Vehicle-mounted IP driving methods, devices, electronic devices and storage media

Abstract

This application relates to the field of vehicle technology and discloses an in-vehicle IP driving method, device, electronic device, and storage medium. The method includes: acquiring a multi-source perception data set inside and outside the vehicle to which the in-vehicle IP belongs, and determining at least the vehicle driving scenario, user emotion level, road condition classification level, and vehicle energy consumption level based on the multi-source perception data set; performing dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization of the levels, and then calculating at least an IP behavior decision score based on the weight reorganization, user emotion level, road condition classification level, and vehicle energy consumption level; and determining at least the display position and service combination strategy of at least one in-vehicle IP based on the IP behavior decision score to achieve the initial display and driving of at least one in-vehicle IP. This application can at least achieve real-time switching of IP image and dynamic adaptation of interaction strategies, and establish a real-time linkage mechanism between the in-vehicle and external environments and IP behavior, which is beneficial to enhancing the value of environmental perception.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to an in-vehicle IP driving method, device, electronic device, and storage medium. Background Technology

[0002] The current implementation of in-vehicle virtual avatars faces at least the following technical challenges:

[0003] 1. Limited interaction: It relies on preset voice commands to trigger fixed animations and cannot actively adjust the IP position and appearance according to the actual vehicle use.

[0004] 2. Disconnection of environmental perception: Environmental data such as road conditions / weather are not associated with IP behavior, making it impossible to achieve scenario-based responses (such as automatic frequency reduction interaction during congestion). Summary of the Invention

[0005] The purpose of this invention is to provide an in-vehicle IP driving method, device, electronic device and storage medium, which can at least realize real-time switching of IP image and dynamic adaptation of interaction strategy, break through the traditional fixed response mode, and establish a real-time linkage mechanism between the in-vehicle environment and IP behavior, which is conducive to enhancing the value of environmental perception.

[0006] To address the aforementioned technical problems, in a first aspect, the present invention provides an in-vehicle IP driving method, comprising at least:

[0007] Acquire a multi-source perception data set inside and outside the vehicle belonging to the vehicle IP, and determine at least the vehicle driving scenario, user emotion level, road condition classification level and vehicle energy consumption level based on the multi-source perception data set.

[0008] At least based on the vehicle driving scenario, a dynamic weight allocation is performed to obtain a weight reorganization, and then at least based on the weight reorganization, the user emotion level, the road condition classification level, and the vehicle energy consumption level, an IP behavior decision score is calculated.

[0009] Based on the IP behavior decision score, at least one vehicle IP display position and service table combination strategy are determined to achieve the initial display and driving of at least one vehicle IP.

[0010] Optionally, it may also include at least:

[0011] Predefine the interactive attributes of each in-vehicle display unit;

[0012] In response to the cross-screen collaborative display requirement of at least one in-vehicle IP, at least the collaborative task type that each in-vehicle IP needs to perform should be parsed.

[0013] Based at least on the collaborative task type corresponding to any vehicle IP and the interactive attributes of each vehicle display unit required for collaborative display, the start and end coordinates, transition animation decision and animation duration of the corresponding vehicle IP when performing cross-screen display between any adjacent vehicle display units are determined.

[0014] At least based on the start and end coordinates, the transition animation decision, and the animation duration, the corresponding vehicle IP is driven to perform cross-screen display between any adjacent vehicle display units.

[0015] Optionally, the step of driving the corresponding in-vehicle IP to perform cross-screen display between any adjacent in-vehicle display units based at least on the start and end coordinates, the transition animation decision, and the animation duration specifically includes at least:

[0016] The virtual movement path is determined based on at least the end coordinates of any vehicle IP in the current vehicle display unit and its start coordinates in the target vehicle display unit;

[0017] The corresponding vehicle IP is driven to move along the virtual movement path according to the transition animation decision during the duration of the animation, and the loading and release of image rendering resources are performed synchronously at least during the movement of the vehicle IP, so as to realize the cross-screen display of the corresponding vehicle IP between any adjacent vehicle display units.

