Perception fusion software simulation method

Abstract

The invention relates to a perception fusion software simulation method, a vehicle-mounted system and a computer readable storage medium. The perceptual fusion software simulation method comprises the steps of extracting a first controller area network CAN signal for perceptual fusion software based on information provided by a CAN database to obtain a second CAN signal; extracting a first software operation measurement signal for the perception fusion software to obtain a second software operation measurement signal; converting the second software operation measurement signal according to the second CAN signal based on the signal mapping relation library to generate a third software operation measurement signal; and simulating the perceptual fusion software based on the first software operation measurement signal and the third software operation measurement signal.

Description

Technical Field

[0001] The present disclosure relates to the field of simulation, and particularly to a perception fusion software simulation method, a vehicle-mounted system, and a computer-readable storage medium. Background Art

[0002] Currently, a large number of various types of sensors (such as cameras, lidars, millimeter-wave radars, etc.) are arranged on vehicles for assisted driving. For the update of various perception fusion software (algorithms) set for the sensors, the current perception fusion software simulation and testing are limited to re-collecting and recording the software operation measurement signals and the Controller Area Network CAN signals, and using the two for the simulation and testing of the perception fusion software. Such simulation and testing require CAN data (signals) and real-time recorded software operation measurement signals, occupying a large amount of memory. Even when using a measurement tool (such as CANape), the data recording stability is not high, and situations such as overload are likely to occur. Summary of the Invention

[0003] In view of the above problems, the present disclosure aims to provide a perception fusion software simulation method, a vehicle-mounted system, and a computer-readable storage medium.

[0004] The perception fusion software simulation method according to the first aspect of the present disclosure includes: extracting a first Controller Area Network CAN signal for the perception fusion software based on the information provided by the CAN database to obtain a second CAN signal; extracting a first software operation measurement signal for the perception fusion software to obtain a second software operation measurement signal; converting the second software operation measurement signal according to the second CAN signal based on the signal mapping relationship library to generate a third software operation measurement signal; and simulating the perception fusion software based on the first software operation measurement signal and the third software operation measurement signal.

[0005] The vehicle-mounted system according to the second aspect of the present disclosure includes a processing unit and a storage unit. The storage unit stores instructions, and when the instructions are executed by the processing unit, the simulation method according to any embodiment herein is implemented.

[0006] The computer-readable storage medium according to the third aspect of the present disclosure stores instructions, and when the instructions are executed by a processor, the simulation method according to any embodiment herein is implemented.

[0007] As described above, according to the perception fusion software simulation method of the present disclosure, the data supply in the perception fusion software simulation process can be realized when there is little or no software operation measurement signal, reducing the cost of the simulation process and improving the efficiency of the simulation test. Brief Description of the Drawings

[0008] Figure 1It is a schematic flowchart of a perception fusion software simulation method 100 according to some embodiments of the present disclosure.

[0009] Figure 2 It is a schematic diagram of the process and modules 200 of a perception fusion software simulation method according to some embodiments of the present disclosure.

[0010] Figure 3 It is a schematic flowchart of a perception fusion software simulation method 300 according to some embodiments of the present disclosure.

[0011] Figure 4 It is a schematic diagram of a conversion process 400 according to some embodiments of the present disclosure. Detailed Description of the Invention

[0012] The following describes some of the multiple embodiments of the present disclosure, aiming to provide a basic understanding of the present disclosure. It is not intended to identify the key or decisive elements of the present disclosure or to limit the scope to be protected.

[0013] For the sake of simplicity and illustrative purposes, the principles of the present disclosure are mainly described herein with reference to its exemplary embodiments. However, those skilled in the art will readily recognize that the same principles can be equivalently applied to all types of perception fusion software simulation methods, vehicle-mounted systems, and computer-readable storage media, and these same principles can be implemented therein, and any such variations do not depart from the true spirit and scope of this patent application.

[0014] Moreover, in the following description, reference is made to the accompanying drawings, which illustrate specific exemplary embodiments. Electrical, mechanical, logical, and structural changes can be made to these embodiments without departing from the spirit and scope of the present disclosure. In addition, although a feature of the present disclosure is disclosed in combination with only one of several embodiments / embodiments, this feature can be combined with one or more other features of other embodiments / embodiments as may be desired and / or advantageous for any given or identifiable function. Therefore, the following description should not be construed in a limiting sense, and the scope of the present disclosure is defined by the appended claims and their equivalents.

