Visualization processing method, device and equipment for vehicle model

Abstract

The embodiment of the invention provides a vehicle model visualization processing method, device and equipment, and relates to the technical field of automatic driving. In the scheme, when a display style of a vehicle-mounted large screen of a vehicle is an interesting display mode, if it is determined that a target vehicle exists in a preset range of the vehicle and driving characteristics of the target vehicle meet interesting display preset conditions, a target visualization model of the target vehicle is determined; and the target vehicle is displayed in the vehicle-mounted large screen through the target visual model, so that personalized driving experience is provided for the user, and man-machine interaction is improved.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a method, device and equipment for visualizing a vehicle model. Background Art

[0002] With the rapid development of autonomous driving technology, drivers usually rely on large screens in the car to obtain information about the driving environment around the vehicle.

[0003] At present, the in-vehicle large screen uses a preset model display style to present the vehicle model to convey key information about the vehicle's surroundings. Specifically, the in-vehicle large screen relies on a preset graphical interface to display the core information of the vehicle and its surroundings in a concise and clear manner.

[0004] However, during the autonomous driving process, the existing human-computer interaction functions are relatively simple and it is difficult to provide a personalized driving experience. Summary of the invention

[0005] The embodiments of the present application provide a method, device and apparatus for visualizing a vehicle model, so as to provide a personalized driving experience and improve human-computer interaction.

[0006] In a first aspect, the present application provides a method for visualizing a vehicle model, the method comprising:

[0007] When the display style of the vehicle-mounted large screen is the fun display mode, if it is determined that there is a target vehicle within the preset range of the vehicle, and the driving characteristics of the target vehicle meet the preset conditions of the fun display, then the target visualization model of the target vehicle is determined;

[0008] The target vehicle is displayed on the in-vehicle large screen using the target visualization model.

[0009] In a possible design of the first aspect, determining the target visualization model of the target vehicle includes:

[0010] Determining a visualization model corresponding to the driving characteristics of the target vehicle from the visualization model library as the target visualization model;

[0011] The visualization model material library includes a variety of driving characteristics and a corresponding relationship between at least one driving characteristic and a visualization model.

[0012] In a possible design of the first aspect, the target vehicle includes a vehicle having at least one of the following driving characteristics:

[0013] A vehicle traveling in the lane directly in front of the vehicle;

[0014] adjacent and / or preceding vehicles travelling in the road to the left of the vehicle;

[0015] A vehicle that changes lanes from in front of the vehicle and enters the lane where the vehicle is located;

[0016] Vehicles that drive illegally within the preset range;

[0017] A vehicle of a preset type within the preset range.

[0018] In a possible design of the first aspect, if the target vehicle is a vehicle that changes lanes illegally from in front of the vehicle and enters the lane where the vehicle is located, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model, including:

[0019] From the visualization model material library, visualization models corresponding to two driving characteristics of illegal driving and lane change ahead are obtained as the target visualization model.

[0020] In a possible design of the first aspect, if the target vehicle is a vehicle traveling in front of the lane where the vehicle is located, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model, including:

[0021] From the visualization model material library, visualization models corresponding to two driving characteristics, namely, driving at a slow speed and driving directly in front of the lane where the vehicle is located, are obtained as the target visualization model.

[0022] In a possible design of the first aspect, if the target vehicle is a vehicle adjacent to and / or in front of the vehicle traveling on the left side of the road, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model, including:

[0023] From the visualization model material library, a visualization model corresponding to two driving characteristics, namely, driving at a slow speed and driving adjacent to and / or in front of the vehicle on the left side road, is obtained as the target visualization model.

[0024] In a possible design of the first aspect, the method further includes:

[0025] When the driving characteristics of the target vehicle do not meet the preset conditions for the interesting display, the target vehicle is displayed on the vehicle-mounted large screen in a conventional visual model;

[0026] and / or,

[0027] When the duration of displaying the target visualization model on the vehicle-mounted large screen reaches a preset duration, the target vehicle is displayed on the vehicle-mounted large screen using the conventional visualization model.

[0028] In a second aspect, the present application provides a visualization processing device for a vehicle model, comprising:

[0029] A processing module, for determining a target visualization model of the target vehicle if it is determined that there is a target vehicle within a preset range of the vehicle and the driving characteristics of the target vehicle meet the preset conditions of the interesting display when the display style of the vehicle-mounted large screen is an interesting display mode;

[0030] A display module is used to display the target vehicle using the target visualization model on the vehicle-mounted large screen.

[0031] In a third aspect, the present application provides a large in-vehicle screen, comprising: a transceiver, a processor, and a memory connected to the processor in communication; the memory stores computer-executable instructions;

[0032] The processor executes the computer-executable instructions stored in the memory to implement the visualization processing method of the vehicle model as described in any one of the first aspects.

[0033] In a fourth aspect, the present application provides a vehicle, comprising: a vehicle body and the large vehicle-mounted screen described in the third aspect.

[0034] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0035] In a sixth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0036] The visualization processing method, device and equipment of the vehicle model provided in the embodiments of the present application relate to the field of autonomous driving technology. Compared with the single-style display mode in the prior art, this method provides users with an interesting display mode through the vehicle's large on-board screen, which significantly improves the fun and interactivity of the user experience. When the on-board large screen is in the fun display mode, the method can intelligently identify the target vehicle within the preset range of the vehicle, and determine and display the personalized visualization model of the target vehicle based on whether its driving characteristics meet the preset conditions of the fun display, thereby enhancing driving entertainment, improving human-computer interaction, and providing users with a personalized driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0038] Figure 1 A schematic diagram of a scene of a method for visualizing a vehicle model provided in this application;

[0039] Figure 2 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 1 ;

[0040] Figure 3 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 2 ;

[0041] Figure 4 A schematic diagram of a target vehicle that changes lanes illegally provided in this application;

[0042] Figure 5 A target visualization model of a target vehicle provided in this application is shown in FIG. Figure 1 ;

[0043] Figure 6 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 3 ;

[0044] Figure 7 A target visualization model of a target vehicle provided in this application is shown in FIG. Figure 2 ;

[0045] Figure 8 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 4 ;

[0046] Fig. 9 A target visualization model of a target vehicle provided in this application is shown in FIG. Figure 3 ;

[0047] Fig.10 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 5 ;

[0048] Fig.11 A schematic diagram of the framework of the visualization processing method of the vehicle model provided in this application;

[0049] Fig.12 A schematic diagram of the structure of a first embodiment of a visual processing device for a vehicle model provided by the present application;

[0050] Fig.13 This is a schematic diagram of the structure of the large vehicle screen provided for this application.

