Virtual driving simulation method, electronic equipment, storage medium and vehicle

Abstract

The invention relates to the technical field of vehicles, in particular to a virtual driving simulation method, electronic equipment, a storage medium and a vehicle, which can improve the efficiency of virtual driving simulation and optimize the virtual driving experience of a user, the virtual driving simulation method comprises the following steps: when the vehicle is in a virtual driving mode, determining target virtual driving simulation data; wherein the virtual driving mode comprises a self-adaptive mode or a self-defined mode; the target virtual driving mode data is used for simulating the driving experience of the user; and performing virtual driving simulation based on the target virtual driving simulation data and a virtual driving system of the vehicle.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more particularly to a virtual driving simulation method, electronic device, storage medium, and vehicle. Background Technology

[0002] With the rapid development of vehicle electrification and intelligence, new energy vehicles are generally equipped with multiple switchable driving modes such as economy, comfort, and sport, and can independently adjust vehicle dynamic parameters such as braking energy recovery intensity, steering assist characteristics, and suspension height. In order to reduce the learning cost for users and improve the pre-purchase experience, various OEMs and science popularization venues have successively deployed virtual driving devices.

[0003] However, existing virtual driving devices, being independent of the real vehicle's electronic control system, prevent users from previewing the differences between modes. This forces users to switch modes "while driving" on the road, which not only has a high learning cost and low experience efficiency, but also distracts them from frequent operation of the central control screen or buttons, significantly increasing driving safety risks. Summary of the Invention

[0004] The purpose of this application is to provide a virtual driving simulation method, electronic device, storage medium, and vehicle that can improve the efficiency of virtual driving simulation and optimize the user's virtual driving experience.

[0005] In a first aspect, this application provides a virtual driving simulation method, the method comprising: determining target virtual driving simulation data when the vehicle is in a virtual driving mode; wherein the virtual driving mode includes an adaptive mode or a custom mode; the target virtual driving mode data is used to simulate the user's driving experience; and performing virtual driving simulation based on the target virtual driving simulation data and the vehicle's virtual driving system.

[0006] The virtual driving simulation method provided in this application adds two modes to the virtual driving system: adaptive and custom. After the vehicle enters virtual driving, the system automatically matches the target simulation data according to the driver's driving characteristics and environmental data. Users can also customize key parameters and drive the virtual driving system to complete the virtual cockpit simulation. This method can improve the automation level of virtual driving simulation, reduce the cost of manual adjustment, and improve the efficiency of virtual driving simulation.

[0007] In some embodiments, the target virtual driving simulation data includes target motion simulation data and target audiovisual simulation data.

[0008] In some embodiments, when the virtual driving mode is an adaptive mode, determining the target virtual driving simulation data includes: acquiring the driver's historical driving operation data in the target virtual driving environment; determining the driver's driving style based on the historical driving operation data and a preset driving style recognition algorithm; determining the target somatosensory simulation data that matches the driver's driving style based on the driver's driving style; and determining the target audiovisual simulation data based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data.

[0009] In some embodiments, determining target somatosensory simulation data that matches the driver's driving style based on the driver's driving style includes: determining target somatosensory simulation data based on the driver's driving style and a preset correspondence; wherein the preset correspondence represents the correspondence between driving style and somatosensory simulation data.

[0010] In some embodiments, when the virtual driving mode is a custom mode, determining the target virtual driving simulation data includes: determining the target somatosensory simulation data based on the driver's adjustment of vehicle dynamic characteristic adjustment parameters; wherein the vehicle dynamic characteristic adjustment parameters are used to reflect the driver's driving habits; acquiring the driver's current driving operation data in the target virtual driving environment; and determining the target audiovisual simulation data based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data.

[0011] In some embodiments, determining target audiovisual simulation data based on the driver's current driving operation data and target somatosensory simulation data in the target virtual driving environment includes: inputting the driver's current driving operation data and target somatosensory simulation data in the target virtual driving environment into a preset virtual driving vehicle model to obtain target audiovisual simulation data; the preset virtual driving vehicle model is obtained by integrating the current vehicle's appearance model, dynamics model, and multi-field coupling model.

[0012] Secondly, this application also provides a virtual driving simulation device, which includes a processing module and a simulation module.

[0013] The processing module is used to determine the target virtual driving simulation data when the vehicle is in virtual driving mode; wherein, the virtual driving mode includes adaptive mode or custom mode; the target virtual driving mode data is used to simulate the user's driving experience; the simulation module is used to perform virtual driving simulation based on the target virtual driving simulation data and the vehicle's virtual driving system.

[0014] In some embodiments, the target virtual driving simulation data includes target motion simulation data and target audiovisual simulation data.

[0015] In some embodiments, when the virtual driving mode is an adaptive mode, the processing module is specifically used to acquire the driver's historical driving operation data in the target virtual driving environment; determine the driver's driving style based on the historical driving operation data and a preset driving style recognition algorithm; determine the target somatosensory simulation data that matches the driver's driving style based on the driver's driving style; and determine the target audiovisual simulation data based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data.

