Driving simulation method and system

Abstract

The invention belongs to the field of analog simulation, particularly relates to a driving analog simulation method and system, and aims to solve the problems of limitation of a kinetic model, singleness of a control mode and insufficient visual angle flexibility. The method comprises the following steps: acquiring control information when a user operates a simulated driving device, sending the control information to a dynamics simulation system through a simulation interaction system, and calculating to obtain pose information; the simulation interaction system performs data exception filtering on the pose information, and controls the length and angle of a telescopic cylinder in the six-axis motion feedback system in combination with a debugging coefficient obtained by pre-debugging after filtering; and the simulation interaction system converts the filtered pose information into data which can be acquired by the virtual environment rendering system, and sends the data to the virtual environment rendering system to update the pose of the virtual vehicle. The dynamic simulation precision is enhanced, diversified control modes are provided, and the visual angle flexibility is improved.

Description

Background Art

[0002] With the progress of technology, driving simulation systems play an increasingly important role in fields such as training, entertainment, and vehicle engineering design. Such systems aim to provide a safe and economical environment for users to experience or test different driving situations without involving actual road risks. To achieve a realistic simulation effect, these systems usually combine advanced technologies such as dynamic simulation, motion feedback, and virtual reality (VR).

[0003] Currently, the driving simulation methods on the market mainly rely on comprehensive dynamic simulation systems, six-axis motion feedback systems, and virtual environment rendering systems to simulate the driving process. However, the existing technologies have the following deficiencies:

[0004] Limitations of the dynamic model: The existing user end (UE) focuses on creating highly realistic simulation scenarios and accurate sensor data simulation, but its built-in dynamic simulation is relatively simple and the adjustable parameters are limited. This results in the inability to meet the high-precision simulation requirements for complex components such as vehicle chassis and steering systems. Therefore, although it can provide visual realism, there are still deficiencies in physical behavior simulation, limiting the system's ability to truly reproduce the dynamic characteristics of vehicles.

[0005] Single control mode: Traditional methods are often limited to controlling through a computer interface, that is, only indirectly manipulating virtual vehicles through simulation software. This mode lacks the realism brought by direct operation and affects the quality of the user experience. In addition, due to the lack of an operating device that matches ergonomics, it is difficult to fully reproduce the tactile feedback in actual driving, reducing the training effect.

[0006] Lack of perspective flexibility: In traditional driving simulators, the user's perspective is often fixed or preset, which not only reduces the immersion but also poses obstacles to the detailed observation in certain specific scenarios. Such a design is not conducive to cultivating the driver's ability to handle complex traffic conditions and is also not conducive to more meticulous operation practice.

[0007] Based on this, the present invention proposes a driving simulation method and system. Summary of the Invention

[0008] To solve the above problems in the existing technology, namely the limitations of the dynamic model, the single control mode, and the lack of perspective flexibility, the present invention provides a driving simulation method and system.

[0009] In the first aspect of the present invention, a driving simulation method is proposed, which integrates a dynamic simulation system, a simulation interaction system, a virtual environment rendering system, and a driving simulator. The method includes:

[0010] Obtain the control information of the user when operating the simulation driving simulator, and send the control information to the dynamics simulation system through the simulation interaction system. The dynamics simulation system calculates the pose information based on the road surface information and the control information; wherein, the road surface information is obtained based on the simulation scene in the virtual environment rendering system.

[0011] The simulation interaction system filters data anomalies of the pose information. After filtering, it controls the length and angle of the telescopic cylinder in the six-axis motion feedback system of the simulation driving simulator in combination with the debugging coefficient obtained through pre-debugging.

[0012] The simulation interaction system converts the filtered pose information into data that can be acquired by the virtual environment rendering system, and sends it to the virtual environment rendering system to update the pose of the virtual vehicle.

[0013] Further, the control information at least includes the steering wheel angle, the throttle pedal opening, the brake pedal opening, and the gear position.

[0014] Further, the pose information at least includes angle data and accelerations in different directions. The angle data at least includes the roll angle, the yaw angle, and the pitch angle.

