Intelligent parking simulation system, method and host computer

Abstract

The application relates to the technical field of intelligent driving, in particular to an intelligent parking simulation system and method and an upper computer, wherein the lower computer comprises a vehicle dynamics model, a driving assistance system VTD and a software-defined softECU, the vehicle dynamics model is used for controlling the movement of a vehicle in a virtual road scene simulated by the VTD according to a parking control signal, the softECU generates the parking control signal according to environment perception information and whole-vehicle signals simulated by the VTD; a real controller board is used for perceiving the environment perception information according to the virtual road scene simulated by the VTD; the upper computer performs simulation configuration on the lower computer based on a simulation configuration function, manages the simulation test process of the intelligent parking function of the lower computer based on a test management function, collects simulation test data of the lower computer based on a data collection function, and generates a simulation test result of the intelligent parking function. Therefore, the problems of high test risk and cost, long cycle, lag and waste caused by HIL simulation customization and insufficient environment perception capability of the MIL are solved.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to an intelligent parking simulation system, method and host computer. Background Technology

[0002] Automated parking technology offers convenience and ease to drivers in large cities, addressing challenges such as parking space scarcity, limited space, and varying driver skill levels. However, because automated parking technology is widely applicable to diverse vehicle models, built upon a complex technical architecture, and needs to handle varied parking scenarios, its development process requires rigorous testing and verification to ensure efficiency and safety in real-world applications.

[0003] Currently, testing of automated parking systems largely relies on real-vehicle testing. While this method can intuitively demonstrate a vehicle's performance in a real environment, it comes with high costs, collision risks, and lengthy testing cycles. Although HIL (Hardware-in-the-Loop) simulation testing systems can compensate for this, interface customization leads to delays and resource waste. MIL (Model-in-the-Loop) testing is cost-effective and efficient, but it lacks a real sensor environment, making it difficult to comprehensively evaluate the system's adaptability and reliability. Summary of the Invention

[0004] This application provides an intelligent parking simulation system, method, and host computer to solve problems such as high testing risks and costs, long cycles, delays and waste caused by HIL simulation customization, and insufficient awareness of the MIL testing environment in the prior art.

[0005] The first aspect of this application provides an intelligent parking simulation system, comprising: a lower-level computer, wherein the lower-level computer includes a vehicle dynamics model, a driver assistance system (VTD, Virtual Test Drive, simulation toolchain), and a software-defined electronic control unit (softECU). The VTD is used to simulate road scenarios, the vehicle dynamics model is used to control the movement of the vehicle in the virtual road scenario simulated by the VTD according to parking control signals, and the softECU generates parking control signals according to environmental perception information and vehicle signals simulated by the VTD; a real controller board, used to perceive environmental perception information according to the virtual road scenario simulated by the VTD; and a higher-level computer, wherein the higher-level computer has simulation configuration functions, test management functions, and data acquisition functions. Based on the simulation configuration function, the higher-level computer performs simulation configuration on the lower-level computer; based on the test management function, the higher-level computer manages the simulation test process of the lower-level computer for intelligent parking functions; based on the data acquisition function, the higher-level computer collects simulation test data of the lower-level computer; and the higher-level computer also generates simulation test results of intelligent parking functions based on the simulation test data.

[0006] Optionally, the softECU includes a parking space recognition module, a parking planning and control module, and a vehicle control signal conversion module. The parking space recognition module recognizes parking space information in the environmental perception information. The parking planning and control module generates parking planning instructions based on the parking space information and the vehicle signals. The vehicle control signal conversion module converts the parking planning instructions into parking control signals.

[0007] Optionally, the VTD generates a surround view signal from the virtual road scene, renders the surround view signal through a visual rendering station, and then inputs it into the real controller.

[0008] Optionally, the real controller board includes a video injection module and an environment perception fusion control module. The video injection module is used to input the surround view signal rendered by the scene rendering station into the environment perception fusion control module, and the environment perception fusion control module senses the surround view signal to obtain environment perception information.

[0009] Optionally, the environmental perception information includes at least one of parking space information, vehicle information, and pedestrian information.

[0010] Optionally, the real controller board may further include a power management module for supplying power to the real controller board.

[0011] Optionally, the VTD is also used to simulate an ultrasonic radar system, and the simulated ultrasonic radar system outputs an ultrasonic radar simulation signal.

[0012] Optionally, the vehicle signals include vehicle position and orientation, tire contact points, and ultrasonic radar simulation signals.

