Vehicle occupant protection system self-diagnosis method and device

Abstract

The present invention discloses a vehicle occupant protection system self-diagnosis method and device, and relates to the field of vehicle safety technology. The present invention inputs the real control parameters of the vehicle into the AEB digital twin model, calculates the virtual second vehicle motion response parameter and the second AEB system response parameter, calculates the correlation between the real first vehicle motion response parameter of the vehicle and the virtual second vehicle motion response parameter, and the correlation between the real first AEB system response parameter of the vehicle and the virtual second AEB system response parameter, and can judge whether the AEB system is abnormal according to the correlation between the real response parameter and the virtual response parameter, thereby realizing the AEB system self-diagnosis function based on the digital twin technology.

Description

Technical Field

[0001] The present invention relates to the field of vehicle safety technology, and in particular to a self-diagnosis method and device for a vehicle occupant protection system. Background Art

[0002] The vehicle occupant protection system includes the AEB (Autonomous Emergency Braking) system and the MSB (Motorized Seat Belt) system. The AEB system can automatically brake when the distance between the vehicle and the obstacle in front is less than the safe distance, thereby avoiding a collision; the MSB system can protect the occupants after a collision occurs; the AEB system and the MSB system work together to protect the occupants.

[0003] However, the AEB system cannot always provide good occupant protection. When its safety performance declines, this abnormal performance decline needs to be discovered in a timely manner. Therefore, the industry needs to consider how to detect whether a vehicle's AEB system is abnormal. Summary of the invention

[0004] The present invention solves the technical problem of how to detect whether a vehicle AEB system is abnormal by providing a vehicle occupant protection system self-diagnosis method and device.

[0005] On the one hand, the present invention provides the following technical solutions:

[0006] A vehicle occupant protection system self-diagnosis method, comprising:

[0007] Obtaining a vehicle control parameter, a first vehicle motion response parameter, and a first AEB system response parameter within a first time period before and within a second time period after each event that triggers the AEB function;

[0008] Inputting the vehicle control parameter into the AEB digital twin model to calculate a second vehicle motion response parameter and a second AEB system response parameter;

[0009] calculating a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter;

[0010] If both the first correlation coefficient and the second correlation coefficient are higher than corresponding correlation thresholds, it is determined that the AEB system is normal;

[0011] If at least one of the first correlation coefficient or the second correlation coefficient is lower than the corresponding correlation threshold, it is determined that the AEB system is abnormal.

[0012] Optionally, the vehicle control parameters include gear position, steering, vehicle speed, steering wheel angle and vehicle distance.

[0013] Optionally, the first vehicle motion response parameter or the second vehicle motion response parameter includes vehicle relative distance, vehicle relative speed and vehicle acceleration.

[0014] Optionally, the first AEB system response parameter or the second AEB system response parameter includes AEB warning and brake pressure.

[0015] Optionally, the calculating a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter, includes:

[0016]

[0017] f[n] is the first vehicle motion response parameter, g[n] is the second vehicle motion response parameter, and R is the first correlation coefficient; or f[n] is the first AEB system response parameter, g[n] is the second AEB system response parameter, and R is the second correlation coefficient.

[0018] Optionally, the vehicle occupant protection system self-diagnosis method further includes:

[0019] Obtain the first MSB system response parameter within a first time period before each event triggering the AEB function and within a second time period after the event ends;

[0020] After calculating the first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and the second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter, the method further includes:

[0021] If both the first correlation coefficient and the second correlation coefficient are higher than the corresponding correlation threshold, the second vehicle motion response parameter is input into the MSB digital twin model to calculate a second MSB system response parameter;

[0022] calculating a third correlation coefficient between the first MSB system response parameter and the second MSB system response parameter;

[0023] If the third correlation coefficients are all higher than the corresponding correlation thresholds, it is determined that the MSB system is normal;

[0024] If at least one of the third correlation coefficients is lower than the corresponding correlation threshold, it is determined that the MSB system is abnormal.

[0025] Optionally, the first MSB system response parameter or the second MSB system response parameter includes a preload force, a preload moment, and a retraction amount.