[0015] Terms such as "comprising" and "including" indicate that in addition to having the units (modules) and steps directly and explicitly stated in the specification and claims, the technical solutions of the present disclosure do not exclude the case of having other units (modules) and steps not directly or explicitly stated.

[0016] Hereinafter, various exemplary embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings.

[0017] Known perception fusion software simulation solutions need to record CAN ports (CAN trace) and software operation measurement signal ports, which may cause large memory occupancy. Using CANape to record internal signals will face problems such as instability and overload. In addition, it may be limited to only having CAN data, but the perception fusion software does not have corresponding CAN components to process this CAN data. Therefore, the simulation uses poor data or even cannot perform the simulation.

[0018] Figure 1 FIG. 4 is a schematic flow chart of a perception fusion software simulation method 100 according to some embodiments of the present disclosure. The perception fusion software simulation method 100 includes the following steps:

[0019] In step 110, based on the information provided by the CAN database, the first Controller Area Network CAN signal for the perception fusion software is extracted to obtain a second CAN signal, and in step 120, the first software operation measurement signal for the perception fusion software is extracted to obtain a second software operation measurement signal. It can be understood that step 110 and step 120 can be executed together or the order can be swapped.

[0020] In some examples, the first CAN signal and the first software operation measurement signal can be extracted separately. For example, a function in Asammdf lib (an open library based on python for MF4 files) for extracting software operation measurement signals (and their related file formats) can be used to extract the first software operation measurement signal to remove the redundant part of the software operation measurement signal and leave the signal part that needs to be converted and simulated in the first software operation measurement signal.

[0021] In some examples, the CAN database can define, for example, the signal name, signal value (such as physical value) of the CAN signal and its calculation, and optionally include related parameters (such as offset) of the CAN signal. Therefore, a function in Python can lib (an open library based on python for CAN data) for extracting CAN signals can be used to extract the first CAN signal to remove the redundant part of the CAN signal and leave the signal part that needs to be converted and simulated in the first CAN signal. The remaining part can be the signals related to the problems targeted by the simulation process or changes in the perception fusion software. For example, if the problems of a certain perception fusion software involve CAN signals including at least speed signals and heading angle signals, then signals with the same signal names as these two signals can be filtered out from the first CAN signal.

[0022] Among them, the first CAN signal may include sensed data transmitted via the CAN bus from sensors of the vehicle (such as radar data including the sensed target), or may include vehicle state information (such as heading angle, vehicle speed, vehicle attitude, etc.) provided by other electronic control units (ECUs) of the vehicle. In some examples, the first CAN signal may typically include a type of signal related to the problem part or the changed part of the perception fusion software (algorithm) for the sensors. For example, in a certain perception fusion software usage scenario or problem diagnosis, if it is necessary to simulate the speed signal, the first CAN signal may include such speed signal recording data. The first software running measurement signal may come from, for example, a memory (container) for simulation / testing, which characterizes the internal measurement signal when the perception fusion software is running, such as including runnable, intermediate quantity, running result, sensed data related information, etc. For example, the first software running measurement signal may be MF4 format data characterizing the relevant states and parameters of the internal process of software running and the processing process. The memory stores multiple types of multiple first software running measurement signals, and the time scheduling information and framework of the first software running measurement signal are basically consistent with the time scheduling information and framework of the software running measurement signal observable after the first CAN signal passes through the perception fusion software.

[0023] That is to say, limited by certain scenarios, only the first CAN signal is provided, and there is no device or software to record the software running measurement signal generated during the process of the first CAN signal passing through the perception fusion software. In this case, there is a lack of software running measurement signals to simulate and test the perception fusion software. Therefore, the time scheduling information and framework of the existing or real-time generated software running measurement signals in the memory (container) can be used to write the relevant information values of the first CAN signal to form the above-mentioned third software running measurement signal, and then used for simulation.

