CN116409332A - Functional defect analysis method, device, system and readable storage medium - Google Patents
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/02—Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures
- B60W50/0205—Diagnosing or detecting failures; Failure detection models
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/02—Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures
- B60W50/0205—Diagnosing or detecting failures; Failure detection models
- B60W2050/0215—Sensor drifts or sensor failures
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The application discloses a functional defect analysis method, a device, a system and a readable storage medium, which relate to the technical field of vehicles and aim to accurately analyze reasons of functional defects. The method comprises the following steps: determining a plurality of perception characteristics associated with the target functional defect, wherein the plurality of perception characteristics are used for indicating to-be-perceived items of which the difference value of the perception data of a plurality of vehicle sensors for the same to-be-perceived item is larger than a first threshold value; determining a probability of generating a target functional defect in the presence of a first perceived characteristic of the vehicle; the first perceptual characteristic is any one of a plurality of perceptual characteristics; based on the probability of generating the target functional defect, determining a target perceived characteristic from the plurality of perceived characteristics as a trigger condition for the target functional defect, and constructing a trigger logic table for the target functional defect, the trigger logic table including at least one trigger condition and the target functional defect.
Description
Technical Field
The invention relates to the technical field of vehicles, in particular to a functional defect analysis method, a device, a system and a readable storage medium.
Background
With the rapid development of automatic driving technology, more and more sensors are carried on intelligent vehicles, and more driving convenience is brought to users, but more and more potential safety hazards are generated. The sources of the hidden troubles are all from the perception errors of various sensors in different running environments, and the automatic driving system does not appropriately reflect the perception, so that the risks of braking omission and false braking are caused.
In the related art, in order to improve the reliability of an automatic driving system, the expected functional safety of the automatic driving system can be analyzed by utilizing a design operation domain (Operational design domain, ODD), the damage event caused by the function to be analyzed is triggered, the ODD element with high coverage and the system functional defect are decomposed, and the triggering condition of the damage event is constructed by analyzing the triggering relation between the ODD element and the system functional defect, so that the triggering condition is ensured to have higher coverage. However, ODD elements are not exhaustive, and system functional defects and the hazard event triggering conditions for the ODD element construction tend to be unreliable. Therefore, how to accurately analyze the cause of the functional defect is a technical problem to be solved.
Disclosure of Invention
The invention aims to provide a functional defect analysis method, a device, a system and a readable storage medium, so as to accurately analyze the reasons of functional defects.
In a first aspect, a method for analyzing a functional defect is provided, the method comprising: determining a plurality of perception characteristics associated with the target functional defect, wherein the plurality of perception characteristics are used for indicating to-be-perceived items of which the difference value of the perception data of a plurality of vehicle sensors for the same to-be-perceived item is larger than a first threshold value; determining a probability of generating a target functional defect in the presence of a first perceived characteristic of the vehicle; the first perceptual characteristic is any one of a plurality of perceptual characteristics; based on the probability of generating the target functional defect, determining a target perceived characteristic from the plurality of perceived characteristics as a trigger condition for the target functional defect, and constructing a trigger logic table for the target functional defect, the trigger logic table including at least one trigger condition and the target functional defect.
According to the technical means, the plurality of perception characteristics associated with the target functional defect are determined, and the probability of generating the target functional defect under the condition that only the first perception characteristic exists is determined, so that the plurality of perception characteristics associated with the target functional defect can be associated, and the probability of generating the target functional defect by different perception characteristics can be reflected. Further, based on the probability of generating the target functional defect, determining the target perceived characteristic from the plurality of perceived characteristics as a trigger condition for the target functional defect, and constructing a trigger logic table for the target functional defect, the trigger logic table including at least one trigger condition and the target functional defect. The sensing characteristics are used for indicating the to-be-sensed items, in which the difference value of the sensing data of the plurality of vehicle sensors to the same to-be-sensed item is larger than the first threshold value, namely the sensing data of the plurality of vehicle sensors are abstracted to be the sensing characteristics, so that the generation reason of the target functional defect can be accurately determined.
Further, determining the target perceptual characteristic from the plurality of perceptual characteristics as a trigger condition of the target functional defect based on the probability of generating the target functional defect, comprising: and determining the first perception characteristic as a triggering condition of the target functional defect in the case that the probability of generating the target functional defect is larger than the second threshold value.
Thus, the target perception characteristic causing the target functional defect can be determined from the plurality of perception characteristics, and the triggering condition of the target functional defect can be further accurately analyzed.