[0018] Optionally, the IP behavior decision score is calculated at least in the following ways:

[0019] W z =α×W qx +β×W lk +γ×W nh ;

[0020] Among them, W z The IP behavior decision score is represented by α, where α represents the emotion level weight, and W represents the emotional level weight. qx β represents the user's emotional level, W represents the road condition level weight, and W represents the user's emotional level. lk The road condition classification level is represented by γ, and the energy consumption level weight is represented by W. nh The energy consumption level of the vehicle is represented by α, β, and γ; these together constitute the weighted reorganization of the level.

[0021] Based on the same concept, in a second aspect, the present invention also provides an in-vehicle IP driving device for performing the in-vehicle IP driving method described in any one of the first aspects;

[0022] The vehicle-mounted IP drive device includes at least:

[0023] The rating determination module is used to acquire multi-source perception data groups inside and outside the vehicle to which the vehicle IP belongs, and to determine at least the vehicle driving scenario, user emotion level, road condition classification level and vehicle energy consumption level based on the multi-source perception data groups.

[0024] The scoring calculation module is used to perform dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization, and then calculate an IP behavior decision score based on the weight reorganization, the user emotion level, the road condition classification level, and the vehicle energy consumption level.

[0025] The initial driving module is used to determine at least one display position and service table combination strategy of vehicle IP based on the IP behavior decision score, so as to realize the initial display and driving of at least one vehicle IP.

[0026] Optionally, it may also include at least a cross-screen driver module;

[0027] The cross-screen driving module is used for at least:

[0028] Predefine the interactive attributes of each in-vehicle display unit;

[0029] In response to the cross-screen collaborative display requirement of at least one in-vehicle IP, at least the collaborative task type that each in-vehicle IP needs to perform should be parsed.

[0030] Based at least on the collaborative task type corresponding to any vehicle IP and the interactive attributes of each vehicle display unit required for collaborative display, the start and end coordinates, transition animation decision and animation duration of the corresponding vehicle IP when performing cross-screen display between any adjacent vehicle display units are determined.

[0031] At least based on the start and end coordinates, the transition animation decision, and the animation duration, the corresponding vehicle IP is driven to perform cross-screen display between any adjacent vehicle display units.

[0032] Optionally, the cross-screen driving module is specifically used for at least:

[0033] The virtual movement path is determined based on at least the end coordinates of any vehicle IP in the current vehicle display unit and its start coordinates in the target vehicle display unit;

[0034] The corresponding vehicle IP is driven to move along the virtual movement path according to the transition animation decision during the duration of the animation, and the loading and release of image rendering resources are performed synchronously at least during the movement of the vehicle IP, so as to realize the cross-screen display of the corresponding vehicle IP between any adjacent vehicle display units.

[0035] Optionally, the IP behavior decision score is calculated at least in the following ways:

[0036] W z =α×W qx +β×W lk +γ×W nh ;

[0037] Among them, W z The IP behavior decision score is represented by α, where α represents the emotion level weight, and W represents the emotional level weight. qx β represents the user's emotional level, W represents the road condition level weight, and W represents the user's emotional level. lk The road condition classification level is represented by γ, and the energy consumption level weight is represented by W. nh The energy consumption level of the vehicle is represented by α, β, and γ; these together constitute the weighted reorganization of the level.

[0038] Based on the same concept, in a third aspect, the present invention also provides an electronic device including a memory and a processor, the memory storing a computer program executable on the processor, the processor executing the program to implement the steps of the vehicle IP driving method according to any one of the first aspects.

[0039] Based on the same concept, in a fourth aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the vehicle IP driving method according to any one of the first aspects.

