Supporting extended vehicle-mounted multi-camera simulation method and system

Abstract

The application provides a kind of support extended vehicle-mounted multi-channel camera simulation method and system.Method includes: obtaining specified picture or video data, generating the original picture data of each frame, and according to the format of PPI, it is packed into PPI data format, and the ECC and CRC data required for each line are calculated;According to the resolution size of each camera, the required simulation simulation platform memory space is generated;The generated PPI, ECC and CRC data are injected into the memory space;According to the output state of the platform, update the data in the memory space to the next frame data during frame blanking;Using the PPI format module of the platform, according to the configuration of each channel, the data is divided into different Lane according to PPI format, and is output to CSI2 HOST according to PPI format.The application can simulate different types of cameras and their parameters.

Description

Technical Field

[0001] This invention relates to the fields of chip verification and multi-camera simulation technology, specifically to a method and system for simulating extended vehicle-mounted multi-camera systems, and also to a corresponding computer device and computer-readable storage medium. Background Technology

[0002] China's automotive industry is undergoing a profound transformation driven by intelligent technology. Currently, in-vehicle cameras have evolved from basic functions like reversing cameras to core sensors in Advanced Driver Assistance Systems (ADAS). At the same time, multi-camera fusion solutions are becoming mainstream.

[0003] Based on their image sensors and optical characteristics, cameras are categorized into telephoto cameras, wide-angle / short-angle cameras, fisheye cameras, surround-view cameras, and also include some infrared cameras and high-frame-rate cameras. Each camera has different key parameters and specifications, including: resolution, frame rate, dynamic range, viewing angle, low-light performance, and signal-to-noise ratio.

[0004] In some autonomous driving systems, to improve the accuracy of distance measurement, binocular cameras are deployed in the forward-looking system. The distance to objects is calculated by the parallax of the two cameras, thus achieving high-precision distance measurement. Some high-end autonomous driving companies also use tri- or quad-camera combinations for multi-dimensional perception and scene recognition to improve the overall reliability of the system.

[0005] Therefore, in the large-scale development of autonomous driving chips or cockpit chips, it is necessary to conduct sufficient simulations in front of silicon for so many parameters, types and various combinations of cameras, so as to verify whether the chip architecture is reasonable, whether the algorithm and system hardware design such as ISP / GPU / NPU are compatible, whether the performance is optimal, whether the power consumption is optimized, and whether it can adapt to different scenarios.

[0006] However, the data duration in these scenarios is generally in the range of several seconds to several minutes. Traditional simulations can no longer support such a long time and such a large amount of data. Therefore, it is usually necessary to use accelerated simulation platforms, such as Emulation or FPGA platforms, to achieve pre-silicon verification.

[0007] These platforms are typically deployed directly in laboratories due to their weight and power consumption. For example, the Emulation platform usually uses devices such as VSB SpeedBridge to directly use camera input for images and videos by reducing the speed for adaptation. However, because such devices are generally expensive and the interface resources for accessing the system are limited, the number of cameras that can be supported is limited.

[0008] Furthermore, in a laboratory environment, due to limitations such as space and lighting, it is impossible to simulate the real driving environment. Even if the entire device is deployed on a vehicle and tested directly on the road, the processing speed of the device differs significantly from that of a real chip, making it impossible to demonstrate the system's processing and simulation capabilities in a real-world scenario.

[0009] MIPI PHY includes three types of interfaces: DPHY, MPHY, and CPHY. All three use differential signal transmission. DPHY has a clock signal (clk) as a synchronization clock, while CPHY and MPHY do not. DPHY and MPHY are two-wire differential, while CPHY is three-wire differential. The DPHY interface consists of a pair of differential clock lanes and several pairs of differential data lanes. Internally, the DPHY connects to the MIPI controller via a PPI interface. The DPHY data channel includes LP mode and HS mode. In LP mode, the data lane voltage can reach 1.2V; in HS mode, high-speed data transmission is performed with a differential voltage of only a few hundred mV.