[0015] Further, the method for the simulation interaction system to filter data anomalies of the pose information includes:

[0016] Perform data cleaning on the pose information; after cleaning, perform differential derivation on the roll angle, and multiply the derivative by the sampling time to obtain feedback data.

[0017] After delaying one sampling period, judge whether the absolute value of the feedback data is greater than a preset threshold. If it is greater, it is determined as abnormal data, and the abnormal feedback data is attenuated by a preset multiple of the sampling time.

[0018] If it is less than or equal to, it is determined as normal data, and the current normal feedback data is summed with the normal feedback data obtained in the previous sampling period to obtain the roll angle after data anomaly filtering.

[0019] Further, the method for obtaining the debugging coefficient includes the following steps:

[0020] Step S1, establish a simulation scene with a slope, and read the standard roll angle output by the simulation interaction system.

[0021] Step S2, obtain the current real-time roll angle of the six-axis motion feedback system according to the six-axis platform sensor, and judge whether the real-time roll angle is positive or negative.

[0022] If it is a positive value, add the first preset threshold to the current debugging coefficient; if it is a negative value, multiply the current debugging coefficient by the second preset threshold. Wherein, the first preset threshold and the second preset threshold are set based on the number of debugging times.

[0023] Step S3: Multiply the adjusted debugging coefficient by the real-time roll angle and calculate the difference from the standard roll angle.

[0024] If the difference is not within the set range, jump to step S2, increment the number of debugging times by one, and update the real-time roll angle in step S2 to the real-time roll angle after multiplying by the debugging coefficient until the difference is within the set range and then stop jumping.

[0025] If the difference is within the set range, end the debugging, and take the average of the debugging coefficients obtained from multiple debuggings as the final debugging coefficient.

[0026] Further, the calculation methods of the first preset threshold and the second preset threshold are as follows:

[0027] First preset threshold = a × n; Second preset threshold = b n ;

[0028] Wherein, a and b are both preset values, and n is the number of debugging times.

[0029] Further, the integrated driving simulation method further includes comparing the pose information with a pre-constructed safety protection constraint value to prevent safety accidents in the six-axis motion feedback system. The specific method is as follows:

[0030] Compare the pose information with the safety protection constraint value. When any one of the parameters in the pose information is greater than the corresponding safety protection constraint value, judge whether the rollover danger growth value is greater than 0. If so, judge that a dangerous phenomenon appears briefly, and at this time, judge whether the time when the dangerous phenomenon appears exceeds the rollover process parameter overrun time.

[0031] If it does not exceed, and the parameter in the pose information that is greater than the safety protection constraint value returns to within the safety value, attenuate the rollover danger value through the danger coefficient.

[0032] If it times out, accumulate the rollover danger value multiple times according to the rollover danger value growth rate, and judge whether the sum of the accumulations is greater than the danger upper limit value. If so, lower the Z-axis height in the six-axis motion feedback system to the lowest. Wherein, the rollover danger value is calculated based on the dynamic simulation system.

[0033] Further, the calculation method of the danger value growth rate C9 is as follows:

[0034] C9 = (C8 + T_over × C7 / Tp) × Tp / (6 × T_over × K);

[0035] Among them, C8 is the upper limit value of danger, T_over is the time when the parameters in the rollover process exceed the limit, C7 is the danger attenuation coefficient, Tp is the discrete step length, and K is the percentage at which the rollover process error reporting ends.

[0036] Furthermore, a camera model is created in the virtual environment rendering system. The camera model can adjust its position and angle and obtain the pose information in the simulation interaction system.

[0037] The position data and rotation data of the camera in the virtual environment rendering system are adjusted through the pose information.

[0038] On the other hand, the present invention proposes a driving simulation system based on a driving simulation method. The system includes:

[0039] A pose information acquisition module configured to acquire the control information of the user when operating the simulation driving device, send the control information to the dynamics simulation system through the simulation interaction system, and the dynamics simulation system calculates the pose information according to the road surface information and the control information; wherein, the road surface information is obtained based on the simulation scene in the virtual environment rendering system.

[0040] A control module configured to filter data anomalies of the pose information through the simulation interaction system, and control the length and angle of the telescopic cylinder in the six-axis motion feedback system of the simulation driving device by combining the debugging coefficient obtained through pre-debugging after filtering.