[0040] The technical solution provided by this invention first acquires a multi-source perception data set inside and outside the vehicle to which the in-vehicle IP belongs, and determines at least the vehicle driving scenario, user emotion level, road condition classification level, and vehicle energy consumption level based on the multi-source perception data set. Then, it performs dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization of the levels, and calculates at least an IP behavior decision score based on the weight reorganization, user emotion level, road condition classification level, and vehicle energy consumption level. Finally, it determines at least the display position and service combination strategy of at least one in-vehicle IP based on the IP behavior decision score to achieve the initial display and driving of at least one in-vehicle IP. Thus, this invention, on the one hand, employs multi-source data collaborative processing with dynamic weight allocation, which can adjust the influence weight of each modality data according to scenario requirements, making IP interaction more aligned with user needs and scenario changes, improving interaction accuracy and user experience; on the other hand, it can at least establish a mapping relationship between environmental parameters such as road conditions and weather and IP expressions and actions, giving the IP emotional companionship capabilities, reducing driving fatigue, and improving the travel experience. Attached Figure Description

[0041] Figure 1 This is a flowchart of an in-vehicle IP driving method provided in an embodiment of the present invention;

[0042] Figure 2This is a flowchart of another vehicle IP driving method provided in an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of the structure of an in-vehicle IP drive device provided in an embodiment of the present invention;

[0044] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0046] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0047] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0048] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0049] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0050] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0051] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0052] Figure 1 This is a flowchart of an in-vehicle IP driving method provided by an embodiment of the present invention. This embodiment is applicable to at least any driving control scenario for in-vehicle virtual avatars in a car. The in-vehicle IP driving method can be, but is not limited to, executed by the in-vehicle IP driving device in this embodiment of the present invention as the execution subject. This execution subject can be implemented in software and / or hardware. Figure 1 As shown, the vehicle-mounted IP driving method includes at least the following steps:

[0053] S1. Obtain the multi-source perception data set inside and outside the vehicle to which the vehicle IP belongs, and determine at least the vehicle driving scenario, user emotion level, road condition classification level and vehicle energy consumption level based on the multi-source perception data set.

[0054] The multi-source perception data group can be composed of various perception data acquired simultaneously by multiple data acquisition devices, such as cockpit area images acquired by a wide-angle camera, user voice commands acquired by a microphone array, vehicle exterior fusion point cloud data based on lidar and millimeter-wave radar, vehicle speed signals acquired by the CAN bus, and weather information acquired by the vehicle network.

[0055] Furthermore, there can be various vehicle driving scenarios, such as acceleration driving scenarios, temporary parking scenarios, and rainy driving scenarios. In addition, the user's emotional level can be determined at least through a combination of visual images (68 facial key points and gaze direction vectors) and audio analysis (voiceprint and sound source localization), the road condition classification level can be determined at least based on lidar point cloud data (150m detection) and millimeter-wave radar point cloud data (±90°), and the vehicle energy consumption level can be determined at least based on the power battery and / or fuel consumption data provided by the CAN bus.

[0056] S2. Perform dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization, and then calculate an IP behavior decision score based on the weight reorganization, user emotion level, road condition classification level, and vehicle energy consumption level.

[0057] The reorganization of ranking weights can include multiple weights.

[0058] In one specific implementation, the IP behavior decision score may optionally be calculated in at least the following ways:

[0059] W z =α×W qx +β×W lk +γ×W nh ;

[0060] Among them, W z This represents the IP behavior decision score, α represents the emotional level weight, and W... qx β represents the user's emotional level, and W represents the weight of the road condition level. lk Indicates the road condition classification level, γ represents the energy consumption level weight, and W nh This indicates the vehicle's energy consumption level; α, β, and γ together constitute the weighted reorganization of the level.

[0061] In another specific implementation, when the vehicle is in an acceleration driving scenario, α, β and γ can be assigned values ​​of 0.3, 0.6 and 0.1 respectively; when the vehicle is in a temporary parking scenario, α, β and γ can be assigned values ​​of 0.5, 0.3 and 0.2 respectively.

[0062] S3. Determine at least one vehicle IP's display position and service table combination strategy based on IP behavior decision scoring to achieve the initial display and driving of at least one vehicle IP.

[0063] The costume combination strategy can include clothing schemes and emoticon numbers for in-vehicle IPs.