[0013] A second aspect of this application provides an intelligent parking simulation method for the intelligent parking simulation system, comprising the following steps: obtaining test requirements for intelligent parking functions; configuring a lower-level machine for simulation based on the test requirements, and controlling the lower-level machine in conjunction with a real controller board to execute a simulation test process for the intelligent parking function after configuration; and generating simulation test results for the intelligent parking function based on the simulation test data from the lower-level machine.

[0014] A third aspect of this application provides a host computer, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the intelligent parking simulation method as described in the above embodiments.

[0015] Therefore, this application has the following beneficial effects:

[0016] This application's embodiments achieve comprehensive virtual testing of intelligent parking functions by integrating vehicle dynamics models, VTD (Vehicle Dynamics Assistance) systems, and softECUs into the lower-level computer. This effectively avoids the safety and economic risks associated with actual road testing. Furthermore, the rapid iteration capabilities of the virtual environment shorten the testing cycle and accelerate the testing process. The flexibility of the softECU further eliminates the lag and resource waste associated with HIL (High-Intensity Logic) simulation customization, while the introduction of real controller boards and VTD enhances the simulation accuracy of the MIL (Multi-Level Logic) testing environment in terms of real vehicle environmental perception information. Therefore, this solves the technical problems in existing technologies, such as excessively high testing risks and costs, long testing cycles, lag and waste caused by HIL simulation customization, and insufficient environmental perception capabilities in MIL.

[0017] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0018] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0019] Figure 1 Here is an example diagram of an intelligent parking simulation system according to an embodiment of this application;

[0020] Figure 2 This is a schematic diagram illustrating the simulation principle of intelligent parking according to an embodiment of this application;

[0021] Figure 3 Here is an example diagram of an intelligent parking simulation system according to an embodiment of this application;

[0022] Figure 4 This is a flowchart of the intelligent parking simulation method provided according to the embodiments of this application;

[0023] Figure 5 This is a flowchart of an intelligent parking simulation method provided according to an embodiment of this application;

[0024] Figure 6 This is a schematic diagram of the structure of the host computer according to an embodiment of this application. Detailed Implementation

[0025] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0026] The intelligent parking simulation system, method, and host computer of this application are described below with reference to the accompanying drawings. Addressing the problems mentioned in the background art regarding testing of automatic parking during the prototype development stage, this application provides an intelligent parking simulation system. In this system, by integrating a vehicle dynamics model, a VTD driving assistance system, and a softECU into the lower-level computer, comprehensive virtual testing of the intelligent parking function is achieved. This effectively avoids the safety and economic losses associated with actual road testing. Simultaneously, the rapid iteration capability of the virtual environment shortens the testing cycle and accelerates the testing process. Furthermore, the flexibility of the softECU further eliminates the lag and resource waste associated with HIL simulation customization, while the introduction of real controller boards and VTD enhances the simulation accuracy of the MIL testing environment for actual vehicle environmental perception information. Therefore, this solves the problems of excessively high testing risks and costs, long testing cycles, lag and waste caused by HIL simulation customization, and insufficient environmental perception capabilities in the prior art.

[0027] Specifically, Figure 1 This is a block diagram of an example of an intelligent parking simulation system provided in an embodiment of this application.

[0028] like Figure 1 As shown, the intelligent parking simulation system 10 includes: a lower-level computer 100, a real controller board 200, and a higher-level computer 300.

[0029] The lower-level computer 100 includes a vehicle dynamics model, a vehicle-to-everything (VTD) driver assistance system, and a software-defined electronic control unit (softECU). The VTD is used to simulate road scenarios, the vehicle dynamics model is used to control the vehicle's movement in the virtual road scenario simulated by the VTD according to parking control signals, and the softECU generates parking control signals based on environmental perception information and vehicle signals simulated by the VTD. The real controller board 200 is used to perceive environmental perception information based on the virtual road scenario simulated by the VTD. The upper-level computer 300 has simulation configuration, test management, and data acquisition functions. Based on the simulation configuration function, it performs simulation configuration on the lower-level computer 100. Based on the test management function, it manages the simulation test process of the lower-level computer 100 for intelligent parking function. Based on the data acquisition function, it collects the simulation test data of the lower-level computer 100. The upper-level computer 300 also generates simulation test results of intelligent parking function based on the simulation test data.

