Extreme weather HIL in-loop simulation test system, test method and electronic equipment

Abstract

The invention relates to the technical field of vehicles, in particular to an extreme weather HIL in-loop simulation test system and method and electronic equipment, and the system comprises a V2X data collection module which is used for collecting obstacle dynamic information, traffic light dynamic information, pedestrian flow dynamic information and traffic flow dynamic information in a preset weather scene; and the HIL simulation platform is used for generating a plurality of groups of simulation scenes according to the obstacle dynamic information, the traffic light dynamic information, the pedestrian flow dynamic information and the traffic flow dynamic information, and performing an automatic driving HIL simulation test based on the plurality of groups of simulation scenes to obtain a simulation test result. Therefore, the problems of poor data timeliness and relatively high acquisition cost caused by acquiring the driving data by the driver of the real vehicle on the actual road are solved. The data timeliness is improved, and the data acquisition cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to an extreme weather HIL in-the-loop simulation test system, a test method and electronic equipment. Background Art

[0002] Extreme weather scenarios are a pain point in simulation in environmental testing. Implementing extreme weather simulation testing can complement real vehicle testing and improve test accuracy.

[0003] In the prior art, real car drivers are usually used to drive on actual roads to collect road driving data.

[0004] However, the collection of road information through real vehicles has poor timeliness of collected data and high data acquisition costs, which need to be urgently addressed. Summary of the invention

[0005] The present invention provides an extreme weather HIL in-the-loop simulation test system, test method and electronic equipment, which collects traffic flow dynamic information, pedestrian flow dynamic information, traffic light dynamic information and obstacle dynamic information in extreme weather scenarios through the V2X system, and inputs the information into the HIL simulation platform to realize intelligent driving HIL simulation test in real extreme weather scenarios. It solves the problem of poor data timeliness and high collection cost caused by real car drivers collecting driving data on actual roads. It improves data timeliness and reduces data collection costs.

[0006] To achieve the above-mentioned objectives, the first aspect of the present invention proposes an extreme weather HIL in-the-loop simulation test system, comprising: a V2X data acquisition module, used to collect obstacle dynamic information, traffic light dynamic information, pedestrian flow dynamic information and traffic flow dynamic information under preset weather scenarios; a HIL simulation platform, wherein the HIL simulation platform is used to generate multiple groups of simulation scenarios according to the obstacle dynamic information, the traffic light dynamic information, the pedestrian flow dynamic information and the traffic flow dynamic information, and perform autonomous driving HIL simulation tests based on the multiple groups of simulation scenarios to obtain simulation test results.

[0007] Furthermore, in one embodiment, the HIL simulation platform includes: a feature extraction unit, which is used to extract the geometric features and the motion features of the obstacles from the obstacle dynamic information, and to extract the timing features and the state features of the traffic lights from the traffic light dynamic information, and to extract the behavior features and the motion features of the pedestrians from the pedestrian flow dynamic information, and to extract the density distribution of the traffic flow, the speed distribution of the traffic flow and the flow change features of the traffic flow from the traffic flow dynamic information; a scene reproduction unit, which is used to determine the simulation environment parameters according to the preset weather scene, and based on A preset vehicle-obstacle interaction strategy, a preset vehicle-traffic light interaction strategy, a preset pedestrian-vehicle interaction strategy and a preset vehicle-traffic flow interaction strategy, wherein the plurality of simulation scenarios are obtained according to the geometric characteristics of the obstacle, the movement characteristics of the obstacle, the timing characteristics of the traffic light, the state characteristics of the traffic light, the behavior characteristics of the pedestrian, the movement characteristics of the pedestrian, the density distribution of the traffic flow, the speed distribution of the traffic flow and the flow change characteristics of the traffic flow; and a scenario generalization unit, which is used to generalize each simulation scenario to obtain the plurality of groups of simulation scenarios.

[0008] Furthermore, in one embodiment, the HIL simulation platform also includes: an autonomous driving HIL simulation system, used to perform autonomous driving HIL simulation tests based on the multiple groups of simulation scenarios to obtain simulation test results.

[0009] Furthermore, in one embodiment, the HIL simulation platform also includes: a vehicle dynamics module, a scenario simulation module, a CAN signal injection board and a video injection device; wherein the multiple groups of simulation scenarios enter the autonomous driving HIL simulation system through the vehicle dynamics module, the scenario simulation module, the CAN signal injection board and the video injection device.