[0041] A simulation module configured to convert the filtered pose information into data that can be acquired by the virtual environment rendering system through the simulation interaction system and send it to the virtual environment rendering system to update the pose of the virtual vehicle.

[0042] Advantages of the present invention:

[0043] Enhanced dynamics simulation accuracy: By improving the dynamics model, the simulation of complex dynamic characteristics such as the vehicle chassis and steering system becomes more accurate. This not only improves the realism of physical behavior but also enhances the ability to reproduce the vehicle's dynamic characteristics, helping users obtain a driving experience closer to reality.

[0044] Diversified control methods: The introduction of direct operation devices such as simulation steering wheels, pedals, and other devices that match ergonomics increases tactile feedback, enhances the user's immersion and the authenticity of operation, thereby improving the training effect.

[0045] Enhanced Perspective Flexibility: The user's perspective can be freely adjusted, no longer limited to fixed or preset perspectives. Users are allowed to select the best viewing angle according to their needs. This helps improve the driver's adaptability in complex traffic situations and supports more detailed operation practice.

[0046] Comprehensive Optimization of User Experience: By integrating the dynamic simulation system, six-axis motion feedback system, and virtual environment rendering system, a full-range simulation from vision to touch is achieved, providing users with a highly realistic driving environment and promoting a double improvement in training efficiency and entertainment experience.

[0047] Data Processing and Security Mechanism: It includes data anomaly filtering for pose information to ensure data accuracy and reliability. At the same time, debugging coefficients are combined to optimize the response of the six-axis motion feedback system, further ensuring the stable operation of the system and the security of the user experience. Description of the Drawings

[0048] Other features, objectives, and advantages of this application will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings:

[0049] Figure 1 is a flowchart of a driving simulation method of the present invention;

[0050] Figure 2 is a schematic connection diagram of each system in a driving simulation method of the present invention;

[0051] Figure 3 is a schematic diagram of the dynamic modeling of the vehicle data in a driving simulation method of the present invention. Detailed Embodiments

[0052] The following further elaborates on this application in conjunction with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the relevant invention and are not intended to limit the invention. Additionally, it should be noted that for the sake of description, only parts related to the relevant invention are shown in the drawings.

[0053] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will elaborate on this application in detail with reference to the drawings and embodiments.

[0054] The present invention provides a driving simulation method that integrates a dynamic simulation system, a simulation interaction system, a virtual environment rendering system, and a driving simulator. The method includes:

[0055] Obtain the control information of the user when operating the driving simulator, and send the control information to the dynamics simulation system through the simulation interaction system. The dynamics simulation system calculates the pose information based on the road surface information and the control information. Among them, the road surface information is obtained based on the simulation scene in the virtual environment rendering system;

[0056] The simulation interaction system filters data anomalies of the pose information, and after filtering, controls the length and angle of the telescopic cylinder in the six-axis motion feedback system of the driving simulator in combination with the debugging coefficient obtained through pre-debugging;

[0057] The simulation interaction system converts the filtered pose information into data that can be obtained by the virtual environment rendering system and sends it to the virtual environment rendering system to update the pose of the virtual vehicle.

[0058] To more clearly illustrate a driving simulation method of the present invention, the following is combined with Figure 1 Expand and describe in detail in the embodiments of the present invention, and the detailed description is as follows:

[0059] Obtain the control information of the user when operating the driving simulator, and send the control information to the dynamics simulation system through the simulation interaction system. The dynamics simulation system calculates the pose information based on the road surface information and the control information. Among them, the road surface information is obtained based on the simulation scene in the virtual environment rendering system;

[0060] In this embodiment, refer to Figure 2 , the set dynamics simulation system is preferably Carsim in this embodiment, the simulation interaction system is preferably Matlab or simlink, and the virtual environment rendering system is preferably UE.

[0061] In this embodiment, the control information at least includes the steering wheel angle, the throttle pedal opening, the brake pedal opening, and the gear position. In simlink, a serial port receiving module is used to receive the vehicle control information of the hardware steering wheel and pedals, such as the steering wheel angle, the throttle pedal opening, the brake pedal opening, the gear position, etc., and transfer the control information to Casim for control.