[0064] In another specific implementation, when the IP behavior decision score is within the first scoring threshold range (e.g., corresponding to a driving scenario where the user is in a positive mood, the road conditions are smooth, and the vehicle's battery and / or fuel level are sufficient), the in-vehicle IP display is positioned on the driver's side, the IP clothing is selected as casual wear, and the expression is smiling; when the IP behavior decision score is within the second scoring threshold range (e.g., corresponding to a driving scenario where the user is in a negative mood, the road conditions are congested, and the vehicle's battery and / or fuel level are insufficient), the in-vehicle IP display is positioned in the center of the dashboard, the IP clothing is selected as formal wear, and the expression is encouraging; when the IP behavior decision score is within the third scoring threshold range (e.g., corresponding to a driving scenario where the user is in a calm mood, the road is icy, and the vehicle's battery and / or fuel level are moderate), the in-vehicle IP display is minimized, the IP clothing is selected as safety clothing, and the expression is focused.

[0065] The technical solution provided in this embodiment first acquires a multi-source perception data set inside and outside the vehicle to which the in-vehicle IP belongs, and determines at least the vehicle driving scenario, user emotion level, road condition classification level, and vehicle energy consumption level based on the multi-source perception data set. Then, it performs dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization of the levels, and calculates at least an IP behavior decision score based on the weight reorganization, user emotion level, road condition classification level, and vehicle energy consumption level. Finally, it determines at least the display position and service combination strategy of at least one in-vehicle IP based on the IP behavior decision score to achieve the initial display and driving of at least one in-vehicle IP. Therefore, this embodiment, on the one hand, adopts multi-source data collaborative processing with dynamic weight allocation, which can adjust the influence weight of each modality data according to scenario requirements, making IP interaction more aligned with user needs and scenario changes, improving interaction accuracy and user experience; on the other hand, it can at least establish a mapping relationship between environmental parameters such as road conditions and weather and IP expressions and actions, giving the IP emotional companionship capabilities, reducing driving fatigue, and improving the travel experience.

[0066] It should be noted that there are corresponding relationships between the aforementioned vehicle driving scenarios, user emotion levels, road condition classification levels, vehicle energy consumption levels, display positions of in-vehicle IPs, and service combination strategies. Therefore, in other implementations, the above parameters can also be integrated into a behavior mapping model or behavior mapping rule base based on multi-dimensional context awareness. This model or rule base can transform abstract sensor data into concrete IP behavior combinations that meet user expectations and scenario requirements.

[0067] Of course, whether it's formula calculation or model or rule base mapping, the embodiments of this invention also support the following dynamic adjustment mechanisms:

[0068] 1. Short-term memory: By recording the user's proactive adjustments to IP-specific behaviors during a single trip (such as manually changing clothing), this preference is prioritized for use in the same trip (or in similar scenarios in subsequent trips).

[0069] 2. Long-term evolution: Based on big data analysis, we mine the behavioral preferences of user groups and iteratively update the global rules through OTA.

[0070] It is understood that by incorporating a dynamic adjustment mechanism, the embodiments of the present invention can achieve at least the following beneficial effects:

[0071] 1. Behavioral contextualization: The behavior (location, appearance, expression) of the IP character is highly correlated with the real-time driving scenario, which solves the problem of the disconnect between IP behavior and scenario.

[0072] 2. Ensure driving safety: By mapping states such as "dangerous road conditions" and "low energy consumption" to behaviors such as "minimized display", the system proactively reduces interference with the driver and improves safety.

[0073] 3. Proactive Service: It can anticipate user needs based on comprehensive scenarios, drive IP characters to provide more forward-looking services, and improve interaction efficiency.

[0074] 4. Construct a learning system of short-term memory, medium-term adaptation, and long-term evolution: By combining user behavior analysis and scene feature extraction, the IP behavior pattern is dynamically updated, which can realize personalized interaction for each user and improve user stickiness and user satisfaction.

[0075] Based on the above embodiments or implementation methods, in another specific implementation method, optionally, the vehicle IP driving method further includes at least:

[0076] Predefine the interactive attributes of each in-vehicle display unit;

[0077] In response to the cross-screen collaborative display requirement of at least one in-vehicle IP, at least the collaborative task type that each in-vehicle IP needs to perform should be parsed.

