same age. One can query the driving data of male drivers to compare and analyze areas for improvement.

[0069] In some optional implementations of this embodiment, the target spatiotemporal virtual avatar can be the driving data of a user who specifies certain conditions. Their driving time and location may be the same as or different from the current user's. Recommendations can be made based on the user's preferences; for example, if the current user wants to know where their peers drive on weekends, they can specify age and time, without limiting the location.

[0070] In some optional implementations of this embodiment, users can proactively initiate requests to query other users' driving data. This does not involve personal privacy; it simply queries the driving time, acceleration, and braking frequency of other users at a specific time and on a specific road segment. The cloud server can score the virtual avatars across different time periods, selecting users with good driving habits as role models for other users to reference.

[0071] In some optional implementations of this embodiment, the cloud server integrates a large language model and records user interaction voice. By understanding the context of the current user interaction voice, it optimizes the voice interaction method and matches a more suitable spatiotemporal virtual avatar, thereby improving the user interaction experience.

[0072] In some optional implementations of this embodiment, the restriction on inviting multiple users or multiple spatiotemporal virtual avatars to interact simultaneously can be unlocked by guiding users to use the spatiotemporal virtual avatar multiple times. Unlocking rules can be set; for example, a user gains the right to invite multiple users or multiple spatiotemporal virtual avatars to interact simultaneously by using the spatiotemporal virtual avatar multiple times. However, if a user does not use this right for a long period (e.g., one week), the right can be revoked. To regain this right, the user must use the spatiotemporal virtual avatar multiple times again.

[0073] In some optional implementations of this embodiment, users can also search for and interact with other users' spatiotemporal virtual avatars within a specific time or geographical area in the community to match companions that better meet their needs. For example, specifying a user's spatiotemporal virtual avatar who drives from the West Third Ring Road to the East Third Ring Road between 8:00 and 9:00 AM on Monday.

[0074] In some optional implementations of this embodiment, spatiotemporal virtual avatar interaction data between users and other users is used to filter spatiotemporal virtual avatar features that users are interested in, such as aggressive driving, off-road driving, and night driving. This increases user engagement in interactive activities and enhances brand loyalty.

[0075] In some optional implementations of this embodiment, when preset real-person interaction invitation conditions are met, the system proactively recommends similar or interested real users to engage in social activities such as virtual racing games. Users can pre-set their friend-making permissions; if they allow others to add them as friends, similar or interested real users can be pushed to that user as friends. If no friend-making permissions are set, a friend request can be initiated, providing some recommendation information to pique the user's interest, which may lead to permission to add them as a friend. This attracts users to actively make friends in the community, increases community activity, and thereby enhances brand loyalty.

[0076] In some optional implementations of this embodiment, users can acquire corresponding benefits by participating in spatiotemporal virtual avatar social activities. For example, they can obtain points and membership levels, which can be redeemed in the social mall for spatiotemporal virtual avatar-related benefits, such as naming rights, and virtual goods such as referral opportunities from real users. This can increase user participation in spatiotemporal virtual avatar social activities and attract new users, thereby increasing community activity and enhancing brand loyalty in the automotive industry.

[0077] In some optional implementations of this embodiment, the spatiotemporal virtual clone includes feature tags; and the step of determining the target spatiotemporal virtual clone from the set of spatiotemporal virtual clones based on the current driving data includes: extracting the user's driving characteristics based on at least one of the following from the current driving data: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening; matching the driving characteristics with the feature tags in the set of spatiotemporal virtual clones, and using the successfully matched spatiotemporal virtual clone as the target spatiotemporal virtual clone. The driving characteristics described above can determine the current user's driving habits, such as aggressive driving, off-road driving, and night driving. These driving habits are used as feature tags to label each spatiotemporal virtual clone. This transforms the driving data matching process into feature tag matching, reducing the computational load and thus accelerating the matching speed.

[0078] In some optional implementations of this embodiment, the step of initiating a request to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar includes: inviting the user to participate in interactive activities related to the target spatiotemporal virtual avatar by playing voice or displaying text through a predetermined device, wherein the predetermined device includes at least one of the following: a vehicle infotainment screen, a head-up display system, or an augmented reality device.

