Vehicle test control method and system and electronic equipment

Abstract

The invention provides a vehicle test control method and system and electronic equipment, and relates to the field of vehicle test control, and the method employs a mechanical arm and a signal simulator to simulate various manual test scenes, and simulates various environmental conditions in combination with an environmental simulation cabin. And the multi-sensor cooperative triggering mechanism is tested through the alarm response data of the vehicle, so that the problems of low manual test efficiency, single test scene, lack of sensor cooperative verification means and the like in the prior art are solved.

Description

Technical Field

[0001] This invention relates to the field of vehicle test control, and in particular to a vehicle test control method, system and electronic equipment. Background Technology

[0002] With the increasing popularity of electric vehicles, plug-in hybrid electric vehicles, and range-extended hybrid electric vehicles, more and more vehicles are equipped with active security systems. For example, some vehicles have a built-in sentry mode. When it detects vandalism or abnormal impact on the vehicle, it will actively trigger video recording and alarm actions, thus preserving video evidence at the scene, which has high practical value. When the sentry mode triggers the alarm, it requires various sensors to accurately analyze the surrounding environment. In actual use, various environmental conditions such as light intensity, weather factors, and camera obstruction can affect the sensor's recognition performance. Therefore, it is necessary to accurately set the trigger thresholds of various sensors to minimize false alarms and missed alarms.

[0003] Therefore, testing active security systems requires consideration of various triggering events, necessitating comprehensive settings for the trigger thresholds of corresponding sensors. However, current technologies still rely on manual simulation for these events, such as manually tapping or shaking the vehicle. This method is inefficient, lacks traceability, and lacks verification methods for multi-sensor collaborative responses (e.g., the linkage of vibration sensors, cameras, and ultrasonic radar). Furthermore, existing test scenarios are relatively limited, making it difficult to simulate complex environmental conditions (e.g., different lighting conditions, weather, background noise, etc.). Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a vehicle test control method, system and electronic device. The method uses a robotic arm and a signal simulator to simulate various manual test scenarios, and combines an environmental simulation chamber to simulate various environmental conditions. Then, it tests the multi-sensor collaborative triggering mechanism of the vehicle through the vehicle's alarm response data, thereby solving the problems of low efficiency of manual testing, single test scenarios and lack of sensor collaborative verification methods in the prior art.

[0005] In a first aspect, embodiments of the present invention provide a vehicle testing control method, the method comprising: Test preparation steps: Construct a test scenario matrix corresponding to the vehicle under test based on the preset environment simulation chamber, robotic arm and signal simulator, and determine the environmental setting parameters and trigger test parameters corresponding to the vehicle under test according to the test scenario matrix; Trigger control steps: After the control environment simulation chamber reaches the test environment corresponding to the environmental setting parameters, the robotic arm is controlled to contact the body of the vehicle under test using the trigger test parameters, and the signal simulator is controlled to generate obstacle simulation signals to the vehicle under test using the trigger test parameters. Response monitoring steps: Monitor and acquire alarm events after the vehicle under test responds to the test parameters in real time, and determine the alarm response data corresponding to the vehicle under test based on the alarm trigger time, alarm video recording parameters and alarm accuracy parameters corresponding to the alarm events; Result generation steps: Determine the test threshold corresponding to the test environment based on the test scenario matrix, and determine the test result corresponding to the vehicle under test based on the comparison result between the alarm response data and the test threshold.

[0006] Optional test preparation steps include: The environmental simulation chamber, robotic arm, and signal simulator corresponding to the vehicle under test are determined. The environmental simulation chamber is used to provide the vehicle under test with simulated environmental scenarios of light, precipitation, and noise. The robotic arm is used to provide the vehicle under test with simulated trigger scenarios of knocking and shaking. The signal simulator is used to provide the vehicle under test with simulated human body scenarios corresponding to ultrasonic signals and radar signals. After the control environment simulation chamber, robotic arm and signal simulator are calibrated, the environmental parameters corresponding to the environment simulation chamber, the trigger parameters corresponding to the robotic arm and the signal parameters corresponding to the signal simulator are obtained according to the preset benchmark test environment. The test scenario matrix corresponding to the vehicle under test in the benchmark test environment is determined based on environmental parameters, trigger parameters, and signal parameters. Obtain the target test environment corresponding to the vehicle under test, and use the test scenario matrix to determine the environmental parameters, trigger parameters and signal parameters corresponding to the target test environment; The environmental settings parameters for the vehicle under test are determined based on the environmental parameters, and the trigger test parameters for the vehicle under test are determined based on the trigger parameters and signal parameters.

[0007] Optionally, the trigger control steps include: After the vehicle under test is placed in the environmental simulation chamber, the target light intensity, target precipitation and target noise value corresponding to the environmental simulation chamber are determined based on the environmental setting parameters, and the target test environment corresponding to the vehicle under test is determined based on the target light intensity, target precipitation and target noise value. Obtain the trigger test parameters corresponding to the environmental settings parameters under the target test environment, and determine the trigger control parameters of the robotic arm and the signal control parameters corresponding to the signal simulator based on the trigger test parameters; After the environment simulation chamber is controlled to reach the target test environment by setting environmental parameters, the robotic arm is controlled to make contact with the vehicle body under test by trigger control parameters, and the signal simulator is controlled to generate obstacle simulation signals to the vehicle under test by signal control parameters.

[0008] Optionally, after controlling the environment simulation chamber to reach the target test environment using environmental setting parameters, controlling the robotic arm to contact the vehicle body using trigger control parameters, and controlling the signal simulator to generate obstacle simulation signals to the vehicle using signal control parameters, the steps include: The environmental simulation chamber is controlled by setting environmental parameters to achieve the target light intensity, target precipitation, and target noise value corresponding to the target test environment. The corresponding tapping frequency and tapping force of the robotic arm are determined based on the trigger control parameters, and the robotic arm is controlled to contact the vehicle under test according to the tapping frequency and tapping force using the trigger control parameters. Based on the signal control parameters, the infrared and ultrasonic signals corresponding to the signal simulator are determined. The infrared signal control parameters are used to control the signal simulator to emit infrared and ultrasonic signals to the vehicle under test, respectively. The infrared signal is used to simulate the heat source of a human body approaching the vehicle under test, and the ultrasonic signal is used to simulate obstacles approaching the vehicle under test.

[0009] Optional response monitoring steps include: The vehicle body contact event corresponding to the robotic arm and the obstacle approach event corresponding to the signal simulator are determined based on the trigger test parameters. Real-time monitoring of the first alarm event corresponding to the vehicle's response to a body contact event and the second alarm event corresponding to the response to an obstacle approach event in the test environment; Acquire alarm time data, alarm video recording data, and alarm count data corresponding to the first and second alarm events, and acquire real-time sensor data of the vehicle under test under the trigger test parameters; The alarm trigger time corresponding to the alarm event is determined based on the alarm time data; the alarm video recording parameters corresponding to the alarm event are determined based on the alarm video recording data and real-time sensor data; and the alarm accuracy corresponding to the alarm event is determined based on the alarm count data. The alarm response data for the vehicle under test is determined based on the alarm trigger time, alarm video recording parameters, and alarm accuracy parameters.