[0010] Currently, CMOS chips in cameras integrate PHY, which can package the acquired large amounts of image data into PPI format data, serialize it, and then output it to the SOC chip via a high-speed serial signal through the PHY interface. The DPHY parses the input high-speed serial signal and finally outputs it to the receiving channel in PPI data format, including PPI8, PPI16, and PPI32 formats. However, traditional VSB SpeedBridge cannot support all PPI 8 / 16 / 32 formats. Furthermore, some special camera models may have special settings for PPI frame data format, which traditional VSB SpeedBridge cannot support, thus preventing sufficient pre-silicon verification. Summary of the Invention

[0011] To address the aforementioned shortcomings in the prior art, this invention provides a method and system for simulating extended vehicle-mounted multi-channel cameras, along with a corresponding computer device and computer-readable storage medium.

[0012] According to a first aspect of the present invention, a method for simulating extended vehicle-mounted multi-camera systems is provided, comprising: Based on the simulation requirements and the number of cameras to be configured, instantiate a corresponding number of PPI Driver modules, and according to the parameter requirements of different simulated cameras, obtain the specified image or video data to generate the raw image data for each frame. Each generated raw image data is packaged and processed into the corresponding PPI data format according to the PPI format, and the required ECC data and CRC data for each row are calculated. Based on the resolution of each camera, generate the required simulation platform memory space; The generated PPI data, ECC data, and CRC data are injected into the generated simulation platform memory space; based on the output status in the simulation platform, the data in the memory space is updated to the next frame data during frame blanking. Using the PPI format module in the simulation platform, the data is divided into different lanes according to the configuration of each channel and output to the CSI2 HOST in PPI format.

[0013] According to a second aspect of the present invention, a vehicle-mounted multi-camera simulation system based on multi-channel expansion is provided, comprising: The data preprocessing module is used to instantiate a corresponding number of PPI Driver modules according to the simulation requirements and the number of cameras to be configured, and to obtain the specified image or video data according to the parameter requirements of the different cameras being simulated, and generate the raw image data of each frame. The data automation processing module is used to package each generated raw image data into the corresponding PPI data format according to the PPI format, and calculate the required ECC data and CRC data for each row; inject the generated PPI data, ECC data and CRC data into the generated simulation platform memory space; and update the data in the memory space to the next frame data during frame blanking according to the output status in the simulation platform. The memory space calculation module is used to generate the required simulation platform memory space based on the resolution of each camera. The data output module utilizes the PPI format module in the simulation platform to divide the data into different lanes according to the PPI format based on the configuration of each channel, and outputs the data to the CSI2 HOST in the PPI format.

[0014] According to a third aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it can be used to perform the method described in any one of the above inventions, or to run the system described in the above inventions.

[0015] According to a fourth aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, can be used to perform the method described in any one of the above-described inventions, or to run the system described in the above-described inventions.

[0016] By adopting the above technical solution, the present invention has at least one of the following beneficial effects compared with the prior art: In the development of smart cockpit SOC chips and autonomous driving SOC chips on Emulation or Simulation platforms, it is difficult to complete the simulation of multiple cameras with the same number and type as the final product. The present invention provides an expandable vehicle multi-camera simulation method and system that can effectively simplify the overall simulation process, flexibly and conveniently simulate multiple camera data, and expand according to needs.

[0017] The present invention provides an extended vehicle-mounted multi-camera simulation method and system that can simulate different types of cameras and set different formats for the cameras.

[0018] The present invention provides an extended vehicle-mounted multi-camera simulation method and system that is easy to use and supports automatic conversion and automatic data injection of input image and video data according to format and parameters.

[0019] The present invention provides an extended vehicle-mounted multi-camera simulation method and system that supports importing video data collected from roads into the device, and in an accelerated simulation environment, fully and accurately reproduces the real road environment.

[0020] The present invention provides an extended vehicle multi-camera simulation method and system that simulates the processing status of the chip's ISP, GPU, NPU and other parts with high precision at each clock edge, effectively ensuring sufficient verification in the chip pre-silicon stage.

[0021] The present invention provides an extended vehicle-mounted multi-channel camera simulation method and system that can combine post-chip acquisition data to perform high-precision on-site reproduction on an Emulation or Simulation platform, and compare it with the actual chip results, facilitating fault analysis, performance optimization, and power consumption optimization.

[0022] The present invention provides an extended vehicle multi-camera simulation method and system that completely bypasses VSBSpeedbridge, thus facilitating the implementation of multi-camera systems. By exploring how to reproduce real driving scenarios through the simulation of multiple cameras, the functionality and performance of each component are verified, effectively ensuring the optimal architecture of the chip.