[0051] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0052] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0053] With the rapid development of autonomous driving technology, users mainly rely on the large screen on the vehicle to obtain information about the driving environment around the vehicle.

[0054] At present, the in-vehicle large screen usually uses a preset model display style to present the information of the vehicle model and its surrounding environment. Specifically, the in-vehicle large screen relies on a preset graphic interface to display the core information of the vehicle and its surrounding environment in a concise and clear manner. This display method is based on a two-dimensional or three-dimensional graphic model, combined with sensor data, and presented to the user in an intuitive way.

[0055] However, the existing large-screen display solutions for vehicles can provide basic environmental information, but during the autonomous driving process, the human-computer interaction function is relatively simple, making it difficult to provide a personalized driving experience. Specifically, the fixed display style cannot adapt to the preferences and needs of different users, resulting in limitations in user experience. At the same time, the fixed display style lacks interactive and interesting interface design, and cannot effectively improve user participation and satisfaction. Therefore, how to achieve a more personalized and interactive display mode on the large-screen vehicle has become an urgent problem to be solved in the current field of autonomous driving technology.

[0056] In view of the above problems, the inventor discovered during the research on the visualization processing method of the vehicle model that the existing technical solutions usually use a fixed vehicle model to display the vehicle when realizing the visualization display of the vehicle model, lacking human-computer interaction and making it difficult to provide users with a personalized driving experience. Based on this, the inventor considered whether it is possible to display the vehicle in a personalized manner on the on-board large screen according to the driving characteristics of the vehicle. Specifically, in addition to providing the display style of the conventional display mode, the on-board large screen of the vehicle provides the user with the display style of the fun display mode. At the same time, when the display style of the on-board large screen of the vehicle is the fun display mode, if it is determined that there is a target vehicle within the preset range of the vehicle, and the driving characteristics of the target vehicle meet the preset conditions of the fun display, the target visualization model of the target vehicle is determined, and the target vehicle is displayed on the on-board large screen with the target visualization model, thereby providing the fun of human-computer interaction and providing users with a personalized driving experience.

[0057] Figure 1 A schematic diagram of a scene of the method for visualizing a vehicle model provided in this application. Figure 1 As shown, the application scenario of the visualization processing method of the vehicle model provided by the present application is a human-machine co-driving scenario. In the human-machine co-driving scenario, a vehicle 100 is included. Among them, an automatic driving control system 101 and a large vehicle screen 102 are deployed in the vehicle 100. It is worth noting that although Figure 1 Only one vehicle 100 is shown in FIG. 1 , but it should be understood that two or more vehicles 100 may be present.

[0058] When the display style of the on-board large screen 102 is the fun display mode, the automatic driving control system 101 will detect whether there is a target vehicle within the preset range of the vehicle 100. If there is a target vehicle and the driving characteristics of the target vehicle meet the preset conditions of the fun display, the automatic driving control system 101 will determine the target visualization model of the target vehicle and display the target vehicle with the target visualization model on the on-board large screen 102.

[0059] It should be noted that the above scenario is only an example of an application scenario provided by an embodiment of the present application. The embodiment of the present application does not limit the actual form of the various devices included in the scenario. In the specific application of the solution, it can be set according to actual needs.

[0060] It should be noted that the terms "user" and "driver" are interchangeable in this document.

[0061] For the convenience of description, the following takes the automatic driving control system as an example to introduce the implementation of the method for visualizing the vehicle model. It can be understood that the automatic driving control system as the execution subject of the method is only an exemplary description and should not be understood as a limitation of the method.

[0062] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0063] Figure 2 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 1 .like Figure 2 As shown, the process of the visualization processing method of the vehicle model may include:

[0064] S201: When the display style of the vehicle's large screen is the fun display mode, if it is determined that there is a target vehicle within a preset range of the vehicle and the driving characteristics of the target vehicle meet the preset conditions of the fun display, then a target visualization model of the target vehicle is determined.

[0065] In this step, in order to achieve a personalized driving experience and provide emotional value to users during vehicle driving, the present application further provides users with a display style of a vehicle model fun display mode based on the display style of the existing vehicle model conventional display mode.

[0066] It is worth noting that the display style of the vehicle-mounted large screen of the current vehicle can be determined according to the user's preferences. In one possible implementation, the display style of the vehicle's vehicle-mounted large screen includes but is not limited to conventional display, fun display and customized display, etc., to provide users with diverse and interesting visual display styles. The display style can be set with an optional switch. During the vehicle's driving process or when parked on the roadside, the vehicle responds to the user's display style selection operation and controls the vehicle-mounted large screen to be in the display mode corresponding to the display style selected by the user. Among them, the vehicle-mounted large screen is used to display vehicles, obstacles, navigation, lane lines, surrounding environment, etc., to provide users with visual vehicle driving information. The vehicle-mounted large screen is the central control screen in the vehicle. It is worth noting that if the user wants to select the fun display mode, and the display style of the vehicle-mounted large screen has been the fun display mode during the last vehicle driving process, the user does not need to make a selection at this time. If the user wants to display in a conventional visual model, the corresponding selection can be made, and the vehicle responds to the user's display style selection operation to control the vehicle-mounted large screen to be in the display mode corresponding to the display style selected by the user.