[0010] Optionally, acquire real-time sensor data of the vehicle under test under the triggered test parameters, including: Based on the trigger test parameters, determine one or more of the following sensors in the vehicle under test: camera, vibration sensor, ultrasonic radar, millimeter-wave radar, light sensor, and horn sensor. The real-time sensor data of the vehicle under test is determined based on video and image data collected by cameras, waveform data collected by vibration sensors, radar wave data corresponding to ultrasonic radar and millimeter-wave radar, light status data corresponding to light sensors, and horn activation data corresponding to horn sensors.

[0011] Optional, the result generation step includes: Based on the test scenario matrix, determine the alarm delay threshold, video frame loss threshold, and false trigger threshold corresponding to the test environment; Based on the alarm response data, obtain the alarm trigger time, alarm video recording parameters, and alarm accuracy of the vehicle under test; The first comparison result between alarm trigger time and alarm delay threshold, the second comparison result between alarm video recording parameters and video frame loss threshold, and the third comparison result between alarm accuracy and false trigger threshold are obtained respectively. The test results for the vehicle under test are determined based on the first comparison results, the second comparison results, and the third comparison results.

[0012] Optionally, before triggering the control step, the method further includes: Vehicle control steps: When the power battery charge of the vehicle under test is greater than a preset threshold, the vehicle under test is controlled to enter a sleep state; among them, the standby power consumption of the vehicle under test is the lowest in the sleep state.

[0013] Secondly, the present invention provides a vehicle test control system, the system comprising: Test preparation module: used to construct the test scenario matrix corresponding to the vehicle under test based on the preset environment simulation chamber, robotic arm and signal simulator, and to determine the environmental setting parameters and trigger test parameters corresponding to the vehicle under test according to the test scenario matrix; Trigger control module: After the environment simulation chamber reaches the test environment corresponding to the environmental setting parameters, it uses the trigger test parameters to control the robotic arm to contact the body of the vehicle under test, and uses the trigger test parameters to control the signal simulator to generate obstacle simulation signals to the vehicle under test; Response monitoring module: Used to monitor and acquire alarm events after the vehicle under test responds to the test parameters in real time, and determine the alarm response data of the vehicle under test based on the alarm trigger time, alarm video recording parameters and alarm accuracy parameters corresponding to the alarm event; The result generation module is used to determine the test thresholds corresponding to the test environment based on the test scenario matrix, and to determine the test results corresponding to the vehicle under test based on the comparison results between the alarm response data and the test thresholds.

[0014] Thirdly, embodiments of the present invention also provide an electronic device, which includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, and the processor executing the computer-executable instructions to implement the steps of the vehicle test control method provided in the first aspect.

[0015] This invention provides a vehicle testing control method, system, and electronic device. During the testing of a vehicle's active safety system, the method first constructs a test scenario matrix corresponding to the vehicle under test based on a preset environmental simulation chamber, a robotic arm, and a signal simulator. Then, it determines the environmental setting parameters and trigger test parameters corresponding to the vehicle under test based on the test scenario matrix. Next, after controlling the environmental simulation chamber to reach the test environment corresponding to the environmental setting parameters, it uses the trigger test parameters to control the robotic arm to contact the vehicle body and uses the trigger test parameters to control the signal simulator to generate obstacle simulation signals to the vehicle under test. Subsequently, it monitors and acquires alarm events triggered by the vehicle under test in real time. Based on the alarm trigger time, alarm video recording parameters, and alarm accuracy parameters corresponding to the alarm events, it determines the alarm response data corresponding to the vehicle under test. Finally, it determines the test threshold corresponding to the test environment based on the test scenario matrix and determines the test result corresponding to the vehicle under test based on the comparison between the alarm response data and the test threshold. This method utilizes robotic arms and signal simulators to simulate various manual testing scenarios, and combines them with an environmental simulation chamber to simulate various environmental conditions. Then, it tests the multi-sensor collaborative triggering mechanism of the vehicle through alarm response data, thereby solving the problems of low efficiency of manual testing, single testing scenarios, and lack of sensor collaborative verification methods in existing technologies.

[0016] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1A flowchart of a vehicle testing control method provided in an embodiment of the present invention; Figure 2 This is a flowchart of the test preparation step S101 in a vehicle test control method provided by an embodiment of the present invention; Figure 3 This is a flowchart of the trigger control step S102 in a vehicle test control method provided by an embodiment of the present invention; Figure 4 This is a flowchart of step S303 in a vehicle test control method provided in an embodiment of the present invention; Figure 5 This is a flowchart of the response monitoring step S103 in a vehicle test control method provided by an embodiment of the present invention; Figure 6 The flowchart of step S503 of a vehicle test control method provided in an embodiment of the present invention, which is a process for obtaining real-time sensor data of the vehicle under test under trigger test parameters; Figure 7 This is a flowchart of the result generation step S104 in a vehicle test control method provided in an embodiment of the present invention; Figure 8 A flowchart of another vehicle test control method provided in an embodiment of the present invention; Figure 9 This is a schematic diagram of the structure of a vehicle test control system provided in an embodiment of the present invention; Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0020] icon: 910 - Test Preparation Module; 920 - Trigger Control Module; 930 - Response Monitoring Module; 940 - Result Generation Module; 101 - Processor; 102 - Memory; 103 - Bus; 104 - Communication interface. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] To facilitate understanding of this embodiment, the vehicle testing control method disclosed in this embodiment of the invention will be described below, such as... Figure 1 As shown, the method includes: Test preparation step S101: Construct a test scenario matrix corresponding to the vehicle under test based on the preset environment simulation chamber, robotic arm and signal simulator, and determine the environmental setting parameters and trigger test parameters corresponding to the vehicle under test according to the test scenario matrix.

[0023] This step serves as the foundation for testing, with the core objective of establishing a comprehensive testing framework to provide a clear basis for subsequent testing. Specifically, it begins by using a pre-set environmental simulation chamber (simulating lighting, weather, etc.), a robotic arm (simulating physical contact actions), and a signal simulator (generating sensor detection signals) as core testing equipment. This is combined with the design specifications of the vehicle's active safety system (such as sensor type and protection range) to construct a multi-dimensional test scenario matrix. This matrix must comprehensively cover three dimensions: "environmental conditions, triggering methods, and sensor combinations," including typical scenarios such as "strong light and heavy rain environment + heavy impact on the vehicle body + vibration sensor + camera linkage" and "nighttime low light environment + close-range obstacles + ultrasonic radar + camera linkage."

[0024] After the scenario matrix is ​​determined, the core parameters of each test scenario are further broken down. On the one hand, the environmental setting parameters of the environmental simulation chamber (such as light intensity, humidity, rainfall level, etc.) are clarified, and on the other hand, the trigger test parameters (such as the contact force, contact position, and action frequency of the robotic arm, and the simulation signal parameters such as obstacle distance and movement speed generated by the signal simulator) are determined to ensure that each test scenario has quantifiable and executable parameter standards.