[0024] In step 130, based on the signal mapping relationship library, the second software operation measurement signal is converted according to the second CAN signal to generate a third software operation measurement signal. Among them, the signal mapping relationship library provides the mapping relationship (for example, comma-separated value CSV) for conversion between CAN signals and software operation measurement signals. After extracting the CAN signal and the software operation measurement signal, it is necessary to correspond them one by one. The types of the values of the CAN signal and the software operation measurement signal can be made consistent according to the mapping relationship and the signal value of the CAN signal. Then, operations such as numerical replacement of the signal value and time synchronization of the software operation measurement signal can be performed based on the signal value of the CAN signal, for example. The second software operation measurement signal after operations such as numerical replacement is converted into a third software operation measurement signal. In some examples, some transceiver message information and signals corresponding to these messages are defined in the CAN database. Therefore, it can be defined according to the customer and the system architecture function. For example, the maximum value, minimum value, offset, etc. of each signal can be defined. In some cases, the signal value extracted from the CAN signal may not be a physical value. Therefore, the information in the CAN database can be used to convert this value. In some examples, the information provided by the signal mapping relationship library and the CAN database can be used to process the extracted CAN signal and software operation measurement signal through, for example, the Cantools lib function library.

[0025] In step 140, based on the first software operation measurement signal and the third software operation measurement signal, the perception fusion software is simulated. That is to say, after generating the third software operation measurement signal in the previous step, the third software operation measurement signal can be combined with the original first software operation measurement signal and input to the corresponding perception fusion software for operation, and the result is output by the perception fusion software. The simulation test of the perception fusion software can be carried out by comparing the result with the input third software operation measurement signal, for example, or the output result can be directly analyzed to diagnose problems. These simulation tests can be, for example, for the update or partial update of the perception fusion software, detection of operation problems, etc.

[0026] In some examples, the method of the present disclosure uses the signals on the CAN line and the stored software operation measurement signals to perform software simulation, which can reduce the data volume of the software operation measurement signals that need to be recorded by a measurement tool (such as CANape). Moreover, without reproducing the scenario corresponding to the perception fusion software simulation and without re-collecting and recording test data, the simulation of the perception fusion software can be carried out. This greatly improves the efficiency of the simulation test, can ensure the effect of the simulation test, and reduces the cost of the simulation process.

[0027] Reference can be further made to Figure 2, which shows the flowchart of the perception fusion software simulation method according to some embodiments of the present disclosure and the schematic diagram of module 200. Optionally, the first software running measurement signal can be stored in the software running measurement signal container 210 so that it can be repeatedly used for various types of simulations or simulations for different first CAN signals, having good reusability, thus helping to alleviate or solve the problem of excessive memory occupation. The container 210 provides the first software running measurement signal to the system 230 for performing some steps of the method described in the present disclosure (including the extraction step and the conversion step). In addition, block 220 (e.g., from the CAN bus) provides the input of the first CAN signal (e.g., BLF / ASC).

[0028] In some examples, optionally, the verification of the first software running measurement signal can be performed in block 231, and the verification of the first CAN signal can be performed in block 233. The verification can be, for example, a cyclic redundancy check CRC, or other types of format checks. Then, optionally, the first software running measurement signal and the first CAN signal can be extracted via the signal filtering rules provided by blocks 232 and 234 (together with the CAN database 236) (such as Figure 2 points A and B in). After extraction, the extracted second software running measurement signal and the second CAN signal can be transmitted to the conversion module 235 for conversion, for example, to replace the signal values of the second software running measurement signal at some timestamps with the signal values of the second CAN signal. In this conversion module 235, the conversion can be performed via the mapping relationship provided by the signal mapping relationship library 237. Then, a new third software running measurement signal 238 can be generated, and the third software running measurement signal 238 can be combined and output together with the first software running measurement signal originally generated by the container 210, for example, outputting a fourth software running measurement signal 240 for input to the perception fusion software for simulation. Or, in some other examples, the third software running measurement signal 238 can also be directly used for simulation, for example, parsing the third software running measurement signal 238 processed by the perception fusion software to diagnose problems or changed running effects of the perception fusion software.