[0067] When the display style of the vehicle's large on-board screen is the fun display mode, the perception module in the vehicle's automatic driving control system will detect and judge the environment around the vehicle, especially whether there is a target vehicle within the preset range of the vehicle. Among them, the automatic driving control system collects and analyzes data from the surrounding environment to identify the existence of other vehicles and their driving characteristics, thereby deciding whether to trigger the personalized display function of the fun display mode. This process not only enhances the interactivity of driving, but also provides users with a richer visual experience. The preset range is determined according to the detectable range of various perception devices in the automatic driving control system, and this application does not make specific limitations on this.

[0068] The perception module in the autonomous driving control system detects and calculates roads and road participants (people and vehicles) based on sensors such as on-board cameras, millimeter-wave radars, and lidars. The system can calculate the position, lateral and longitudinal speeds, lateral and longitudinal acceleration, and other information of each road participant around the vehicle, which is used to provide information to the autonomous driving system for automated control decisions.

[0069] In one possible implementation, the driving characteristics recognized by the automatic driving control system include but are not limited to the lateral driving speed, longitudinal driving speed, lateral driving acceleration, longitudinal driving acceleration, driving position and lane line information of other vehicles.

[0070] If it is determined that there is a target vehicle within the preset range of the vehicle, it is further determined whether the driving characteristics of the target vehicle meet the preset conditions for the interesting display.

[0071] If the driving characteristics of the target vehicle meet the preset conditions for interesting display, the target visualization model of the target vehicle is further determined.

[0072] Correspondingly, if the driving characteristics of the target vehicle do not meet the preset conditions for the interesting display, the target vehicle is displayed on the vehicle's onboard large screen as a conventional visualization model.

[0073] In a possible implementation, the preset conditions for interesting display include, but are not limited to, any one or any combination of road speed limit, speed threshold, traffic speed, lane change, relative distance, direction change, etc. Specifically, the road speed limit refers to whether the target vehicle's driving speed is within the speed limit range specified by the lane in which it is traveling. The speed threshold refers to whether the target vehicle's driving speed is within a certain specific range in the scenario of high-speed driving or low-speed driving. The traffic speed refers to whether the target vehicle's driving speed is within the average speed range of the current traffic flow. Lane change refers to whether the target vehicle is changing lanes or making other significant lateral movements. The relative distance refers to whether the distance between the target vehicle and the host vehicle is within a specific range to ensure the relevance and safety of the display. The direction change refers to whether the target vehicle's driving direction has changed significantly, such as turning or turning around.

[0074] In a possible implementation, a method of determining a target visualization model of a target vehicle based on an interesting display preset condition includes but is not limited to any one or any combination of dynamic analysis based on driving characteristics, situational awareness, user preference settings, etc.

[0075] Specifically, dynamic analysis based on driving characteristics refers to dynamically generating a visualization model based on the specific driving characteristics of the target vehicle, such as speed, acceleration, and direction changes. For example, if the target vehicle is accelerating rapidly, a streamlined animation effect can be selected to represent this acceleration state.

[0076] Situational awareness refers to selecting the appropriate visualization model based on the current driving situation. For example, in a traffic jam, the target vehicle can be displayed as a slow-moving icon, while on the highway it can be displayed as a fast-moving arrow.

[0077] User preference settings mean that users can set their preferences in advance and choose different visualization styles. The vehicle will determine the display method of the target vehicle based on these preferences, such as choosing cartoon style, futuristic technology style or simple style.

[0078] The specific types of the target visualization model include but are not limited to different animal images, different object images, etc., and this application does not make specific restrictions on this. Through the vivid visualization model display, the driving behavior of the target vehicle is implied, which helps to provide emotional value for the driver of the vehicle, dilute the irritation caused by bad road conditions with fun, and at the same time practice the advocated compliant driving values ​​and drive safely.

[0079] It is worth noting that the number of target vehicles that meet the preset conditions for the fun display can be 0, 1 or more, and this application does not make specific restrictions on this. At the same time, whether the vehicle is in the process of driving or not, if the driver is in the vehicle and selects the display style of the vehicle-mounted large screen as the fun display mode, the vehicle-mounted large screen will display the vehicle model within the preset range with the corresponding model.

[0080] S202: Displaying the target vehicle as a target visualization model on the vehicle-mounted large screen.

[0081] In this step, after the target visualization model is determined based on step S201, the target vehicle is displayed on the vehicle-mounted large screen as the target visualization model. It is worth noting that if there are multiple target visualization models at the same time, these target visualization models are all displayed on the vehicle-mounted large screen.

[0082] In one possible implementation, when the target vehicle is displayed on the vehicle-mounted large screen as a target visualization model, relevant information can be superimposed and displayed in text form or icon form on the basis of the target visualization model, such as the target vehicle's driving speed, the driving distance from the vehicle, the target vehicle's driving direction, etc., to help users obtain key information.

[0083] It is worth noting that there is a certain time limit for displaying the target vehicle as a target visualization model on the vehicle-mounted large screen. The specific implementation method can refer to the following step S1001 and will not be repeated here.

[0084] It is worth noting that vehicles that are not target vehicles within the preset range of the vehicle or target vehicles that do not meet the preset conditions for the fun display are displayed on the vehicle's large on-board screen as conventional visualization models.

[0085] The visualization processing method of the vehicle model provided in the embodiment of the present application provides users with a personalized driving experience through an interesting display mode. Specifically, the automatic driving control system detects the target vehicle within the preset range of the vehicle to ensure real-time perception of the surrounding environment, thereby improving driving safety. At the same time, the automatic driving system screens out vehicles that meet user needs by judging whether the driving characteristics of the target vehicle meet the preset conditions of the interesting display, effectively avoiding the problem of information overload. In addition, the target vehicles that meet the conditions will be presented on the large in-vehicle screen in the form of a target visualization model, which not only enhances the fun of human-computer interaction, but also brings users a unique personalized driving experience.

[0086] In a possible implementation, the process of determining the target visualization model of the target vehicle includes:

[0087] A visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model; wherein the visualization model material library includes a plurality of driving characteristics and a corresponding relationship between at least one driving characteristic and the visualization model.