[0010] Furthermore, in one embodiment, the extreme weather HIL in-the-loop simulation test system further includes: a report generation module for generating a test report according to the simulation test results; and a display module for displaying the generated test report.

[0011] According to the extreme weather HIL in-the-loop simulation test system proposed in the embodiment of the present invention, the V2X system collects traffic flow dynamic information, pedestrian flow dynamic information, traffic light dynamic information, and obstacle dynamic information in extreme weather scenarios, and inputs the information into the HIL simulation platform to realize intelligent driving HIL simulation testing in real extreme weather scenarios. It solves the problem of poor data timeliness and high collection cost caused by real car drivers collecting driving data on actual roads. It improves data timeliness and reduces data collection costs.

[0012] The second aspect of the present invention proposes an extreme weather HIL in-the-loop simulation test method, which adopts the extreme weather HIL in-the-loop simulation test system as described above, and the method steps include: collecting obstacle dynamic information, traffic light dynamic information, pedestrian flow dynamic information and traffic flow dynamic information under preset weather scenarios; generating multiple groups of simulation scenarios based on the obstacle dynamic information, the traffic light dynamic information, the pedestrian flow dynamic information and the traffic flow dynamic information; performing autonomous driving HIL simulation tests based on the multiple groups of simulation scenarios to obtain simulation test results.

[0013] Furthermore, in one embodiment, the generating of multiple sets of simulation scenarios according to the obstacle dynamic information, the traffic light dynamic information, the pedestrian flow dynamic information and the traffic flow dynamic information includes: extracting the geometric features of the obstacle and the motion features of the obstacle from the obstacle dynamic information, extracting the time sequence features of the traffic light and the state features of the traffic light from the traffic light dynamic information, extracting the behavior features of the pedestrian and the motion features of the pedestrian from the pedestrian flow dynamic information, and extracting the density distribution of the traffic flow, the speed distribution of the traffic flow and the flow change features of the traffic flow from the traffic flow dynamic information; extracting the traffic flow dynamic information according to the predicted Assume that the weather scenario determines the simulation environment parameters, and based on the preset vehicle-obstacle interaction strategy, the preset vehicle-traffic light interaction strategy, the preset pedestrian-vehicle interaction strategy and the preset vehicle-traffic flow interaction strategy, the multiple simulation scenarios are obtained according to the geometric characteristics of the obstacles, the movement characteristics of the obstacles, the timing characteristics of the traffic lights, the state characteristics of the traffic lights, the behavior characteristics of the pedestrians, the movement characteristics of the pedestrians, the density distribution of the traffic flow, the speed distribution of the traffic flow and the flow change characteristics of the traffic flow; and generalize the scenario for each of the simulation scenarios to obtain the multiple groups of simulation scenarios.

[0014] Furthermore, in one embodiment, the multiple groups of simulation scenarios enter the autonomous driving HIL simulation system through a vehicle dynamics module, a scenario simulation module, a CAN signal injection board and a video injection device.

[0015] Furthermore, in one embodiment, the extreme weather HIL in-the-loop simulation test method further includes: generating a test report according to the simulation test results; and displaying the generated test report.

[0016] According to the extreme weather HIL in-the-loop simulation test method for vehicles proposed in an embodiment of the present invention, the V2X system collects traffic flow dynamic information, pedestrian flow dynamic information, traffic light dynamic information, and obstacle dynamic information in extreme weather scenarios, and inputs the information into the HIL simulation platform to realize intelligent driving HIL simulation testing in real extreme weather scenarios. This solves the problem of poor data timeliness and high collection cost caused by real car drivers collecting driving data on actual roads. It improves data timeliness and reduces data collection costs.

[0017] The third aspect of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the extreme weather HIL in-the-loop simulation test method as described above.

[0018] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0020] Figure 1 A block diagram of an extreme weather HIL-in-the-loop simulation test system provided according to an embodiment of the present invention;

[0021] Figure 2 A block diagram of a HIL simulation platform according to an embodiment of the present invention;

[0022] Figure 3 A flow chart of an extreme weather HIL in-the-loop simulation test method according to a specific embodiment of the present invention;

[0023] Figure 4 A flow chart of an extreme weather HIL in-the-loop simulation test method provided according to an embodiment of the present invention;

[0024] Figure 5 The present invention is a block diagram of an electronic device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

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

[0026] The following describes an extreme weather HIL-in-the-loop simulation test system, a test method, and an electronic device according to an embodiment of the present invention with reference to the accompanying drawings.