[0079] It supports multiple methods for inviting users to participate in interactive activities related to the target spatiotemporal virtual avatar. Various methods can be combined; for example, the invitation can be projected onto the windshield via a head-up display while simultaneously being played via voice. Users can customize their preferred notification methods.

[0080] In some optional implementations of this embodiment, the method further includes: in response to detecting that the user accepts the request, in response to receiving user voice, understanding the user voice through a large language model to obtain limiting conditions for the request; and reselecting a target spatiotemporal virtual clone that matches the current driving data according to the limiting conditions.

[0081] Users can confirm acceptance of the request via voice or touchpad. The controller can directly recognize the voice, perform semantic understanding, and convert it into control commands. Alternatively, the voice can be transmitted to a cloud server for voice recognition and semantic understanding, which will then convert it into control commands. For example, if the invitation asks "Do you agree to participate in the interactive activity?", but the user doesn't directly answer "agree" but instead uses "yes," it will be interpreted as "agree" through semantic understanding. Or, if the user answers "no time" or "busy," it will be interpreted as "disagree."

[0082] If the user agrees to accept the invitation, the interaction can continue, guiding the user to state their requirements for the activity as limiting conditions. For example, "female driver," "same route home from get off work," etc.

[0083] It can also perform semantic recognition and semantic understanding on the user's speech to determine the limiting conditions that can be used to filter the stored data. For example, if the user says "young people", the speech can be converted into the limiting condition "age between 18 and 30 years old".

[0084] Based on the aforementioned limiting conditions, a target spatiotemporal virtual clone matching the current driving data is reselected. For example, if there are multiple spatiotemporal virtual clones that originally match the user's driving data, but only one spatiotemporal virtual clone meets the condition of being "between 18 and 30 years old", then that one will be selected as the target spatiotemporal virtual clone.

[0085] Alternatively, a candidate set of spatiotemporal virtual avatars can be selected first based on limiting conditions, and then the target spatiotemporal virtual avatar that matches the current driving data can be determined from the candidate set. This method can reduce computation, increase matching speed, reduce latency, and thus improve user experience.

[0086] In some optional implementations of this embodiment, the method further includes: in response to the user participating in the interactive activity more than a predetermined threshold, initiating a request to invite multiple other users to participate in the interactive activity.

[0087] If a user participates in interactive activities more than a predetermined threshold, they will be granted higher privileges. They can now initiate interactive activities themselves, rather than waiting for the cloud server to do so; they can only receive interactive activities. For example, if a user participates in fewer than 5 interactive activities, they can only passively receive activities initiated by other users or the cloud server. Once a user has participated in more than 5 interactive activities, they can be notified to initiate their own. The cloud server can provide a list of candidate interactive activities for the user to choose from, or the user can customize the interactive activities, including details such as content, time, location, and restrictions on participation.

[0088] Granting higher privileges to users who frequently participate in interactive activities can increase their enthusiasm for participation, thereby achieving the goal of an active community.

[0089] In some optional implementations of this embodiment, determining the target spatiotemporal virtual clone from the spatiotemporal virtual clone set based on the current driving data includes: receiving a search request input by a user, wherein the search request includes: time and location; searching for a candidate spatiotemporal virtual clone set in the spatiotemporal virtual clone set according to the search request; and determining the target spatiotemporal virtual clone from the candidate spatiotemporal virtual clone set based on the current driving data.

[0090] Search requests can be input via voice or touchpad. Voice-input search requests can be converted into text through speech recognition, followed by semantic understanding to obtain the specific search request. The search request can include time and location. Since driving data includes time and location, the corresponding spatiotemporal virtual avatar also includes time and location. By limiting time and location, the set of spatiotemporal virtual avatars can be filtered to obtain a candidate set. Then, based on the current driving data, the target spatiotemporal virtual avatar is determined from the candidate set. Alternatively, the current driving data can be directly matched one by one with the candidate spatiotemporal virtual avatars in the candidate set to determine the target spatiotemporal virtual avatar. Or, the current user's feature tags can be matched one by one with the feature tags of the candidate spatiotemporal virtual avatars to determine the target spatiotemporal virtual avatar.