[0030] The softECU may include a parking space recognition module, a parking planning and control module, and a vehicle control signal conversion module; the real controller board 200 may include a video injection module and an environmental perception fusion control module; and the vehicle signals may include vehicle position and posture, tire contact points, and ultrasonic radar simulation signals.

[0031] Simulation configuration functions can include configuring vehicle dynamics model parameters, configuring simulation platform software interaction, communication and interface, etc.; test management can include test case design, test sequence generation, test data monitoring, test report generation, etc.

[0032] It is understood that this application embodiment, by integrating the vehicle dynamics model, VTD driving assistance system, and softECU into the lower-level computer 100, achieves comprehensive virtual testing of the intelligent parking function, effectively avoiding the safety and economic loss risks of actual road testing. Simultaneously, leveraging the rapid iteration capability of the virtual environment, it shortens the testing cycle and accelerates the testing process. The flexibility of the softECU further eliminates the lag and resource waste associated with HIL simulation customization, while the introduction of the real controller board 200 and VTD enhances the simulation accuracy of the MIL testing environment for actual vehicle environmental perception information.

[0033] Specifically, such as Figure 2 As shown, VTD is used to simulate road scenarios and can realize the interaction of information such as vehicle dynamics, road environment, sensors, parking control, and vehicle status. The fine control commands generated by the automatic parking control module need to be accurately converted by the vehicle control signal conversion module in the softECU to adapt to the signal format required by the vehicle dynamics system, such as steering wheel angle commands, longitudinal acceleration commands, and braking torque distribution.

[0034] During simulation, the vehicle dynamics module receives converted lateral and longitudinal control signals, driving the vehicle to precisely execute parking trajectories within the virtual road scene constructed by VTD. Simultaneously, utilizing VTD's unique shared memory mechanism, the vehicle model's real-time position and attitude information within the scene are efficiently synchronized, ensuring high consistency and real-time performance during the simulation. This mechanism not only improves simulation accuracy but also enhances the system's ability to handle complex parking scenarios.

[0035] In this embodiment, the space parking space recognition module identifies space parking space information in the environmental perception information, the parking planning and control module generates parking planning instructions based on the space parking space information and vehicle signals, and the vehicle control signal conversion module is used to convert the parking planning instructions into parking control signals.

[0036] Among them, environmental perception information includes at least one of parking space information, vehicle information, and pedestrian information.

[0037] It is understood that the embodiments of this application achieve efficient, intelligent, and safe parking by integrating spatial parking space recognition, parking planning and control, and vehicle control signal conversion modules. This system can automatically identify available parking spaces, plan the optimal parking path based on vehicle status and parking space information, and convert the planning instructions into control signals that directly act on the vehicle, thereby achieving intelligent and automated parking operations.

[0038] Specifically, such as Figure 2 As shown in the embodiment of this application, a comprehensive simulation test link is constructed. This link integrates a road scene and virtual sensor module, an environmental perception fusion module, a parking planning and control module, and a vehicle dynamics model, forming a closed-loop system. This system uses video injection technology to achieve 360-degree surround view functionality, enabling rich information in the virtual scene to be captured and transmitted to the perception fusion controller in real time and accurately.

[0039] The automatic parking planning and control module is implemented using a highly integrated algorithm model (MIL), which not only ensures the accuracy and efficiency of the parking algorithm but also endows the system with extremely high flexibility. The software interface design fully considers configurability, breaking free from the limitations of traditional vehicle platform interfaces, allowing the testing environment to easily adapt to the needs of different vehicle models and configurations.

[0040] The embodiments of this application not only achieve a high degree of realism in environmental perception, that is, the virtual scene can simulate a complex and ever-changing environment close to the real world, thereby effectively verifying the performance of the perception system; but also ensure the sufficiency and flexibility of parking algorithm testing, so that the algorithm can be fully verified under various extreme and edge conditions, providing solid data support for the optimization and improvement of the algorithm.

[0041] It should be noted that 360-degree surround view uses video injection technology to collect environmental information in VTD scenarios, identify lanes, obstacles, parking spaces, etc., and ultrasonic radar outputs simulated ground truth information, such as obstacle distance and parking space information.

[0042] In this embodiment, VTD generates a surround view signal from the virtual road scene, renders the surround view signal through a visual rendering station, and then inputs it into the real controller.

[0043] It is understood that in this embodiment, VTD generates virtual road scenes and surround-view signals, and uses a visual rendering station for image rendering. The processed image is then input into a real controller for testing. This simulates various complex situations in real road environments, providing rich data input for the system's perception, decision-making, and control algorithms. Through VTD simulation testing, testing efficiency can be significantly improved, testing costs reduced, and testing safety enhanced.