[0027] Figure 1 The block diagram of the extreme weather HIL-in-the-loop simulation test system provided according to an embodiment of the present invention.

[0028] like Figure 1 As shown, the extreme weather HIL in-the-loop simulation test system 10 includes: a V2X data acquisition module 100 and a HIL simulation platform 200.

[0029] Among them, the V2X data acquisition module 100 is used to collect obstacle dynamic information, traffic light dynamic information, pedestrian flow dynamic information and traffic flow dynamic information under preset weather scenarios; the HIL simulation platform 200 is used to generate multiple sets of simulation scenarios according to the obstacle dynamic information, traffic light dynamic information, pedestrian flow dynamic information and traffic flow dynamic information, and perform autonomous driving HIL simulation tests based on the multiple sets of simulation scenarios to obtain simulation test results.

[0030] It should be noted that the V2X data acquisition module 100 of the embodiment of the present invention may be a module integrated with multiple data acquisition and communication devices such as laser radar, high-definition camera, wireless communication equipment, etc. Among them, the preset extreme weather in the module may be scenes that affect driving safety such as rain, snow, fog, and hail, the obstacle dynamic information may be the information of debris blown by the wind onto the road that affects driving safety, the traffic light dynamic information may include information such as the change cycle of the red light, yellow light, and green light on the road, the pedestrian flow dynamic information may include information such as the rate of change of the size of the pedestrian flow over time and the direction of pedestrian movement, and the traffic flow dynamic information includes information such as the size of the road traffic flow and the road maintenance status.

[0031] Further, in one embodiment, if Figure 2As shown, the HIL simulation platform 200 further includes: a feature extraction unit 201 , a scene reproduction unit 202 and a scene generalization unit 203 . Among them, the feature extraction unit 201 is used to extract the geometric features and motion features of obstacles from the dynamic information of obstacles, and to extract the timing features and state features of traffic lights from the dynamic information of traffic lights, and to extract the behavior features and motion features of pedestrians from the dynamic information of pedestrian flow, and to extract the density distribution of traffic flow, the speed distribution of traffic flow and the flow change features of traffic flow from the dynamic information of traffic flow; the scene reproduction unit 202 is used to determine the simulation environment parameters according to the preset weather scene, and based on the preset vehicle-obstacle interaction strategy, the preset vehicle-traffic light interaction strategy, the preset pedestrian-vehicle interaction strategy and the preset vehicle-traffic flow interaction strategy, according to the geometric features of obstacles, the motion features of obstacles, the timing features of traffic lights, the state features of traffic lights, the behavior features of pedestrians, the motion features of pedestrians, the density distribution of traffic flow, the speed distribution of traffic flow and the flow change features of traffic flow, multiple simulation scenes are obtained; the scene generalization unit 203 is used to generalize each simulation scene to obtain multiple groups of simulation scenes.

[0032] Furthermore, in one embodiment, the HIL simulation platform 200 also includes: an autonomous driving HIL simulation system 208, which is used to perform autonomous driving HIL simulation tests based on multiple groups of simulation scenarios to obtain simulation test results.

[0033] Furthermore, in one embodiment, the HIL simulation platform 200 also includes: a vehicle dynamics module 204, a scene simulation module 205, a CAN signal injection board 206 and a video injection device 207; wherein, multiple groups of simulation scenes enter the autonomous driving HIL simulation system 208 through the vehicle dynamics module 204, the scene simulation module 205, the CAN signal injection board 206 and the video injection device 207.

[0034] It should be understood that the simulation environment plays a vital role in the development and testing of autonomous vehicles. Through highly realistic simulation, the performance of the vehicle in various complex situations can be tested without the risk of actual roads. The feature extraction unit 201 of the embodiment of the present invention obtains the data collected by the V2X data acquisition module 100 and extracts the scene features through an algorithm. Among them, the simulation environment parameters are determined according to the preset weather scene, which may include information such as weather, light, temperature and humidity, for example: a preset weather scene with low light intensity, low temperature and high humidity on a rainy and snowy day. The interaction strategy between the vehicle and the obstacle may include the geometric characteristics and motion characteristics of the obstacle, for example: judging the obstacle avoidance path planning based on the debris of different sizes appearing on the road ahead. The interaction strategy between the vehicle and the traffic light may include the timing characteristics and state characteristics of the traffic light, for example: the duration of the red, yellow and green lights and their changing trends. The interaction strategy between the vehicle and the pedestrian may include the behavior characteristics and motion characteristics of the pedestrian, for example: whether the pedestrian is ready to cross the road or suddenly change direction, and the pedestrian's speed, direction, acceleration and other information. The interaction strategies between vehicles and traffic flow can include: traffic flow density, speed distribution and flow change characteristics, such as: the number of vehicles and driving speed during peak hours in the morning and evening.