[0025] Trigger control step S102: After the control environment simulation chamber reaches the test environment corresponding to the environment setting parameters, the robotic arm is controlled to contact the body of the vehicle under test using the trigger test parameters, and the signal simulator is controlled to generate obstacle simulation signals to the vehicle under test using the trigger test parameters.

[0026] This step is the core of the test execution. By simulating various triggering scenarios in real use through the collaborative work of the equipment, the authenticity and controllability of the test are ensured. First, according to the environmental setting parameters determined in S101, the environmental simulation chamber is controlled to start the corresponding environmental simulation program. After the environment inside the chamber (such as temperature, light, rain and snow conditions) stabilizes and reaches the target parameters, the trigger test process is then started.

[0027] During the testing process, on the one hand, the robotic arm is controlled to perform precise actions based on the trigger test parameters, and controlled contact operations are performed on key parts of the vehicle under test (such as doors, windows, trunk, and sides of the vehicle body, which are easily damaged), simulating physical triggering behaviors such as knocking and collisions by personnel; on the other hand, obstacle simulation signals are sent to the sensor system of the vehicle under test through a signal simulator to simulate the scenario of pedestrians and vehicles approaching, achieving dual coverage of "physical contact triggering + virtual signal triggering". At the same time, the triggering sequence of multiple sensors can be precisely controlled (such as triggering the vibration sensor first, and then triggering the camera after a delay of 0.5 seconds), providing conditions for verifying the collaborative mechanism.

[0028] Response monitoring step S103: Monitor and acquire alarm events after the test vehicle responds to the test parameters in real time, and determine the alarm response data corresponding to the test vehicle based on the alarm trigger time, alarm video recording parameters and alarm accuracy parameters corresponding to the alarm events.

[0029] This step aims to comprehensively and in real-time collect response data from the vehicle security system, providing data support for subsequent result evaluation. Simultaneously with the triggering operation in S102, dedicated monitoring equipment is activated to capture alarm events from the vehicle under test in real time, focusing on recording three core parameters to form complete alarm response data: First, there's the alarm trigger time, the time difference between the trigger action and the system's alarm activation, reflecting the system's response speed. Second, there are the alarm video recording parameters, including the timeliness of recording initiation, video clarity, and screen coverage, verifying the validity of the video evidence. Third, there's the alarm accuracy parameter, calculated by comparing actual trigger scenarios with system alarm types (such as "vehicle knocking alarm" and "obstacle approach alarm"), determining the accuracy and false alarm rate (e.g., an alarm without triggering is a false alarm, and no alarm when triggered is a missed alarm). Integrating these three types of parameters creates a complete response data archive for each test scenario.

[0030] Result generation step S104: Determine the test threshold corresponding to the test environment based on the test scenario matrix, and determine the test result corresponding to the vehicle under test based on the comparison result between the alarm response data and the test threshold.

[0031] This step is the final stage of the test, and its core is to conduct an objective evaluation of the vehicle security system through data comparison. First, based on the test scenario matrix built by S101, and combined with industry standards and vehicle design requirements, corresponding test thresholds are set for each scenario (such as alarm trigger time ≤ 1 second, alarm accuracy ≥ 95%, video frame drop rate less than 3 frames / second, etc.).

[0032] The alarm response data collected by S103 was then compared with the test thresholds for the corresponding scenarios one by one. If all parameters met the threshold requirements, the test was considered passed for that scenario. If any parameters failed to meet the standards (such as excessively long trigger time or low accuracy), the test was marked as failed, and the problematic aspects were clearly identified (such as single sensor response delay or asynchronous multi-sensor linkage). Finally, the test results from all scenarios were integrated to form a complete test report containing "scenario details - response data - compliance status - problem analysis," providing clear direction for parameter optimization of the vehicle security system.

[0033] Optionally, test preparation step S101, such as Figure 2 As shown, it includes: Step S201: Determine the environmental simulation chamber, robotic arm, and signal simulator corresponding to the vehicle under test; wherein, the environmental simulation chamber is used to provide the vehicle under test with simulated environmental scenarios of light, precipitation, and noise; the robotic arm is used to provide the vehicle under test with simulated trigger scenarios of knocking and shaking; and the signal simulator is used to provide the vehicle under test with simulated human body scenarios corresponding to ultrasonic signals and radar signals.

[0034] The primary task of this step is to identify the three types of core testing equipment suitable for the vehicle under test and to clarify the specific testing functions of each device, providing hardware support for subsequent test scenario simulation. Among them, the environmental simulation chamber, as an "environmental scenario generator," plays a core role in creating a realistic lighting environment (such as strong light, weak light, backlight), precipitation (such as light rain, heavy rain, fog), and noise (such as urban traffic noise, construction noise) for the vehicle under test; the robotic arm simulates human physical triggering, and through program control, it can achieve precise knocking on different parts of the vehicle body (simulating human smashing) and controlled shaking (simulating pushing or prying the car); the signal simulator, as a virtual target generator, specifically sends simulated signals to the vehicle's ultrasonic sensors and radar sensors to simulate the scenario of living targets such as humans and pedestrians approaching, triggering the sensor's detection response.

[0035] Step S202: After the control environment simulation chamber, robotic arm and signal simulator have completed calibration, the environmental parameters corresponding to the environment simulation chamber, the trigger parameters corresponding to the robotic arm and the signal parameters corresponding to the signal simulator are obtained according to the preset benchmark test environment.

[0036] To avoid equipment errors affecting test accuracy, this step first involves a comprehensive calibration of the established environmental simulation chamber, robotic arm, and signal simulator to ensure that the output accuracy of each device meets the test standards (e.g., robotic arm impact force error ≤ ±5%, signal simulator output frequency deviation ≤ ±1%). After calibration, all devices are placed in a preset benchmark test environment (e.g., a standard environment with ambient temperature of 25℃, natural light, and no additional noise). The basic parameters of the three types of devices are collected: benchmark environmental parameters of the environmental simulation chamber (e.g., benchmark light intensity, benchmark humidity), benchmark trigger parameters of the robotic arm (e.g., benchmark impact force, benchmark movement speed), and benchmark signal parameters of the signal simulator (e.g., benchmark ultrasonic frequency, benchmark radar detection distance), forming a benchmark parameter database for the test.

[0037] Step S203: Determine the test scenario matrix corresponding to the vehicle under test in the benchmark test environment based on environmental parameters, trigger parameters, and signal parameters.

[0038] Based on the baseline environmental parameters, baseline trigger parameters, and baseline signal parameters collected in step S202, and combined with the test requirements of the vehicle's security system (such as sensor coverage and protection level), a test scenario matrix under the baseline test environment is constructed. This matrix essentially systematically combines the three types of baseline parameters to form executable basic test scenarios, such as "sunny environment + robotic arm gently knocking on the car door + signal simulator simulating a human body at 1 meter," and "rainy environment + robotic arm shaking the vehicle body + signal simulator simulating a pedestrian at 3 meters." Each scenario corresponds to a specific set of parameter combinations, providing a basic framework for subsequent expansion of test scenarios.