[0016] In some embodiments, the processing module is specifically used to determine target somatosensory simulation data based on the driver's driving style and a preset correspondence; wherein the preset correspondence represents the correspondence between driving style and somatosensory simulation data.

[0017] In some embodiments, when the virtual driving mode is a custom mode, the processing module is specifically used to determine target somatosensory simulation data based on the driver's adjustment of vehicle dynamic characteristic adjustment parameters; wherein, the vehicle dynamic characteristic adjustment parameters are used to reflect the driver's driving habits; to acquire the driver's current driving operation data in the target virtual driving environment; and to determine target audiovisual simulation data based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data.

[0018] In some embodiments, the processing module is specifically used to input the driver's current driving operation data and target somatosensory simulation data in the target virtual driving environment into a preset virtual driving vehicle model to obtain target audiovisual simulation data; the preset virtual driving vehicle model is obtained by integrating the current vehicle's appearance model, dynamics model and multi-field coupling model.

[0019] Thirdly, this application provides an electronic device comprising: a processor and a memory; the memory storing processor-executable instructions; when the processor is configured to execute the instructions, causing the electronic device to implement the method of the first aspect described above.

[0020] Fourthly, this application provides a computer-readable storage medium comprising: computer software instructions; which, when executed in an electronic device, cause the electronic device to implement the method described in the first aspect.

[0021] Fifthly, the present invention provides a vehicle that includes the electronic equipment described in the third aspect, or the vehicle that includes the computer-readable storage medium described in the fourth aspect.

[0022] Sixthly, this application provides a computer program product comprising a computer program; when the computer program is run in an electronic device, it causes the electronic device to implement the method described in the first aspect.

[0023] The beneficial effects of the second to sixth aspects mentioned above are described in the corresponding description of the first aspect and will not be repeated here. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the structure of a virtual driving system provided in an embodiment of this application; Figure 2 A flowchart illustrating a virtual driving simulation method provided in this application embodiment; Figure 3 A flowchart illustrating another virtual driving simulation method provided in this application embodiment; Figure 4 A schematic diagram of a human-machine interface provided in an embodiment of this application; Figure 5 A flowchart illustrating yet another virtual driving simulation method provided in this application embodiment; Figure 6 A schematic diagram of another human-machine interface provided in an embodiment of this application; Figure 7 A flowchart illustrating yet another virtual driving simulation method provided in this application embodiment; Figure 8 This is a schematic diagram of the structure of a virtual driving simulation device provided in an embodiment of this application; Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0026] Reference numerals: Virtual driving system 100, human-computer interaction module 101, driving operation input module 102, virtual signal processor 103, visual simulation device 104, auditory simulation device 105, and motion simulation module 106. Detailed Implementation

[0027] In the embodiments of this application, the terms "first," "second," "third," "fourth," "fifth," and "sixth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," "third," "fourth," "fifth," and "sixth" may explicitly or implicitly include one or more of that feature.

[0028] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0029] "A and / or B" includes the following three combinations: A only, B only, and a combination of A and B.

[0030] As the electrification of automobiles increases, most new energy vehicles now offer users a variety of driving mode options (economy, comfort, sport, etc.) and some adjustable vehicle dynamics options (brake energy recovery, steering mode, suspension height, etc.). However, drivers cannot initially understand the changes in the vehicle and driving experience after adjusting each adjustable option. Faced with numerous adjustable options, users can only make adjustments during actual driving and experience the different experiences after each adjustment. As the number of adjustable options increases, customers will face problems such as increased time costs in adapting to switching / adjusting driving modes, the inability to fully experience the differences between all adjustable options after multiple drives, and the potential for mode switching / adjustment during driving to affect driver attention.

[0031] To address the aforementioned technical problems, this application provides a virtual driving simulation method, electronic device, storage medium, and vehicle, which can improve the efficiency of virtual driving simulation and optimize the user's virtual driving experience. The virtual driving simulation method is based on the following steps: when the vehicle is in virtual driving mode, target virtual driving simulation data is determined; wherein, the virtual driving mode includes adaptive mode or custom mode; the target virtual driving mode data is used to simulate the user's driving experience; and virtual driving simulation is performed based on the target virtual driving simulation data and the vehicle's virtual driving system.

[0032] Figure 1 This application provides a virtual driving system that is applied to real vehicles, such as... Figure 1 As shown, the virtual driving system 100 includes a human-computer interaction module 101, a driving operation input module 102, a virtual signal processor 103, a visual simulation device 104, an auditory simulation device 105, and a motion simulation module 106. The virtual signal processor 103 is connected to the human-computer interaction module 101, the driving operation input module 102, the visual simulation device 104, the auditory simulation device 105, and the motion simulation module 106, respectively.