[0078] Based at least on the collaborative task type corresponding to any vehicle IP and the interactive attributes of each vehicle display unit required for collaborative display, the start and end coordinates, transition animation decisions and animation duration of the corresponding vehicle IP when performing cross-screen display between any adjacent vehicle display units should be determined.

[0079] At least based on the start and end coordinates, transition animation decisions, and animation duration, the corresponding vehicle IP is driven to perform cross-screen display between any adjacent vehicle display units.

[0080] In another specific implementation, optionally, the corresponding in-vehicle IP is driven to perform cross-screen display between any adjacent in-vehicle display units based at least on the start and end coordinates, transition animation decisions, and animation duration, specifically including at least:

[0081] The virtual movement path is determined based on at least the end coordinates of any vehicle IP in the current vehicle display unit and its start coordinates in the target vehicle display unit;

[0082] The corresponding vehicle IP is driven to move along the virtual movement path according to the transition animation decision during the animation duration, and the loading and release of image rendering resources are performed synchronously at least during the movement of the vehicle IP, so as to realize the cross-screen display of the corresponding vehicle IP between any adjacent vehicle display units.

[0083] Based on this Figure 2 This is a flowchart of another vehicle-mounted IP driving method provided by an embodiment of the present invention, such as... Figure 2As shown, the vehicle-mounted IP driving method includes at least the following steps:

[0084] S1. Obtain the multi-source perception data set inside and outside the vehicle to which the vehicle IP belongs, and determine at least the vehicle driving scenario, user emotion level, road condition classification level and vehicle energy consumption level based on the multi-source perception data set.

[0085] S2. Perform dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization, and then calculate an IP behavior decision score based on the weight reorganization, user emotion level, road condition classification level, and vehicle energy consumption level.

[0086] S3. Determine at least one vehicle IP's display position and service table combination strategy based on IP behavior decision scoring to achieve the initial display and driving of at least one vehicle IP.

[0087] S4. Predefine the interaction attributes of each in-vehicle display unit.

[0088] The in-vehicle display unit can be of various types, such as the instrument panel, the central control screen, and the AR-HUD; each in-vehicle display unit can be connected to the vehicle's high-speed communication bus (such as CAN FD).

[0089] In another specific implementation, the interaction attributes of each in-vehicle display unit can be configured as follows:

[0090] The instrument panel can be defined as the core driving information area, at least suitable for displaying simple IP status directly related to driving safety; the central control screen can be defined as the main interactive stage, at least suitable for IP to perform full-function, high-expression interaction; the AR-HUD can be defined as the augmented reality information layer, at least suitable for IP to perform navigation and safety prompts integrated with the road environment.

[0091] S5. In response to the cross-screen collaborative display requirement of at least one vehicle IP, at least the collaborative task type to be executed by each vehicle IP is parsed.

[0092] The types of collaborative tasks can include navigation guidance, entertainment control, and security warnings.

[0093] S6. Based at least on the collaborative task type corresponding to any vehicle IP and the interactive attributes of each vehicle display unit required for collaborative display, determine at least the start and end coordinates, transition animation decisions, and animation duration when the corresponding vehicle IP performs cross-screen display between any adjacent vehicle display units.

[0094] S7. Determine the virtual movement path based at least on the end coordinates of any vehicle IP in the current vehicle display unit and its starting coordinates in the target vehicle display unit.

[0095] S8 drives the corresponding vehicle IP to move along the virtual movement path according to the transition animation decision during the animation duration, and at least during the movement of the vehicle IP, loads and releases image rendering resources synchronously to realize cross-screen display of the corresponding vehicle IP between any adjacent vehicle display units.

[0096] Steps S6-S8 essentially determine, based on the collaborative task type and the screen role definition (i.e., the interactive attributes of the aforementioned in-vehicle display unit), which screen(s) the IP should perform and what display(s) on (e.g., a "navigation guidance" task might simultaneously display arrows on the AR-HUD and simplified icons on the dashboard). Further, when the IP needs to move from one screen to another, the following operations can be performed: A virtual movement path is calculated based on the IP's end coordinates on the current screen and its starting coordinates on the target screen; the IP image is driven along this path (non-screen paths can be implemented through projection, etc.) using a preset transition animation (such as fly-in or glide-in), with the animation duration controlled between 0.3 and 0.5 seconds; during the animation, image rendering resources are loaded and released synchronously to ensure a smooth, lag-free transition.