[0088] Specifically, when the autonomous driving system determines that the driving characteristics of the target vehicle meet the preset conditions for the fun display, the next step is to determine a target visualization model of the target vehicle.

[0089] The target visualization model of the target vehicle may be determined by a preset visualization model material library.

[0090] The visualization model library is a database containing a variety of driving characteristics and their corresponding visualization models. The driving characteristics include but are not limited to the driving speed of the target vehicle, the driving acceleration of the target vehicle, the steering angle of the target vehicle, and other dynamic behavior characteristics. It is worth noting that each driving characteristic is associated with one or more visualization models to visually reflect the behavior characteristics of the vehicle.

[0091] When the autonomous driving control system detects a target vehicle, it analyzes the current driving characteristics of the target vehicle. For example, assuming that the autonomous driving control system determines that the target vehicle is in an aggressive driving state based on its driving characteristics, it will search the visualization model library for a visualization model that corresponds to the aggressive driving characteristics, such as a model with strong color contrast and dynamic effects to express the state of high-speed driving. For another example, assuming that the autonomous driving control system determines that the target vehicle is in a stable driving state based on its driving characteristics, it will search the visualization model library for a visualization model that corresponds to the stable driving characteristics, such as a visualization model with soft tones and rounded shapes to express a smooth and safe driving state.

[0092] It is worth noting that the visualization models in the visualization model library are not limited to the performance of a single feature. There are visualization models that are a combination of multiple features. For example, a vehicle driving at a high speed on a highway while maintaining high stability, this complex driving behavior combination will trigger a visualization model designed for a combination of multiple features.

[0093] Optionally, in a possible implementation, when the driving day is a traditional holiday, the autonomous driving system can select a target visualization model that matches the holiday theme from the visualization model library to render a festive atmosphere and enhance human-computer interaction. This method not only provides the driver with a more personalized and interesting driving experience, but also adds a festive atmosphere to the driving process.

[0094] For example, during the Dragon Boat Festival, the target visualization model can choose the image of a dragon boat, which symbolizes the tradition and vitality of the festival, reminding the driver of the arrival of the festival and adding to the fun of the festival. Similarly, during the Spring Festival, the autonomous driving system can choose a snowman or other images related to winter festivals to create a warm and festive atmosphere. This kind of holiday-themed visualization model can not only enhance the driver's sense of pleasure, but also maintain the driver's attention and interest in the interface through visual changes.

[0095] In addition, through the visualization model related to the festival, the autonomous driving system can also promote the dissemination of cultural heritage and traditional customs, so that drivers can feel the cultural connotation of the festival in their daily travel. This practice not only improves the fun and interactivity of human-computer interaction, but also provides drivers with a unique driving experience, allowing them to feel the atmosphere and warmth of the festival while driving.

[0096] By using holiday-themed visualization models, the autonomous driving system can improve driving safety while adding fun and cultural value to the driving process. This flexible visualization strategy provides users with a creative and personalized driving environment, further enhancing the user-friendliness and attractiveness of the system.

[0097] Optionally, in a possible implementation, the target visualization model of the target vehicle can be dynamically generated based on its driving characteristics, rather than being limited to a preset model library. By analyzing the behavior and environmental data of the target vehicle in real time, the autonomous driving system is able to generate a visualization model that is highly matched to the current driving situation. This dynamic generation method provides real-time adaptability, allowing the driver to more accurately understand and predict the behavior of the target vehicle, thereby improving driving safety. In addition, personalized experience and environmental perception capabilities enhance the fun of driving and the comprehensiveness of information. By utilizing advanced graphics technology and algorithms, the autonomous driving system can generate unique models, enhance interactivity and flexibility, and provide drivers with more accurate and personalized support and guidance.

[0098] The vehicle model visualization processing method provided in this embodiment determines the target visualization model of the target vehicle by using a preset visualization model library, so that users can quickly identify the dynamic characteristics of surrounding vehicles through intuitive visual elements. This method not only improves driving safety and efficiency, but also brings a personalized driving experience to users, increasing the fun and interactivity of driving. At the same time, through this personalized visual presentation, users can better understand and adapt to complex traffic environments, thereby enjoying a more pleasant and safe driving journey.

[0099] In a possible implementation manner, the target vehicle includes a vehicle having at least one of the following driving characteristics:

[0100] Vehicles traveling in the lane directly in front of your vehicle;

[0101] Adjacent and / or preceding vehicles travelling in the road to the left of the vehicle;

[0102] A vehicle changing lanes from in front of the vehicle into the lane where the vehicle is located;

[0103] Vehicles that drive illegally within the preset range;

[0104] Vehicles of a preset type within a preset range.

[0105] Specifically, the perception module in the automatic driving control system perceives the driving characteristics of other vehicles within the preset range of the vehicle in real time to determine whether it is the target vehicle. The following will be discussed in detail.

[0106] Among them, if there is a vehicle with the driving characteristics of driving in front of the lane where the own vehicle is located, the vehicle will be identified as the target vehicle. Identifying vehicles with such driving characteristics is crucial to maintaining a safe following distance. The autonomous driving system needs to continuously monitor the speed, acceleration and braking behavior of these vehicles so that it can adjust the speed of its own vehicle when necessary to avoid rear-end collisions. For example, if the vehicle in front suddenly slows down, the autonomous driving control system can warn the driver in advance or automatically adjust the speed.

[0107] If there is a vehicle whose driving characteristics are that it is adjacent to and / or in front of the left side of the road of the own vehicle, the vehicle is identified as a target vehicle. Specifically, these vehicles are located in the adjacent lane to the left of the own vehicle and may be traveling parallel to or slightly ahead of the own vehicle. Identifying these vehicles is crucial for safe lane changing and overtaking operations. The autonomous driving control system needs to determine the speed and position of these vehicles to ensure that they do not collide with them when changing lanes. For example, on the highway, the driver may need to overtake. At this time, the autonomous driving control system will provide real-time information about vehicles in the left lane to help the driver make safe lane change decisions.