[0062] The pose information at least includes angular data and accelerations in different directions. The angular data at least includes roll angle, yaw angle, and pitch angle. Specifically, a socket is created in Simulink, and the pose information received from Carsim, such as the pitch angle, yaw angle, roll angle of the vehicle, and accelerations in the x, y, and z directions, is packed and sent to the six-axis platform. The six-axis platform changes the lengths of the six-axis telescopic rods by obtaining the pitch, roll, yaw angles, etc., and at the same time creates a simulation scenario according to the real vehicle scenario, runs the simulation scenario in real time, outputs simulation data, and compares it with the real vehicle data to simulate an experience effect close to that of the real vehicle and achieve the overall movement of the platform.

[0063] Among them, referring to Figure 3 , the vehicle data parameters can be input in the vehicle model of Carsim to complete the preliminary dynamic modeling.

[0064] The simulation interaction system filters data anomalies in the pose information, and after filtering, controls the lengths and angles of the telescopic cylinders in the six-axis motion feedback system of the simulation driver in combination with the debugging coefficients obtained from pre-debugging;

[0065] Specifically, multiply the roll angle in the pose information by the debugging coefficient to obtain the debugged roll angle, and debug the roll angle in the six-axis motion feedback system according to the debugged roll angle.

[0066] Among them, the six-axis motion feedback system receives six-axis data through the UDP method. A UDP sender is created in Simulink and the data is packed and sent. In addition to roll, pitch, and yaw for controlling the six-axis motion, the data also includes a control interface for the Z-axis height, that is, the height at which the six-axis should rise during data initialization. However, during the actual operation process, the rising height is too fast, affecting comfort;

[0067] It is controlled by the start button on the steering wheel, and a model is created in Simulink to achieve a slow rising effect;

[0068] When the start button is triggered, the Z-axis height slowly accumulates with the number of UDP packet sending frames until it reaches the middle height to meet the motion conditions.

[0069] The simulation interaction system filters data anomalies in the pose information, and the method includes:

[0070] Perform data cleaning on the pose information; after cleaning, perform differential derivative on the roll angle, and multiply the derivative by the sampling time to obtain the feedback data;

[0071] After delaying for one sampling period, determine whether the absolute value of the feedback data is greater than a preset threshold. If it is greater, it is determined as abnormal data, and the abnormal feedback data is attenuated at a preset multiple of the sampling time.

[0072] If it is less than or equal to, it is determined as normal data. The current normal feedback data is summed with the normal feedback data obtained in the previous sampling period to obtain the roll angle after abnormal filtering.

[0073] Among them, the preset threshold is preferably 3, the preset multiple is preferably 0.5, and the sampling time is preferably 0.001 s.

[0074] Specifically:

[0075] Through the data cleaning algorithm model, data such as roll, yaw, and pitch output by carsim are cleaned.

[0076] The model differentiates the roll angle, multiplies it by the sampling time 0.001, delays the obtained derivative by one sampling period, and then gives feedback to determine whether abnormal data (absolute value greater than 3) appears. If abnormal data appears, it is attenuated at 0.5 times the sampling time. If no abnormal data appears, it is normally output, and the determined data is summed with the derivative data of the next frame, and then output and fed back.

[0077] Among them, the debugging coefficient can be calculated according to two schemes. Specifically:

[0078] Scheme 1:

[0079] The method for obtaining the debugging coefficient includes the following steps:

[0080] Step S1, establish a simulation scenario with a slope and read the standard roll angle output by the simulation interaction system.

[0081] Step S2, obtain the current real-time roll angle of the six-axis motion feedback system according to the six-axis platform sensor, and judge whether the difference between the standard roll angle and the real-time roll angle is positive or negative.

[0082] If it is positive, add the first preset threshold to the current debugging coefficient. If it is negative, multiply the current debugging coefficient by the second preset threshold. Among them, the first preset threshold and the second preset threshold are set based on the number of debugging times.

[0083] Step S3, multiply the adjusted debugging coefficient by the real-time roll angle and calculate the difference from the standard roll angle.