[0039] Step S204: Obtain the target test environment corresponding to the vehicle under test, and use the test scenario matrix to determine the environmental parameters, trigger parameters and signal parameters corresponding to the target test environment.

[0040] First, identify the target test environment that the vehicle under test needs to focus on (i.e., the environment that occurs frequently or is extreme in actual use, such as high temperature and sun exposure, heavy rain and fog, low light at night, etc.). Then, based on the benchmark test scenario matrix constructed in step S203, adjust and match the benchmark parameters according to the characteristics of the target test environment, and extract the parameter combination corresponding to the target environment.

[0041] Adjust environmental parameters according to the climate and lighting characteristics of the target environment (e.g., increase precipitation intensity parameters in rainstorm environments), adjust trigger parameters based on possible triggering behaviors in the target environment (e.g., enhance parameters for knocking on concealed parts of the robotic arm in nighttime scenarios), and adjust signal parameters according to the detection requirements of the target environment (e.g., optimize radar signal penetration parameters in foggy scenarios) to ensure that the extracted parameters can truly reflect the testing requirements of the target environment.

[0042] Step S205: Determine the environmental setting parameters corresponding to the vehicle under test based on the environmental parameters, and determine the trigger test parameters corresponding to the vehicle under test based on the trigger parameters and signal parameters.

[0043] This step is the final stage of test preparation. The parameters extracted in step S204 are categorized and integrated to form the final test execution parameters. Specifically, the environmental parameters corresponding to the target environment are further refined, defining them as the environmental settings parameters for the environmental simulation chamber (such as specific light intensity, precipitation level, and noise level). Then, the trigger parameters and signal parameters corresponding to the target environment are merged and optimized, eliminating parameter conflicts and supplementing parameter details. Finally, the trigger test parameters for controlling the robotic arm and signal simulator are determined (such as the robotic arm's striking position coordinates and striking force level, and the signal simulator's target simulation distance and signal transmission frequency). At this point, all the core parameters of the test preparation stage are determined, providing a direct basis for the subsequent execution of the formal test.

[0044] Optionally, trigger control step S102, such as Figure 3 As shown, it includes: Step S301: After controlling the vehicle under test to be placed in the environmental simulation chamber, determine the target light intensity, target precipitation and target noise value corresponding to the environmental simulation chamber based on the environmental setting parameters, and determine the target test environment corresponding to the vehicle under test based on the target light intensity, target precipitation and target noise value.

[0045] This step first completes the physical docking of the vehicle under test with the test environment, and then transforms the abstract environmental setting parameters into specific indicators that the environmental simulation chamber can execute. First, the vehicle under test is smoothly driven into the environmental simulation chamber and secured, ensuring that the vehicle's sensors (cameras, radar, vibration sensors, etc.) are unobstructed and in normal working order. Then, based on the environmental setting parameters determined in the test preparation phase, three core target indicators that the environmental simulation chamber must achieve are further broken down: target light intensity (e.g., 5 lux in low light at night, 100 klux in strong light at noon), target precipitation (e.g., 5 mm / h in light rain, 50 mm / h in heavy rain), and target noise level (e.g., 60 dB on urban main roads, 90 dB in construction areas). These three types of quantitative indicators clarify the specific standards of the target test environment, providing a precise basis for subsequent environmental simulation.

[0046] Step S302: Obtain the trigger test parameters corresponding to the environmental setting parameters under the target test environment, and determine the trigger control parameters of the robotic arm and the signal control parameters corresponding to the signal simulator based on the trigger test parameters.

[0047] This step is crucial in connecting "environmental conditions" with "trigger actions." The core task is to break down the integrated trigger test parameters into specific control parameters for each device type: robotic arm and signal simulator. First, the trigger test parameters corresponding to the target test environment are extracted. Then, the parameters are refined for each type of device: For the robotic arm, trigger control parameters are determined, including contact type (tapping or shaking), contact location (car door, hood, trunk, etc.), tapping force (e.g., light 10N, heavy 50N), and shaking frequency (e.g., 2 times / second). For the signal simulator, signal control parameters are determined, covering signal type (ultrasonic or radar signal), simulated target (adult, child), target distance (e.g., 0.8m, 3m), and movement speed (e.g., 1m / s, 3m / s), ensuring that the actions of each device have clear, quantifiable control standards.

[0048] Step S303: After the environment simulation chamber reaches the target test environment by using the environment setting parameters, the robotic arm is controlled to contact the vehicle body under test by using the trigger control parameters, and the signal simulator is controlled to generate obstacle simulation signals to the vehicle under test by using the signal control parameters.

[0049] This step follows the principle of "environment priority, synchronous triggering," ensuring that the triggering action is performed only after the target environment has stabilized, thus guaranteeing the authenticity of the test and the accuracy of the data. First, the control system of the environmental simulation chamber is activated according to the environmental setting parameters. Once the light intensity, precipitation, and noise levels inside the chamber have stabilized and reached the target indicators determined in step S301, the triggering process is initiated. On one hand, according to the triggering control parameters of the robotic arm, the robotic arm is controlled to perform precise physical contact actions with the vehicle under test, simulating scenarios of human sabotage or abnormal contact. On the other hand, simultaneously, according to the signal control parameters of the signal simulator, obstacle simulation signals are sent to the vehicle's ultrasonic and radar sensors, simulating a person approaching the vehicle. Through the coordinated action of physical triggering and virtual signal triggering, the response mechanism of the vehicle's active security system is fully activated.

[0050] Optionally, after controlling the environment simulation chamber to reach the target test environment using environment setting parameters, controlling the robotic arm to contact the vehicle body using trigger control parameters, and controlling the signal simulator to generate obstacle simulation signals to the vehicle under test using signal control parameters, step S303, such as... Figure 4 As shown, it includes: Step S401: Use environmental setting parameters to control the environmental simulation chamber to achieve the target light intensity, target precipitation, and target noise value corresponding to the target test environment.

[0051] The core task of this step is to precisely adjust the key indicators of the environmental simulation chamber to the target values ​​and maintain their stability, providing a consistent environmental benchmark for subsequent trigger tests. During operation, based on the environmental settings determined in the test preparation phase, the light intensity adjustment module, precipitation simulation system, and noise generator of the environmental simulation chamber are activated. The light intensity, precipitation, and noise levels within the chamber are respectively adjusted to the target light intensity, precipitation, and noise level. After confirming through the real-time monitoring module that all three indicators are stable within the error range corresponding to the target values, the operating status of the environmental simulation chamber is locked to ensure that subsequent trigger tests are not affected by environmental fluctuations.

[0052] Step S402: Determine the corresponding tapping frequency and tapping force of the robotic arm based on the trigger control parameters, and use the trigger control parameters to control the robotic arm to contact the vehicle under test according to the tapping frequency and tapping force.