[0108] If there is a vehicle whose driving characteristics are changing lanes from the front of the vehicle into the lane where the vehicle is located, the vehicle is identified as the target vehicle. Specifically, these vehicles change lanes from other lanes into the driver's lane, usually in urban traffic or at the entrance of a highway. The autonomous driving control system needs to quickly identify the intentions and lane-changing behaviors of these vehicles to adjust the speed and distance of the vehicle to avoid traffic accidents caused by sudden lane changes.

[0109] If there is a vehicle whose driving characteristics are illegal driving within a preset range, the vehicle is determined as a target vehicle. Specifically, these vehicles perform illegal operations within a preset safety range, such as speeding, driving in the wrong direction, changing lanes without following regulations, or running red lights.

[0110] If there is a vehicle whose driving characteristics are of a preset type within a preset range, the vehicle is identified as a target vehicle. Specifically, these vehicles include specific types of vehicles, such as emergency vehicles (ambulances, fire trucks), large vehicles (trucks, buses) or other types of vehicles that require special attention. Identifying these vehicles helps the driver make concessions or adjust driving strategies when necessary.

[0111] It is worth noting that the driving characteristics of the target vehicle can be any one of the above driving characteristics, or a combination of any of the above driving characteristics. For example, if there is a vehicle whose driving characteristics are a preset type within a preset range and is traveling directly in front of the own vehicle, the vehicle is determined as the target vehicle. If there is a vehicle whose driving characteristics are a preset type within a preset range and is traveling adjacent to and / or in front of the left side road of the own vehicle, the vehicle is determined as the target vehicle. Therefore, this application does not make specific limitations on this.

[0112] By identifying and processing these target vehicles, the autonomous driving control system can significantly improve driving safety and efficiency and help drivers make more informed decisions in complex traffic environments.

[0113] The visualization processing method of the vehicle model provided in this embodiment mainly describes the method of determining the target vehicle. By analyzing the driving characteristics of the vehicle, the automatic driving control system can accurately identify and judge the target vehicle within the preset range. This method not only improves the accuracy of target vehicle identification, but also enhances the adaptability of the automatic driving control system in complex traffic environments.

[0114] Next, how to determine a target visualization model of a target vehicle with different driving characteristics from a visualization model library will be discussed in detail. Figure 3 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 2 .like Figure 3 As shown, based on any one of the above embodiments, the process of the visualization processing method of the vehicle model may include:

[0115] S301: If the target vehicle is a vehicle that changes lanes illegally from the front of the vehicle into the lane where the vehicle is located, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model.

[0116] In this step, the driving characteristics of the target vehicle are illegal driving within a preset range and changing lanes from in front of the own vehicle into the lane where the own vehicle is located.

[0117] Specifically, the target vehicle and the own vehicle are not in the same lane, and the target vehicle changes lanes illegally from in front of the own vehicle into the lane where the own vehicle is located.

[0118] In a possible implementation, whether the target vehicle violates the rules when changing lanes is determined based on the lane line and the estimated collision time between the own vehicle and the target vehicle. Specifically, if the target vehicle is traveling near or in front of the left side of the road of the own vehicle before changing lanes, and the lane line between the target vehicle and the own vehicle is a solid line, when the target vehicle performs the lane change operation, the estimated collision time between the target vehicle and the own vehicle is less than or equal to the preset time length, it is regarded as an illegal lane change. Similarly, if the target vehicle is traveling near or in front of the right side of the road of the own vehicle before changing lanes, and the lane line between the target vehicle and the own vehicle is a solid line, when the target vehicle performs the lane change operation, the estimated collision time between the target vehicle and the own vehicle is less than or equal to the preset time length, it is also regarded as an illegal lane change. Preferably, the preset time length is 1.2 seconds.

[0119] It is worth noting that the estimated collision time between the target vehicle and the own vehicle is determined based on the ratio of the shortest distance between the two and the driving speed of the own vehicle. The shortest distance is calculated based on the characteristic positions of the target vehicle and the own vehicle.

[0120] When it is determined that the driving characteristics of the target vehicle are the two driving characteristics of illegal driving and lane change ahead, the visualization models corresponding to the two driving characteristics of illegal driving and lane change ahead are obtained from the visualization model material library as the target visualization model.

[0121] Figure 4 A schematic diagram of a target vehicle that changes lanes illegally provided in this application. Figure 4 As shown, the lane line between the target vehicle and the own vehicle is a solid line, and the target vehicle is illegally changing lanes from in front of the own vehicle into the lane where the own vehicle is located.

[0122] Figure 5 A target visualization model of a target vehicle provided in this application is shown in FIG. Figure 1 .like Figure 5 As shown, the target vehicle has driving characteristics of illegal driving and lane change. Based on the above driving characteristics, the target visualization model determined from the visualization model library is a crab model.

[0123] The visualization processing method of the vehicle model provided in this embodiment can generate a corresponding target visualization model when the target vehicle has two driving characteristics of illegal driving and changing lanes in front, thereby effectively helping the driver to relieve his emotions. Specifically, when the target vehicle changes lanes illegally, by generating a corresponding visualization model, the driver can not only intuitively understand the violation, but also shift his attention from anger to dealing with traffic conditions. This kind of visual feedback not only improves safety awareness, but also reminds the driver to stay calm in a relaxed way to avoid driving decisions affected by anger. In addition, the vivid visualization effect can help the driver face complex traffic with a more positive attitude, reduce anxiety, and thus improve the overall driving experience. At the same time, this kind of visualization model optimizes the human-computer interaction experience, and the information presentation is intuitive, so that the driver can quickly understand the surrounding traffic conditions and improve the friendliness and responsiveness of the interaction.

[0124] Figure 6 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 3 .like Figure 6 As shown, based on any one of the above embodiments, the process of the visualization processing method of the vehicle model may include:

[0125] S601: If the target vehicle is a vehicle traveling in the lane directly in front of the vehicle, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model.

[0126] In this step, the target vehicle has the driving characteristics of driving slowly and driving in front of the lane where the own vehicle is located.