[0026] On the other hand, the present invention also provides the following technical solutions:

[0027] A vehicle occupant protection system self-diagnosis device, comprising:

[0028] An acquisition module, used to acquire a vehicle control parameter, a first vehicle motion response parameter, and a first AEB system response parameter within a first time period before each event triggering the AEB function and within a second time period after the event ends;

[0029] a calculation module, configured to input the vehicle control parameter into the AEB digital twin model, calculate a second vehicle motion response parameter and a second AEB system response parameter; calculate a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter;

[0030] A judgment module is used to judge that the AEB system is normal if both the first correlation coefficient and the second correlation coefficient are higher than corresponding correlation thresholds; and to judge that the AEB system is abnormal if at least one of the first correlation coefficient or the second correlation coefficient is lower than the corresponding correlation threshold.

[0031] On the other hand, the present invention also provides the following technical solutions:

[0032] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any of the above-mentioned vehicle occupant protection system self-diagnosis methods is implemented.

[0033] On the other hand, the present invention also provides the following technical solutions:

[0034] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements any of the above-mentioned vehicle occupant protection system self-diagnosis methods.

[0035] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0036] The present invention inputs the vehicle's real control parameters into the AEB digital twin model, calculates a virtual second vehicle motion response parameter and a second AEB system response parameter, calculates the correlation between the vehicle's real first vehicle motion response parameter and the virtual second vehicle motion response parameter, and the correlation between the vehicle's real first AEB system response parameter and the virtual second AEB system response parameter, and can judge whether the AEB system is abnormal based on the correlation between the real response parameter and the virtual response parameter, thereby realizing the AEB system self-diagnosis function based on the digital twin technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0038] Figure 1 is a flow chart of a self-diagnosis method for a vehicle occupant protection system according to an embodiment of the present invention;

[0039] Figure 2 Schematic diagram of a self-diagnosis device for a vehicle occupant protection system in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The embodiments of the present invention solve the technical problem of how to detect whether the vehicle AEB system is abnormal by providing a vehicle occupant protection system self-diagnosis method and device.

[0041] In order to better understand the technical solution of the present invention, the technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0042] like Figure 1 As shown, the vehicle occupant protection system self-diagnosis method of this embodiment includes:

[0043] Step S1, obtaining a vehicle control parameter, a first vehicle motion response parameter, and a first AEB system response parameter within a first time period before each event triggering the AEB function and within a second time period after each event ends;

[0044] Step S2, inputting the vehicle control parameters into the AEB digital twin model, and calculating the second vehicle motion response parameters and the second AEB system response parameters;

[0045] Step S3, calculating a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter;

[0046] Step S4, if the first correlation coefficient and the second correlation coefficient are both higher than the corresponding correlation thresholds, it is determined that the AEB system is normal;

[0047] Step S5: If at least one of the first correlation coefficient or the second correlation coefficient is lower than the corresponding correlation threshold, it is determined that the AEB system is abnormal.

[0048] In step S1, the event that triggers the AEB function is mainly the detection of an obstacle in front of the vehicle. The first duration and the second duration can both be 5 seconds. Step S1 can obtain the vehicle control parameters, the first vehicle motion response parameters, and the first AEB system response parameters within a few seconds before and after the AEB system takes effect. The vehicle control parameters determine the motion state of the actual vehicle and the response state of the AEB system within a few seconds before and after the AEB system takes effect. The AEB system includes an AEB environmental perception system, an AEB decision system, and an AEB actuator system. The AEB environmental perception is the vehicle control parameters, which can include gear position, steering, vehicle speed, steering wheel angle, and vehicle distance.

[0049] In step S2, the AEB digital twin model is a simulation model consistent with the actual vehicle AEB system, which can fully simulate the functions of the AEB system, and the accuracy of the AEB digital twin model meets the requirements. The AEB digital twin model includes an AEB model, an AEB actuator model, and a vehicle dynamics model. The vehicle motion response parameter represents the motion state of the vehicle within a few seconds before and after each AEB system takes effect. The AEB system response parameter represents the response state of the AEB system within a few seconds before and after each AEB system takes effect. The vehicle control parameter determines the motion state of the vehicle and the response state of the AEB system, that is, determines the second vehicle motion response parameter and the second AEB system response parameter. The first vehicle motion response parameter includes the relative distance of the vehicle, the relative speed of the vehicle, and the acceleration of the vehicle. The relative distance of the vehicle is the distance of the vehicle relative to the obstacle in front, and the relative speed of the vehicle is the speed of the vehicle relative to the obstacle in front. Then the second vehicle motion response parameter also includes the relative distance of the vehicle, the relative speed of the vehicle, and the acceleration of the vehicle. The first AEB system response parameter includes the AEB warning and the brake pressure, then the second AEB system response parameter also includes the AEB warning and the brake pressure. The first vehicle motion response parameter and the first AEB system response parameter are both real response signals of the vehicle, and the second vehicle motion response parameter and the second AEB system response parameter are both virtual response signals obtained by simulation.