[0023] The present invention provides an extended vehicle-mounted multi-camera simulation method and system, which is implemented based on the Emulation or Simulation platform. It completely bypasses the DPHY interface and directly converts the simulated or acquired image and video data into a universal PPI interface format, outputting it to the CSI2 HOST module. This facilitates the simulation of multiple cameras, supports various types, and allows for flexible parameter configuration. Attached Figure Description

[0024] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart illustrating the workflow of a preferred embodiment of the present invention for a method to simulate an extended vehicle-mounted multi-camera system.

[0025] Figure 2 This is a schematic diagram of data generation in a preferred embodiment of the present invention.

[0026] Figure 3 This is a schematic diagram illustrating the CRC generation and packaging process of data in a preferred embodiment of the present invention.

[0027] Figure 4 This is a schematic diagram illustrating the operation of automatically segmenting data into PPI format corresponding to the number of lanes configured for each channel and outputting it to the CSI2 host according to the PPI format in a preferred embodiment of the present invention.

[0028] Figure 5 This is a schematic diagram illustrating the physical world from optics to CMOS photosensitive image processing to PPI data transmission to subsequent processing circuits. Detailed Implementation

[0029] The embodiments of the present invention are described in detail below: These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

[0030] In the development of large-scale autonomous driving chips or cockpit chips, it is necessary to perform thorough pre-silicon simulations for the numerous parameters, types, and combinations of cameras to verify the rationality of the chip architecture. In these verification scenarios, accelerated simulation platforms, such as Emulation or FPGA platforms, are typically used for pre-silicon verification. Emulation platforms generally use devices like VSB SpeedBridges to directly use camera input images and videos by reducing speed adaptation. However, because these devices are generally expensive and have limited interface resources for system access, the number of cameras they can support is limited. Traditional VSB SpeedBridges also cannot support all PPI 8 / 16 / 32 formats, and some special camera models may have special settings for PPI frame data formats that traditional VSB SpeedBridges cannot support, thus preventing sufficient pre-silicon verification.

[0031] To address the aforementioned issues, one embodiment of the present invention provides an extended vehicle-mounted multi-camera simulation method. This method simulates PPI data format on the Emulation platform according to standard requirements based on the parameters of the simulated cameras.

[0032] Simultaneously, by running an automated processing program on the server, image or video data, or multi-channel acquired data, is automatically imported. Based on the output status of each frame of Emulation, pixel data for each frame is injected into the PPI data frame. In this way, data from cameras with different image sensors and optical characteristics in the field is captured. After execution, the automated processing program automatically imports this data into the corresponding video and image cache space of the module. This can simulate different image sensors and optical characteristics, such as telephoto cameras, wide-angle short-focus cameras, fisheye cameras, surround-view cameras, and even some infrared cameras and high frame rate cameras. Furthermore, by capturing data from different cameras and automatically processing, importing, and caching it, and by using the PPI format to be compatible with the parameters of different cameras, the different key parameters and indicators of each camera can also be simulated.

[0033] Specifically, the extended vehicle-mounted multi-camera simulation method provided in this embodiment may include: S1, based on the simulation requirements and the number of cameras to be configured, instantiates a corresponding number of PPI Driver modules, and according to the parameter requirements of the different cameras being simulated, acquires the specified image or video data and generates the raw image data for each frame. S2 automatically packages each generated raw image data into the corresponding PPI data format according to the PPI format, and automatically calculates the required ECC data and CRC data for each line. S3 generates the required simulation platform (e.g., Emulation platform or Simulation platform) memory space based on the resolution of each camera. S4. The generated PPI data, ECC data, and CRC data are injected into the generated simulation platform memory space. Based on the output status in the simulation platform, the data in the memory space is updated to the next frame data during frame blanking. S5 utilizes the PPI format module in the simulation platform to divide the data into different lanes according to the PPI format based on the configuration of each channel, and outputs the data to CSI2 HOST according to the PPI format.

[0034] In some preferred embodiments, the specified image or video data can be in image data formats such as RAW12, RAW14, RAW16, RAW20, YUV422_8 / 10, and RGB888.