[0127] Specifically, the target vehicle is traveling in front of the lane where the own vehicle is located, and the driving speed of the target vehicle is less than the preset lane driving speed.

[0128] In a possible implementation manner, whether the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range can be determined according to the following calculation formula:

[0129]

[0130] in, represents the average speed of the target vehicle within the first preset time length, V average represents the average driving speed of all other vehicles within the preset range of the own vehicle within the first preset time length, α represents the first preset calibration parameter, β represents the second preset calibration parameter, and the first preset calibration parameter is less than the second preset calibration parameter, Indicates the maximum driving speed of the target vehicle within the first preset time length. Preferably, α=0.7, β=0.75, and the first preset time length is 5 seconds.

[0131] It is worth noting that α and β are mainly adjusted according to the user's experience to ensure that the frequency of the target visualization model can meet the user's satisfaction. If the frequency is too fast, it may cause information overload, which will confuse and disturb the driver, thus affecting his attention and reaction ability. If the frequency is too slow, it may cause the driver to miss important traffic information and increase potential safety problems. Therefore, a reasonable balance between these two parameters is crucial to improving the driving experience and ensuring driving safety. Through precise adjustment, effective information communication can be achieved to help drivers stay calm and focused in complex traffic environments.

[0132] If the average driving speed and the maximum driving speed of the target vehicle in the first preset time length satisfy the above calculation formula, the driving characteristic of the target vehicle is slow driving.

[0133] Furthermore, if the lane where the target vehicle is located is the lane where the own vehicle is located, and the target vehicle is traveling directly in front of the own vehicle, then the target vehicle also has the driving characteristic of traveling directly in front of the own vehicle.

[0134] Based on the two driving characteristics of slow driving and driving directly in front of the lane where the vehicle is located, a visualization model corresponding to the two characteristics of slow driving and driving directly in front of the lane where the vehicle is located is obtained from the visualization model material library as a target visualization model.

[0135] Figure 7 A target visualization model of a target vehicle provided in this application is shown in FIG. Figure 2 .like Figure 7 As shown, the target vehicle has driving characteristics of slow driving and driving in front of the lane where the vehicle is located. Based on the above driving characteristics, the target visualization model determined from the visualization model library is the golden turtle model.

[0136] The visualization processing method of the vehicle model provided in this embodiment can generate a corresponding target visualization model when the target vehicle has two driving characteristics: slow driving and driving directly in front of the lane where the vehicle is located. This can significantly improve safety and help the driver identify potential problems in advance and take corresponding measures in time by displaying the traffic conditions ahead in real time. In addition, clear visualization feedback can effectively manage the driver's emotions, reduce anxiety and anger, improve driving decisions, and enhance the overall driving experience, thereby improving driving satisfaction and comfort.

[0137] Figure 8 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 4 .like Figure 8 As shown, based on any one of the above embodiments, the process of the visualization processing method of the vehicle model may include:

[0138] S801: If the target vehicle is an adjacent and / or preceding vehicle traveling on the road on the left side of the vehicle, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model.

[0139] In this step, the target vehicle has the driving characteristics of driving slowly and driving adjacent to and / or in front of the own vehicle on the left side of the road.

[0140] Specifically, the target vehicle is traveling adjacent to and / or in front of the own vehicle on the left side of the road, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range.

[0141] It is worth noting that whether the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range can be determined by referring to step S601, which will not be repeated here.

[0142] If the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, the driving characteristic of the target vehicle is slow driving.

[0143] Furthermore, if the lane where the target vehicle is located is on the left side of the lane where the own vehicle is located, and the driving position of the target vehicle is located adjacent to and / or in front of the left road, then the target vehicle also has the driving characteristics of driving adjacent to and / or in front of the left road of the own vehicle.

[0144] Based on the two driving characteristics of slow driving and driving adjacent to and / or in front of the left road of the own vehicle, a visualization model corresponding to the two driving characteristics of slow driving and driving adjacent to and / or in front of the left road of the vehicle is obtained from the visualization model material library as the target visualization model.

[0145] In a possible implementation, when determining the target visualization model in the visualization model material library based on the two driving characteristics of slow driving and driving adjacent to and / or in front of the vehicle on the left side of the road, the vehicle type of the target vehicle may also be taken into consideration. For example, if the target vehicle is a sedan, the target visualization model may be a turtle model. If the target vehicle is a large truck, the target visualization model may be a snail model. The present application does not specifically limit the specific type of the target visualization model.

[0146] Fig. 9 A target visualization model of a target vehicle provided in this application is shown in FIG. Figure 3 .like Fig. 9 As shown, the target vehicle has driving characteristics of slow driving and driving in front of the left side of the vehicle. Based on the above driving characteristics, the target visualization model determined from the visualization model material library is a turtle model.

[0147] The vehicle model visualization processing method provided in this embodiment can generate a corresponding target visualization model when the target vehicle appears to be driving slowly and is located near and / or in front of the road on the left side of the vehicle. By converting the driving characteristics of the target vehicle into an intuitive visualization model, the method makes it easier for the driver to understand and predict the behavior of surrounding vehicles, thereby effectively reducing the anxiety and uneasiness caused by traffic conditions. In addition, the use of a vivid visualization method not only increases the fun and interactivity of the driving process, but also further enhances the personalization and pleasure of the driving experience.

[0148] Optionally, in a possible implementation, if the target vehicle accelerates and passes by the adjacent lane of the own vehicle, the driving characteristics of the target vehicle are fast driving and being adjacent to and / or in front of the left road of the own vehicle, then a visualization model corresponding to the driving characteristics of the target vehicle can be determined from the visualization model library as the target visualization model. For example, the target visualization model is a rocket model.

[0149] Fig.10 Schematic diagram of the process of visual processing of vehicle model provided in this application Figure 5 .like Fig.10 As shown, based on any one of the above embodiments, the process of the visualization processing method of the vehicle model also includes:

[0150] S1001: When the driving characteristics of the target vehicle do not meet the preset conditions for the interesting display, the target vehicle is displayed on the vehicle-mounted large screen as a conventional visualization model; and / or, when the display time of the target visualization model on the vehicle-mounted large screen reaches a preset time length, the target vehicle is displayed on the vehicle-mounted large screen as a conventional visualization model.