[0053] This step focuses on translating the robotic arm's trigger control parameters into specific actions, achieving accurate simulation of physical contact scenarios with the vehicle. First, the core execution indicators of the robotic arm are extracted from the trigger control parameters, such as the tapping frequency (e.g., 1 light probe / second, 3 consecutive attacks / second) and tapping force (e.g., 5N for accidental bumps, 60N for malicious strikes). Simultaneously, the contact points of the robotic arm are identified (e.g., vulnerable areas such as door handles, window edges, and side skirts). After parameter confirmation, the control system issues commands to control the robotic arm to perform standardized contact actions on designated parts of the vehicle under test according to the preset tapping frequency and force, simulating real-world physical triggering behaviors such as human touch and tapping, ensuring the repeatability and accuracy of the triggering actions.

[0054] Step S403: Determine the infrared signal and ultrasonic signal corresponding to the signal simulator based on the signal control parameters, and use the infrared signal control parameters to control the signal simulator to emit infrared signal and ultrasonic signal to the vehicle under test respectively; wherein, the infrared signal is used to simulate the human body heat source approaching the vehicle under test; the ultrasonic signal is used to simulate the obstacle approaching the vehicle under test.

[0055] This step involves using a signal simulator to emit specific types of signals, simulating scenarios where a human body and obstacles approach, complementing the physical triggering of the robotic arm and comprehensively testing the sensor's responsiveness. During operation, the two core signals to be emitted by the signal simulator are first determined based on the signal control parameters: infrared and ultrasonic signals. Then, according to the corresponding signal control parameters (such as infrared signal strength, ultrasonic signal frequency, and detection distance), the corresponding equipment is activated. Infrared signals are emitted to simulate the heat signature of a human body approaching a vehicle, triggering the vehicle's infrared sensors. Simultaneously, ultrasonic signals are emitted to simulate the distance and contour information of obstacles such as pedestrians and bicycles, triggering the vehicle's ultrasonic sensors. Through the coordinated emission of these two signals, scenarios of people approaching and potentially causing damage are accurately reproduced, verifying the collaborative detection capabilities of multiple sensors.

[0056] Optionally, response monitoring step S103, such as Figure 5 As shown, it includes: Step S501: Determine the vehicle body contact event corresponding to the robotic arm and the obstacle approach event corresponding to the signal simulator based on the trigger test parameters.

[0057] This step aims to establish the correspondence between "triggered actions and alarm events," providing a benchmark for subsequent monitoring and data tracing. During operation, based on the trigger test parameters determined in the trigger control phase, two core trigger events are decomposed: one is the vehicle body contact event corresponding to the robotic arm performing a physical contact action (such as "10N knock on the door" or "3 shakes per second on the vehicle body"); the other is the obstacle approach event corresponding to the simulated signal emitted by the signal simulator (such as "human infrared signal at 1 meter" or "ultrasonic obstacle signal at 2 meters"). By clarifying the specific attributes of these two types of trigger events, it ensures that the corresponding alarm feedback can be accurately matched during subsequent monitoring.

[0058] Step S502: Monitor in real time the first alarm event corresponding to the vehicle body contact event and the second alarm event corresponding to the obstacle approach event when the vehicle under test responds to the vehicle body contact event in the test environment.

[0059] This step uses the triggering event determined by S501 as the monitoring target to capture the vehicle's alarm feedback in real time. Simultaneously with the triggering action, the dedicated monitoring terminal of the vehicle security system is activated to conduct dual monitoring. On one hand, it monitors the first alarm event generated when the vehicle responds to a body contact event, focusing on the triggering feedback from related sensors such as vibration sensors and cameras. On the other hand, it monitors the second alarm event generated when an obstacle approaches, focusing on the alarm actions of devices such as infrared sensors and ultrasonic radar. During monitoring, the triggering sequence of alarm events must be accurately recorded to avoid confusion between the response data of the two types of events.

[0060] Step S503: Obtain alarm time data, alarm video recording data, and alarm count data corresponding to the first alarm event and the second alarm event, and obtain real-time sensor data of the vehicle under test under the trigger test parameters.

[0061] This step is the core of data accumulation, requiring the comprehensive collection of alarm-related data and real-time sensor status data to provide sufficient basis for subsequent parameter analysis. Specifically, the following three types of core data should be collected: First, there is the basic data for alarm events, including the alarm time data for the first and second alarm events (such as alarm start / end timestamps), alarm video recording data (such as recording start / stop time, video resolution, and frame rate), and alarm count data (such as the number of alarms corresponding to a single trigger and the interval between repeated alarms). Second, there is real-time data from vehicle sensors, i.e., the real-time output data (such as vibration amplitude and signal reception strength) of various relevant sensors (vibration, infrared, ultrasonic, etc.) of the vehicle under test during the period when the test parameters are applied. All data must be stored according to the correspondence between "trigger event - alarm event" to ensure traceability.

[0062] Step S504: Determine the alarm trigger time corresponding to the alarm event based on the alarm time data, determine the alarm video recording parameters corresponding to the alarm event based on the alarm video recording data and real-time sensor data, and determine the alarm accuracy corresponding to the alarm event based on the alarm count data.

[0063] This step transforms the collected raw data into quantifiable evaluation parameters, representing the core transformation of data from raw to effective. It involves three analytical tasks: Firstly, by analyzing alarm time data, the time difference between the occurrence of the triggering event and the alarm activation is calculated to determine the alarm trigger time (reflecting the system response speed). Secondly, cross-validation is performed by combining alarm video recording data with real-time sensor data. For example, the authenticity of the triggering event is confirmed through sensor data, thereby determining the timeliness of video recording and the effectiveness of the image coverage, and finally determining the alarm video recording parameters. Third, compare the alarm count data with the actual number of triggered events to calculate the alarm accuracy rate (the formula is: number of accurate alarms / total number of triggers × 100%, where accurate alarms refer to valid alarms when the triggered event occurs, excluding false alarms without triggers and missed alarms with triggers).

[0064] Step S505: Determine the alarm response data corresponding to the vehicle under test based on the alarm trigger time, alarm video recording parameters, and alarm accuracy parameters.

[0065] This step is the final stage of response monitoring, systematically integrating the key parameters parsed from S504 to form a complete alarm response data archive. During operation, a single test scenario is used as a unit, associating and binding the three core parameters of the scenario: alarm trigger time, alarm video recording parameters, and alarm accuracy. Simultaneously, auxiliary information such as the corresponding trigger event type and test environment parameters are labeled, ultimately generating the alarm response data for the vehicle under test in that scenario.

[0066] Optionally, real-time sensor data of the vehicle under test can be acquired under the triggered test parameters, such as... Figure 6 As shown, it includes: Step S601: Determine one or more of the following sensors in the vehicle under test: camera, vibration sensor, ultrasonic radar, millimeter-wave radar, light sensor, and horn sensor, based on the trigger test parameters.