[0091] A user's characteristic tags are determined by at least one of the following features: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening.

[0092] User profile tags essentially represent a user's driving habits. By analyzing a user's historical driving data, these habits are identified. The cloud server prioritizes interactions with users who share similar driving habits. This fosters a sense of community among users, attracting them to each other, increasing their participation, boosting community engagement, and enhancing brand loyalty.

[0093] In some optional implementations of this embodiment, the method further includes: determining the characteristics of the user's spatiotemporal virtual avatar based on the interactive driving data; selecting candidate spatiotemporal virtual avatars that meet the characteristics from the set of spatiotemporal virtual avatars; and recommending real users corresponding to the candidate spatiotemporal virtual avatars to the user for social activities.

[0094] The characteristics of a spatiotemporal virtual clone are determined by at least one of the following: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening.

[0095] Feature matching can be used to find real users with similar driving habits to the current user. Based on the contact information of the real user in the community they have pre-registered, the system recommends the real user corresponding to the candidate spatiotemporal virtual avatar to the current user for social activities. For example, if the user has pre-registered on Weibo, the system can recommend the Weibo account of the real user, allowing the user to follow the real user and engage in social activities. These social activities are not limited to the interaction of driving data in the cloud, but can also involve participating in real offline activities, such as participating in community-organized suburban driving events.

[0096] In some optional implementations of this embodiment, the method further includes: accumulating points based on the number of interactive activities the user participates in; and setting corresponding permissions for the user according to predetermined point rules.

[0097] Point rules can be preset, for example, 10 points are awarded for each interactive activity participated in. Different point levels grant corresponding privileges; for example, 100 points allow you to invite 1 user to participate in the activity, and 200 points allow you to invite 3 users to participate in the activity.

[0098] The purpose of setting up points rules is to increase user participation in activities, thereby enlivening the community and promoting the car brand.

[0099] In some optional implementations of this embodiment, the method further includes: cleaning the user's driving data and generating a spatiotemporal virtual clone; inputting the spatiotemporal virtual clone into a pre-trained quality evaluation model and outputting a quality score for the spatiotemporal virtual clone; and storing the spatiotemporal virtual clone in a database in response to determining that the quality score is greater than a predetermined threshold.

[0100] The purpose of data cleaning is to remove outlier data, such as 100 brake applications within 1 kilometer. Driving data that does not conform to normal driving habits is also removed. The cleaned data is then used to generate a spatiotemporal virtual avatar. This generated spatiotemporal virtual avatar cannot be used directly at this stage; it needs to undergo quality evaluation. Only spatiotemporal virtual avatars that pass the quality assessment are stored in the database. A pre-trained quality evaluation model can be used to output a quality score for each spatiotemporal virtual avatar.

[0101] The quality assessment model is a neural network whose training samples include positive samples (spatiotemporal virtual avatars with a quality score of 100) and negative samples (spatiotemporal virtual avatars with a quality score of 0). The positive and negative samples are input into the quality assessment model to obtain predicted quality scores. The predicted quality scores are compared with the actual scores, and a loss value is calculated based on the difference. The network parameters of the quality assessment model are adjusted based on the loss value, continuously reducing the loss until it converges to a predetermined value, or the iteration reaches a predetermined number, at which point the quality assessment model training is complete. The trained quality assessment model can be used to evaluate the quality scores of spatiotemporal virtual avatars.

[0102] In response to determining that the quality score is greater than a predetermined threshold (e.g., 80 points), the spatiotemporal virtual avatar is stored in the database. When it is detected that the user's current driving data meets preset safety and trigger conditions, a target spatiotemporal virtual avatar is determined from the spatiotemporal virtual avatar set based on the current driving data. Then, a request is initiated to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar; in response to detecting that the user accepts the request, the user's interactive driving data during the interactive activity is recorded; the interactive driving data is compared and analyzed with the driving data of the target spatiotemporal virtual avatar, and the comparison result is output.