Further, determining a plurality of perceptual characteristics associated with the target functional defect, comprising: acquiring sensing data of a plurality of vehicle sensors for a plurality of items to be sensed; and determining a plurality of perception characteristics associated with the target functional defect by using the fault tree analysis method and the perception data.
Therefore, the target functional defects can be decomposed to each sensor in the vehicle, the perception characteristics among the sensors are obtained, the coverage is high, and a plurality of perception characteristics related to the target functional defects can be accurately determined.
Further, the method comprises the following steps: obtaining a plurality of groups of sample data, wherein the sample data comprise sample target functional defects and corresponding sample perception data for a plurality of items to be perceived; an average difference of the perception data of a plurality of vehicle sensors of the plurality of sample target functional defects for the same item to be perceived is determined, and the average difference is determined as a first threshold.
In this way, the first threshold may be more reasonably determined from the sample data test than from human experience settings.
Further, the items to be sensed include one or more of lateral position, longitudinal position, lateral velocity, longitudinal velocity, lateral acceleration, longitudinal acceleration.
Thus, the coverage of determining the cause of the target function defect can be improved based on the multidimensional items to be perceived.
In a second aspect, there is provided a functional defect analysis apparatus, the apparatus comprising: a determining unit, a processing unit; the determining unit is used for determining a plurality of perception characteristics associated with the target functional defects, wherein the plurality of perception characteristics are used for indicating to-be-perceived items of which the difference value of the perception data of the plurality of vehicle sensors for the same to-be-perceived item is larger than a first threshold value; a determining unit for determining a probability of generating a target functional defect in case only the first perceptual characteristic is present; the first perceptual characteristic is any one of a plurality of perceptual characteristics; and the processing unit is used for determining the target perception characteristic from the plurality of perception characteristics as a trigger condition of the target functional defect based on the probability of generating the target functional defect, and constructing a trigger logic table of the target functional defect, wherein the trigger logic table comprises at least one trigger condition and the target functional defect.
Further, the determining unit is specifically configured to: and determining the first perception characteristic as a triggering condition of the target functional defect in the case that the probability of generating the target functional defect is larger than the second threshold value.
Further, the determining unit is specifically configured to: acquiring sensing data of a plurality of vehicle sensors for a plurality of items to be sensed; and determining a plurality of perception characteristics associated with the target functional defect by using the fault tree analysis method and the perception data.
Further, the device also comprises an acquisition unit; the acquisition unit is used for acquiring a plurality of groups of sample data, wherein the sample data comprise sample target functional defects and corresponding sample perception data for a plurality of items to be perceived; and the determining unit is used for determining average difference values of the sensing data of the plurality of vehicle sensors of the plurality of sample target functional defects for the same item to be sensed, and determining the average difference values as a first threshold value.
Further, the items to be sensed include one or more of lateral position, longitudinal position, lateral velocity, longitudinal velocity, lateral acceleration, longitudinal acceleration.
In a third aspect, a functional defect analysis system is provided, the functional defect analysis system comprising analysis means for performing the method as in the first aspect or in any of the possible designs of the first aspect.
In a fourth aspect, there is provided a functional defect analyzing apparatus including: a processor; a memory for storing processor-executable instructions; the processor is configured to execute instructions, the functions performed in the first aspect or any of the possible designs of the first aspect.
In a fifth aspect, there is provided a functional defect analysis apparatus that can realize the functions performed by the functional defect analysis apparatus in the above aspects or in each possible design, the functions being realized by hardware, such as: in one possible design, the functional defect analysis device may include: a processor and a communication interface, the processor being operable to support the functionality involved in the functionality of the functionality defect analysis apparatus to implement the first aspect or any one of the possible designs of the first aspect.
In yet another possible design, the functional defect analysis device may further include a memory for holding computer-executable instructions and data necessary for the functional defect analysis device. When the functional defect analysis device is operated, the processor executes the computer-executable instructions stored in the memory to cause the functional defect analysis device to perform any one of the possible functional defect analysis methods of the first aspect or the first aspect.
In a sixth aspect, a computer readable storage medium is provided, which may be a readable non-volatile storage medium, the computer readable storage medium storing computer instructions or a program which, when run on a computer, cause the computer to perform the above first aspect or any one of the possible functional defect analysis methods of the above aspects.
In a seventh aspect, there is provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the functional defect analysis method of the first aspect or any one of the possible designs of the aspects.