[0067] The core of this step is to select sensors directly related to the current test based on the characteristics of the trigger test parameters, avoiding interference from invalid data. The trigger test parameters clearly define the core characteristics of the test scenario. For example, in a physical trigger scenario such as a robotic arm striking or shaking the vehicle, a vibration sensor should be prioritized; in a virtual signal trigger scenario such as an obstacle approaching, ultrasonic radar or millimeter-wave radar should be matched. Regardless of the scenario, cameras (for visual evidence), light sensors (to report the impact of ambient light on imaging), and horn sensors (to monitor the alarm sound trigger status) can all serve as auxiliary monitoring sensors. Therefore, using the trigger test parameters as an anchor point, one or more associated sensors in a working state should be precisely identified from the vehicle's camera, vibration sensor, ultrasonic radar, millimeter-wave radar, light sensor, and horn sensor.

[0068] Step S602: Determine the real-time sensor data of the vehicle under test based on the video and image data collected by the camera, the waveform data collected by the vibration sensor, the radar wave data corresponding to the ultrasonic radar and millimeter-wave radar, the light status data corresponding to the light sensor, and the horn activation data corresponding to the horn sensor.

[0069] This step involves synchronously collecting core data from various related sensors to form a complete real-time sensor data set, providing the initial basis for subsequent alarm parameter analysis. Specifically, key data from each sensor needs to be collected in categories: real-time video streams and captured image data from cameras are obtained to verify the validity of the alarm images; vibration waveform data from vibration sensors are obtained to accurately reflect the impact intensity and frequency experienced by the vehicle body; radar wave reflection data from ultrasonic and millimeter-wave radars are obtained to analyze the distance, speed, and other characteristics of obstacles; real-time lighting status data from lighting sensors are obtained to help determine the impact of ambient light on the camera's recognition performance; and horn activation data from horn sensors are obtained to confirm the timeliness of the alarm sound triggering.

[0070] The above multi-dimensional data are synchronized and integrated according to timestamps to finally form the real-time sensor data of the vehicle under test under the current triggered test parameters.

[0071] Optionally, the result generation step S104, such as Figure 7 As shown, it includes: Step S701: Determine the alarm delay threshold, video frame loss threshold, and false trigger threshold corresponding to the test environment based on the test scenario matrix.

[0072] The core of this step is to set specific pass / fail standards for different test scenarios to ensure the relevance and rationality of the evaluation. The test scenario matrix covers a combination of "environmental conditions + triggering methods." The system's response requirements differ under different scenarios (e.g., in heavy rain and low light conditions, alarm delay can be appropriately relaxed, while video frame loss needs to be strictly controlled). Therefore, based on this matrix, combined with industry standards and vehicle design specifications, three core evaluation thresholds are defined for each test environment: first, the "alarm delay threshold" (e.g., ≤1 second in normal environments, ≤1.5 seconds in extreme environments), which limits the maximum allowable time for alarm triggering; second, the "video frame loss threshold" (e.g., frame loss rate ≤3%), which standardizes the integrity requirements of alarm videos; and third, the "false trigger threshold" (e.g., false trigger rate ≤5%), which clarifies the maximum tolerance limit for invalid alarms.

[0073] Step S702: Obtain the alarm trigger time, alarm video recording parameters, and alarm accuracy of the vehicle under test based on the alarm response data.

[0074] This step aims to accurately extract key indicators corresponding to the evaluation thresholds from the alarm response data collected in the early stages, preparing data for subsequent comparisons. During the operation, using the alarm response data as the data source, three types of core parameters are extracted: first, the alarm trigger time, reflecting the system's response speed; second, alarm video recording parameters, reflecting the effectiveness of video evidence (with the core parameter being the video frame drop rate); and third, the alarm accuracy rate, measuring the system's identification accuracy (inversely correlated with the false trigger rate, alarm accuracy rate = 1 - false trigger rate). This ensures that the extracted parameters correspond one-to-one with the thresholds established by S701, forming a "data-standard" evaluation pair.

[0075] Step S703: Obtain the first comparison result between the alarm trigger time and the alarm delay threshold, the second comparison result between the alarm video recording parameters and the video frame loss threshold, and the third comparison result between the alarm accuracy and the false trigger threshold.

[0076] This step directly compares data with standards to determine the single-dimensional accuracy of each core indicator. The specific comparison logic is as follows: The alarm trigger time is compared to the alarm delay threshold. If the trigger time is less than or equal to the delay threshold, the first comparison result is considered satisfactory; otherwise, it is considered unsatisfactory. The frame drop rate in the alarm video recording parameters is compared to the video frame drop threshold. If the frame drop rate is less than or equal to the frame drop threshold, the second comparison result is considered satisfactory. The false trigger rate corresponding to the alarm accuracy is compared to the false trigger threshold. If the false trigger rate is less than or equal to the threshold (i.e., alarm accuracy ≥ 95%), the third comparison result is considered satisfactory. Each comparison result must be labeled "satisfactory" or "unsatisfactory" and include the specific numerical difference (e.g., "alarm trigger time 1.2 seconds, exceeding the delay threshold by 0.2 seconds").

[0077] Step S704: Determine the test results corresponding to the vehicle under test based on the first comparison result, the second comparison result, and the third comparison result.

[0078] This step integrates the results of three single-dimensional comparisons to form an overall evaluation conclusion for the security system of the vehicle under test. The judgment logic follows the principle of "all standards met, pass; single non-compliance indicates problem location." If the first, second, and third comparison results are all "compliant," the vehicle test result in this test scenario is judged as "pass." If any comparison result is "non-compliant," it is judged as "fail," and the problem type is clearly marked (e.g., "video frame drop rate 5%, exceeding the threshold 2%, risk of video evidence becoming invalid"). If multiple standards are non-compliant, the problem and corresponding parameter deviation must be listed one by one. Finally, combining the conclusions of all test scenarios, a complete test report is generated, including "scenario details - problem summary - optimization suggestions."

[0079] Optionally, before triggering the control step, the method further includes: a vehicle control step: when the power battery charge of the vehicle under test is greater than a preset threshold, the vehicle under test is controlled to enter a sleep state; wherein, the standby power consumption of the vehicle under test is lowest in the sleep state.

[0080] Before executing the trigger control step S102, the vehicle control step must be completed first to build a stable and unified initial operating environment for the active security system test, and to avoid power fluctuations or additional power consumption interfering with the test results.

[0081] Specifically, this step, with the core objective of ensuring the stable operation of the security system, is divided into two key stages: power level determination and state control. First, the power level of the vehicle under test's battery is checked to confirm whether its actual power level exceeds a preset threshold. This threshold is typically set at 60% or more of the total battery capacity. This avoids abnormal responses caused by unstable power supply in low-power conditions and also reserves sufficient power for long-term testing. If the detected power level meets the requirements, a sleep command is issued through the vehicle control system to put the vehicle under test into a sleep state. This sleep state is not a complete power cut-off, but rather, while retaining the core functions of the active security system (such as real-time sensor monitoring and signal reception), it shuts down non-essential electrical equipment such as in-vehicle entertainment, air conditioning, and lighting, minimizing the vehicle's standby power consumption. This ensures that the system's alarm response during subsequent testing is driven solely by trigger events and is not affected by additional power consumption factors.