[0103] See also Figure 3 , Figure 3 This is a schematic diagram illustrating an application scenario of the user interaction method according to this embodiment. Figure 3 In the application scenario, the implementation process is as follows:

[0104] 301. The vehicle collects user driving data, including at least one of the following: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening. The vehicle then sends the driving data to the cloud server.

[0105] 302. The cloud server cleans driving data and generates spatiotemporal virtual avatars. Driving data from different vehicles generates different spatiotemporal virtual avatars, each corresponding to a user. It can also analyze the driving habits of different users, generate feature tags, and assign feature tags to each spatiotemporal virtual avatar, facilitating subsequent identification of the target spatiotemporal virtual avatar using feature matching methods.

[0106] 303. The cloud server needs to evaluate the quality of the generated spatiotemporal virtual avatars, which can be done using a pre-trained quality assessment model. If the evaluation passes, proceed to step 304. If the evaluation fails, continue evaluating the quality of other spatiotemporal virtual avatars. The cloud server continuously receives a large amount of driving data uploaded from vehicles, generating a large number of spatiotemporal virtual avatars. Only spatiotemporal virtual avatars that meet the quality standards will be recommended to users for interactive activities.

[0107] 304. The cloud server will store the spatiotemporal virtual clones that have passed the quality assessment in the database. Time or space features can be added as indexes, such as spatiotemporal virtual clones during the morning rush hour, or spatiotemporal virtual clones with destination airport A.

[0108] 305. The cloud server sets the spatiotemporal virtual clone matching rules and sends them to the vehicle.

[0109] 306. During the driving process, the vehicle performs security checks and calls the spatiotemporal virtual clone matching rules. If the security check passes and the triggering conditions are met, the cloud server is notified to match the spatiotemporal virtual clone.

[0110] 307. The cloud server periodically performs spatiotemporal virtual clone matching to determine the target spatiotemporal virtual clone. If the match is successful, proceed to step 308; otherwise, perform spatiotemporal virtual clone matching again after a period of time.

[0111] 308. The cloud server generates interactive activities based on the successfully matched target spatiotemporal virtual clone and sends the interactive activity information to the vehicle to allow the vehicle to confirm whether to participate.

[0112] 309. After the user on the vehicle agrees to participate in the interactive activity, the vehicle's sensors collect vehicle condition data and generate interactive driving data.

[0113] 310. After the interactive activity ends, the vehicle sends the interactive driving data to the cloud server.

[0114] 311. The cloud server can guide users to participate in various community activities via voice or text.

[0115] Further reference Figure 4 This illustrates a flow 400 of another embodiment of a user interaction method. Flow 400 of this user interaction method includes the following steps:

[0116] Step 401: Clean the user's driving data and generate a spatiotemporal virtual clone.

[0117] In this embodiment, the entity executing the user interaction method can be Figure 1The server shown can also be a third-party server. The purpose of data cleaning is to remove abnormal data, such as 100 brake applications within 1 kilometer. Driving data that does not conform to normal driving habits is removed. A spatiotemporal virtual avatar is generated using the cleaned data. This generated spatiotemporal virtual avatar cannot be used directly at this stage; it needs to undergo quality evaluation. Only spatiotemporal virtual avatars that pass the quality assessment can be stored in the database. A pre-trained quality evaluation model can be used to output the quality score of the spatiotemporal virtual avatar.

[0118] Step 402: Input the spatiotemporal virtual clone into the pre-trained quality evaluation model and output the quality score of the spatiotemporal virtual clone.

[0119] In this embodiment, the quality assessment model is a neural network. The training samples for this neural network include positive samples (spatiotemporal virtual clones with a quality score of 100) and negative samples (spatiotemporal virtual clones with a quality score of 0). The positive and negative samples are input into the quality assessment model to obtain predicted quality scores. The predicted quality scores are compared with the actual scores, and a loss value is calculated based on the difference. The network parameters of the quality assessment model are adjusted according to the loss value, causing the loss value to continuously decrease until it converges to a predetermined value, or the iteration reaches a predetermined number, at which point the quality assessment model training is complete. The trained quality assessment model can be used to evaluate the quality scores of spatiotemporal virtual clones.