[0050] It is understandable that if the safety of the vehicle AEB system is not reduced, the correlation between the obtained second vehicle motion response parameter and the first vehicle motion response parameter should be very high, and the correlation between the second AEB system response parameter and the first AEB system response parameter should also be very high. If the correlation between the second vehicle motion response parameter and the first vehicle motion response parameter or the correlation between the second AEB system response parameter and the first AEB system response parameter is low, it can be considered that the safety of the AEB system is reduced and the AEB system is abnormal. Step S3 provides a correlation coefficient that characterizes the correlation, and step S3 may include:

[0051]

[0052] f[n] is the first vehicle motion response parameter, g[n] is the second vehicle motion response parameter, and R is the first correlation coefficient; or f[n] is the first AEB system response parameter, g[n] is the second AEB system response parameter, and R is the second correlation coefficient. Specifically, let f[n] be the vehicle relative distance and g[n] be the vehicle relative distance, and the first correlation coefficient R obtained is the correlation coefficient of the vehicle relative distance; let f[n] be the vehicle relative speed and g[n] be the vehicle relative speed, and the first correlation coefficient R obtained is the correlation coefficient of the vehicle relative speed; let f[n] be the vehicle acceleration and g[n] be the vehicle acceleration, and the first correlation coefficient R obtained is the correlation coefficient of the vehicle acceleration; let f[n] be the AEB warning and g[n] be the AEB warning, and the second correlation coefficient R obtained is the correlation coefficient of the AEB warning; let f[n] be the brake pressure and g[n] be the brake pressure, and the second correlation coefficient R obtained is the correlation coefficient of the brake pressure.

[0053] For the correlation thresholds in step S4 and step S5, the correlation thresholds corresponding to vehicle relative distance, vehicle relative speed, vehicle acceleration, AEB warning, and brake pressure may be 0.95, 0.90, 0.85, 0.95, and 0.90, respectively.

[0054] As can be seen from the above, the embodiment of the present invention inputs the real control parameters of the vehicle into the AEB digital twin model, calculates the virtual second vehicle motion response parameters and the second AEB system response parameters, calculates the correlation between the real first vehicle motion response parameters and the virtual second vehicle motion response parameters, and the correlation between the real first AEB system response parameters and the virtual second AEB system response parameters of the vehicle, and can judge whether the AEB system is abnormal based on the correlation between the real response parameters and the virtual response parameters, thereby realizing the AEB system self-diagnosis function based on digital twin technology.

[0055] As mentioned above, the vehicle occupant protection system includes the AEB system and the MSB system. Similarly, the MSB system does not always provide good occupant protection. When its safety performance decreases, it is also necessary to promptly detect the abnormal performance decrease. Therefore, the vehicle occupant protection system self-diagnosis method of the embodiment of the present invention may also include:

[0056] Obtain the first MSB system response parameter within a first time period before each event triggering the AEB function and within a second time period after the event ends;

[0057] After step S3, the vehicle occupant protection system self-diagnosis method also includes: if the first correlation coefficient and the second correlation coefficient are both higher than the corresponding correlation threshold, the second vehicle motion response parameter is input into the MSB digital twin model to calculate the second MSB system response parameter; the third correlation coefficient between the first MSB system response parameter and the second MSB system response parameter is calculated; if the third correlation coefficients are all higher than the corresponding correlation threshold, the MSB system is judged to be normal; if at least one third correlation coefficient is lower than the corresponding correlation threshold, the MSB system is judged to be abnormal.