[0097] In summary, the embodiments of the present invention, through the above specific implementation schemes, can achieve at least the following beneficial effects:

[0098] 1. Interactive coherence: By using path animation to connect the display of the IP across different screens, the abruptness and disjointedness of screen transitions are eliminated, providing users with a unified interactive narrative experience.

[0099] 2. Attention Guidance: By moving the IP character, the user's visual focus is naturally guided to the area displaying the most important information, which conforms to natural interaction logic and reduces cognitive load.

[0100] 3. Spatial immersion: This allows the IP character to no longer be confined to a single screen, but to exist throughout the entire cabin space, greatly enhancing its sense of real presence and the user's emotional connection.

[0101] Figure 3 This is a schematic diagram of the structure of an in-vehicle IP driving device provided in an embodiment of the present invention. This embodiment is applicable to at least any driving control scenario for in-vehicle virtual avatars in a car. The in-vehicle IP driving device can be implemented in software and / or hardware. Figure 3 As shown, the vehicle-mounted IP drive unit includes at least:

[0102] The rating determination module 110 is used to acquire multi-source perception data groups inside and outside the vehicle to which the vehicle IP belongs, and to determine at least the vehicle driving scenario, user emotion level, road condition classification level and vehicle energy consumption level based on the multi-source perception data groups.

[0103] The scoring calculation module 120 is used to perform dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization, and then calculate at least an IP behavior decision score based on the weight reorganization, user emotion level, road condition classification level and vehicle energy consumption level.

[0104] The initial driving module 130 is used to determine at least one vehicle IP's display position and service table combination strategy based on at least one IP behavior decision score, so as to realize the initial display and driving of at least one vehicle IP.

[0105] Optionally, it may also include at least a cross-screen driver module 140;

[0106] The cross-screen driver module 140 is used for at least:

[0107] Predefine the interactive attributes of each in-vehicle display unit;

[0108] In response to the cross-screen collaborative display requirement of at least one in-vehicle IP, at least the collaborative task type that each in-vehicle IP needs to perform should be parsed.

[0109] Based at least on the collaborative task type corresponding to any vehicle IP and the interactive attributes of each vehicle display unit required for collaborative display, the start and end coordinates, transition animation decisions and animation duration of the corresponding vehicle IP when performing cross-screen display between any adjacent vehicle display units should be determined.

[0110] At least based on the start and end coordinates, transition animation decisions, and animation duration, the corresponding vehicle IP is driven to perform cross-screen display between any adjacent vehicle display units.

[0111] Optionally, the cross-screen driver module 140 is specifically used for at least:

[0112] The virtual movement path is determined based on at least the end coordinates of any vehicle IP in the current vehicle display unit and its start coordinates in the target vehicle display unit;

[0113] The corresponding vehicle IP is driven to move along the virtual movement path according to the transition animation decision during the animation duration, and the loading and release of image rendering resources are performed synchronously at least during the movement of the vehicle IP, so as to realize the cross-screen display of the corresponding vehicle IP between any adjacent vehicle display units.

[0114] Optionally, the IP behavior decision score can be calculated at least in the following ways:

[0115] W z =α×W qx +β×W lk +γ×W nh ;

[0116] Among them, W z This represents the IP behavior decision score, α represents the emotional level weight, and W... qx β represents the user's emotional level, and W represents the weight of the road condition level. lk Indicates the road condition classification level, γ represents the energy consumption level weight, and W nh This indicates the vehicle's energy consumption level; α, β, and γ together constitute the weighted reorganization of the level.