[0120] Step 403: In response to determining that the quality score is greater than a predetermined threshold, the spatiotemporal virtual clone is stored in the database.

[0121] In this embodiment, in response to determining that the quality score is greater than a predetermined threshold (e.g., 80 points), the spatiotemporal virtual avatar is stored in the database. When it is detected that the user's current driving data meets preset safety and triggering conditions, a target spatiotemporal virtual avatar is determined from the spatiotemporal virtual avatar set based on the current driving data. Then, a request is initiated to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar; in response to detecting that the user accepts the request, the user's interactive driving data during the interactive activity is recorded; the interactive driving data is compared and analyzed with the driving data of the target spatiotemporal virtual avatar, and the comparison result is output.

[0122] The method provided in the above embodiments of this disclosure generates a spatiotemporal virtual clone for each user by collecting driving data from different vehicles.

[0123] Further reference Figure 5 As an implementation of the methods shown in the above figures, this disclosure provides an embodiment of a user interaction device, which is similar to... Figure 2Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0124] like Figure 5 As shown, the user interaction device 500 of this embodiment includes: a determining unit 501, an initiating unit 502, a recording unit 503, and an analysis unit 504. The determining unit 501 is configured to, in response to detecting that the user's current driving data meets preset safety and triggering conditions, determine a target spatiotemporal virtual clone from a set of spatiotemporal virtual clones based on the current driving data, wherein the set of spatiotemporal virtual clones includes driving data from different users; the initiating unit 502 is configured to initiate a request to invite the user to participate in interactive activities related to the target spatiotemporal virtual clone; the recording unit 503 is configured to, in response to detecting that the user accepts the request, record the user's interactive driving data during the interactive activity; and the analysis unit 504 is configured to compare and analyze the interactive driving data with the driving data of the target spatiotemporal virtual clone and output a comparison result.

[0125] The server pre-stores driving data from different users, and generates spatiotemporal virtual clones after preprocessing. The driving data may include at least one of the following: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening.

[0126] The system can match current driving data with a set of spatiotemporal virtual clones, finding those with a similarity greater than a predetermined threshold. For example, if the driving time and route are exactly the same, or the similarity is greater than 90%, a match is considered successful. If multiple matching spatiotemporal virtual clones exist, the one with the highest matching degree is selected.

[0127] Requests inviting users to participate in interactive activities related to a target spatiotemporal virtual avatar can be output through large voice models, HUDs, or AR devices. For example, the voice message could be "Would you like to participate in a race to get to the office first?", or the HUD screen could display other users taking the same route, inviting them to race to see who arrives first. If the user is wearing AR glasses, the interactive activity information can be displayed on the AR glasses.

[0128] Users can accept requests via voice or touchpad. Once accepted, driving data within the specified time and space range of the interactive activity will be recorded as interactive driving data.

[0129] The following driving data can be compared and analyzed: driving time, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening. Item-by-item comparison results can be obtained. For example, the current user's driving time is shorter than other users, but the driving route is longer. The current user's vehicle speed is faster than other users'. The current user's vehicle acceleration is greater than other users'. The current user's steering wheel angle is larger than other users'. The current user's accelerator pedal opening is larger than other users'. The current user's brake pedal opening is larger than other users'. The overall analysis result can be obtained: although the current user drives faster than other users, the driving is unstable, resulting in higher fuel consumption, increased wear and tear on parts, and a poor passenger experience. The advantages and disadvantages of the current user's driving habits can be analyzed, and improvement suggestions can be provided.

[0130] The apparatus provided in the above embodiments of this disclosure generates spatiotemporal virtual avatars from each user's own driving data, interacts with users through a large language model, enhances the user's driving pleasure and interactive experience, and increases the user's acceptance of their private virtual avatar. By interacting with spatiotemporal virtual avatars of different users, interest matching based on driving habits is established in advance among users, thereby guiding users to engage in more extensive real-person social activities and increasing community activity.