[0035] It should be noted that in the development and verification of autonomous driving technology, it is crucial to create a realistic simulation environment, which can help engineers test and optimize the perception, decision-making and control capabilities of the vehicle in a safe virtual environment. The scene reproduction unit 202 of the embodiment of the present invention can generate a variety of simulation scenes based on the environmental features provided by the feature extraction unit 201 through the vehicle dynamics module 204, the scene simulation module 205, the CAN signal injection board 206 and the video injection device 207, and transmit them to the autonomous driving HIL simulation system 208. It covers from simple straight road conditions to complex multi-lane intersections, from unobstructed highways to busy city streets. Each scene will contain specific weather conditions, traffic density, obstacle layout, pedestrian activities and traffic light status to comprehensively evaluate the performance of the autonomous driving vehicle.

[0036] Furthermore, in one embodiment, the extreme weather in-the-loop simulation test system 10 further includes: a report generation module 300 and a display module 400. The report generation module 300 is used to generate a test report according to the simulation test results; and the display module 400 is used to display the generated test report.

[0037] The display module 400 in the embodiment of the present invention may be an LED screen.

[0038] Specifically, the HIL simulation platform 200 of the embodiment of the present invention sends the simulation test results to the report generation module 300, and the report generation module 300 can generate a corresponding test report based on the simulation test results. The display module 400 can display the test report on the LED screen after receiving the test report generated by the report generation module 300. It should be noted that the functions of the report generation module 300 may include: data collection and integration, data analysis and calculation, report design and template, content generation and output, etc.

[0039] In order to enable relevant technical personnel in the field to better understand the extreme weather HIL in-the-loop simulation test method of the embodiment of the present invention, the following is combined with Figure 1 , Figure 2 and Figure 3 Specific embodiments are described in detail.

[0040] Alternatively, if Figure 3 As shown, in a specific embodiment, the extreme weather HIL in-the-loop simulation test method may include the following steps:

[0041] In step S301, the V2X data acquisition module collects dynamic information of obstacles, dynamic information of traffic lights, dynamic information of pedestrian flows and dynamic information of traffic flows under preset weather scenarios.

[0042] In step S302, the information collected by the V2X data acquisition module is transmitted to the feature extraction unit in the HIL simulation platform, and the geometric features and motion features of the obstacle can be extracted from the obstacle dynamic information, and the timing features and state features of the traffic light can be extracted from the traffic light dynamic information, and the behavior features and motion features of the pedestrians can be extracted from the pedestrian flow dynamic information, and the density distribution of the traffic flow, the speed distribution of the traffic flow and the flow change characteristics of the traffic flow can be extracted from the traffic flow dynamic information.

[0043] In step S303, the extracted feature information is transmitted to the scene reproduction unit, and the simulation environment parameters and feature information are determined based on the preset weather scene to obtain multiple simulation scenes.

[0044] In step S304, each simulation scene is generalized by a scene generalization unit to obtain multiple groups of simulation scenes.

[0045] In step S305, multiple groups of simulation scenarios enter the autonomous driving HIL simulation system through the vehicle dynamics module, the scenario simulation module, the CAN signal injection board and the video injection device.

[0046] In step S306, the autonomous driving HIL simulation system performs autonomous driving HIL simulation tests based on multiple sets of simulation scenarios to obtain simulation test results.

[0047] In step S307, the HIL simulation platform sends the simulation test results to a report generation module in the extreme weather HIL-in-the-loop simulation test system, and generates a test report according to the simulation test results.

[0048] In step S308, the test report generated by the generation module is transmitted to the display module, and the report result is displayed.

[0049] According to the extreme weather HIL in-the-loop simulation test system for vehicles proposed in the embodiment of the present invention, the V2X system collects traffic flow dynamic information, pedestrian flow dynamic information, traffic light dynamic information, and obstacle dynamic information in extreme weather scenarios, and inputs the information into the HIL simulation platform to realize intelligent driving HIL simulation testing in real extreme weather scenarios. This solves the problem of poor data timeliness and high collection cost caused by real car drivers collecting driving data on actual roads. It improves data timeliness and reduces data collection costs.