[0035] In some preferred embodiments, S2 above automatically packages each generated original image data into the corresponding PPI data format according to the PPI format, and automatically calculates the required ECC data and CRC data for each row. It may further include: An overall video frame format includes: field blanking, line blanking, valid data area, and embedded data, which correspond to different lines of the PPI data frame, namely: Frame Start, Frame End, Line Start, and Line End. The state machine built using RTL automatically packages each generated raw image data into the corresponding PPI data format and calculates the required ECC and CRC data for each row.

[0036] In some preferred embodiments, the above-described S4, which injects the generated PPI data, ECC data, and CRC data into the generated Emulation platform memory space, may further include: Based on the direct import function of the Simulation or Emulation platform for memory-stored data, the generated PPI data, ECC data, and CRC data are injected into the generated simulation platform memory space.

[0037] In some preferred embodiments, the above method may further include: By recording camera data with different photosensitive chips and optical characteristics in the field and importing it into the corresponding video and image cache space of the module, different photosensitive chips and optical characteristics are simulated.

[0038] In some preferred embodiments, the above method may further include: By recording data from different cameras and importing it into the corresponding video and image cache space of the module, and by using the parameters of different cameras that are compatible with PPI format, the different key parameters and indicators of each camera are simulated.

[0039] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings.

[0040] like Figure 1 The diagram shown is a flowchart of a preferred embodiment of a method for simulating extended vehicle-mounted multi-camera systems. It includes: (1) The camera images or videos simulated by the algorithm system, or the collected and stored, are stored on the storage medium of the running server.

[0041] (2) The server runs an automated processing system to convert the format according to the number and parameters of the cameras and automatically inject it into the specified PPI driver.

[0042] (3) On Emulation / Simulation, instantiate multiple PPI driver modules according to the system requirements.

[0043] (4) The output of the PPI driver bypasses the DPHY circuit and is directly connected to the PPI processing circuit CSI2HOST module.

[0044] (5) After the SOC chip starts Emulation, it can analyze the processing status of the ISP, GPU and NPU on the simulated multi-camera output data.

[0045] like Figure 2 The diagram shown illustrates the data generation process in a preferred embodiment. This includes: (1) As required, the image or video acquisition program retrieves the specified image or video data from the server storage medium according to the number of cameras configured, and generates the original image data for each frame.

[0046] (2) An automated processing program automatically packages each raw image data pixel into PPI data format according to the PPI format, and automatically calculates the required ECC data and CRC data for each row. It supports image data formats such as RAW12, RAW14, RAW16, RAW20, YUV422_8 / 10, and RGB888. like Figure 3 The diagram shown illustrates the CRC generation and packaging process for data in a preferred embodiment. This includes: (1) The Emulation control software running on the server will automatically generate the required memory space according to the resolution of each camera.

[0047] (2) The automated processing program will inject the generated PPI DATA, ECC, and CRC data into the already generated Emulation platform memory space. The automated processing program can update the data in the memory space to the next frame data during frame blanking based on the output status in Emulation.

[0048] like Figure 4 The diagram illustrates a preferred embodiment where, based on the number of lanes configured for each channel, data is automatically segmented into PPI format corresponding to the number of lanes and output to the CSI2 host. This includes: The PPI format module in the Emulation platform automatically segments the data into different lanes according to the PPI format based on the configuration of each channel, and automatically outputs the data to the CSI2 host module according to the PPI format according to the user's steps.

[0049] like Figure 5 The diagram shown illustrates the physical world from optics to CMOS photosensitive sensor to processing into PPI data and sending it to subsequent processing circuits.

[0050] Based on the same inventive concept, one embodiment of the present invention also provides an extended vehicle-mounted multi-camera simulation system.

[0051] Specifically, the extended vehicle-mounted multi-camera simulation system provided in this embodiment may include: The data preprocessing module is used to instantiate a corresponding number of PPI Driver modules according to the simulation requirements and the number of cameras to be configured, and to acquire the specified image or video data according to the parameter requirements of the different cameras being simulated, and generate the raw image data of each frame. The automated data processing module is used to package each generated raw image data into the corresponding PPI data format according to the PPI format, and calculate the required ECC data and CRC data for each row; inject the generated PPI data, ECC data, and CRC data into the memory space of the generated Emulation or Simulation platform; and update the data in the memory space to the next frame data during frame blanking according to the output status in the Emulation or Simulation platform. The memory space calculation module is used to generate the required Emulation or Simulation platform memory space based on the resolution of each camera. The data output module utilizes the PPI format module in the Emulation or Simulation platform to divide the data into different lanes according to the PPI format based on the configuration of each channel, and outputs the data to CSI2HOST in the PPI format.