[0033] The human-machine interaction module 101 is used to acquire the driver's adjustment operations on the vehicle's dynamic characteristic adjustment parameters, thereby determining the target somatosensory simulation data. Simultaneously, the human-machine interaction module 101 is also used to acquire the driver's selection operations on the virtual driving environment, thereby determining the target virtual driving environment.

[0034] For example, the human-machine interaction module 101 can be arranged on the vehicle's central control screen in the form of a touch slider or a physical knob.

[0035] The driving operation input module 102 is used to acquire the driver's driving operation data and send the driving operation data to the virtual signal processor 103.

[0036] For example, the driving operation input module 102 may include a steering wheel angle sensor, a drive pedal position sensor, and a brake pedal position sensor.

[0037] The virtual signal processor 103 is used to continuously monitor the target somatosensory simulation data and target virtual driving environment parameters sent by the human-machine interaction module 101 via the vehicle Ethernet after the vehicle is powered on. At the same time, it collects driving operation data provided by the driving operation input module 102 at a fixed frequency, and then processes the acquired data to obtain virtual driving simulation control instructions. These control instructions are used to instruct the virtual driving system 100 to complete the virtual driving simulation.

[0038] In some embodiments, the virtual signal processor 103 has a built-in preset driving style recognition model and a preset virtual driving vehicle model. After acquiring the driver's driving operation data, the driving operation data is input into the driving style recognition model to identify the driver's driving style and determine the target virtual driving simulation data based on the driving style. The target virtual driving simulation data includes target somatosensory simulation data and target audiovisual simulation data.

[0039] In some embodiments, the virtual signal processor 103 generates video stream data, audio stream data, and control instructions for the motion simulation module 106 based on the target virtual driving simulation data, and sends them to the visual simulation device 104, the auditory simulation device 105, and the motion simulation module 106, respectively.

[0040] For example, the virtual signal processor 103 can be embedded in an in-vehicle high-computing-power domain controller.

[0041] The visual simulation device 104 is used to receive and decode video stream data from the virtual signal processor 103, present the view from outside and inside the vehicle in a three-dimensional distortion correction manner, and display the changes in the vehicle body roll angle and pitch angle in real time, so as to provide virtual dynamic visual feedback to the driver.

[0042] For example, a visual simulation device could be VR glasses.

[0043] The auditory simulation device 105 is used to receive and decode audio stream data from the virtual signal processor 103, and synchronously play engine sound, tire-road rolling noise, wind shear noise and ambient background sound to provide virtual dynamic auditory feedback to the driver.

[0044] An example is an auditory simulation device 105, a headset.

[0045] In some embodiments, the visual simulation device 104 and the auditory simulation device 105 are connected to the virtual signal processor 103 via wired or wireless means and receive data sent by the virtual signal processor 103.

[0046] The motion simulation module 106, based on the control commands issued by the virtual signal processor 103, reproduces the tactile / force sensations caused by longitudinal acceleration and deceleration, lateral acceleration, road surface unevenness excitation, and suspension stiffness changes in real time, and completes the motion simulation.

[0047] In some embodiments, the motion simulation module 106 includes the vehicle's chassis system, such as the drive system, braking system, steering system, and suspension system, and the motion simulation module 106 adjusts the parameters of each system according to control commands.

[0048] It should be noted that the application scenarios of the embodiments in this application are not limited. The system architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0049] The virtual driving simulation method provided in the embodiments of this application will be described in detail below.

[0050] Figure 2 A flowchart of a virtual driving simulation method provided in this application embodiment, which can be applied to the above-mentioned virtual driving system, specifically includes the following: S101. When the vehicle is in virtual driving mode, determine the target virtual driving simulation data.

[0051] In the virtual driving mode, the driver can experience virtual driving from inside the vehicle without actually driving it.

[0052] The virtual driving modes include adaptive mode or custom mode, and the target virtual driving mode data is used to simulate the user's driving experience.

[0053] In some embodiments, adaptive mode means that during virtual driving simulation, the system can automatically adapt to the driver's driving style and automatically adjust the vehicle's performance parameters.

[0054] In some embodiments, the specific process for determining the target virtual driving simulation data in adaptive mode is described in S201-S204.

[0055] In some embodiments, the custom mode means that during virtual driving simulation, the driver can manually adjust the vehicle's performance parameters according to the needs of virtual driving.

[0056] In some embodiments, the specific process for determining the target virtual driving simulation data in custom mode is described in S301-S303.

[0057] In some embodiments, the target virtual driving simulation data includes target haptic simulation data and target audiovisual simulation data. The target haptic simulation data is used to simulate haptic effects in the virtual driving simulation, such as braking nose-diving, road bumps, and steering roll. The target audiovisual simulation data is used to simulate visual and auditory effects in the virtual driving simulation, such as visual effects including road scenes, vehicle dashboard, rearview mirror images, and weather effects, and auditory effects including engine sounds, tire friction sounds, wind noise, and environmental sound effects.