[0084] If the difference is not within the set range, jump to step S2, increment the number of debugging attempts by one, and update the real-time roll angle in step S2 to the real-time roll angle multiplied by the debugging coefficient, and stop jumping until the difference is within the set range;

[0085] If the difference is within the set range, end the debugging, and take the average of the debugging coefficients obtained from multiple debuggings as the final debugging coefficient.

[0086] The calculation methods for the first preset threshold and the second preset threshold are as follows:

[0087] First preset threshold = a × n; Second preset threshold = b n ;

[0088] Where a and b are both preset values. In this embodiment, a is preferably 0.1 and b is preferably 0.9; n is the number of debugging attempts.

[0089] Where the set range is ±0.1 degrees.

[0090] In Solution 1, each debugging is performed through the buttons on the steering wheel. The buttons include Button + and Button -, and the input variables for coefficient adjustment are through Button + and Button -;

[0091] Specifically:

[0092] Set up the simulation environment: Ensure that the simulation scenario includes a terrain with a slope to simulate actual driving conditions.

[0093] Configure the six-axis motion platform: Ensure that the sensors are correctly installed and can accurately read the roll angle.

[0094] Establish the simulation scenario: Build a road model with a slope in the simulation environment.

[0095] Start the simulation interaction system and record the standard roll angle of the vehicle on this ramp as the reference value.

[0096] Use the sensors on the six-axis platform to read the actual roll angle of the vehicle at the same ramp position.

[0097] Determine whether the difference between the standard roll angle and the real-time roll angle is positive or negative, which will determine the type of operation on the debugging coefficient in the subsequent steps.

[0098] If it is positive, increase the current debugging coefficient by the first preset threshold (0.1 × n), where n is the number of debugging attempts.

[0099] If it is negative, multiply the current debugging coefficient by the second preset threshold (0.9^n).

[0100] Multiply the adjusted debugging coefficient by the real-time roll angle, and then calculate the difference between this result and the standard roll angle.

[0101] If the difference exceeds the range of ±0.1 degrees, further adjustment is required. Use the steering wheel buttons of the simulation driver to make manual adjustments:

[0102] Press the "+" key to increment the n value corresponding to the number of debugging times by one;

[0103] Press the "-" key to decrement the n value corresponding to the number of debugging times by one.

[0104] After each adjustment, return to re-evaluate the new real-time roll angle.

[0105] When the difference between the real-time roll angle and the standard roll angle is controlled within the set range (±0.1 degrees), stop the adjustment.

[0106] Collect all the different roll angle values obtained during the debugging process and calculate their average value, which is used as the finally determined debugging coefficient.

[0107] To improve accuracy, repeat the above process at different positions to ensure that the obtained data can represent the performance in the entire simulation environment.

[0108] Among them, the number of debugging times n is initially 0, and the initial debugging coefficient is 1.

[0109] Conduct statistical analysis on the key parameter and roll values during all debugging processes, especially calculate the mean value of the debugging coefficient to determine the optimized debugging coefficient.

[0110] Among them, those skilled in the art can set different slopes, change the position of the vehicle for multiple measurements, so as to obtain a more accurate debugging coefficient.

[0111] Solution 2:

[0112] Create a PID model for angle adjustment in Simulink. Use the roll angle output by Carsim as the target value and the roll value of the six-axis platform sensor as the actual value. The coefficient debugged in Solution 1 can be input as the p value, and then debug the i and d values to achieve precise control of the six-axis platform.

[0113] The simulation interaction system converts the filtered pose information into data that the virtual environment rendering system can obtain, and sends it to the virtual environment rendering system to update the pose of the virtual vehicle.

[0114] Use the UE plug-in module in Simulink to process the received Carsim pose information. For example, the vehicle position coordinates x, y, z are converted through the Euler formula for coordinate system conversion to x, y, z in the geodetic coordinate system. Similarly, the vehicle speed, acceleration, angle and other I / O interfaces are also converted according to the units required by the actual UE, and then sent to UE in real time to achieve dynamic update of the coordinates of the main vehicle in UE;

[0115] Then, through the plug-in module, the received road surface information, such as road surface friction coefficient, four-wheel contact point height, etc., is transmitted to Carsim to meet the requirements of Carsim scene information, and the main vehicle climbing test and tire adhesion test can be carried out, etc.