[0052] In some preferred embodiments, the data preprocessing module, according to requirements and the number of cameras configured, uses an image or video acquisition program to obtain specified image or video data from the server storage medium and generates raw image data for each frame.

[0053] In some preferred embodiments, the aforementioned automated data processing module utilizes a first automated processing unit to automatically package each raw image data pixel into a PPI data format, and automatically calculates the required ECC and CRC data for each row. Supported image data formats include RAW12, RAW14, RAW16, RAW20, YUV422_8 / 10, and RGB888. A second automated processing unit injects the generated PPI DATA, ECC data, and CRC data into the already generated Emulation or Simulation platform memory space. This second automated processing unit can update the data in the memory space to the next frame's data during frame blanking based on the output state in the Emulation.

[0054] In some preferred embodiments, the memory space calculation module automatically generates the required memory space based on the resolution of each camera using the Emulation or Simulation platform control software running on the server.

[0055] In some preferred embodiments, the data output module, based on the PPI format module in the Emulation or Simulation platform, automatically divides the data into different lanes according to the PPI format according to the configuration of each channel, and automatically outputs the data to the CSI2 HOST module according to the PPI format.

[0056] In the above embodiments of the present invention, simulated camera images or videos, or captured images or videos, are stored on the storage medium of the running server; the server runs an automated processing program to convert the format according to the number and parameters of the cameras and automatically inject it into the specified PPI driver; on the Emulation or Simulation platform, multiple PPI driver modules are instantiated according to the required number of cameras; the output of the PPI driver bypasses the DPHY circuit and is directly connected to the PPI processing circuit CSI2 HOST module; after the SOC chip starts on the Emulation or Simulation platform, it can analyze the processing status of the ISP, GPU, and NPU on the simulated multi-channel camera output data.

[0057] It should be noted that the steps in the method provided by the present invention can be implemented using corresponding modules, devices, units, etc. in the system. Those skilled in the art can refer to the technical solution of the method to realize the composition of the system. That is, the embodiments in the method can be understood as preferred examples for building the system, and will not be elaborated here.

[0058] An embodiment of the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, can be used to execute any of the methods described above in the present invention, or to run any of the systems described above in the present invention.

[0059] Optionally, the memory is used to store programs; the memory may include volatile memory, such as random-access memory (RAM), such as static random-access memory (SRAM), double data rate synchronous dynamic random-access memory (DDR SDRAM), etc.; the memory may also include non-volatile memory, such as flash memory. The memory is used to store computer programs (such as application programs and functional modules that implement the above methods), computer instructions, etc., and the aforementioned computer programs and computer instructions can be partitioned and stored in one or more memories. Furthermore, the aforementioned computer programs, computer instructions, data, etc., can be accessed by the processor.

[0060] A processor is used to execute computer programs stored in memory to implement the various steps of the methods or various modules of the systems involved in the above embodiments. For details, please refer to the relevant descriptions in the preceding method and system embodiments.

[0061] The processor and memory can be separate structures or integrated structures. When the processor and memory are separate structures, they can be coupled together via a bus.

[0062] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can be used to perform any of the methods described above, or to run any of the systems described above.

[0063] Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of computer programs from one place to another. Storage media can be any available medium accessible to a general-purpose or special-purpose computer. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Alternatively, the ASIC can reside in a user device. Of course, the processor and storage medium can also exist as discrete components in a communication device.

[0064] The extended vehicle-mounted multi-camera simulation method and system provided in the above embodiments of the present invention can flexibly and conveniently simulate multi-camera data on a Simulation or Emulation platform using C or RTL languages ​​according to actual product needs, and can support image input and video input.

[0065] The vehicle-mounted multi-channel camera simulation method and system provided in the above embodiments of the present invention, based on the Simulation platform or Emulation platform's direct import function of memory-stored data, can support the import of data recorded by actual cameras, thereby facilitating the simulation of different types of cameras and their parameters, such as telephoto, short-focus, and fisheye cameras.