[0058] In some embodiments, after the vehicle is powered on, the driver controls the vehicle to enter virtual driving mode through the vehicle's Human Machine Interface (HMI). For example, the driver clicks the "Virtual Driving Mode" button displayed on the vehicle's HMI to trigger a command. The HMI sends the command to the vehicle controller. After receiving the command, the vehicle controller switches the driving mode flag to virtual driving mode, and the vehicle enters virtual driving mode. At this time, all dynamic parameter adjustments are simulated at the software level and do not drive real hardware actions.

[0059] In some embodiments, a preset condition is set to determine whether the vehicle can enter the virtual driving mode. For example, after the vehicle is powered on, it is determined whether the vehicle is currently in a parked state. If so, the vehicle is allowed to enter the virtual driving mode; otherwise, the vehicle is not allowed to enter the virtual driving mode.

[0060] S102. A virtual driving system based on target virtual driving simulation data and vehicles performs virtual driving simulation.

[0061] In some embodiments, when the vehicle is in virtual driving mode, the vehicle system disconnects the physical connection between the driving operation input module (such as steering wheel, brake pedal, drive pedal, etc.) and the real actuator, and sends the data collected by the driving operation input module to the virtual signal processor of the vehicle's virtual driving system. The virtual signal processor generates target virtual driving simulation data, and then uses the target virtual driving simulation data to drive the virtual vehicle model to complete closed-loop operation in the simulation environment.

[0062] The virtual driving simulation method provided in this application adds two modes to the virtual driving system: adaptive and custom. After the vehicle enters virtual driving, the system automatically matches the target simulation data according to the driver's driving characteristics and environmental data. Users can also customize key parameters and drive the virtual driving system to complete the virtual cockpit simulation. This method can improve the automation level of virtual driving simulation, reduce the cost of manual adjustment, and improve the efficiency of virtual driving simulation.

[0063] Figure 3 The flowchart shows another virtual driving simulation method provided in the embodiments of this application. When the virtual driving simulation mode is adaptive mode, the above S101 can be implemented as S201-S204, as follows: S201. Obtain the driver's historical driving operation data in the target virtual driving environment.

[0064] In virtual driving simulation, the driver's historical driving operation data is the basic data support for subsequent personalized simulation. To ensure the integrity and validity of the data, it is necessary to obtain the driver's historical driving operation data in the target virtual driving environment.

[0065] A virtual driving environment is a virtual scene constructed based on real-world application scenarios, featuring real physical characteristics and traffic elements (including other vehicles, pedestrians, traffic lights, traffic signs, etc.).

[0066] In some embodiments, the target virtual driving environment can be determined by driver input, with the driver selecting the target virtual driving environment through the touch menu or physical buttons of the vehicle's human-machine interface.

[0067] In some embodiments, the optional content of the virtual driving environment includes, but is not limited to, road surface selection (such as cement road, asphalt road, gravel road, dirt road, polished ice surface, compacted snow surface, etc.), environment selection (such as city streets, highways, country roads, desert off-road, suburban roads, etc.), weather selection (such as sunny, cloudy, light rain, heavy rain, light snow, heavy snow, etc.), and additional selections (speed bumps, traffic cones, traffic lights, pedestrians, etc.).

[0068] For example, the virtual driving environment includes, but is not limited to, urban road conditions, highway conditions, snow, sand, wet and slippery road conditions, uneven road conditions, and different weather conditions. Different scenarios are incorporating actually collected road feature parameters (such as road adhesion coefficient, undulation height, slope, etc.).

[0069] For example, Figure 4 A schematic diagram of a human-machine interface provided in an embodiment of this application is shown, illustrating, for example, the optional content of a virtual driving environment for the driver to select.

[0070] In some embodiments, historical driving operation data specifically includes various types of operation information generated by the driver when performing driving operations in the target virtual driving environment, such as steering operation data, acceleration operation data, braking operation data, and gear shifting operation data.

[0071] In some embodiments, to ensure data accuracy, it is necessary to acquire sufficiently rich historical driving operation data, such as historical driving operation data acquired based on a 10Hz acquisition frequency. At the same time, the acquired historical driving operation data needs to be preprocessed, including data denoising and data completion, to finally form a structured historical driving operation dataset, which is stored in the database of the virtual driving system to provide data support for subsequent driving style recognition.

[0072] For example, the driver is asked to drive continuously for no less than 5km in a virtual environment of "two-way four-lane city" with an average speed of 45km / h, including 3 stops and starts at traffic lights. Steering wheel angle, accelerator pedal opening, brake line pressure, and gear signal are collected synchronously at a frequency of 10Hz. Then, high-frequency noise is removed from the original signal, and linear interpolation is used to complete the missing sampling points, thereby obtaining the above-mentioned historical driving operation data.

[0073] S202. Based on historical driving operation data and a preset driving style recognition model, determine the driver's driving style.