[0151] In this step, in order to further enhance the user's personalized driving experience, the display time of the target visualization model is subject to certain conditions.

[0152] Specifically, the conditions for limiting the display time of the target visualization model include but are not limited to the following three conditions, which will be described in detail below.

[0153] In the first case, when the driving characteristics of the target vehicle do not meet the preset interesting display conditions, the autonomous driving system will choose to use a conventional visualization model for display. Interesting displays are usually used in specific driving scenarios, such as when the target vehicle is driving slowly or in a specific lane, to enhance the driver's attention and driving experience. However, in ordinary cases, the use of conventional displays can avoid overly complex interfaces, thereby reducing the cognitive burden on the driver. This approach ensures the clarity and consistency of information transmission, allowing the driver to focus on the driving task without being distracted.

[0154] The second situation is that when the target visualization model is displayed on the large screen of the vehicle for a preset time, the autonomous driving system will automatically switch back to the regular visualization model. This strategy is designed to prevent the driver from visual fatigue or habitual neglect of the interesting display. Displaying the same interesting model for a long time may cause it to lose its freshness and appeal. Therefore, by setting a reasonable display time, the autonomous driving system can help keep the driver's attention focused and ensure the simplicity and effectiveness of the interface.

[0155] The third case is when the driving characteristics of the target vehicle do not meet the preset fun display conditions or the target visualization model is displayed on the large screen on the vehicle for a preset time. When any of these two conditions are met, the autonomous driving system will automatically switch back to the regular visualization model. This strategy provides double protection to ensure that the driver's attention is always kept in a better state. First, when the driving characteristics are no longer suitable for fun display, switching back to regular display can avoid unnecessary visual interference and ensure the accuracy and conciseness of information transmission. Second, when the fun display time is too long, switching back to regular display can prevent the driver from visual fatigue or habitual neglect of the fun display, thereby maintaining the freshness and effectiveness of the interface. By combining these two conditions, the autonomous driving system can dynamically adjust the display strategy in different driving scenarios, which can not only provide a personalized and fun experience, but also ensure driving safety and information clarity.

[0156] Optionally, in a possible implementation, if the target vehicle drives out of the preset range of the own vehicle, the autonomous driving system will automatically switch back to the conventional visualization model. By reducing unnecessary interesting displays, the simplicity of the interface is maintained, and the cognitive burden of the driver is reduced.

[0157] It is worth noting that the conditional restrictions corresponding to the display time of the target visualization model can be used alone or in any combination. The specific restrictions can be determined based on actual conditions, and this application does not make specific limitations on this.

[0158] The visualization processing method of the vehicle model provided in this embodiment and the dynamically adjusted display strategy not only improve the driving experience, but also take into account driving safety and information clarity. By using interesting displays in appropriate situations and reverting to regular displays when necessary, it is possible to provide users with a personalized driving experience while avoiding potential distractions and information overload.

[0159] Fig.11 The schematic diagram of the framework of the visualization processing method of the vehicle model provided in this application. Fig.11 As shown, the automatic driving control system of the own vehicle detects the environmental information within the preset range in real time, thereby obtaining the surrounding environment detection results. Among them, the surrounding environment detection results include the driving information and lane line information of all vehicles within the preset range. The driving information of the vehicle includes but is not limited to the speed, lateral acceleration, longitudinal acceleration and position, etc., and the lane line information includes but is not limited to the solid line, dotted line and lane line position, etc. Based on the surrounding environment detection results, the vehicle display system provides two modes of conventional display and fun display to display the vehicle model. Among them, the vehicle displayed in the fun display mode meets the fun display preset conditions. It is worth noting that when the vehicle display system deployed in the own vehicle visualizes the model of the surrounding vehicles on the large screen of the vehicle, its display effect is consistent with the relative position relationship between the surrounding vehicles and the own vehicle in the actual scene. At the same time, during the driving process of the own vehicle, if it is judged that there is a target vehicle in the surrounding vehicles that meets the fun display preset conditions, the corresponding vehicle model is displayed in a fun way. This visualization processing method focuses on the non-compliant driving phenomenon of slow vehicles occupying the fast lane and changing lanes to squeeze in, and uses the interactive method of fun display to provide users with emotional value and divert road rage. At the same time, practice the advocated compliant driving values, drive safely, and guide correct driving values. Optionally, in a possible implementation, environmental information around the vehicle, such as obstacles, pedestrians, etc., can also be displayed in an interesting display mode.

[0160] Fig.12 This is a schematic diagram of the structure of the first embodiment of the visualization processing device for the vehicle model provided by the present application. Fig.12 As shown, the visualization processing device 1200 of the vehicle model includes:

[0161] The processing module 1201 is used to determine a target visualization model of the target vehicle if it is determined that there is a target vehicle within a preset range of the vehicle and the driving characteristics of the target vehicle meet the preset conditions of the interesting display when the display style of the vehicle-mounted large screen is the interesting display mode;

[0162] The display module 1202 is used to display the target vehicle in the vehicle-mounted large screen using a target visualization model.

[0163] Optionally, the processing module 1201 is further used for:

[0164] A visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model; wherein the visualization model material library includes a plurality of driving characteristics and a corresponding relationship between at least one driving characteristic and the visualization model.

[0165] Optionally, the target vehicle includes a vehicle having at least one of the following driving characteristics:

[0166] Vehicles traveling in the lane directly in front of your vehicle;

[0167] Adjacent and / or preceding vehicles travelling in the road to the left of the vehicle;

[0168] A vehicle changing lanes from in front of the vehicle into the lane where the vehicle is located;

[0169] Vehicles that drive illegally within the preset range;

[0170] Vehicles of a preset type within a preset range.