The invention has the beneficial effects that:
(1) According to the technical means, the plurality of perception characteristics associated with the target functional defect are determined, and the probability of generating the target functional defect under the condition that only the first perception characteristic exists is determined, so that the plurality of perception characteristics associated with the target functional defect can be associated, and the probability of generating the target functional defect by different perception characteristics can be reflected. Further, based on the probability of generating the target functional defect, determining the target perceived characteristic from the plurality of perceived characteristics as a trigger condition for the target functional defect, and constructing a trigger logic table for the target functional defect, the trigger logic table including at least one trigger condition and the target functional defect. The sensing characteristics are used for indicating the to-be-sensed items, in which the difference value of the sensing data of the plurality of vehicle sensors to the same to-be-sensed item is larger than the first threshold value, namely the sensing data of the plurality of vehicle sensors are abstracted to be the sensing characteristics, so that the generation reason of the target functional defect can be accurately determined.
(2) Thus, the target perception characteristic causing the target functional defect can be determined from the plurality of perception characteristics, and the triggering condition of the target functional defect can be further accurately analyzed.
(3) The target functional defects can be decomposed to each sensor in the vehicle, the perception characteristics among the sensors are obtained, the coverage is high, and a plurality of perception characteristics associated with the target functional defects can be accurately determined.
(4) The first threshold may be determined more reasonably from sample data testing than from human experience settings.
(5) Based on the multidimensional items to be perceived, the coverage of determining the cause of the target function defect can be improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application and do not constitute an undue limitation on the application.
Fig. 1 is a schematic structural diagram of a fault tree according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of a functional defect analysis system according to an embodiment of the present disclosure;
FIG. 3 is a schematic structural diagram of a functional defect analysis device according to an embodiment of the present disclosure;
FIG. 4 is a schematic flow chart of a functional defect analysis method according to an embodiment of the present disclosure;
FIG. 5 is a flowchart illustrating another method for analyzing functional defects according to an embodiment of the present disclosure;
FIG. 6 is a schematic structural diagram of yet another fault tree according to an embodiment of the present disclosure;
FIG. 7 is a schematic structural diagram of another fault tree according to an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of another functional defect analysis device according to an embodiment of the present application.
Detailed Description
In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with aspects of embodiments of the present application as detailed in the accompanying claims.
It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, and/or components.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present invention by way of illustration, and only the components related to the present invention are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
With the rapid development of automatic driving technology, more and more sensors are carried on intelligent vehicles, and more driving convenience is brought to users, but more and more potential safety hazards are generated. The sources of the hidden troubles are all from the perception errors of various sensors in different running environments, and the automatic driving system does not appropriately reflect the perception, so that the risks of braking omission and false braking are caused.
In the related art, in order to improve the reliability of the automatic driving system, the expected functional safety of the automatic driving system can be analyzed by utilizing the ODD, the damage event caused by the function to be analyzed is triggered, the ODD element with high coverage and the system functional defect are decomposed, and the triggering condition of the damage event is constructed by analyzing the triggering relationship between the ODD element and the system functional defect, so that the triggering condition is ensured to have higher coverage. However, ODD elements are not exhaustive, and system functional defects and the hazard event triggering conditions for the ODD element construction tend to be unreliable. Therefore, how to accurately analyze the cause of the functional defect is a technical problem to be solved.
In view of this, an embodiment of the present application provides a method for analyzing a functional defect, including: determining a plurality of perception characteristics associated with the target functional defect, wherein the plurality of perception characteristics are used for indicating to-be-perceived items of which the difference value of the perception data of a plurality of vehicle sensors for the same to-be-perceived item is larger than a first threshold value; determining a probability of generating a target functional defect in the presence of only the first perceptual characteristic; the first perceptual characteristic is any one of a plurality of perceptual characteristics; based on the probability of generating the target functional defect, determining a target perceived characteristic from the plurality of perceived characteristics as a trigger condition for the target functional defect, and constructing a trigger logic table for the target functional defect, the trigger logic table including at least one trigger condition and the target functional defect.
The method provided in the embodiments of the present application will be described in detail below with reference to the accompanying drawings.
For a clearer understanding of the present application, a brief description will be first provided of what is relevant to the present application.
The fault tree analysis (fault tree analysis, FTA) method is an important method for evaluating the reliability and safety of complex systems. For one fault scenario (also referred to as a fault phenomenon), a plurality of fault root causes are corresponding, and the fault root cause of the fault scenario can be determined by the FTA method. One way of FTA method is to determine the root cause of a fault through a fault tree. Referring to fig. 1, taking "target functional defect" as the top layer, constructing branches of a fault tree, including: sensor a, sensor B, etc., each of which may detect a plurality of sensed data. For example, attribute 1, attribute 2, and the like may be included.