[0074] Driving style refers to a driver's preferences in accelerating, decelerating, steering, and maintaining speed while driving. For example, driving styles can include mild and aggressive driving styles.

[0075] Driving style recognition is a crucial step in realizing virtual driving simulation. By analyzing the characteristic patterns in the driver's historical driving operation data and matching them with preset driving style types, the driver's specific driving style can be determined.

[0076] In some embodiments, historical driving operation data is input into a preset driving style recognition model, which extracts key features that can characterize driving style from the historical driving operation data, and analyzes the feature data after extracting the key features.

[0077] For example, key features characterizing driving style may include features characterizing operational smoothness, such as the standard deviation of steering angle, the rate of change of accelerator pedal depth, the frequency of brake pedal application, and the fluctuation coefficient of vehicle speed.

[0078] For example, key features characterizing driving style may include features characterizing aggressiveness of operation, such as maximum accelerator pedal depth, maximum brake pedal depth, and maximum vehicle acceleration.

[0079] For example, key features characterizing driving style may include features characterizing operational initiative, such as average following distance and frequency of overtaking maneuvers.

[0080] For example, the preset driving style recognition model can employ machine learning algorithms, such as support vector machine, random forest, K-means clustering algorithm, etc.

[0081] In some embodiments, different driving style recognition models are designed for different vehicle models. For example, for any vehicle model, real-world driving data from different drivers under the same driving style label are input into a recurrent neural network or Transformer architecture bound to that vehicle model. A transfer learning strategy is employed, using the parameters of a general driving style model as initial weights, and fine-tuned using a vehicle-specific dataset to obtain a converged style recognition model corresponding to that vehicle model. Different vehicle models can be distinguished in terms of their powertrain structure, overall vehicle weight distribution, and electronic control architecture.

[0082] One possible implementation involves constructing a driving style sample library containing driver operation feature samples of multiple known driving style types (such as smooth, mild, aggressive, cautious, etc.). Each sample is labeled with a corresponding driving style tag. Then, the key feature data of the extracted driver's historical operation data is input into a pre-trained driving style recognition model (the model has been trained using sample data from the sample library). The model calculates the similarity between the key feature data and the features of each style type in the sample library (e.g., using Euclidean distance, cosine similarity, etc. to calculate the similarity between feature vectors) to determine the matching degree between the target driver's features and a certain style type. Finally, when the matching degree exceeds a preset threshold (e.g., 80%), the driver's driving style can be determined as the corresponding style type. If the matching degree of all style types does not exceed the threshold, the driving style can be determined as a hybrid driving style (e.g., smooth-mild) based on the two style types with the highest matching degree.

[0083] In some embodiments, to ensure the dynamism and accuracy of driving style recognition and to enable the recognition results to adapt to changes in the driver's driving habits, a periodic update mechanism can be set up. That is, every preset period (such as after every 10 virtual driving simulations), the newly generated historical driving operation data of the driver is added to the dataset, features are re-extracted, and the driving style recognition model is updated.

[0084] S203. Based on the driver's driving style, determine the target somatosensory simulation data that matches the driver's driving style.

[0085] As one possible implementation, target somatosensory simulation data is determined based on the driver's driving style and a preset correspondence, where the preset correspondence represents the correspondence between driving style and somatosensory simulation data.

[0086] In some embodiments, a static mapping table is pre-stored in the virtual signal processor of the virtual driving system as the aforementioned preset correspondence. This table uses driving style as the key and motion simulation data as the value. When a certain driving style is identified, the corresponding motion simulation data is found through the mapping table. The mapping table can be obtained experimentally.

[0087] S204. Based on the driver's current driving operation data in the target virtual driving environment and the target's somatosensory simulation data, determine the target's audiovisual simulation data.

[0088] In some embodiments, audiovisual simulation data is the core data that provides visual and auditory feedback to the driver in the virtual driving system. It needs to work in conjunction with the driver's current driving operation and target haptic simulation data to form a multi-dimensional immersive driving experience and ensure the consistency of visual, auditory and haptic feedback.

[0089] In some embodiments, the driver’s current driving operation data in the target virtual driving environment includes relevant data generated by the driver’s operation behavior on vehicle control components (such as steering wheel, accelerator pedal, brake pedal, gear shift device, etc.) in the target virtual driving environment.

[0090] In some embodiments, after the driver operates the vehicle control components, the sensors built into the control components (such as steering wheel angle sensor, accelerator pedal position sensor, brake pedal pressure sensor, etc.) immediately convert the mechanical displacement or pressure signal into an analog signal. These analog signals are transmitted to the virtual signal processor of the virtual driving system via a wiring harness. The virtual signal processor analyzes and extracts these analog signals to obtain the current driving operation data.

[0091] In some embodiments, the target audiovisual simulation data includes visual simulation data and auditory simulation data. The visual simulation data is the visual scene data presented to the driver by the display module of the virtual driving system (such as a head-mounted display, a multi-screen splicing display, etc.), and the auditory simulation data is the sound data played to the driver by the audio module of the virtual driving system (such as surround sound speakers, headphones, etc.).