[0050] Next, the extreme weather HIL in-the-loop simulation test method of an embodiment of the present invention is introduced.

[0051] like Figure 4 As shown, the embodiment of the present invention also proposes an extreme weather HIL in-the-loop simulation test method, comprising the following steps:

[0052] In step S401, dynamic information of obstacles, dynamic information of traffic lights, dynamic information of pedestrian flows and dynamic information of traffic flows under a preset weather scenario are collected;

[0053] In step S402, multiple sets of simulation scenarios are generated according to the obstacle dynamic information, the traffic light dynamic information, the pedestrian flow dynamic information and the traffic flow dynamic information;

[0054] In step S403, an autonomous driving HIL simulation test is performed based on multiple groups of simulation scenarios to obtain simulation test results.

[0055] Further, in one embodiment, multiple groups of simulation scenarios are generated based on obstacle dynamic information, traffic light dynamic information, pedestrian flow dynamic information and traffic flow dynamic information, including: extracting the geometric characteristics of obstacles and the movement characteristics of obstacles from the obstacle dynamic information, extracting the timing characteristics of traffic lights and the state characteristics of traffic lights from the traffic light dynamic information, extracting the behavior characteristics of pedestrians and the movement characteristics of pedestrians from the pedestrian flow dynamic information, and extracting the density distribution of traffic flow, the speed distribution of traffic flow and the flow change characteristics of traffic flow from the traffic flow dynamic information; determining the simulation environment parameters according to the preset weather scenario, and based on the preset vehicle-obstacle interaction strategy, the preset vehicle-traffic light interaction strategy, the preset pedestrian-vehicle interaction strategy and the preset vehicle-traffic flow interaction strategy, obtaining multiple simulation scenarios according to the geometric characteristics of obstacles, the movement characteristics of obstacles, the timing characteristics of traffic lights, the state characteristics of traffic lights, the behavior characteristics of pedestrians, the movement characteristics of pedestrians, the density distribution of traffic flow, the speed distribution of traffic flow and the flow change characteristics of traffic flow; and generalizing each simulation scenario to obtain multiple groups of simulation scenarios.

[0056] Furthermore, in one embodiment, multiple groups of simulation scenarios enter the autonomous driving HIL simulation system through a vehicle dynamics module, a scenario simulation module, a CAN signal injection board, and a video injection device.

[0057] Furthermore, in one embodiment, the extreme weather HIL in-the-loop simulation test method further includes: generating a test report according to the simulation test results; and displaying the generated test report.

[0058] It should be noted that the aforementioned explanation of the extreme weather HIL-in-the-loop simulation test method embodiment is also applicable to the extreme weather HIL-in-the-loop simulation test system of this embodiment, and will not be repeated here.

[0059] According to the extreme weather HIL in-the-loop simulation test method for vehicles proposed in an embodiment of the present invention, the V2X system collects traffic flow dynamic information, pedestrian flow dynamic information, traffic light dynamic information, and obstacle dynamic information in extreme weather scenarios, and inputs the information into the HIL simulation platform to realize intelligent driving HIL simulation testing in real extreme weather scenarios. This solves the problem of poor data timeliness and high collection cost caused by real car drivers collecting driving data on actual roads. It improves data timeliness and reduces data collection costs.

[0060] Figure 5 A block diagram of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0061] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0062] When the processor 502 executes the program, the extreme weather HIL-in-the-loop simulation test method provided in the above embodiment is implemented.

[0063] Furthermore, the electronic device also includes:

[0064] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0065] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0066] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0067] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0068] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0069] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0070] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0071] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0072] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0073] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0074] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

Claims

1. An extreme weather HIL in-the-loop simulation test system, characterized in that: include: V2X data collection module, used to collect dynamic information of obstacles, traffic lights, pedestrian flow and traffic flow under preset weather scenarios; The HIL simulation platform is used to generate multiple sets of simulation scenarios according to the obstacle dynamic information, the traffic light dynamic information, the pedestrian flow dynamic information and the traffic flow dynamic information, and perform autonomous driving HIL simulation tests based on the multiple sets of simulation scenarios to obtain multiple simulation test results.