[0029] Of course, the method of the present disclosure is not limited to the order described above, but can be executed in various ways that can achieve the generation of the third software running measurement signal and the perception fusion software simulation. Figure 3FIG. 0 is a schematic flowchart of a perception fusion software simulation method 300 according to some embodiments of the present disclosure, which shows another specific method flow, including steps S1-S12. In step S1, the process of the whole method is started; in step S2, the signal mapping relationship is read; in step S3, the CAN signal for replacing the subsequent software running measurement signal is read; in step S4, the timestamp of the CAN signal is initialized, for example, the starting point of its time interval is adjusted to time point 0, so as to facilitate the alignment of the subsequent software running measurement signal with this time point 0; in step S5, the software running measurement signal is read; in step S6, an extraction operation is performed on the read CAN signal and software running measurement signal, and the signal part for subsequent simulation is retained; in step S7, the format check and judgment of the software running measurement signal can be optionally performed. If there are some special format signals (i.e., signals that are not in the measurement data format, such as the fault false signal) in the software running measurement signal, then this special format signal can be converted in step S8 into a signal in the measurement data format and proceed to the next step; in step S9, the software running measurement signal can be aligned to the time point 0 adjusted for the CAN signal in step S4; then, in step S10, the conversion of the software running measurement signal is performed; in step S11, a new software running measurement signal (i.e., for example, the fourth software running measurement signal mentioned in this article) is generated based on the converted software running measurement signal and the original software running measurement signal; finally, the method flow ends in step S12.

[0030] In some embodiments, the above conversion process may further include converting the first signal value of the second software running measurement signal at the first timestamp into a second signal value, where the second signal value is obtained by converting the signal value of the second CAN signal at the second timestamp based on the mapping relationship information provided by the signal mapping relationship library, and the second timestamp is the earliest timestamp with the shortest time interval from the first timestamp.

[0031] Reference Figure 4 , shows a schematic diagram of a conversion process 400 according to some embodiments of the present disclosure. Among them, 410 represents the timeline of the CAN signal, with signal values at five timestamps (time points) D1-D5; 420 represents the timeline of the software running measurement signal, with signal values at five timestamps X1-X5. Taking Figure 4Taking the example timestamp as an example, an example of the conversion process of the present disclosure may include the following conversion correspondence: both X1 and X2 correspond to D1, X3 corresponds to D2, X4 corresponds to D4, and X5 corresponds to D5. The rule based on this example correspondence is that D1 is the earliest timestamp on the timeline of the CAN signal with the shortest time interval from X1 and also the earliest timestamp with the shortest time interval from X2. Similarly, D2 is the earliest timestamp on the timeline of the CAN signal with the shortest time interval from X3, D4 is the earliest timestamp on the timeline of the CAN signal with the shortest time interval from X4, and D5 is the earliest timestamp on the timeline of the CAN signal with the shortest time interval from X5.

[0032] Therefore, based on this rule, according to the signal mapping relationship and signal value information, the signal value of the software running measurement signal 420 at X1 / X2 can be replaced with the signal value of the CAN signal 410 at D1, and so on for X3 - X5. This replacement rule can make the signal content or signal value represented by the software running measurement signal and the CAN signal relatively close, which is beneficial to ensuring the effect of subsequent simulation tests.

[0033] Thus, in some embodiments, referring to Figure 4 , the conversion process 400 may further include aligning the starting point of the time interval of the second software running measurement signal with the starting point of the time interval of the second CAN signal (430). In this way, a certain degree of time synchronization between the CAN signal and the software running measurement signal can be achieved before the conversion, which makes the timestamps referred to in the subsequent conversion process more accurate.

[0034] In some embodiments, continuing to refer to Figure 4 , the conversion process 400 may further include, after the starting point alignment, discarding the parts of the second software running measurement signal and the second CAN signal within the first time sub - interval at the beginning of the time interval. That is, for example, discarding a small section of the signal timeline at the very beginning, so that the newly generated software running measurement signal (the third software running measurement signal 440) after the subsequent conversion does not have the part of the first small section of time (442), and only leaving the effective part (444) for subsequent simulation. This can avoid the inaccuracy problem caused by the influence of some internal state signals on the simulation results in the first small section of time, making the subsequent simulation results more accurate.

[0035] Therefore, as described above, the steps of the simulation test may further include comparing the third software running measurement signal with the third software running measurement signal processed by the perception fusion software. Or, comparing the generated fourth software running measurement signal with the fourth software running measurement signal processed by the perception fusion software. Through the comparison, the simulation result analysis can be carried out for the problem part or updated part of the perception fusion software.