[0082] like Figure 8 Another vehicle test control method shown mainly includes the following four stages: preparation stage, triggering stage, response monitoring stage, and result evaluation stage.

[0083] The preparation phase includes environmental configuration and equipment calibration. During environmental configuration, the vehicle is placed in an adjustable environmental chamber, and parameters such as light intensity (e.g., simulating noon / night), precipitation (50mm / h), and background noise (65dB) required for the test are set. In addition, it is ensured that the vehicle enters a low-power sleep state (battery charge > 60%).

[0084] Equipment calibration mainly targets the robotic arm, camera, and vibration sensor; robotic arm calibration mainly adjusts the striking force (adjustable from 50N to 200N) and positioning accuracy (±1mm); camera calibration adjusts the focus and white balance to ensure clear focus on the test area; vibration sensor calibration eliminates baseline noise interference.

[0085] The triggering phase involves both physical and electronic triggering. Physical triggering primarily includes impact and shaking tests. The impact test involves vertically striking a specific location on the car door with a set force (e.g., 50N-200N, 0.5s interval). The shaking test simulates vehicle body shaking at different frequencies (e.g., 5-15Hz sine waves). Electronic triggering is signal injection triggering, simulating the movement of a human heat source around the vehicle using infrared signals and generating reflected waveforms of approaching obstacles using ultrasonic signals. The aforementioned control parameters are obtained through a preset test scenario matrix. This matrix is ​​pre-constructed based on specific test scenarios and includes various physical triggering parameters, environmental parameters, signal parameters, and other parameters corresponding to different test scenarios. This matrix allows for the generation of corresponding scenario test combinations, such as: heavy rain environment + moderate-force impact on the car door + simulated human approach.

[0086] The response monitoring phase involves vehicle response and sensor data storage. When the vehicle responds, it is necessary to record the alarm trigger time, video recording start and end time, and the activation status of the headlights / horn. Sensor data storage includes vibration waveforms, camera images, raw radar signal data, and other relevant data.

[0087] The test is judged based on the vehicle response results and relevant threshold judgment conditions. Threshold judgment conditions may include: whether the time difference between the alarm delay from triggering to the cloud receiving the alarm is less than 1.5 seconds; video recording integrity analysis; whether the video frame loss rate and frame loss due to screen occlusion are less than 3 frames / second; and whether the number of false triggers in non-threat scenarios is less than 0.1%.

[0088] The results evaluation phase mainly involves report generation and problem analysis. Report generation automatically marks items as passed or failed by comparing measured data with preset thresholds. When problems occur, problem analysis is required to provide corresponding suggestions and parameter adjustment strategies to update and adjust the triggering phase. For example, if vibration triggering is normal but video is lost, check the camera's waterproof performance; if the false alarm rate is high, it is recommended to adjust the ultrasonic sensor sensitivity threshold.

[0089] As can be seen from the above vehicle test control method, this method uses a robotic arm and a signal simulator to simulate various manual test scenarios, and combines an environmental simulation chamber to simulate various environmental conditions. Then, it tests the multi-sensor collaborative triggering mechanism of the vehicle through the vehicle's alarm response data, thereby solving the problems of low efficiency of manual testing, single test scenarios, and lack of sensor collaborative verification methods in the existing technology.

[0090] Corresponding to the above embodiments of the vehicle test control method, this invention also provides a vehicle test control system, such as... Figure 9 As shown, the system includes: Test preparation module 910: is used to construct a test scenario matrix corresponding to the vehicle under test based on a preset environment simulation chamber, robotic arm and signal simulator, and to determine the environmental setting parameters and trigger test parameters corresponding to the vehicle under test according to the test scenario matrix; Trigger control module 920: After the environment simulation chamber reaches the test environment corresponding to the environmental setting parameters, it uses the trigger test parameters to control the robotic arm to contact the body of the vehicle under test, and uses the trigger test parameters to control the signal simulator to generate obstacle simulation signals to the vehicle under test; Response monitoring module 930: Used to monitor and acquire alarm events after the vehicle under test responds to the test parameters in real time, and determine the alarm response data of the vehicle under test based on the alarm trigger time, alarm video recording parameters and alarm accuracy parameters corresponding to the alarm event; Result generation module 940: Used to determine the test threshold corresponding to the test environment based on the test scenario matrix, and to determine the test result corresponding to the vehicle under test based on the comparison result between the alarm response data and the test threshold.

[0091] As can be seen from the above vehicle test control system, the system uses a robotic arm and a signal simulator to simulate various manual test scenarios, and combines an environmental simulation chamber to simulate various environmental conditions. Then, it tests the multi-sensor collaborative triggering mechanism of the vehicle through the vehicle's alarm response data, thereby solving the problems of low efficiency of manual testing, single test scenarios, and lack of sensor collaborative verification methods in the existing technology.

[0092] The vehicle test control system provided in this embodiment of the invention has the same implementation principle and technical effects as the aforementioned vehicle test control method embodiment. For the sake of brevity, any parts not mentioned in the system embodiment can be referred to the corresponding content in the aforementioned vehicle test control method embodiment.

[0093] This embodiment also provides an electronic device, the structural schematic diagram of which is shown below. Figure 10 As shown, the device includes a processor 101 and a memory 102; wherein, the memory 102 is used to store one or more computer instructions, which are executed by the processor to implement the steps of the above-described vehicle test control method.

[0094] Figure 10 The electronic device shown also includes a bus 103 and a communication interface 104, with the processor 101, communication interface 104 and memory 102 connected via the bus 103.

[0095] The memory 102 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. The bus 103 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 10 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0096] The communication interface 104 is used to connect to at least one user terminal and other network units through a network interface, and to send encapsulated IPv4 packets or IPv4 packets to the user terminal through the network interface.

[0097] Processor 101 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 101 or by instructions in software form. The processor 101 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this disclosure can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 102, and processor 101 reads the information in memory 102 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

Claims

1. A vehicle testing control method, characterized in that, The method includes: Test preparation steps: Construct a test scenario matrix corresponding to the vehicle under test based on the preset environment simulation chamber, robotic arm and signal simulator, and determine the environmental setting parameters and trigger test parameters corresponding to the vehicle under test according to the test scenario matrix; Triggering control steps: After controlling the environment simulation chamber to reach the test environment corresponding to the environment setting parameters, the robotic arm is controlled to contact the body of the vehicle under test using the triggering test parameters, and the signal simulator is controlled to generate obstacle simulation signals to the vehicle under test using the triggering test parameters. Response monitoring steps: Monitor and acquire alarm events of the vehicle under test after responding to the trigger test parameters in real time, and determine the alarm response data of the vehicle under test based on the alarm trigger time, alarm video recording parameters and alarm accuracy parameters corresponding to the alarm events; Result generation steps: Determine the test threshold corresponding to the test environment based on the test scenario matrix, and determine the test result corresponding to the vehicle under test based on the comparison result between the alarm response data and the test threshold.