2. The extreme weather HIL in-the-loop simulation test system according to claim 1, characterized in that: The HIL simulation platform comprises: a feature extraction unit, for extracting the geometric features of the obstacle and the motion features of the obstacle from the obstacle dynamic information, and extracting the time sequence features of the traffic light and the state features of the traffic light from the traffic light dynamic information, and extracting the behavior features and the motion features of the pedestrians from the pedestrian flow dynamic information, and extracting the density distribution of the traffic flow, the speed distribution of the traffic flow and the flow change features of the traffic flow from the traffic flow dynamic information; A scene reproduction unit, used to determine simulation environment parameters according to the preset weather scene, and based on a preset vehicle-obstacle interaction strategy, a preset vehicle-traffic light interaction strategy, a preset pedestrian-vehicle interaction strategy, and a preset vehicle-traffic flow interaction strategy, obtain the multiple simulation scenes according to the geometric characteristics of the obstacles, the movement characteristics of the obstacles, the timing characteristics of the traffic lights, the state characteristics of the traffic lights, the behavior characteristics of the pedestrians, the movement characteristics of the pedestrians, the density distribution of the traffic flow, the speed distribution of the traffic flow, and the flow change characteristics of the traffic flow; The scene generalization unit is used to generalize the multiple simulation scenes to obtain the multiple groups of simulation scenes.

3. The extreme weather HIL in-the-loop simulation test system according to claim 1, characterized in that: The HIL simulation platform further includes: The autonomous driving HIL simulation system is used to perform autonomous driving HIL simulation tests based on the multiple groups of simulation scenarios to obtain simulation test results.

4. The extreme weather HIL in-the-loop simulation test system according to claim 3, characterized in that: The HIL simulation platform also includes a vehicle dynamics module, a scenario simulation module, a CAN signal injection board and a video injection device; Among them, the multiple groups of simulation scenarios enter the autonomous driving HIL simulation system through the vehicle dynamics module, the scenario simulation module, the CAN signal injection board and the video injection device.

5. The extreme weather HIL in-the-loop simulation test system according to claim 1, characterized in that: Also includes: A report generation module, used to generate a test report according to the simulation test results; The display module is used to display the generated test report.

6. An extreme weather HIL in-the-loop simulation test method, characterized in that: The extreme weather HIL in-the-loop simulation test system according to any one of claims 1 to 5 is used, wherein the method comprises the following steps: Collect dynamic information of obstacles, traffic lights, pedestrian flows and traffic flows under preset weather scenarios; Generate multiple groups of simulation scenarios according to the obstacle dynamic information, the traffic light dynamic information, the pedestrian flow dynamic information and the traffic flow dynamic information; Based on the multiple groups of simulation scenarios, an autonomous driving HIL simulation test is performed to obtain a simulation test result.

7. The method according to claim 6, characterized in that The generating of multiple groups of simulation scenarios according to the obstacle dynamic information, the traffic light dynamic information, the pedestrian flow dynamic information and the traffic flow dynamic information comprises: Extracting the geometric features and the motion features of the obstacles from the obstacle dynamic information, extracting the time sequence features and the state features of the traffic lights from the traffic light dynamic information, extracting the behavior features and the motion features of the pedestrians from the pedestrian flow dynamic information, and extracting the density distribution, the speed distribution and the flow change features of the traffic flow from the traffic flow dynamic information; Determine simulation environment parameters according to the preset weather scenario, and based on a preset vehicle-obstacle interaction strategy, a preset vehicle-traffic light interaction strategy, a preset pedestrian-vehicle interaction strategy, and a preset vehicle-traffic flow interaction strategy, obtain the multiple simulation scenarios according to the geometric characteristics of the obstacle, the movement characteristics of the obstacle, the timing characteristics of the traffic light, the state characteristics of the traffic light, the behavior characteristics of the pedestrian, the movement characteristics of the pedestrian, the density distribution of the traffic flow, the speed distribution of the traffic flow, and the flow change characteristics of the traffic flow; The multiple simulation scenarios are generalized to obtain the multiple groups of simulation scenarios.

8. The method according to claim 6, characterized in that The multiple groups of simulation scenarios enter the autonomous driving HIL simulation system through the vehicle dynamics module, the scenario simulation module, the CAN signal injection board and the video injection device.

9. The method according to claim 6, characterized in that Also includes: Generate a test report according to the simulation test results; The generated test report is displayed.

10. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the extreme weather HIL in-the-loop simulation test method as described in any one of claims 6 to 9.

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