[0036] As mentioned above, the extraction step can filter out irrelevant signal parts in the CAN signal and / or software operation measurement signals according to specific signal filtering rules. Therefore, in some examples, the extraction step may further include: extracting based on the corresponding signal filtering rules, where the signal filtering rules are associated with changes in the perception fusion software. That is to say, in some cases, it may not be necessary to simulate the entire perception fusion software, but only to simulate its key parts. These key parts can be related to, for example, changes, updates, or problems (BUGs) in the perception fusion software. The corresponding signal filtering rules can focus on these changes, making the simulation process and the test data signals used more targeted, thereby improving the simulation efficiency. In some examples, the filter file (signal filtering rules) can be customized based on specific requirements and software architecture. For numerous signals in MF4, for example, the signals required for simulation testing are extracted. For numerous signals and messages in the CAN file, the required CAN signals are also extracted. For example, for the update or problem diagnosis of the perception fusion software in a certain scenario, the speed signal and heading angle signal in the CAN signal, as well as the time scheduling and framework of the software operation measurement signals corresponding to the speed parameter and heading angle parameter, may be required. Therefore, the speed signal and heading angle signal in the CAN signal, and the time scheduling and framework of the software operation measurement signals corresponding to the speed parameter and heading angle parameter can be extracted.

[0037] Correspondingly, in some examples, the first CAN signal can be associated with changes in the perception fusion software. As mentioned above, the first CAN signal can be related to the parts of the perception fusion software that the simulation staff is interested in for simulation / testing. These parts of interest can typically include any changes or errors in the perception fusion software. Thus, what is characterized or indicated by the signal value of the CAN signal used to replace the signal value of the software operation measurement signal can be associated with the parts of interest of the perception fusion software.

[0038] In this document, the software operation measurement signal can, for example, include signals in the measurement data format MDF format (in the form of MF4 files). Such signals in binary file format can indicate data from logs or calculations for later measurement processing, offline evaluation, or long-term storage. And it is organized in a loosely coupled binary block data form to achieve flexible and high-performance writing and reading; fast index-based access to each sample can be achieved through lossless reorganization (i.e., sorting) of the data. In some examples, for signals in the software operation measurement signal that are not in the MDF signal format, the method of the present disclosure may further include an additional format conversion step. That is, convert the non-MDF signal format in the second software operation measurement signal into an MDF format signal for subsequent conversion based on the CAN signal value (corresponding to Figure 2The conversion module 235). Alternatively, the data format not supported by subsequent operations can be converted. For example, the subsequent software running measurement signal MDF may need to be written into MF4, while some signals do not support being written into MF4.

[0039] In some embodiments, the method of the present disclosure may further include: performing format checks on the first software running measurement signal and the first CAN signal, and then extracting. Refer to Figure 2 , format checks on the software running measurement signal and the CAN signal can be respectively performed at blocks 231 and 233 to check for format problems or signal parts with special formats existing in the signals, as well as the integrity of the signals (such as whether there is loss, etc.), so as to achieve the smoothness of the subsequent conversion process.

[0040] In some embodiments, as described above, the simulation method may further include replacing the part corresponding to the third software running measurement signal in the first software running measurement signal with the third software running measurement signal to form a fourth software running measurement signal for the simulation of the perception fusion software. Because the extracted first software running measurement signal (i.e., the second software running measurement signal) only targets a certain or certain parts of the original first software running measurement signal, and the conversion step also only targets the second software running measurement signal. Therefore, after the conversion (such as the Figure 1 step 130 or Figure 2 module 235 as described above), the extracted part of the original first software running measurement signal is replaced with the third software running measurement signal to form a new software running measurement signal (i.e., the fourth software running measurement signal) for subsequent simulation.

[0041] According to another aspect of the present disclosure, a vehicle-mounted system is provided. The vehicle-mounted system includes a processing unit and a storage unit. The storage unit stores instructions that, when executed by the processing unit, implement the method 100 or 200 according to any one of the embodiments herein. Such a vehicle-mounted system can be, for example, a domain controller of a vehicle, or other types of electronic control units ECU, main control unit MCU, etc.

[0042] According to another aspect of the present disclosure, a computer-readable storage medium is provided, in which instructions are stored. When the instructions are executed by a processor, the processor is caused to execute the method 100 or 200 according to any one of the embodiments described above.