[0117] The technical solution provided in this embodiment firstly acquires a multi-source perception data set inside and outside the vehicle to which the in-vehicle IP belongs through a level determination module, and determines at least the vehicle driving scenario, user emotion level, road condition classification level, and vehicle energy consumption level based on the multi-source perception data set. Then, a scoring calculation module performs dynamic weight allocation based on the vehicle driving scenario to obtain a level weight reorganization, and calculates at least an IP behavior decision score based on the level weight reorganization, user emotion level, road condition classification level, and vehicle energy consumption level. Finally, an initial driving module determines at least the display position and service combination strategy of at least one in-vehicle IP based on the IP behavior decision score to achieve the initial display and driving of at least one in-vehicle IP. Therefore, this embodiment, on the one hand, adopts multi-source data collaborative processing with dynamic weight allocation, which can adjust the influence weight of each modality data according to scenario requirements, making IP interaction more aligned with user needs and scenario changes, improving interaction accuracy and user experience; on the other hand, by establishing a mapping relationship between environmental parameters such as road conditions and weather and IP expressions and actions, it endows the IP with emotional companionship capabilities, reduces driving fatigue, and improves the travel experience.

[0118] This embodiment provides an electronic device. Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. See also: Figure 4The electronic device 1000 includes a processor 1001 and a memory 1002. The memory 1002 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 1001, the steps in any of the above-mentioned vehicle IP driving methods are performed. Through the above technical solution, the processor 1001 and the memory 1002 are interconnected and communicate with each other through a communication bus and / or other forms of connection mechanism (not shown). The memory 1002 stores a computer program that can be executed by the processor. When the electronic device 1000 is running, the processor 1001 executes the computer program to execute the vehicle IP driving method in any optional implementation of the above embodiments, so as to achieve at least the following functions: acquiring a multi-source perception data group inside and outside the vehicle to which the vehicle IP belongs, and determining at least the vehicle driving scenario, user emotion level, road condition classification level and vehicle energy consumption level based on at least the multi-source perception data group; performing dynamic weight allocation at least according to the vehicle driving scenario to obtain level weight reorganization, and then calculating at least the IP behavior decision score based on at least the level weight reorganization, user emotion level, road condition classification level and vehicle energy consumption level; determining at least the display position and service table combination strategy of at least one vehicle IP based on at least the IP behavior decision score, so as to realize the initial display and driving of at least one vehicle IP.

[0119] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle IP driving method provided in all embodiments of this application: acquiring a multi-source perception data set inside and outside the vehicle to which the vehicle IP belongs, and determining at least the vehicle driving scenario, user emotion level, road condition classification level, and vehicle energy consumption level based on the multi-source perception data set; performing dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization of the levels, and then calculating at least an IP behavior decision score based on the weight reorganization of the levels, user emotion level, road condition classification level, and vehicle energy consumption level; and determining at least the display position and service table combination strategy of at least one vehicle IP based on the IP behavior decision score to achieve the initial display and driving of at least one vehicle IP.

[0120] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, 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 device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0121] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0122] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0123] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle-mounted IP driving method, characterized in that, At least including: Acquire a multi-source perception data set inside and outside the vehicle belonging to the vehicle IP, and determine at least the vehicle driving scenario, user emotion level, road condition classification level and vehicle energy consumption level based on the multi-source perception data set. At least based on the vehicle driving scenario, a dynamic weight allocation is performed to obtain a weight reorganization, and then at least based on the weight reorganization, the user emotion level, the road condition classification level, and the vehicle energy consumption level, an IP behavior decision score is calculated. Based on the IP behavior decision score, at least one vehicle IP display position and service table combination strategy are determined to achieve the initial display and driving of at least one vehicle IP.

2. The vehicle-mounted IP driving method according to claim 1, characterized in that, It also includes at least: Predefine the interactive attributes of each in-vehicle display unit; In response to the cross-screen collaborative display requirement of at least one in-vehicle IP, at least the collaborative task type that each in-vehicle IP needs to perform should be parsed. Based at least on the collaborative task type corresponding to any vehicle IP and the interactive attributes of each vehicle display unit required for collaborative display, the start and end coordinates, transition animation decision and animation duration of the corresponding vehicle IP when performing cross-screen display between any adjacent vehicle display units are determined. At least based on the start and end coordinates, the transition animation decision, and the animation duration, the corresponding vehicle IP is driven to perform cross-screen display between any adjacent vehicle display units.