It should be noted that, the functional defect analysis system described in the embodiments of the present application is for more clearly describing the technical solution of the embodiments of the present application, and does not constitute a limitation on the technical solution provided in the embodiments of the present application, and those skilled in the art can know that, with the evolution of the functional defect analysis system and the appearance of other functional defect analysis systems, the technical solution provided in the embodiments of the present application is equally applicable to similar technical problems.
Fig. 2 is a schematic diagram of a functional defect analysis system 10 according to an embodiment of the present application, and as shown in fig. 2, the functional defect analysis system 10 may include a functional defect analysis device (hereinafter referred to as an analysis device) 11 and a database 12. The analysis means 11 are connected to a database 12. For example, the analysis device 11 and the database 12 may be connected by wireless or wired connection, which is not limited in the embodiment of the present invention.
The analysis device 11 according to the embodiment of the present application may be an operator background analysis device, a server, a computer, or the like. The server may be a single server, or may be a server cluster formed by a plurality of servers. In some implementations, the server cluster may also be a distributed cluster. The embodiment of the present application is not limited to the specific technique, specific number, and specific apparatus configuration employed for the analysis device 11.
The database 12 of the terminal device in the embodiment of the present application may be a hazard event road test database, etc., and the embodiment of the present application does not limit the specific technology, the specific number and the specific device configuration adopted in the database 12.
In different application scenarios, the analysis device 11 and the database 12 may be independent devices, or may be integrated in the same device. The embodiment of the present invention is not particularly limited thereto.
It should be noted that fig. 2 is only an exemplary frame diagram, and names of the respective modules included in fig. 2 are not limited, and other modules may be included in addition to the functional modules shown in fig. 2, which is not limited in this embodiment of the present application.
In particular, the apparatus of fig. 2 may take the form of the constituent structure shown in fig. 3 or may include the components shown in fig. 2. Fig. 3 is a schematic structural diagram of a functional defect analysis device 200 according to an embodiment of the present application, where the functional defect analysis device 200 may be the analysis device 11 in the functional defect analysis system, or the functional defect analysis device 200 may be a chip or a system on a chip in the analysis device 11. As shown in fig. 3, the functional defect analyzing apparatus 200 includes a processor 201, a communication interface 202, and a communication line 203.
Further, the functional defect analysis device 200 may further include a memory 204. The processor 201, the memory 204, and the communication interface 202 may be connected by a communication line 203.
The processor 201 is a CPU, general-purpose processor, network processor (network processor, NP), digital signal processor (digital signal processing, DSP), microprocessor, micro-analysis device, programmable logic device (programmable logic device, PLD), or any combination thereof. The processor 201 may also be other devices with processing functions, such as, without limitation, circuits, devices, or software modules.
A communication line 203 for transmitting information between the respective components included in the functional defect analysis apparatus 200.
The memory 204 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device capable of storing static information and/or instructions, a random access memory (random access memory, RAM) or other type of dynamic storage device capable of storing information and/or instructions, an EEPROM, a CD-ROM (compact disc read-only memory) or other optical disk storage, an optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, etc.
It should be noted that the memory 204 may exist separately from the processor 201 or may be integrated with the processor 201. Memory 204 may be used to store instructions or program code or some data, etc. The memory 204 may be located inside the functional defect analysis device 200 or outside the functional defect analysis device 200, and is not limited. The processor 201 is configured to execute instructions stored in the memory 204 to implement a method for adjusting computing resources according to the following embodiments of the present application.
In one example, processor 201 may include one or more CPUs, such as CPU0 and CPU1 in fig. 3.
As an alternative implementation, the functional defect analysis device 200 includes a plurality of processors, for example, the processor 205 may be included in addition to the processor 201 in fig. 3.
It should be noted that the constituent structures shown in fig. 3 do not constitute limitations of the respective apparatuses in fig. 2, and that the respective analysis apparatuses in fig. 2 may include more or less components than those shown in fig. 3, or may combine some components, or may be arranged differently, in addition to those shown in fig. 3.
In the embodiment of the application, the chip system may be formed by a chip, and may also include a chip and other discrete devices.
Further, actions, terms, etc. referred to between embodiments of the present application may be referred to each other without limitation. In the embodiment of the present application, the name of the message or the name of the parameter in the message, etc. interacted between the devices are only an example, and other names may also be adopted in the specific implementation, and are not limited.