[0044] Specifically, the real controller integrates 360-degree surround view video and CAN bus parking space information. It processes the video signal through filtering and recognition algorithms, and fuses the output information on parking spaces, obstacles, and lane lines. It adopts a modular design to decouple environmental perception and parking control algorithms, and achieves efficient information interaction through a standardized platform interface to support intelligent parking decisions.

[0045] It should be noted that the platform content includes communication between modules, hardware board interfaces, SoftECU models, simulation scenario libraries, and test case libraries, etc.

[0046] In this embodiment, the video injection module is used to input the surround view signal rendered by the visual rendering station into the environment perception fusion control module, and the environment perception fusion control module perceives the surround view signal to obtain environment perception information.

[0047] It is understood that the embodiments of this application input the surround-view signal generated by the visual rendering map station into the environmental perception fusion control module through the video injection module, which significantly improves the environmental perception capability of the autonomous driving system and enhances the system safety and overall performance.

[0048] Specifically, the scene simulation software constructs a virtual environment and renders a video stream. The video injection module inputs the surround-view signal into the environment perception fusion control module, which combines sensor information such as ultrasonic radar and vehicle status such as vehicle speed to comprehensively analyze and obtain environmental perception information.

[0049] In this embodiment, the real controller board 200 further includes a power management module for supplying power to the real controller board 200.

[0050] In this embodiment, VTD is also used to simulate an ultrasonic radar system, and the simulated ultrasonic radar system outputs an ultrasonic radar simulation signal.

[0051] The ultrasonic radar system can include four short-range ultrasonic radars pointing forward and backward, and four long-range ultrasonic radars on each side.

[0052] It is understood that in this embodiment of the application, VTD outputs high-precision simulation signals by simulating an ultrasonic radar system. The ultrasonic radar simulation signals are filtered in the ultrasonic parking space detection softECU and combined with information such as vehicle speed to accurately calculate the spatial parking space information. It is mainly used for the detection of nearby obstacles and supports functions such as collision avoidance warning and side parking space search, thereby improving the testing efficiency and safety of the autonomous driving system, reducing costs, and ensuring the authenticity and reliability of the simulation results.

[0053] Specifically, during driving, ultrasonic radar signals identify the spatial distance between vehicles facing lateral obstacles, as well as vehicle speed and other information. A specific algorithm is then used to identify parking spaces, and the result is output. The vehicle control signals output by the parking control algorithm also require corresponding conversion to ensure accurate vehicle control.

[0054] The intelligent parking simulation system proposed in this application integrates a vehicle dynamics model, a VTD (Vehicle Dynamics Assistance) system, and a softECU in the lower-level computer, achieving comprehensive virtual testing of intelligent parking functions. This effectively avoids the safety and economic risks associated with actual road testing. Furthermore, the rapid iteration capability of the virtual environment shortens the testing cycle and accelerates the testing process. The flexibility of the softECU further eliminates the lag and resource waste associated with HIL (High-Intensity Logic) simulation customization, while the introduction of real controller boards and VTD enhances the simulation accuracy of the MIL (Multi-Intensity Logic) testing environment in terms of actual vehicle environmental perception information. Therefore, this system solves the problems of excessively high testing risks and costs, long testing cycles, lag and waste caused by HIL simulation customization, and insufficient environmental perception capabilities in existing technologies.

[0055] The following will combine Figure 3 The intelligent parking simulation system is described in detail. This system includes a lower-level computer, a real controller board, and a higher-level computer, as detailed below:

[0056] The host computer 300 runs on a Windows system and undertakes multiple tasks, including simulation model configuration and loading, test process design and control, comprehensive data acquisition, and automatic test report generation. Its intuitive interface and powerful management functions enable users to easily complete complex simulation settings and test management.

[0057] The lower-level machine 100, running on a Linux system environment, integrates the road scene simulation software VTD, capable of simulating signals from key sensors such as ultrasonic radar, ensuring the realism and diversity of the simulation environment. By loading key information such as the softECU, vehicle dynamics model, road scene, and sensors, the lower-level machine 100 runs in real-time machine interaction, achieving real-time communication with the physical controller and ensuring accurate transmission and processing of simulation data. A CAN board acts as a connecting bridge, enabling seamless integration between the lower-level machine 100 and the physical controller.