3. The vehicle-mounted IP driving method according to claim 2, characterized in that, The step of driving the corresponding vehicle IP to perform cross-screen display between any adjacent vehicle display units based at least on the start and end coordinates, the transition animation decision, and the animation duration specifically includes at least the following: The virtual movement path is determined based on at least the end coordinates of any vehicle IP in the current vehicle display unit and its start coordinates in the target vehicle display unit; The corresponding vehicle IP is driven to move along the virtual movement path according to the transition animation decision during the duration of the animation, and the loading and release of image rendering resources are performed synchronously at least during the movement of the vehicle IP, so as to realize the cross-screen display of the corresponding vehicle IP between any adjacent vehicle display units.

4. The vehicle-mounted IP driving method according to claim 1, characterized in that, The IP behavior decision score is calculated at least in the following ways: IN z =α×W qx +β×W lk +γ×W nh ; Among them, W z The IP behavior decision score is represented by α, where α represents the emotion level weight, and W represents the emotional level weight. qx β represents the user's emotional level, W represents the road condition level weight, and W represents the user's emotional level. lk The road condition classification level is represented by γ, and the energy consumption level weight is represented by W. nh The energy consumption level of the vehicle is represented by α, β, and γ; these together constitute the weighted reorganization of the level.

5. A vehicle-mounted IP drive device, characterized in that, Used to perform the vehicle IP driving method according to any one of claims 1-4; The vehicle-mounted IP drive device includes at least: The rating determination module is used to acquire multi-source perception data groups inside and outside the vehicle to which the vehicle IP belongs, and to determine at least the vehicle driving scenario, user emotion level, road condition classification level and vehicle energy consumption level based on the multi-source perception data groups. The scoring calculation module is used to perform dynamic weight allocation based on the vehicle driving scenario to obtain a weight reorganization, and then calculate an IP behavior decision score based on the weight reorganization, the user emotion level, the road condition classification level, and the vehicle energy consumption level. The initial driving module is used to determine at least one display position and service table combination strategy of vehicle IP based on the IP behavior decision score, so as to realize the initial display and driving of at least one vehicle IP.

6. The vehicle-mounted IP drive device according to claim 5, characterized in that, It should also include at least a cross-screen driver module; The cross-screen driving module is used for at least: Predefine the interactive attributes of each in-vehicle display unit; In response to the cross-screen collaborative display requirement of at least one in-vehicle IP, at least the collaborative task type that each in-vehicle IP needs to perform should be parsed. Based at least on the collaborative task type corresponding to any vehicle IP and the interactive attributes of each vehicle display unit required for collaborative display, the start and end coordinates, transition animation decision and animation duration of the corresponding vehicle IP when performing cross-screen display between any adjacent vehicle display units are determined. At least based on the start and end coordinates, the transition animation decision, and the animation duration, the corresponding vehicle IP is driven to perform cross-screen display between any adjacent vehicle display units.

7. The vehicle-mounted IP drive device according to claim 6, characterized in that, The cross-screen driving module is specifically used for at least: The virtual movement path is determined based on at least the end coordinates of any vehicle IP in the current vehicle display unit and its start coordinates in the target vehicle display unit; The corresponding vehicle IP is driven to move along the virtual movement path according to the transition animation decision during the duration of the animation, and the loading and release of image rendering resources are performed synchronously at least during the movement of the vehicle IP, so as to realize the cross-screen display of the corresponding vehicle IP between any adjacent vehicle display units.

8. The vehicle-mounted IP drive device according to claim 5, characterized in that, The IP behavior decision score is calculated at least in the following ways: IN z =α×W qx +β×W lk +γ×W nh ; Among them, W z The IP behavior decision score is represented by α, where α represents the emotion level weight, and W represents the emotional level weight. qx β represents the user's emotional level, W represents the road condition level weight, and W represents the user's emotional level. lk The road condition classification level is represented by γ, and the energy consumption level weight is represented by W. nh The energy consumption level of the vehicle is represented by α, β, and γ; these together constitute the weighted reorganization of the level.

9. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the vehicle IP driving method according to any one of claims 1-4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the vehicle IP driving method according to any one of claims 1-4.

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