The following describes a method for analyzing a functional defect according to an embodiment of the present application with reference to the functional defect analyzing system shown in fig. 2.
The embodiment of the present application will be described by taking an example of application to an analysis device, as shown in fig. 4, the method includes the following steps S301 to S303:
s301, determining a plurality of perception characteristics associated with the target functional defects by the analysis device.
The target functional defects may include, for example, a vehicle being in adaptive cruise (adaptive ccruise control, ACC) and a vehicle being subject to false braking, a vehicle being subject to missed braking, and the like.
The plurality of perception characteristics are used for indicating to-be-perceived items, wherein the difference value of the perception data of the plurality of vehicle sensors for the same to-be-perceived item is larger than a first threshold value. For example, the plurality of vehicle sensors may include cameras, radars (e.g., may be millimeter wave radars), and the like. The item to be sensed may comprise one or more of a lateral position, a longitudinal position, a lateral velocity, a longitudinal velocity, a lateral acceleration, a longitudinal acceleration.
As a possible implementation manner, when the vehicle has the target functional defect, the analysis device may acquire sensing data of a plurality of vehicle sensors from a background control data record of the vehicle, compare sensing data of the same item to be sensed by the plurality of vehicle sensors to obtain a comparison result, and further determine a plurality of sensing characteristics associated with the target functional defect according to the comparison result.
For example, in the comparison result, if the difference between the sensing data of the plurality of vehicle sensors for the same item to be sensed is greater than the first threshold, the analysis device determines that the item to be sensed is a sensing characteristic.
It should be noted that the first threshold values of different to-be-sensed items may be the same value or different values. For example, where the plurality of vehicle sensors includes cameras, millimeter wave radars, and the items to be sensed include lateral position, longitudinal position, lateral speed, longitudinal speed, lateral acceleration, longitudinal acceleration, the plurality of sensing characteristics may be as shown in table 1 below:
TABLE 1 schematic representation of perceptual properties
Wherein the numbers in the table may be used to represent a first threshold for different items to be perceived
It should be noted that the data of table 1 are only exemplary. Other perceptual features may also be included in embodiments of the present application, without limitation.
S302, the analysis device determines the probability of generating the target function defect under the condition that the first perception characteristic exists in the vehicle.
Wherein the first perceptual characteristic is any one of a plurality of perceptual characteristics.
As a possible implementation manner, the analysis device may configure the first sensing characteristics for the plurality of test vehicles, and perform a driving test on the test vehicles configured with the first sensing characteristics to obtain a driving test result, and further, the analysis device may determine, according to the driving test result, a probability of generating the target functional defect under the condition that the first sensing characteristics exist in the vehicles.
The driving test result includes the numbers of the test vehicles, and whether the target functional defect occurs in each numbered test vehicle, and the analysis device may determine the probability of generating the target functional defect according to the ratio of the number of the test vehicles in which the target functional defect occurs to the total number of the test vehicles.
In some embodiments, the analysis device may further determine a probability of generating the target functional defect in a case where false detection of the vehicle sensor occurs, and the sensed data of the vehicle sensor for the item to be sensed does not satisfy the kinematic integral relationship, respectively.
S303, the analysis device determines the target perception characteristic from the plurality of perception characteristics as a trigger condition of the target functional defect based on the probability of generating the target functional defect, and constructs a trigger logic table of the target functional defect.
Wherein the trigger logic table includes at least one trigger condition and a target functional defect.
As a possible implementation, the analysis means may determine the first perceptual characteristic as a trigger condition of the target functional defect if the probability of generating the target functional defect is greater than a second threshold.
For example, when the target functional defect is that the vehicle is braked by mistake, the plurality of vehicle sensors comprise a camera and a millimeter wave radar, and the items to be sensed comprise a transverse position, a longitudinal position, a transverse speed, a longitudinal speed, a transverse acceleration and a longitudinal acceleration, the logic table for triggering the braking by mistake can be as shown in the following table 2:
table 2 false brake trigger logic table
The first perceptual characteristic may be a triggering condition 1, and the triggering condition 1 may be used to indicate that a difference between the millimeter wave radar and the perceived data of the camera detection longitudinal speed is greater than a first threshold.
It should be noted that the data of table 2 are merely exemplary. Other triggering conditions may also be included in embodiments of the present application, without limitation.