[0058] The visual rendering station renders the virtual scene constructed by VTD scene simulation software with high fidelity, outputting realistic video streams through a high-performance graphics card. These video streams are then passed to the video injection module, providing rich visual data input to the environmental perception fusion controller.

[0059] The real controller board 200 may include an environmental perception fusion controller, a video injection board, a power module, etc. The video injection board receives the video stream from the visual rendering station and converts it to output analog signals from the camera to the perception fusion controller; the power module is responsible for supplying power to the controller, simulation system boards, etc.

[0060] It should be noted that the power supply is for the physical controller.

[0061] Next, the intelligent parking simulation method proposed according to the embodiments of this application is described with reference to the accompanying drawings.

[0062] Figure 4 This is a flowchart illustrating an intelligent parking simulation method provided in an embodiment of this application.

[0063] like Figure 4 As shown, this intelligent parking simulation method is used in an intelligent parking simulation system. The method includes the following steps:

[0064] In step S101, the test requirements for the intelligent parking function are obtained.

[0065] The testing requirements can be environmental perception information and vehicle signals. The environmental perception information is realized through an environmental perception fusion controller, whose interface meets the platform requirements and is decoupled from the vehicle model. The vehicle signals are realized through vehicle model simulation.

[0066] It is understood that the test requirements for the intelligent parking function obtained in this application embodiment ensure the comprehensiveness and relevance of the test, facilitating subsequent simulation testing.

[0067] In step S102, the lower-level machine is configured for simulation according to the test requirements, and after the configuration is completed, the lower-level machine is controlled to jointly execute the simulation test process of the intelligent parking function with the real controller board.

[0068] It is understood that the embodiments of this application, through detailed testing requirements of the intelligent parking function, accurately simulate and configure the lower-level machine, and successfully combine this simulation environment with the real controller board to execute a comprehensive intelligent parking function simulation test process. This not only significantly improves testing efficiency and reduces testing costs, but also ensures the accuracy and reliability of test results by highly simulating real-world scenarios.

[0069] In step S103, simulation test results of the intelligent parking function are generated based on the simulation test data from the lower-level machine.

[0070] It is understood that this application embodiment successfully generated simulation test results for the intelligent parking function by collecting and analyzing simulation test data from the lower-level machine, providing quantitative indicators and objective basis for evaluating the performance of the intelligent parking function. At the same time, the generation of simulation test results also ensures product quality and reliability, reduces risks caused by defects, and helps improve user experience and meet user needs.

[0071] It should be noted that the foregoing explanation of the intelligent parking simulation system embodiment also applies to the intelligent parking simulation method of this embodiment, and will not be repeated here.

[0072] The intelligent parking simulation method proposed in this application integrates a vehicle dynamics model, a VTD (Vehicle Dynamics Assistance) system, and a softECU in the lower-level computer, achieving comprehensive virtual testing of the intelligent parking function. This effectively avoids the safety and economic risks associated with actual road testing. Furthermore, the rapid iteration capability of the virtual environment shortens the testing cycle and accelerates the testing process. The flexibility of the softECU further eliminates the lag and resource waste associated with HIL (High-Intensity Logic) simulation customization, while the introduction of real controller boards and VTD enhances the simulation accuracy of the MIL (Multi-Intensity Logic) testing environment for real vehicle environmental perception information. Therefore, this method solves the problems of excessively high testing risks and costs, long testing cycles, lag and waste caused by HIL simulation customization, and insufficient environmental perception capabilities in existing technologies.

[0073] The following will combine Figure 5 This paper elaborates on the intelligent parking simulation method. The simulation testing process is based on relevant simulation testing software. After parameterizing the test cases, they are loaded into the automated response testing software. The software reads and writes relevant parameters in the simulation model, sends commands, and controls the testing process according to a certain timing sequence or message triggering method, automating the execution of one or more test conditions. Automated testing for verifying the automatic parking algorithm can include parking space search function, parking function testing under different parking space conditions, parking performance testing referencing Ivista, parking diagnostic testing, etc. The specific process is as follows:

[0074] Simulation preparation phase: Start the simulation system, ensure that all necessary software and hardware resources are ready, and start the simulation system platform;

[0075] Power on the controller to ensure it is in normal working order and ready to receive and execute simulation commands.

[0076] Load a simulation model of the intelligent parking function into the simulation system;

[0077] Automated testing process: Configure the corresponding test parameters in the simulation system according to the test requirements;

[0078] Load preset or custom simulation scenarios, which cover various complex situations that may be encountered during actual parking to ensure the comprehensiveness and effectiveness of the test.