[0116] Through the socket plug-in of UE, a UDP communication interface can be created in the blueprint of UE, and data is sent to Simulink in the form of UDP. UDP reception is carried out in Simulink, and the received data can be associated with algorithm interfaces or other hardware; conversely, data can be sent in Simulink and received in UE, so as to realize the control of other scene elements in UE except the main vehicle.

[0117] Carsim dynamics: Use the Carsim S-fuction module in Simulink to receive control information and road surface information in real time. For control information, adapt to the hardware driving simulator, such as unit conversion, proportional coefficient debugging, etc. For road surface information, such as height, etc., carry out safety limit processing to prevent the platform from moving violently when dangerous scenes occur. After Carsim receives the processed control and scene information, the main vehicle synchronizes the pose information in real time, and then realizes the real-time information interaction between the UE scene, Carsim and the motion platform.

[0118] In this embodiment, when performing extreme scenario tests, phenomena such as vehicle rollover occur. To prevent the platform from moving violently and causing injuries to test personnel, a safety protection model is constructed in Simulink

[0119] Take the rollrate, pitchrate, yawrate, ax, ay, az, and danger feedback value dang_pre output by the carsim vehicle model as input variables.

[0120] According to different driving habits, set driving constraint values C1~C6,

[0121] C1: 60, C2: 50, C3: 150, C4: 3, C5: 3, C6: 6

[0122] T_over = 0.04: The overrun time of the rollover process parameters; K = 0.4: The percentage of error termination in the rollover process; Tp = 0.001: The discrete step size; C7 = 0.0001: The danger attenuation coefficient; C8 = 3: The upper limit of the danger value.

[0123] Compare the pose information with the pre - constructed safety protection constraint values to prevent safety accidents in the six - axis motion feedback system. The specific method is as follows:

[0124] Compare the pose information with the safety protection constraint values. When any parameter in the pose information is greater than the corresponding safety protection constraint value, determine whether the rollover danger growth value is greater than 0. If so, determine that a dangerous phenomenon appears briefly, and then determine whether the time when the dangerous phenomenon appears exceeds the overrun time of the rollover process parameters;

[0125] If it does not exceed, and the parameter in the pose information that is greater than the safety protection constraint value returns to the safe value range, attenuate the rollover danger value through the danger coefficient;

[0126] If it times out, accumulate the rollover danger value multiple times according to the rollover danger value growth rate, and determine whether the sum of the accumulations is greater than the upper limit of the danger value. If so, lower the Z - axis height in the six - axis motion feedback system to the lowest. Among them, the rollover danger value is calculated based on the dynamic simulation system.

[0127] The danger value growth rate C9, and its calculation method is:

[0128] C9 = (C8 + T_over × C7 / Tp) × Tp / (6 × T_over × K);

[0129] Among them, C8 is the upper limit of the danger value, T_over is the overrun time of the rollover process parameters, C7 is the danger attenuation coefficient, Tp is the discrete step size, and K is the percentage of error termination in the rollover process.

[0130] This embodiment further includes: creating a camera model in the virtual environment rendering system, the camera model can adjust its position and angle, and obtain the pose information in the simulation interaction system;

[0131] Adjust the position data and rotation data of the camera in the virtual environment rendering system through the pose information.

[0132] Create an additional camera model on the UE side. Enter the blueprint of the camera and create a UDP data receiving function. Unpack and associate the received data packets according to the required x, y, z, pitch, roll, yaw, etc. of the camera. Then, on the Simulink side, control information can be obtained through the steering wheel buttons or other hardware, and the logic of the yaw angle output when the driver rotates with the head is simulated and sent to the UE through UDP packaging. Finally, during the operation of the project, the driver's perspective can be changed in real time to simulate the picture observed by the real human eye.

[0133] In the above embodiments, although the various steps are described in the above sequential manner, those skilled in the art can understand that in order to achieve the effects of this embodiment, different steps do not have to be executed in such an order. They can be executed simultaneously (in parallel) or in a reversed order, and these simple changes are all within the protection scope of the present invention.