[0058] The MSB digital twin model is a simulation model that is consistent with the MSB system of the real vehicle and can fully simulate the functions of the MSB system. The MSB digital twin model includes the MSB model, the MSB actuator model, and the vehicle and occupant motion model. The MSB system response parameters represent the response state of the MSB system within a few seconds before and after each MSB system takes effect. The vehicle's motion state determines the response state of the MSB system, that is, the second vehicle motion response parameter determines the second MSB system response parameter. After the second vehicle motion response parameter is input into the MSB digital twin model, the virtual second MSB system response parameter can be simulated. The first MSB system response parameters include preload, preload moment, and retraction amount, so the second MSB system response parameters also include preload, preload moment, and retraction amount.

[0059] It can be understood that if the safety of the vehicle's MSB system has not decreased, the correlation between the second MSB system response parameter and the first MSB system response parameter should be very high. If the correlation between the second MSB system response parameter and the first MSB system response parameter is low, it can be considered that the safety of the MSB system has decreased and the MSB system is abnormal. The correlation coefficient is used to characterize the correlation, and the third correlation coefficient is the same as the calculation formula of step S3. Let f[n] be the preload force and g[n] be the preload force, and the third correlation coefficient R obtained is the correlation coefficient of the preload force; let f[n] be the preload moment and g[n] be the preload moment, and the third correlation coefficient R obtained is the correlation coefficient of the preload moment; let f[n] be the retraction amount and g[n] be the retraction amount, and the third correlation coefficient R obtained is the correlation coefficient of the retraction amount.

[0060] like Figure 2 As shown, an embodiment of the present invention further provides a vehicle occupant protection system self-diagnosis device, comprising:

[0061] An acquisition module, used to acquire a vehicle control parameter, a first vehicle motion response parameter, and a first AEB system response parameter within a first time period before each event triggering the AEB function and within a second time period after the event ends;

[0062] A calculation module is used to input the vehicle control parameter into the AEB digital twin model to calculate a second vehicle motion response parameter and a second AEB system response parameter; calculate a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter;

[0063] The judgment module is used to judge that the AEB system is normal if both the first correlation coefficient and the second correlation coefficient are higher than the corresponding correlation threshold; and judge that the AEB system is abnormal if at least one of the first correlation coefficient or the second correlation coefficient is lower than the corresponding correlation threshold.

[0064] Furthermore, the acquisition module may also be used to acquire a first MSB system response parameter within a first time period before each event triggering the AEB function and within a second time period after each event triggering the AEB function;

[0065] The calculation module may also be used to input the second vehicle motion response parameter into the MSB digital twin model to calculate the second MSB system response parameter if both the first correlation coefficient and the second correlation coefficient are higher than the corresponding correlation threshold; calculate the third correlation coefficient between the first MSB system response parameter and the second MSB system response parameter;

[0066] The judgment module can also be used to judge that the MSB system is normal if all the third correlation coefficients are higher than the corresponding correlation threshold; and judge that the MSB system is abnormal if at least one third correlation coefficient is lower than the corresponding correlation threshold.

[0067] Based on the same inventive concept as the vehicle occupant protection system self-diagnosis method described above, an embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any one of the vehicle occupant protection system self-diagnosis methods described above are implemented.

[0068] Among them, the bus architecture (represented by the bus), the bus can include any number of interconnected buses and bridges, and the bus links various circuits including one or more processors represented by the processor and memory represented by the memory. The bus can also link various other circuits such as peripherals, voltage regulators, and power management circuits together, which are all well known in the art and are therefore not further described herein. The bus interface provides an interface between the bus and the receiver and transmitter. The receiver and transmitter can be the same element, namely a transceiver, which provides a unit for communicating with various other devices on a transmission medium. The processor is responsible for managing the bus and general processing, while the memory can be used to store data used by the processor when performing operations.

[0069] Since the electronic device introduced in the embodiment of the present invention is an electronic device used to implement the vehicle occupant protection system self-diagnosis method in the embodiment of the present invention, based on the vehicle occupant protection system self-diagnosis method introduced in the embodiment of the present invention, the technical personnel of the field can understand the specific implementation of the electronic device of the embodiment of the present invention and its various variations, so how the electronic device implements the method in the embodiment of the present invention is not described in detail here. As long as the technical personnel of the field implement the electronic device used in the vehicle occupant protection system self-diagnosis method in the embodiment of the present invention, it belongs to the scope of protection of the present invention.