[0131] In this embodiment, the specific processing of the determining unit 501, initiating unit 502, recording unit 503, and analysis unit 504 of the user interaction device 500 can be referred to Figure 2 The corresponding steps are 201, 202, 203 and 204 in the embodiment.

[0132] In some optional implementations of this embodiment, the spatiotemporal virtual clone includes feature tags; and the determining unit 501 is further configured to: extract the user's driving characteristics based on at least one of the following in the current driving data: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening; match the driving characteristics with the feature tags in the spatiotemporal virtual clone set, and take the successfully matched spatiotemporal virtual clone as the target spatiotemporal virtual clone.

[0133] In some optional implementations of this embodiment, the initiating unit 502 is further configured to: invite the user to participate in interactive activities related to the target spatiotemporal virtual clone by playing voice or displaying text through a predetermined device, wherein the predetermined device includes at least one of the following: vehicle central control screen, head-up display system, augmented reality device.

[0134] In some optional implementations of this embodiment, the device 500 further includes a reselection unit (not shown in the figures), configured to: in response to detecting that the user accepts the request, in response to receiving user voice, understand the user voice through a large language model to obtain limiting conditions for the request; and reselect a target spatiotemporal virtual clone that matches the current driving data according to the limiting conditions.

[0135] In some optional implementations of this embodiment, the initiating unit 502 is further configured to: in response to the user participating in the interactive activity more than a predetermined threshold, initiate a request to invite multiple other users to participate in the interactive activity.

[0136] In some optional implementations of this embodiment, the determining unit 501 is further configured to: receive a search request input by a user, wherein the search request includes: time and location; search for a candidate set of spatiotemporal virtual clones in the set of spatiotemporal virtual clones according to the search request; and determine a target spatiotemporal virtual clone from the candidate set of spatiotemporal virtual clones based on the current driving data.

[0137] In some optional implementations of this embodiment, the device 500 further includes a recommendation unit (not shown in the figures), configured to: determine the characteristics of the user's spatiotemporal virtual avatar based on the interactive driving data; filter out candidate spatiotemporal virtual avatars that meet the characteristics from the set of spatiotemporal virtual avatars; and recommend real users corresponding to the candidate spatiotemporal virtual avatars to the user for social activities.

[0138] In some optional implementations of this embodiment, the device 500 further includes a permission unit (not shown in the figures), configured to: accumulate points based on the number of interactive activities the user participates in; and set corresponding permissions for the user according to predetermined point rules.

[0139] In some optional implementations of this embodiment, the device 500 further includes a construction unit (not shown in the figures), configured to: clean the user's driving data and generate a spatiotemporal virtual clone; input the spatiotemporal virtual clone into a pre-trained quality evaluation model and output a quality score for the spatiotemporal virtual clone; and, in response to determining that the quality score is greater than a predetermined threshold, store the spatiotemporal virtual clone in a database.

[0140] It should be noted that the collection, gathering, updating, analysis, processing, use, transmission, and storage of user personal information involved in this disclosed technical solution all comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken to prevent unauthorized access to user personal information data and to safeguard user personal information security, network security, and national security.

[0141] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.

[0142] An electronic device includes: one or more processors; and a storage device having one or more computer programs stored thereon, which, when executed by the one or more processors, cause the one or more processors to implement the method described in process 200 or 400.

[0143] A computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in process 200 or 400.

[0144] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0145] like Figure 6 As shown, device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 602 or a computer program loaded from storage unit 608 into random access memory (RAM) 603. RAM 603 may also store various programs and data required for the operation of device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0146] Multiple components in device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0147] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as road planning methods. For example, in some embodiments, the road planning method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the road planning method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the road planning method by any other suitable means (e.g., by means of firmware).

[0148] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0149] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0150] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0151] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0152] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0153] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be servers in distributed systems or servers incorporating blockchain technology. Servers can also be cloud servers, or intelligent cloud computing servers or intelligent cloud hosts with artificial intelligence technology.