[0134] A driving simulation system according to the second embodiment of the present invention is based on a driving simulation method. The system includes:

[0135] A pose information acquisition module configured to acquire control information of a user when operating a driving simulator, send the control information to a dynamics simulation system through a simulation interaction system, and the dynamics simulation system calculates pose information based on road surface information and the control information; wherein, the road surface information is acquired based on a simulation scene in a virtual environment rendering system;

[0136] A control module configured to filter data anomalies of the pose information through the simulation interaction system, and control the length and angle of a telescopic cylinder in a six-axis motion feedback system of the driving simulator in combination with a debugging coefficient obtained through pre-debugging after filtering;

[0137] A simulation module configured to convert the filtered pose information into data that can be acquired by the virtual environment rendering system through the simulation interaction system and send it to the virtual environment rendering system to update the pose of the virtual vehicle. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process and related explanations of the above-described system can refer to the corresponding process in the foregoing method embodiments and will not be elaborated here.

[0138] It should be noted that, for the driving simulation system provided in the above embodiments, only the division of the above functional modules is used as an example for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the modules or steps in the embodiments of the present invention can be further decomposed or combined. For example, the modules in the above embodiments can be merged into one module, or further split into multiple sub-modules to complete all or part of the functions described above. For the names of the modules and steps involved in the embodiments of the present invention, they are only used to distinguish each module or step, and are not regarded as an improper limitation of the present invention.

[0139] An electronic device according to the third embodiment of the present invention includes:

[0140] At least one processor; and

[0141] A memory communicatively connected to at least one of the processors; wherein,

[0142] The memory stores instructions executable by the processor, and the instructions are used to be executed by the processor to implement the above-mentioned driving simulation method.

[0143] A computer-readable storage medium according to the fourth embodiment of the present invention stores computer instructions, and the computer instructions are used to be executed by the computer to implement the above-mentioned driving simulation method.

[0144] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, the specific working processes and related descriptions of the above-mentioned storage device and processing device can refer to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0145] Those skilled in the art should be able to realize that the modules and method steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. The programs corresponding to the software modules and method steps can be placed in a random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the art. To clearly illustrate the interchangeability of electronic hardware and software, the components and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in the form of electronic hardware or software 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 to exceed the scope of the present invention.

[0146] The terms "first", "second", etc. are used to distinguish similar objects and are not used to describe or indicate a specific order or sequence.

[0147] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that comprises a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to those processes, methods, articles, or apparatus / devices.

[0148] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the drawings. However, it is easily understood by those skilled in the art that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

Claims

1. A driving simulation method, which integrates a dynamics simulation system, a simulation interaction system, a virtual environment rendering system and a simulated driver, characterized in that: The method includes: Acquire control information of the user when operating the simulated driving device, and send the control information to the dynamic simulation system through the simulation interaction system, and the dynamic simulation system calculates the posture information according to the road surface information and the control information; wherein the road surface information is acquired based on the simulation scene in the virtual environment rendering system; The simulation interaction system performs data anomaly filtering on the posture information, and after filtering, combines the debugging coefficient obtained in pre-debugging to control the length and angle of the telescopic cylinder in the six-axis motion feedback system of the simulated driver; The simulation interaction system converts the filtered posture information into data that can be obtained by the virtual environment rendering system, and sends it to the virtual environment rendering system to update the posture of the virtual vehicle.

2. A driving simulation method according to claim 1, characterized in that: The control information at least includes a steering wheel angle, an accelerator pedal opening, a brake pedal opening and a gear position.

3. A driving simulation method according to claim 1, characterized in that: The posture information includes at least angle data and accelerations in different directions, and the angle data includes at least a roll angle, a yaw angle, and a pitch angle.

4. A driving simulation method according to claim 3, characterized in that: The simulation interaction system performs data anomaly filtering on the posture information, and the method includes: The posture information is cleaned; after cleaning, the roll angle is differentiated and multiplied by the sampling time to obtain feedback data; After a delay of one sampling period, determine whether the absolute value of the feedback data is greater than a preset threshold value. If so, determine it as abnormal data, and attenuate the abnormal feedback data by a preset multiple of the sampling time; If it is less than or equal to, it is determined to be normal data, and the current normal feedback data is summed with the normal feedback data obtained in the previous sampling period to obtain the roll angle after abnormal filtering.