[0070] Based on the same inventive concept as the above-mentioned vehicle occupant protection system self-diagnosis method, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and the computer program implements any of the above-mentioned vehicle occupant protection system self-diagnosis methods when executed by a processor.

[0071] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0072] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0073] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0074] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0075] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0076] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A vehicle occupant protection system self-diagnosis method, characterized in that: include: Obtaining a vehicle control parameter, a first vehicle motion response parameter, and a first AEB system response parameter within a first time period before and within a second time period after each event that triggers the AEB function; Inputting the vehicle control parameter into the AEB digital twin model to calculate a second vehicle motion response parameter and a second AEB system response parameter; calculating a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter; The calculating a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter, includes: f[n] is the first vehicle motion response parameter, g[n] is the second vehicle motion response parameter, and R is the first correlation coefficient; or f[n] is the first AEB system response parameter, g[n] is the second AEB system response parameter, and R is the second correlation coefficient; If both the first correlation coefficient and the second correlation coefficient are higher than corresponding correlation thresholds, it is determined that the AEB system is normal; If at least one of the first correlation coefficient or the second correlation coefficient is lower than the corresponding correlation threshold, it is determined that the AEB system is abnormal.

2. The vehicle occupant protection system self-diagnosis method according to claim 1, characterized in that: The vehicle control parameters include gear position, steering, vehicle speed, steering wheel angle and vehicle distance.

3. The vehicle occupant protection system self-diagnosis method according to claim 1, characterized in that: The first vehicle motion response parameter or the second vehicle motion response parameter includes a vehicle relative distance, a vehicle relative speed and a vehicle acceleration.

4. The vehicle occupant protection system self-diagnosis method according to claim 1, characterized in that: The first AEB system response parameter or the second AEB system response parameter includes AEB warning and brake pressure.

5. The vehicle occupant protection system self-diagnosis method according to claim 1, characterized in that: Also includes: Obtain the first MSB system response parameter within a first time period before each event triggering the AEB function and within a second time period after the event ends; After calculating the first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and the second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter, the method further includes: If both the first correlation coefficient and the second correlation coefficient are higher than the corresponding correlation threshold, the second vehicle motion response parameter is input into the MSB digital twin model to calculate a second MSB system response parameter; calculating a third correlation coefficient between the first MSB system response parameter and the second MSB system response parameter; If the third correlation coefficients are all higher than the corresponding correlation thresholds, it is determined that the MSB system is normal; If at least one of the third correlation coefficients is lower than the corresponding correlation threshold, it is determined that the MSB system is abnormal.

6. The vehicle occupant protection system self-diagnosis method according to claim 5, characterized in that: The first MSB system response parameter or the second MSB system response parameter includes a preload force, a preload moment, and a retraction amount.

7. A vehicle occupant protection system self-diagnosis device, characterized in that: include: An acquisition module, used to acquire a vehicle control parameter, a first vehicle motion response parameter, and a first AEB system response parameter within a first time period before each event triggering the AEB function and within a second time period after the event ends; a calculation module, configured to input the vehicle control parameter into the AEB digital twin model, calculate a second vehicle motion response parameter and a second AEB system response parameter; calculate a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter; The calculating a first correlation coefficient between the first vehicle motion response parameter and the second vehicle motion response parameter, and a second correlation coefficient between the first AEB system response parameter and the second AEB system response parameter, includes: f[n] is the first vehicle motion response parameter, g[n] is the second vehicle motion response parameter, and R is the first correlation coefficient; or f[n] is the first AEB system response parameter, g[n] is the second AEB system response parameter, and R is the second correlation coefficient; A judgment module is used to judge that the AEB system is normal if both the first correlation coefficient and the second correlation coefficient are higher than corresponding correlation thresholds; and to judge that the AEB system is abnormal if at least one of the first correlation coefficient or the second correlation coefficient is lower than the corresponding correlation threshold.

8. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the vehicle occupant protection system self-diagnosis method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the vehicle occupant protection system self-diagnosis method according to any one of claims 1 to 6 is implemented.

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