It will be appreciated that determining the target perceptual characteristic that causes the target functional defect from a plurality of perceptual characteristics may more accurately analyze the triggering condition of the target functional defect. In addition, the coverage of determining the cause of the target function defect can be improved based on the multidimensional items to be perceived.
In some embodiments, the analysis device may further determine a false braking trigger logic table based on the perceived characteristics when false detection of the vehicle sensor occurs, and the perceived data of the vehicle sensor for the item to be perceived does not satisfy the kinematic integral relationship.
For example, the false brake trigger logic table may also be as shown in table 3 below:
table 3 false brake trigger logic table
It should be noted that the data of table 3 are merely exemplary. Other triggering conditions may also be included in embodiments of the present application, without limitation.
The triggering condition 2 indicates that false detection occurs on the camera, and the sensing data of the longitudinal speed detected by the millimeter wave radar does not meet the kinematic integral relation. The triggering condition 3 indicates that the sensing data of the longitudinal speed detected by the camera does not meet the kinematic integral relation, and the millimeter wave radar is subjected to false detection. The triggering condition 4 indicates that the camera and the millimeter wave radar are simultaneously subjected to false detection.
Based on the technical scheme provided by the application, a plurality of perception characteristics associated with the target functional defects are determined, and the probability of generating the target functional defects under the condition that the first perception characteristics exist is determined, so that the plurality of perception characteristics associated with the target functional defects can be associated and generated, and the probability of generating the target functional defects by different perception characteristics is reflected. Further, based on the probability of generating the target functional defect, determining the target perceived characteristic from the plurality of perceived characteristics as a trigger condition for the target functional defect, and constructing a trigger logic table for the target functional defect, the trigger logic table including at least one trigger condition and the target functional defect. The sensing characteristics are used for indicating the to-be-sensed items, in which the difference value of the sensing data of the plurality of vehicle sensors to the same to-be-sensed item is larger than the first threshold value, namely the sensing data of the plurality of vehicle sensors are abstracted to be the sensing characteristics, so that the generation reason of the target functional defect can be accurately determined.
In one possible embodiment, as shown in fig. 5, in order to determine a plurality of perceptual characteristics associated with the target functional defect, the functional defect analysis method of the present application may further include the following S401-S402.
S401, the analysis device acquires sensing data of a plurality of vehicle sensors for a plurality of items to be sensed.
The flap signal is used for indicating whether a flap of the external power supply interface is in a closed state or not.
As a possible implementation, the analysis device may obtain the perception data of the plurality of vehicle sensors for the plurality of items to be perceived from a database communicatively connected to the analysis device.
As a further possible implementation, the analysis device may obtain perception data of a plurality of vehicle sensors for a plurality of items to be perceived from a vehicle communicatively connected to the analysis device.
S402, the analysis device determines a plurality of perception characteristics associated with the target functional defects by using the fault tree analysis method and the perception data.
For example, as shown in fig. 6, the analysis device may take the vehicle false brake as the top layer, and construct branches of the fault tree, including: camera, millimeter wave radar. The perceptual features obtained along the camera branches include: the difference value of the sensing data of the longitudinal speed detected by the millimeter wave radar and the camera is larger than a first threshold value, the difference value of the sensing data of the transverse speed detected by the millimeter wave radar and the camera is larger than a first threshold value, and the like.
As another example, as shown in fig. 7, the analysis device may take the vehicle false brake as a top layer, and construct a branch of the fault tree, including: camera, millimeter wave radar. The perceptual features obtained along the camera branches include: false detection of the camera, unsatisfied kinematic integral relation of the longitudinal speed detected by the camera, and the like. The perceptual features obtained along the millimeter wave radar branch include: false detection occurs in the millimeter wave radar, and the longitudinal speed detected by the millimeter wave radar does not meet the kinematic integral relation.
Therefore, the target functional defects can be decomposed to each sensor in the vehicle, the perception characteristics among the sensors are obtained, the coverage is high, and a plurality of perception characteristics related to the target functional defects can be accurately determined.
In one possible embodiment, to determine the first threshold, the method for analyzing a functional defect of the present application may further include S501 to S502 described below.
S501, the analysis device acquires a plurality of groups of sample data.
The sample data comprises sample target functional defects and corresponding sample perception data for a plurality of items to be perceived.
S502, the analysis device determines average difference values of sensing data of a plurality of vehicle sensors of a plurality of sample target functional defects for the same item to be sensed, and determines the average difference values as a first threshold value.
For example, the sample target functional defect is false braking, the plurality of vehicle sensors include cameras and millimeter wave radars, and the item to be sensed is longitudinal speed.