5. A driving simulation method according to claim 3, characterized in that: The debugging coefficient, the method for obtaining it comprises the following steps: Step S1, establishing a simulation scene with a slope, and reading a standard roll angle output by the simulation interaction system; Step S2, obtaining the current real-time roll angle of the six-axis motion feedback system according to the six-axis platform sensor, and determining whether the difference between the standard roll angle and the real-time roll angle is a positive value or a negative value; If it is a positive value, the current debugging coefficient is added to the first preset threshold value, and if it is a negative value, the current debugging coefficient is multiplied by the second preset threshold value; wherein the first preset threshold value and the second preset threshold value are set based on the number of debugging times; Step S3, multiplying the adjusted debugging coefficient by the real-time roll angle, and calculating the difference from the standard roll angle; If the difference is not within the set range, jump to step S2, increase the debugging times by one, and update the real-time roll angle in step S2 to the real-time roll angle multiplied by the debugging coefficient, until the difference is within the set range, stop jumping; If the difference is within the set range, the debugging is terminated, and the average value of the debugging coefficients obtained from multiple debugging is taken as the final debugging coefficient.

6. A driving simulation method according to claim 5, characterized in that: The first preset threshold and the second preset threshold are calculated as follows: The first preset threshold = a×n; the second preset threshold = b n ; Wherein, a and b are preset values, and n is the number of debugging times.

7. A driving simulation method according to claim 1, characterized in that: The integrated driving simulation method further includes comparing the posture information with the pre-built safety protection constraint value to prevent the six-axis motion feedback system from having a safety accident, and the specific method is as follows: Compare the posture information with the safety protection constraint value, and when any parameter in the posture information is greater than the corresponding safety protection constraint value, determine whether the rollover risk growth value is greater than 0, and if so, determine that a dangerous phenomenon occurs briefly, and at this time determine whether the time when the dangerous phenomenon occurs exceeds the overrun time of the rollover process parameter; If it does not exceed, and the parameters in the posture information that are greater than the safety protection constraint value return to the safe value, the rollover risk value is attenuated by the risk factor; If it times out, the rollover risk value will be accumulated multiple times according to the growth rate of the rollover risk value to determine whether the accumulated sum is greater than the upper limit of the risk value. If so, the Z-axis height in the six-axis motion feedback system will be reduced to the minimum, wherein the rollover risk value is calculated based on the power simulation system.

8. A driving simulation method according to claim 7, characterized in that: The calculation method of the growth rate of the risk value C9 is: C9=(C8+T_over×C7 / Tp)×Tp / (6×T_over×K); Among them, C8 is the upper limit of danger, T_over is the over-limit time of the rollover process parameters, C7 is the danger attenuation coefficient, Tp is the discrete step length, and K is the percentage of the rollover process error end.

9. A driving simulation method according to claim 1, characterized in that: Creating a camera model in the virtual environment rendering system, wherein the camera model can adjust the position and angle and obtain the position and posture information in the simulation interaction system; The position data and rotation data of the camera in the virtual environment rendering system are adjusted according to the position information.

10. A driving simulation system, based on a driving simulation method according to any one of claims 1 to 9, characterized in that: The system includes: A posture information acquisition module is configured to acquire control information of a user when operating a simulated driver, and send the control information to a dynamics simulation system through a simulation interaction system, wherein the dynamics simulation system calculates posture information according to road surface information and the control information; wherein the road surface information is acquired based on a simulation scene in a virtual environment rendering system; A control module configured to filter the posture information for data anomalies through the simulation interaction system, and after filtering, control the length and angle of the telescopic cylinder in the six-axis motion feedback system of the simulated driver in combination with the debugging coefficient obtained in pre-debugging; The simulation module is configured to convert the filtered posture information into data that can be obtained by the virtual environment rendering system through the simulation interaction system, and send it to the virtual environment rendering system to update the posture of the virtual vehicle.

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