[0066] The extended vehicle-mounted multi-camera simulation method and system provided in the above embodiments of the present invention, through a state machine built using RTL, supports the automatic generation of required PPI interface data and ECC verification data from input image and video data according to format and parameters. Simultaneously, it can directly import video data collected from roads into the device, completely and accurately reproducing the real road environment.

[0067] The extended vehicle multi-camera simulation method and system provided in the above embodiments of the present invention utilize the characteristics of the Emulation platform or Simulation platform to perform simulation strictly according to the clock progress. It can realistically simulate the processing status of the chip's ISP, GPU, NPU and other parts with high precision at each clock edge. By analyzing and balancing the processing flow, software algorithm and chip architecture, the chip design can be optimized to the greatest extent.

[0068] Any matters not covered in the above embodiments of the present invention are well-known in the art.

[0069] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A method for simulating extended vehicle-mounted multi-channel cameras, characterized in that, include: Based on the simulation requirements and the number of cameras to be configured, instantiate a corresponding number of PPI Driver modules, and according to the parameter requirements of different simulated cameras, acquire the specified image or video data and generate the raw image data for each frame. Each generated raw image data is packaged and processed into the corresponding PPI data format according to the PPI format, and the required ECC data and CRC data for each row are calculated. Based on the resolution of each camera, generate the required simulation platform memory space; The generated PPI data, ECC data, and CRC data are injected into the memory space of the generated simulation platform. Based on the output status in the simulation platform, during frame blanking, the data in the memory space is updated to the next frame data. Using the PPI format module in the simulation platform, the data is divided into different lanes according to the configuration of each channel and output to the CSI2 HOST in PPI format.

2. The method for simulating extended vehicle-mounted multi-channel cameras according to claim 1, characterized in that, The process involves packaging each generated raw image data into its corresponding PPI data format, and calculating the required ECC and CRC data for each row, including: A complete video frame format includes: field blanking, line blanking, valid data area and embedded data, which correspond to different lines of the PPI data frame: Frame Start, Frame End, Line Start and Line End; The state machine built using RTL automatically packages each generated raw image data into the corresponding PPI data format and calculates the required ECC and CRC data for each row.

3. The vehicle-mounted multi-channel camera simulation method based on multi-channel expansion according to claim 1, characterized in that, The simulation platform adopts either the Simulation platform or the Emulation platform.

4. The method for simulating extended vehicle-mounted multi-channel cameras according to claim 1, characterized in that, The step of injecting the generated PPI data, ECC data, and CRC data into the generated simulation platform memory space includes: Based on the direct import function of the Simulation or Emulation platform for memory-stored data, the generated PPI data, ECC data, and CRC data are injected into the generated simulation platform memory space.

5. The vehicle-mounted multi-channel camera simulation method supporting expansion according to any one of claims 1-4, characterized in that, Also includes: By recording camera data with different photosensitive chips and optical characteristics in the field and importing it into the corresponding video and image cache space of the module, different photosensitive chips and optical characteristics are simulated.

6. The vehicle-mounted multi-camera simulation method supporting expansion according to any one of claims 1-4, characterized in that, Also includes: By recording data from different cameras and importing it into the corresponding video and image cache space of the module, and by using the parameters of different cameras that are compatible with PPI format, the different key parameters and indicators of each camera are simulated.

7. A vehicle-mounted multi-channel camera simulation system based on multi-channel expansion, characterized in that, include: The data preprocessing module is used to instantiate a corresponding number of PPI Driver modules according to the simulation requirements and the number of cameras to be configured, and to acquire the specified image or video data according to the parameter requirements of the different cameras being simulated, and generate the raw image data of each frame. The data automation processing module is used to package each generated raw image data into the corresponding PPI data format according to the PPI format, and calculate the required ECC data and CRC data for each row. The generated PPI data, ECC data, and CRC data are injected into the memory space of the generated simulation platform. Based on the output status in the simulation platform, during frame blanking, the data in the memory space is updated to the next frame data. The memory space calculation module is used to generate the required simulation platform memory space based on the resolution of each camera. The data output module utilizes the PPI format module in the simulation platform to divide the data into different lanes according to the PPI format based on the configuration of each channel, and outputs the data to the CSI2 HOST in the PPI format.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it can be used to perform the method of any one of claims 1-6, or to run the system of claim 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program can be used to perform the method of any one of claims 1-6, or to run the system of claim 7.

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