If the plurality of sets of sample data include sample 1, sample 2, and sample 3, and the values of the sensing data of the cameras and the millimeter wave radar in sample 1, sample 2, and sample 3 for the longitudinal speed are respectively 5, 6, and 4, the analysis device may have a first threshold value of 5.
In this way, the first threshold may be more reasonably determined from the sample data test than from human experience settings.
The various schemes in the embodiments of the present application may be combined on the premise of no contradiction.
The embodiment of the present application may divide the functional modules or functional units of the functional defect analysis apparatus according to the above method example, for example, each functional module or functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated modules may be implemented in hardware, or in software functional modules or functional units. The division of the modules or units in the embodiments of the present application is merely a logic function division, and other division manners may be implemented in practice.
In the case of dividing the respective functional modules by the respective functions, fig. 8 shows a schematic configuration of a functional defect analyzing apparatus 600, which may be a server or a chip applied to the server, and which may be used to perform the functions of the server as described in the above embodiments. The functional defect analyzing apparatus shown in fig. 8 may include: a determination unit 601, a processing unit 602; a determining unit 601, configured to determine a plurality of perception characteristics associated with the target functional defect, where the plurality of perception characteristics are used to indicate to-be-perceived items, where a difference between perception data of a plurality of vehicle sensors for a same to-be-perceived item is greater than a first threshold; a determining unit 601, configured to determine a probability of generating a target functional defect in the case where only the first perceptual characteristic is present; the first perceptual characteristic is any one of a plurality of perceptual characteristics; the processing unit 602 is configured to determine, based on a probability of generating the target functional defect, the target perceived characteristic from the plurality of perceived characteristics as a trigger condition for the target functional defect, and construct a trigger logic table for the target functional defect, where the trigger logic table includes at least one trigger condition and the target functional defect.
Further, the determining unit 601 is specifically configured to: and determining the first perception characteristic as a triggering condition of the target functional defect in the case that the probability of generating the target functional defect is larger than the second threshold value.
Further, the determining unit 601 is specifically further configured to: acquiring sensing data of a plurality of vehicle sensors for a plurality of items to be sensed; and determining a plurality of perception characteristics associated with the target functional defect by using the fault tree analysis method and the perception data.
Further, the apparatus further comprises an acquisition unit 603; an obtaining unit 603, configured to obtain a plurality of sets of sample data, where the sample data includes a sample target functional defect and corresponding sample sensing data for a plurality of items to be sensed; a determining unit 601, configured to determine average differences of sensing data of a plurality of vehicle sensors of a plurality of sample target functional defects for a same item to be sensed, and determine the average differences as a first threshold.
Further, the items to be sensed include one or more of lateral position, longitudinal position, lateral velocity, longitudinal velocity, lateral acceleration, longitudinal acceleration.
Embodiments of the present application also provide a computer-readable storage medium. All or part of the flow in the above method embodiments may be implemented by a computer program to instruct related hardware, where the program may be stored in the above computer readable storage medium, and when the program is executed, the program may include the flow in the above method embodiments. The computer readable storage medium may be the functional defect analysis device of any of the foregoing embodiments or an internal storage unit of the analysis device (including the data transmitting side and/or the data receiving side), such as a hard disk or a memory of the functional defect analysis device. The computer readable storage medium may be an external storage device of the terminal apparatus, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card), or the like, which are provided in the terminal apparatus. Further, the above-described computer-readable storage medium may further include both the internal storage unit and the external storage device of the above-described functional defect analysis apparatus. The computer-readable storage medium is used for storing the computer program and other programs and data required by the functional defect analyzing apparatus. The above-described computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.
The embodiment of the application also provides a vehicle, which comprises the functional defect analysis system, the analysis device or the functional defect analysis device related to the embodiment of the method.
Further, actions, terms, etc. referred to between embodiments of the present application may be referred to each other without limitation. In the embodiment of the present application, the name of the message or the name of the parameter in the message, etc. interacted between the devices are only an example, and other names may also be adopted in the specific implementation, and are not limited.
It should be noted that the terms "first" and "second" and the like in the description, claims and drawings of the present application are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.
It should be understood that, in the present application, "at least one (item)" means one or more, "a plurality" means two or more, "at least two (items)" means two or three and three or more, "and/or" for describing an association relationship of an association object, three kinds of relationships may exist, for example, "a and/or B" may mean: only a, only B and both a and B are present, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
From the foregoing description of the embodiments, it will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be implemented by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to implement all or part of the functions described above.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and the parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present application may be essentially or a part contributing to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions for causing a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.