[0092] In some embodiments, after determining the visual simulation data and the auditory simulation data, a synchronization check needs to be performed on the two. By aligning the timestamps, it is ensured that the visual and auditory effects can be performed synchronously or maintain a small time deviation (such as a deviation of no more than 50ms). After the check is passed, the final target audiovisual simulation data can be determined.

[0093] In some embodiments, since the driving style of the same driver is less likely to change due to external factors, the driving style of the driver can remain relatively stable in different target virtual driving environments. Therefore, the virtual driving system can continuously optimize and reuse the driver's driving style based on the driver's historical behavior data. In the process of the same driver selecting different target virtual driving environments for virtual driving simulation, there is no need to re-collect or adjust the data each time, thereby improving simulation efficiency and experience consistency.

[0094] As one possible implementation, the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data are input into a preset virtual driving vehicle model to obtain target audiovisual simulation data. The preset virtual driving vehicle model is obtained by integrating the current vehicle's appearance model, dynamics model, and multi-field coupling model.

[0095] In some embodiments, current driving operation data and target somatosensory simulation data are input into a preset virtual driving vehicle model. The preset virtual driving vehicle model is used to perform a comprehensive simulation calculation of the vehicle state changes in the target virtual driving environment, and the calculation results are converted into simulation data that conforms to human visual and auditory perception habits, thereby obtaining target visual and auditory simulation data.

[0096] In some embodiments, the current vehicle appearance model is used to restore the external morphological features of the actual vehicle (such as body outline, headlight style, wheel size, etc.), providing a basic morphological basis for the generation of the visual part (such as vehicle appearance display, relative position changes of the surrounding environment, etc.) in the audiovisual simulation data.

[0097] In some embodiments, the dynamic model is used to simulate the changes in the motion state of an actual vehicle under different driving operations (such as acceleration performance, braking distance, steering response speed, etc.). The vehicle motion parameters calculated by the dynamic model are used to simulate the visual dynamic effects (such as vehicle speed display, changes in vehicle posture, etc.) and auditory effects (such as the sound corresponding to engine speed, braking sound, etc.) in the audiovisual simulation data.

[0098] In some embodiments, by collecting real vehicle K&C test data, handling and ride comfort test data, a multibody parametric model containing nonlinear suspension, steering, tires, and bushings is constructed. The suspension kinematics and elastic characteristics are calibrated using K&C test results, the steady-state and transient lateral and yaw responses are corrected using handling and stability data, and the vertical nonlinearity and damping are optimized using ride comfort data. A weighted least squares-genetic hybrid algorithm is used for iterative analysis under different working conditions and channels. After cross-validation and sensitivity analysis, the model is solidified to obtain a vehicle dynamics model that highly corresponds to the three test data.

[0099] In some embodiments, the multi-field coupling model is used to realize multi-dimensional interactive coupling simulation between vehicle appearance, dynamic motion and the surrounding environment. For example, it simulates the impact of different road conditions (such as asphalt road, cement road and gravel road) on vehicle dynamic performance, thereby indirectly affecting the auditory feedback (such as the difference in tire noise when driving on different road surfaces) and visual feedback (such as the body undulation of the vehicle on bumpy roads) in the audiovisual simulation data, ensuring that the audiovisual simulation data can fully reflect the interactive relationship between various elements in the virtual driving environment and improve the realism and accuracy of the virtual driving experience.

[0100] By comprehensively processing the current driving operation data and target somatosensory simulation data through the integrated virtual driving vehicle model, the final generated target audiovisual simulation data can achieve precise matching with the driver's operating behavior, vehicle motion state and changes in the surrounding environment, thus meeting the requirements of the virtual driving system for audiovisual simulation.

[0101] Figure 5The flowchart illustrates another virtual driving simulation method provided in this application embodiment. When the virtual driving simulation mode is a custom mode, the above S101 can be implemented as S301-S303, as follows: S301. Based on the driver's adjustment of the vehicle dynamic characteristic adjustment parameters, determine the target somatosensory simulation data.

[0102] Among them, the vehicle dynamic characteristic adjustment parameters are used to reflect the driver's driving habits.

[0103] In some embodiments, the vehicle dynamic characteristics adjustment parameters include relevant parameters of the vehicle chassis system.

[0104] For example, a vehicle chassis system may include a drive system, and the relevant parameters of the drive system may include the drive force response rate, etc.

[0105] For example, the vehicle chassis system may include a braking system, and the relevant parameters of the braking system may include the electric motor braking feedback intensity, etc.

[0106] For example, a vehicle chassis system may include a steering system, and the relevant parameters of the steering system may include steering ratio, steering assist, etc.

[0107] For example, a vehicle chassis system may include a suspension system, and the relevant parameters of the suspension system may include suspension height, suspension damping, suspension stiffness, etc.