2. The vehicle testing control method according to claim 1, characterized in that, The test preparation steps include: The environmental simulation chamber, robotic arm, and signal simulator corresponding to the vehicle under test are determined; wherein, the environmental simulation chamber is used to provide the vehicle under test with simulated environmental scenarios of light, precipitation, and noise; the robotic arm is used to provide the vehicle under test with simulated trigger scenarios of knocking and shaking; and the signal simulator is used to provide the vehicle under test with simulated human body scenarios corresponding to ultrasonic signals and radar signals. After the environmental simulation chamber, the robotic arm, and the signal simulator are calibrated, the environmental parameters corresponding to the environmental simulation chamber, the trigger parameters corresponding to the robotic arm, and the signal parameters corresponding to the signal simulator are obtained according to the preset benchmark test environment. Based on the environmental parameters, the triggering parameters, and the signal parameters, the test scenario matrix corresponding to the vehicle under test in the benchmark test environment is determined; Obtain the target test environment corresponding to the vehicle under test, and use the test scenario matrix to determine the environmental parameters, trigger parameters and signal parameters corresponding to the target test environment; The environmental setting parameters corresponding to the vehicle under test are determined based on the environmental parameters, and the trigger test parameters corresponding to the vehicle under test are determined based on the trigger parameters and the signal parameters.

3. The vehicle testing control method according to claim 1, characterized in that, The trigger control steps include: After the vehicle under test is placed in the environmental simulation chamber, the target light intensity, target precipitation and target noise value corresponding to the environmental simulation chamber are determined based on the environmental setting parameters, and the target test environment corresponding to the vehicle under test is determined based on the target light intensity, the target precipitation and the target noise value. Obtain the trigger test parameters corresponding to the environment setting parameters under the target test environment, and determine the trigger control parameters of the robotic arm and the signal control parameters corresponding to the signal simulator based on the trigger test parameters; After the environment simulation chamber is controlled to reach the target test environment using the environment setting parameters, the robotic arm is controlled to contact the body of the vehicle under test using the trigger control parameters, and the signal simulator is controlled to generate obstacle simulation signals to the vehicle under test using the signal control parameters.

4. The vehicle testing control method according to claim 3, characterized in that, The steps of controlling the environment simulation chamber to reach the target test environment using the environment setting parameters, controlling the robotic arm to contact the vehicle body using the trigger control parameters, and controlling the signal simulator to generate obstacle simulation signals to the vehicle body using the signal control parameters include: The environmental setting parameters are used to control the environmental simulation chamber to achieve the target light intensity, target precipitation, and target noise value corresponding to the target test environment; The knocking frequency and knocking force of the robotic arm are determined based on the trigger control parameters, and the robotic arm is controlled to contact the vehicle under test according to the knocking frequency and the knocking force using the trigger control parameters. Based on the signal control parameters, the infrared signal and ultrasonic signal corresponding to the signal simulator are determined. The signal control parameters are used to control the signal simulator to emit the infrared signal and the ultrasonic signal to the vehicle under test, respectively. The infrared signal is used to simulate a human heat source approaching the vehicle under test, and the ultrasonic signal is used to simulate an obstacle approaching the vehicle under test.

5. The vehicle testing control method according to claim 1, characterized in that, The response monitoring steps include: Based on the trigger test parameters, determine the vehicle body contact event corresponding to the robotic arm and the obstacle approach event corresponding to the signal simulator; Real-time monitoring of the first alarm event corresponding to the vehicle body contact event and the second alarm event corresponding to the obstacle approach event of the vehicle under test in the test environment; Acquire alarm time data, alarm video recording data, and alarm count data corresponding to the first alarm event and the second alarm event, and acquire real-time sensor data of the vehicle under test under the trigger test parameters; The alarm trigger time corresponding to the alarm event is determined based on the alarm time data, the alarm video recording parameters corresponding to the alarm event are determined based on the alarm video recording data and the real-time sensor data, and the alarm accuracy rate corresponding to the alarm event is determined based on the alarm count data. The alarm response data corresponding to the vehicle under test is determined based on the alarm trigger time, the alarm video recording parameters, and the alarm accuracy parameters.

6. The vehicle testing control method according to claim 5, characterized in that, Acquiring real-time sensor data of the vehicle under test under the triggered test parameters includes: Based on the trigger test parameters, determine one or more of the following sensors in the vehicle under test: camera, vibration sensor, ultrasonic radar, millimeter-wave radar, light sensor, and horn sensor. The real-time sensor data of the vehicle under test is determined based on the video and image data collected by the camera, the waveform data collected by the vibration sensor, the radar wave data corresponding to the ultrasonic radar and the millimeter-wave radar, the light status data corresponding to the light sensor, and the horn activation data corresponding to the horn sensor.

7. The vehicle testing control method according to claim 1, characterized in that, The result generation step includes: Based on the test scenario matrix, determine the alarm delay threshold, video frame loss threshold, and false trigger threshold corresponding to the test environment; Based on the alarm response data, obtain the alarm trigger time, alarm video recording parameters, and alarm accuracy of the vehicle under test; The following comparison results are obtained: a first comparison result between the alarm trigger time and the alarm delay threshold; a second comparison result between the alarm video recording parameters and the video frame loss threshold; and a third comparison result between the alarm accuracy and the false trigger threshold. The test results for the vehicle under test are determined based on the first comparison result, the second comparison result, and the third comparison result.

8. The vehicle testing control method according to claim 1, characterized in that, Prior to the trigger control step, the method further includes: Vehicle control steps: When the power battery charge of the vehicle under test is greater than a preset threshold, the vehicle under test is controlled to enter a sleep state; wherein, the standby power consumption of the vehicle under test is lowest in the sleep state.

9. A vehicle test control system, characterized in that, The system includes: Test preparation module: used to construct a test scenario matrix corresponding to the vehicle under test based on a preset environment simulation chamber, robotic arm and signal simulator, and to determine the environmental setting parameters and trigger test parameters corresponding to the vehicle under test according to the test scenario matrix; Trigger control module: used to control the environment simulation chamber to reach the test environment corresponding to the environment setting parameters, and then use the trigger test parameters to control the robotic arm to contact the body of the vehicle under test, and use the trigger test parameters to control the signal simulator to generate obstacle simulation signals to the vehicle under test; Response monitoring module: used to monitor and acquire alarm events of the vehicle under test after responding to the trigger test parameters in real time, and determine the alarm response data of the vehicle under test according to the alarm trigger time, alarm video recording parameters and alarm accuracy parameters corresponding to the alarm events; Result generation module: used to determine the test threshold corresponding to the test environment based on the test scenario matrix, and to determine the test result corresponding to the vehicle under test based on the comparison result between the alarm response data and the test threshold.

10. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the steps of the vehicle test control method according to any one of claims 1 to 8.

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