The foregoing is merely a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (13)
1. A method of functional defect analysis, the method comprising:
determining a plurality of perception characteristics associated with the target functional defect, wherein the plurality of perception characteristics are used for indicating to-be-perceived items, of which the difference value of the perception data of a plurality of vehicle sensors for the same to-be-perceived item is larger than a first threshold value;
determining a probability of generating the target functional defect in the presence of a first perceived characteristic of the vehicle; the first perceptual characteristic is any one of the plurality of perceptual characteristics;
determining a target perception characteristic from the plurality of perception characteristics as a trigger condition for the target functional defect based on the probability of generating the target functional defect, and constructing a trigger logic table for the target functional defect, wherein the trigger logic table comprises at least one trigger condition and the target functional defect.
2. The method of claim 1, wherein determining a target perceptual characteristic from the plurality of perceptual characteristics as a trigger condition for the target functional defect based on a probability of generating the target functional defect, comprises:
And determining the first perception characteristic as a triggering condition of the target functional defect under the condition that the probability of generating the target functional defect is larger than a second threshold value.
3. The method of claim 1, wherein determining the plurality of perceptual characteristics associated with the target functional defect comprises:
acquiring sensing data of the plurality of vehicle sensors for a plurality of items to be sensed;
and determining a plurality of perception characteristics associated with the target functional defect by using a fault tree analysis method and the perception data.
4. The method according to claim 1, wherein the method further comprises:
obtaining a plurality of groups of sample data, wherein the sample data comprise sample target functional defects and corresponding sample perception data for a plurality of items to be perceived;
an average difference value of perception data of a plurality of vehicle sensors of a plurality of sample target functional defects for the same item to be perceived is determined, and the average difference value is determined as the first threshold value.
5. The method according to any one of claims 1 to 4, wherein,
the items to be sensed include one or more of lateral position, longitudinal position, lateral velocity, longitudinal velocity, lateral acceleration, longitudinal acceleration.
6. A functional defect analysis apparatus, characterized in that the apparatus comprises: a determining unit, a processing unit;
the determining unit is used for determining a plurality of perception characteristics associated with the target functional defects, wherein the plurality of perception characteristics are used for indicating to-be-perceived items, of which the difference value of the perception data of a plurality of vehicle sensors for the same to-be-perceived item is larger than a first threshold value;
the determining unit is further configured to determine a probability of generating the target functional defect in the case where only the first perceptual characteristic exists; the first perceptual characteristic is any one of the plurality of perceptual characteristics;
the processing unit is configured to determine, based on a probability of generating the target functional defect, a target perceptual characteristic from the plurality of perceptual characteristics as a trigger condition of the target functional defect, and construct a trigger logic table of the target functional defect, where the trigger logic table includes at least one trigger condition and the target functional defect.
7. The apparatus according to claim 6, wherein the determining unit is specifically configured to:
and determining the first perception characteristic as a triggering condition of the target functional defect under the condition that the probability of generating the target functional defect is larger than a second threshold value.
8. The apparatus according to claim 6, wherein the determining unit is further specifically configured to:
acquiring sensing data of the plurality of vehicle sensors for a plurality of items to be sensed;
and determining a plurality of perception characteristics associated with the target functional defect by using a fault tree analysis method and the perception data.
9. The apparatus of claim 6, further comprising an acquisition unit;
the acquisition unit is used for acquiring a plurality of groups of sample data, wherein the sample data comprise sample target functional defects and corresponding sample perception data for a plurality of items to be perceived;
the determining unit is configured to determine an average difference value of sensing data of a plurality of vehicle sensors of a plurality of sample target functional defects for a same item to be sensed, and determine the average difference value as the first threshold.
10. The device according to any one of claims 6 to 9, wherein,
the items to be sensed include one or more of lateral position, longitudinal position, lateral velocity, longitudinal velocity, lateral acceleration, longitudinal acceleration.
11. A functional defect analysis system is characterized in that the functional defect analysis system comprises a functional defect analysis device,
The functional defect analysis device is configured to perform the method of any one of claims 1 to 5.
12. A functional defect analysis apparatus, comprising: a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of any one of claims 1 to 5.
13. A computer readable storage medium, characterized in that, when computer-executable instructions stored in the computer readable storage medium are executed by a processor of an electronic device, the electronic device is capable of performing the method of any one of claims 1 to 5.
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