[0108] In some embodiments, the driver's adjustment operations on vehicle dynamic characteristic parameters can be obtained from the vehicle's human-machine interface. For example, the human-machine interface may be a central control (touchscreen), a voice assistant, a button combination, etc.

[0109] For example, Figure 6 A schematic diagram illustrating another human-machine interface provided in an embodiment of this application is shown, such as... Figure 6 As shown, the human-machine interface displays multiple vehicle dynamic characteristic adjustment parameters. Figure 6 The system displays eight adjustable options: suspension height, suspension damping, suspension stiffness, drive force response, motor brake feedback, steering assist, steering ratio, and active rear wing tilt. Each adjustable option has a slider or button for adjusting the left and right limits, allowing the driver or user to adjust the corresponding parameters steplessly by dragging or clicking.

[0110] S302. Obtain the driver's current driving operation data in the target virtual driving environment.

[0111] In some embodiments, the driver’s current driving operation data in the target virtual driving environment includes relevant data generated by the driver’s operation behavior on vehicle control components (such as steering wheel, accelerator pedal, brake pedal, gear shift device, etc.) in the target virtual driving environment.

[0112] In some embodiments, after the driver operates the vehicle control components, the sensors built into the control components (such as steering wheel angle sensor, accelerator pedal position sensor, brake pedal pressure sensor, and gear position Hall sensor) immediately convert the mechanical displacement or pressure signal into an analog signal. These analog signals are transmitted to the virtual signal processor of the virtual driving system via a wiring harness. The virtual signal processor analyzes and extracts these analog signals to obtain the current driving operation data.

[0113] S303. Based on the driver's current driving operation data in the target virtual driving environment and the target's somatosensory simulation data, determine the target's audiovisual simulation data.

[0114] In some embodiments, the specific implementation of S303 is described in S204, and will not be repeated here.

[0115] The virtual driving simulation method provided in this application is described below through a complete embodiment, such as... Figure 7 As shown, the process includes the following: S1. Vehicle powered on.

[0116] S2. Obtain the target virtual driving environment selected by the driver.

[0117] S3. Obtain the virtual driving mode selected by the driver.

[0118] Among them are the virtual driving modes: Boakai adaptive mode and custom mode.

[0119] S4. The driver conducts virtual driving through the virtual driving system.

[0120] When the virtual driving mode is in adaptive mode, proceed with steps S5-S6: S5. Identify driver's driving style based on driver's driving operations.

[0121] S6. Driver's driving style determines target haptic simulation data.

[0122] If the virtual driving mode is set to custom mode, proceed to step S7: S7. In response to the driver's input operation, determine the target somatosensory simulation data.

[0123] After completing step S6 or S7 above, proceed to step S8: S8. Determine the target audiovisual simulation data based on the target virtual driving environment and the driver's driving operation.

[0124] S9. Based on the target's somatosensory simulation data, target's audiovisual simulation data, target's virtual driving environment, and virtual driving system, complete the virtual driving simulation.

[0125] As can be seen, the above mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, the embodiments of this application provide corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the modules and algorithm steps of the various examples described in the embodiments disclosed herein, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0126] This application embodiment can divide the vehicle steering control device into functional modules according to the above method example. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. Optionally, the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0127] Figure 8 This is a schematic diagram of a virtual driving simulation device provided in an embodiment of this application, used to implement the virtual driving simulation method provided in the above embodiments, such as... Figure 8 As shown, the virtual driving simulation device 700 includes a processing module 701 and a simulation module 702.

[0128] The processing module 701 is used to determine target virtual driving simulation data when the vehicle is in virtual driving mode; wherein, the virtual driving mode includes adaptive mode or custom mode; the target virtual driving mode data is used to simulate the user's driving experience; the simulation module 702 is used to perform virtual driving simulation based on the target virtual driving simulation data and the vehicle's virtual driving system.

[0129] In some embodiments, the target virtual driving simulation data includes target motion simulation data and target audiovisual simulation data.

[0130] In some embodiments, when the virtual driving mode is an adaptive mode, the processing module 701 is specifically used to acquire the driver's historical driving operation data in the target virtual driving environment; determine the driver's driving style based on the historical driving operation data and a preset driving style recognition algorithm; determine the target somatosensory simulation data that matches the driver's driving style based on the driver's driving style; and determine the target audiovisual simulation data based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data.

[0131] In some embodiments, the processing module 701 is specifically used to determine target somatosensory simulation data based on the driver's driving style and a preset correspondence; wherein the preset correspondence represents the correspondence between driving style and somatosensory simulation data.

[0132] In some embodiments, when the virtual driving mode is a custom mode, the processing module 701 is specifically used to determine target somatosensory simulation data based on the driver's adjustment of vehicle dynamic characteristic adjustment parameters; wherein, the vehicle dynamic characteristic adjustment parameters are used to reflect the driver's driving habits; to obtain the driver's current driving operation data in the target virtual driving environment; and to determine target audiovisual simulation data based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data.