[0171] Optionally, the processing module 1201 is further used for:

[0172] If the target vehicle is a vehicle that changes lanes illegally from the front of the vehicle into the lane where the vehicle is located, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model, including:

[0173] From the visualization model library, visualization models corresponding to the two driving characteristics of illegal driving and lane change ahead are obtained as target visualization models.

[0174] Optionally, the processing module 1201 is further used for:

[0175] If the target vehicle is a vehicle traveling in the lane directly in front of the vehicle, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model library as the target visualization model, including:

[0176] From the visualization model library, visualization models corresponding to two driving characteristics, namely, driving at a slow speed and driving directly in front of the lane where the vehicle is located, are obtained as target visualization models.

[0177] Optionally, the processing module 1201 is further used for:

[0178] If the target vehicle is a vehicle adjacent to and / or in front of the vehicle traveling on the left side of the road, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model, including:

[0179] From the visualization model material library, visualization models corresponding to two driving characteristics, namely, driving slowly and driving adjacent to and / or in front of the vehicle on the left side road, are obtained as target visualization models.

[0180] Optionally, the processing module 1201 is further used for:

[0181] When the driving characteristics of the target vehicle do not meet the preset conditions for the interesting display, the target vehicle is displayed on the vehicle's large screen with a conventional visualization model; and / or, when the target visualization model is displayed on the vehicle's large screen for a preset time length, the target vehicle is displayed on the vehicle's large screen with a conventional visualization model.

[0182] The visualization processing device for a vehicle model provided in an embodiment of the present application can be used to execute the visualization processing method for a vehicle model in any of the aforementioned method embodiments. Its implementation principle and technical effects are similar and will not be repeated here.

[0183] Fig.13 This is a schematic diagram of the structure of the large in-vehicle screen provided in this application. Fig.13 As shown, the vehicle-mounted large screen 102 provided in this embodiment includes: at least one transceiver 1301, a processor 1302 and a memory 1303. Optionally, the vehicle-mounted large screen 102 also includes a communication component. Among them, the processor 1302, the memory 1303 and the communication component are connected through a bus.

[0184] In the specific implementation process, at least one transceiver 1301 is used to realize data transmission with the automatic driving control system, and at least one processor 1302 executes computer execution instructions stored in the memory 1303, so that at least one processor 1302 executes the above-mentioned vehicle model visualization processing method.

[0185] The specific implementation process of the processor 1302 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0186] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0187] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0188] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0189] The present application also provides a vehicle, comprising a vehicle body and Fig.13 The large in-vehicle screen 102 is shown.

[0190] The present application also provides a computer program product, including a computer program, which implements the above-mentioned vehicle model visualization processing method when executed by a processor.

[0191] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above-mentioned vehicle model visualization processing method is implemented.

[0192] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0193] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0194] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0195] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0196] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0197] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0198] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0199] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for visualizing a vehicle model, characterized in that: The method comprises: When the display style of the vehicle-mounted large screen is the fun display mode, if it is determined that there is a target vehicle within the preset range of the vehicle, and the driving characteristics of the target vehicle meet the preset conditions of the fun display, then the target visualization model of the target vehicle is determined; The target vehicle is displayed on the in-vehicle large screen using the target visualization model.

2. The method according to claim 1, characterized in that Determining a target visualization model of the target vehicle includes: Determining a visualization model corresponding to the driving characteristics of the target vehicle from the visualization model library as the target visualization model; The visualization model material library includes a variety of driving characteristics and a corresponding relationship between at least one driving characteristic and a visualization model.

3. The method according to claim 2, characterized in that The target vehicle includes a vehicle having at least one of the following driving characteristics: A vehicle traveling in the lane directly in front of the vehicle; adjacent and / or preceding vehicles travelling in the road to the left of the vehicle; A vehicle that changes lanes from in front of the vehicle and enters the lane where the vehicle is located; Vehicles that drive illegally within the preset range; A vehicle of a preset type within the preset range.

4. The method according to claim 2 or 3, characterized in that: If the target vehicle is a vehicle that changes lanes illegally from the front of the vehicle into the lane where the vehicle is located, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model, including: From the visualization model material library, visualization models corresponding to two driving characteristics of illegal driving and lane change ahead are obtained as the target visualization model.

5. The method according to claim 2 or 3, characterized in that: If the target vehicle is a vehicle traveling in front of the lane where the vehicle is located, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model, including: From the visualization model material library, visualization models corresponding to two driving characteristics, namely, driving at a slow speed and driving directly in front of the lane where the vehicle is located, are obtained as the target visualization model.

6. The method according to claim 2 or 3, characterized in that: If the target vehicle is a vehicle adjacent to and / or ahead of the vehicle traveling on the left side of the road, and the average driving speed and the maximum driving speed of the target vehicle both meet the preset speed range, a visualization model corresponding to the driving characteristics of the target vehicle is determined from the visualization model material library as the target visualization model, including: From the visualization model material library, a visualization model corresponding to two driving characteristics, namely, driving at a slow speed and driving adjacent to and / or in front of the vehicle on the left side road, is obtained as the target visualization model.

7. The method according to claim 1, characterized in that The method further comprises: When the driving characteristics of the target vehicle do not meet the preset conditions for the interesting display, the target vehicle is displayed on the vehicle-mounted large screen in a conventional visual model; and / or, When the duration of displaying the target visualization model on the vehicle-mounted large screen reaches a preset duration, the target vehicle is displayed on the vehicle-mounted large screen using the conventional visualization model.

8. A visualization processing device for a vehicle model, characterized in that: include: A processing module, for determining a target visualization model of the target vehicle if it is determined that there is a target vehicle within a preset range of the vehicle and the driving characteristics of the target vehicle meet the preset conditions of the interesting display when the display style of the vehicle-mounted large screen is an interesting display mode; A display module is used to display the target vehicle using the target visualization model on the vehicle-mounted large screen.

9. A large vehicle screen, comprising: Transceiver, A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the visualization processing method of the vehicle model according to any one of claims 1 to 7.

10. A vehicle, characterized in that: include: A vehicle body and the large vehicle-mounted screen as described in claim 9.

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