[0043] Among them, the computer-readable storage media, memories, storage units, etc. referred to in this disclosure include various types of computer storage media and can be any available media that can be accessed by a general-purpose or special-purpose computer. For example, the computer-readable medium can include RAM, ROM, EPROM, E2PROM, registers, hard disks, removable disks, CD-ROMs or other optical disk memories, magnetic disk memories or other magnetic storage devices, or any other temporary or non-temporary media that can be used to carry or store the desired program code units in the form of instructions or data structures and can be accessed by a general-purpose or special-purpose computer or a general-purpose or special-purpose processor. The above combinations should also be included within the scope of protection of the computer-readable medium. An exemplary storage medium is coupled to the processor so that the processor can read from / write to the storage medium. In an alternative, the storage medium can be integrated into the processor. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In an alternative, the processor and the storage medium can reside in the user terminal as discrete components.

[0044] According to another aspect of the present disclosure, a vehicle is provided, where the vehicle can include the in-vehicle system as described above. The vehicle referred to in this disclosure is intended to represent any suitable vehicle having a drive system, for example, a fuel-powered vehicle, a hybrid vehicle, an electric vehicle, a plug-in hybrid electric vehicle, and so on.

[0045] The above mainly describes the perception fusion software simulation method, in-vehicle system, and computer-readable storage medium of the present disclosure. Although only some specific embodiments of the present disclosure have been described, those of ordinary skill in the art should understand that the present disclosure can be implemented in many other forms without departing from its gist and scope. Therefore, the examples and embodiments shown are regarded as illustrative rather than restrictive, and the present disclosure may cover various adjustments and substitutions without departing from the spirit and scope of the present disclosure as defined by the appended claims.

Claims

1. A perception fusion software simulation method, characterized in that The simulation method includes: Based on the information provided by the CAN database, extracting the first Controller Area Network (CAN) signals for the perception fusion software to obtain second CAN signals; Extracting the first software operation measurement signals for the perception fusion software to obtain second software operation measurement signals; Based on the signal mapping relationship library, converting the second software operation measurement signals according to the second CAN signals to generate third software operation measurement signals; and Based on the first software operation measurement signals and the third software operation measurement signals, simulating the perception fusion software.

2. The simulation method according to claim 1, wherein The conversion further includes: Converting a first signal value of the second software operation measurement signal at a first timestamp to a second signal value, where the second signal value is obtained by converting the signal value of the second CAN signal at a second timestamp based on the mapping relationship information provided by the signal mapping relationship library, and the second timestamp is the earliest timestamp with the shortest time interval from the first timestamp.

3. The simulation method according to claim 1, wherein The conversion further includes aligning the start point of the time interval of the second software operation measurement signal with the start point of the time interval of the second CAN signal.

4. The simulation method according to claim 3, wherein The conversion further includes, after the start point alignment, discarding the parts of the second software operation measurement signal and the second CAN signal within the first time sub-interval at the beginning of the time interval.

5. The simulation method according to claim 1, wherein The simulation further includes parsing the third software operation measurement signals processed by the perception fusion software.

6. The simulation method according to claim 1, characterized in that The extraction further includes: performing the extraction based on corresponding signal filtering rules, where the signal filtering rules are associated with changes to the perception fusion software.

7. The simulation method according to claim 1, wherein The software operation measurement signals include Measurement Data Format (MDF) signals.

8. The simulation method according to claim 7, characterized in that, The method further includes: converting signals in the second software operation measurement signals that are not in the MDF format to the MDF format.

9. The simulation method according to claim 1, wherein The first software operation measurement signals are stored in a software operation measurement signal container.

10. The simulation method according to claim 1, characterized in that The method further includes: performing format checks on the first software operation measurement signals and the first CAN signals.

11. The simulation method according to claim 1, characterized in that, The first CAN signals are associated with changes to the perception fusion software.

12. The simulation method according to claim 1, wherein The method further includes: replacing the part of the first software operation measurement signals corresponding to the third software operation measurement signals with the third software operation measurement signals to form fourth software operation measurement signals for simulating the perception fusion software.

13. A vehicle-mounted system, characterized in that, The vehicle system includes a processing unit and a storage unit, and the storage unit stores instructions that, when executed by the processing unit, implement the simulation method according to any one of claims 1 - 12.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed by a processor, implement the simulation method according to any one of claims 1 - 12.

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