[0133] In some embodiments, the processing module 701 is specifically used to input the driver's current driving operation data and target somatosensory simulation data in the target virtual driving environment into a preset virtual driving vehicle model to obtain target audiovisual simulation data; the preset virtual driving vehicle model is obtained by integrating the current vehicle's appearance model, dynamics model and multi-field coupling model.

[0134] When implementing the functions of the integrated modules described above in hardware, this embodiment of the invention provides a possible structural diagram of the electronic device involved in the above embodiments. For example... Figure 9 As shown, the electronic device 800 includes: a processor 802, a communication interface 803, and a bus 804. Optionally, the electronic device 800 may also include a memory 801.

[0135] Processor 802 may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 802 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 802 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0136] The communication interface 803 is used to connect to other devices via a communication network. This communication network can be Ethernet, wireless access network, wireless local area network (WLAN), etc.

[0137] The memory 801 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage medium or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0138] In one possible implementation, the memory 801 can exist independently of the processor 802. The memory 801 can be connected to the processor 802 via a bus 804 and is used to store instructions or program code. When the processor 802 calls and executes the instructions or program code stored in the memory 801, it can implement the virtual driving simulation method provided in this embodiment of the invention.

[0139] In another possible implementation, the memory 801 can also be integrated with the processor 802.

[0140] The 804 bus can be an extended industry standard architecture (EISA) bus, etc. The 804 bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 9 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0141] Through the above description of the implementation methods, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the service calling device can be divided into different functional modules to complete all or part of the functions described above.

[0142] This application also provides a computer-readable storage medium. All or part of the processes in the above method embodiments can be instructed by computer program instructions to be implemented by related hardware. This program can be stored in the aforementioned computer-readable storage medium. When the computer program instructions are executed on a computer, the computer causes the computer to perform the virtual driving simulation method as described in any of the above embodiments.

[0143] Exemplary examples of computer-readable storage media may include, but are not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes), optical discs (e.g., compact disks (CDs), digital versatile disks (DVDs), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memory (EPROMs), cards, sticks, or key drives, etc.). The various computer-readable storage media described in this disclosure may represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0144] This application also provides a computer program product comprising a computer program that, when run on a computer, causes the computer to execute any of the virtual driving simulation methods provided in the above embodiments.

[0145] In the description of the embodiments of this application, specific features, structures, materials or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0146] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A virtual driving simulation method, characterized in that, The method includes: When the vehicle is in virtual driving mode, target virtual driving simulation data is determined; wherein, the virtual driving mode includes adaptive mode or custom mode; the target virtual driving mode data is used to simulate the user's driving experience; Virtual driving simulation is performed based on the target virtual driving simulation data and the vehicle's virtual driving system.

2. The method according to claim 1, characterized in that, The target virtual driving simulation data includes target somatosensory simulation data and target audiovisual simulation data.

3. The method according to claim 2, characterized in that, When the virtual driving mode is the adaptive mode, determining the target virtual driving simulation data includes: Acquire historical driving operation data of the driver in the target virtual driving environment; Based on the historical driving operation data and the preset driving style recognition algorithm, the driver's driving style is determined; Based on the driver's driving style, determine the target somatosensory simulation data that matches the driver's driving style; The target audiovisual simulation data is determined based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data.

4. The method according to claim 3, characterized in that, The determination of the target somatosensory simulation data matching the driver's driving style based on the driver's driving style includes: Based on the driver's driving style and a preset correspondence, the target somatosensory simulation data is determined; wherein, the preset correspondence represents the correspondence between driving style and somatosensory simulation data.

5. The method according to claim 2, characterized in that, When the virtual driving mode is the custom mode, determining the target virtual driving simulation data includes: The target somatosensory simulation data is determined based on the driver's adjustment of the vehicle dynamic characteristic adjustment parameters; wherein, the vehicle dynamic characteristic adjustment parameters are used to reflect the driver's driving habits. Acquire the driver's current driving operation data in the target virtual driving environment; The target audiovisual simulation data is determined based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data.

6. The method according to claim 3 or 5, characterized in that, The step of determining the target audiovisual simulation data based on the driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data includes: The driver's current driving operation data in the target virtual driving environment and the target somatosensory simulation data are input into a preset virtual driving vehicle model to obtain the target audiovisual simulation data; the preset virtual driving vehicle model is obtained by integrating the current vehicle's appearance model, dynamics model and multi-field coupling model.

7. An electronic device, characterized in that, Electronic devices include: processor; Memory configured to store processor-executable instructions; The processor is configured to execute instructions to implement the method as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 6.

9. A vehicle, characterized in that, include: The electronic device of claim 7, or the computer-readable storage medium of claim 8.

10. A computer program product, characterized in that, The computer program product includes computer instructions that, when executed on an electronic device, cause the electronic device to perform the method as described in any one of claims 1 to 6.

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