[0079] The simulation test process is initiated. The controller executes the intelligent parking function according to the simulation scenario and test parameters. The simulation system simulates vehicle behavior and environmental changes in real time.

[0080] During the test, the simulation system collects key data in real time;

[0081] The test automatically ends when the preset conditions are met or the test time limit is reached. At this point, the system loads the test sequence and matches the parameters during the actual test with the preset test parameters to verify the effectiveness and accuracy of the test.

[0082] Test result processing: Conduct in-depth analysis of the collected test data to evaluate the performance of the intelligent parking function; generate a detailed test report based on the data analysis results.

[0083] Figure 6 This is a schematic diagram of the structure of a host computer provided in an embodiment of this application. The host computer may include:

[0084] The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0085] When the processor 602 executes the program, it implements the intelligent parking simulation method provided in the above embodiments.

[0086] Furthermore, the host computer also includes:

[0087] Communication interface 603 is used for communication between memory 601 and processor 602.

[0088] The memory 601 is used to store computer programs that can run on the processor 602.

[0089] The memory 601 may include high-speed RAM (Random Access Memory) memory, and may also include non-volatile memory, such as at least one disk storage.

[0090] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0091] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0092] The processor 602 may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of this application.

[0093] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0094] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0095] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0096] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any of the following techniques known in the art, or a combination thereof: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (FPGAs), field-programmable gate arrays (FPGAs), etc.

[0097] Those skilled in the art will understand that all or part of the steps of the methods implementing the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0098] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. An intelligent parking simulation system, characterized in that, The system comprises: a lower computer, wherein the lower computer comprises a vehicle dynamics model, a driving assistance system VTD used for simulating a road scene, and a software-defined electronic control unit softECU, wherein the VTD generates a surround view signal for a virtual road scene, and inputs the surround view signal into a real controller board after rendering by a visual rendering station; the vehicle dynamics model is used for controlling the vehicle to move in the virtual road scene simulated by the VTD according to a parking control signal, and the softECU generates the parking control signal according to environmental perception information and a whole vehicle signal simulated by the VTD, wherein the softECU comprises a space parking spot recognition module, a parking planning and control module, and a vehicle control signal conversion module, wherein the space parking spot recognition module recognizes space parking spot information in the environmental perception information, the parking planning and control module generates a parking planning instruction according to the space parking spot information and the whole vehicle signal, and the vehicle control signal conversion module is used for converting the parking planning instruction into the parking control signal; a real controller board used for perceiving environmental perception information according to the virtual road scene simulated by the VTD, wherein the real controller board comprises a video injection module and an environmental perception fusion control module, wherein the video injection module is used for inputting the surround view signal rendered by the visual rendering station into the environmental perception fusion control module, and the environmental perception fusion control module perceives the surround view signal to obtain the environmental perception information; a host computer, wherein the host computer has a simulation configuration function, a test management function, and a data acquisition function, the lower computer is configured based on the simulation configuration function, the simulation test process of the intelligent parking function of the lower computer is managed based on the test management function, and the simulation test data of the lower computer is acquired based on the data acquisition function, and the host computer further generates a simulation test result of the intelligent parking function according to the simulation test data.

2. The intelligent parking simulation system of claim 1, wherein, The environmental perception information comprises at least one of parking spot information, vehicle information, and pedestrian information.

3. The intelligent parking simulation system of claim 1, wherein, The real controller board further comprises a power management module used for powering the real controller board.

4. The intelligent parking simulation system of claim 1, wherein, The VTD is further used for simulating an ultrasonic radar system, and outputs an ultrasonic radar simulation signal based on the simulated ultrasonic radar system.

5. The intelligent parking simulation system of claim 3, wherein, The whole vehicle signal comprises vehicle pose, tire contact point, and the ultrasonic radar simulation signal.

6. An intelligent parking simulation method, characterized in that, The method is used for controlling the intelligent parking simulation system, and comprises the following steps: acquiring a test requirement of the intelligent parking function; configuring the lower computer according to the test requirement, and controlling the lower computer to execute the simulation test process of the intelligent parking function in combination with the real controller board after the configuration is completed; generating a simulation test result of the intelligent parking function according to the simulation test data of the lower computer.

7. A host computer, characterized by The system comprises: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the intelligent parking simulation method.

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