[0154] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0155] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for user interaction, comprising: In response to the detection that the user's current driving data meets preset safety conditions and triggering conditions, a target spatiotemporal virtual clone is determined from the spatiotemporal virtual clone set based on the current driving data, wherein the spatiotemporal virtual clone set includes driving data of different users; Initiate a request to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar; In response to detecting that the user accepts the request, the user's interactive driving data during the interactive activity is recorded; The interactive driving data is compared and analyzed with the driving data of the target spatiotemporal virtual clone, and the comparison results are output.

2. The method according to claim 1, wherein, Spatiotemporal virtual avatars include feature tags; as well as The step of determining the target spatiotemporal virtual clone from the set of spatiotemporal virtual clones based on the current driving data includes: The user's driving characteristics are extracted based on at least one of the following from the current driving data: driving time period, driving route, vehicle speed, vehicle acceleration, steering wheel angle, accelerator pedal opening, and brake pedal opening. The driving characteristics are matched with the feature tags in the spatiotemporal virtual clone set, and the successfully matched spatiotemporal virtual clone is taken as the target spatiotemporal virtual clone.

3. The method according to claim 1, wherein, The request to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar includes: The request to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar is made by playing voice or displaying text through a predetermined device, wherein the predetermined device includes at least one of the following: a vehicle infotainment screen, a head-up display system, or an augmented reality device.

4. The method according to claim 1, wherein, The method further includes: In response to detecting that the user has accepted the request, and in response to receiving the user's voice, the user's voice is understood through a large language model to obtain the limiting conditions for the request; Based on the aforementioned limiting conditions, a new target spatiotemporal virtual clone matching the current driving data is selected.

5. The method according to claim 1, wherein, The method further includes: In response to the user participating in the interactive activity more than a predetermined threshold, a request is initiated to invite multiple other users to participate in the interactive activity.

6. The method according to claim 1, wherein, The step of determining the target spatiotemporal virtual clone from the set of spatiotemporal virtual clones based on the current driving data includes: Receive a search request input by a user, wherein the search request includes: time and location; Based on the search request, a candidate set of spatiotemporal virtual avatars is searched in the set of spatiotemporal virtual avatars; The target spatiotemporal virtual clone is determined from the candidate spatiotemporal virtual clone set based on the current driving data.

7. The method according to claim 1, wherein, The method further includes: The characteristics of the user's spatiotemporal virtual avatar are determined based on the interactive driving data. Candidate spatiotemporal virtual clones that meet the aforementioned characteristics are selected from the set of spatiotemporal virtual clones; The system recommends real users corresponding to the candidate spatiotemporal virtual avatars to the user for social activities.

8. The method according to claim 1, wherein, The method further includes: Points are accumulated based on the number of interactive activities the user participates in; Set appropriate permissions for the user according to the predetermined points rules.

9. The method according to any one of claims 1-8, wherein, The method further includes: Clean the user's driving data and generate a spatiotemporal virtual clone; The spatiotemporal virtual clone is input into a pre-trained quality evaluation model, and the quality score of the spatiotemporal virtual clone is output. In response to determining that the quality score is greater than a predetermined threshold, the spatiotemporal virtual clone is stored in the database.

10. A user interaction device, comprising: The determining unit is configured to, in response to detecting that the user's current driving data meets preset safety conditions and triggering conditions, determine a target spatiotemporal virtual clone from a set of spatiotemporal virtual clones based on the current driving data, wherein the set of spatiotemporal virtual clones includes driving data of different users; The initiating unit is configured to initiate a request to invite the user to participate in interactive activities related to the target spatiotemporal virtual avatar; The recording unit is configured to record the user's interactive driving data during the interactive activity in response to detecting that the user has accepted the request; The analysis unit is configured to compare and analyze the interactive driving data with the driving data of the target spatiotemporal virtual clone, and output the comparison results.

11. An electronic device, comprising: One or more processors; Storage device, on which one or more computer programs are stored, When the one or more computer programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-9.

12. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-9.

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