CN114152272A

CN114152272A - Fault detection method, apparatus, vehicle, readable storage medium, and program product

Info

Publication number: CN114152272A
Application number: CN202111350617.2A
Authority: CN
Inventors: 金燕江; 尚进; 丛炜
Original assignee: Guoqi Intelligent Control Beijing Technology Co Ltd
Current assignee: Guoqi Intelligent Control Beijing Technology Co Ltd
Priority date: 2021-11-15
Filing date: 2021-11-15
Publication date: 2022-03-08

Abstract

The application provides a fault detection method, a fault detection device, a vehicle, a readable storage medium and a program product, wherein the method comprises the following steps: the method comprises the steps of obtaining sensor data collected by a sensor in a vehicle, preprocessing the sensor data to obtain a preprocessing result, performing fault detection on the sensor data in parallel when preprocessing the sensor data to obtain a fault detection result, and determining a control strategy according to the preprocessing result and the fault detection result. According to the technical scheme, the fault detection of the sensor data is performed in parallel with the preprocessing process, and after respective results are obtained, the results are integrated to determine the control strategy of the vehicle. The problem that fault detection and preprocessing are serial and take a large amount of time is solved, and the working efficiency of the automatic driving system can be improved.

Description

Fault detection method, apparatus, vehicle, readable storage medium, and program product

Technical Field

The present application relates to the field of vehicle automatic driving technologies, and in particular, to a fault detection method, apparatus, vehicle, readable storage medium, and program product.

Background

The automatic driving system adopts advanced communication, computer, network and control technology to realize real-time and continuous control of the vehicle so as to realize automatic driving of the vehicle. The core of the automatic driving system is mainly various vehicle-mounted sensors, and the automatic driving system needs to have the capabilities of identifying and processing faults of the sensors so as to ensure the integrity and reliability of data captured by the sensors.

In the prior art, when detecting the reliability of sensor data, the processing flow usually first detects a fault, and if the sensor has no fault, then executes the subsequent data processing flow according to the sensor data, and finally obtains an automatic driving strategy.

However, in real life, the probability of unreliable sensor data is very low, and the sensor data needs to be checked every time, which wastes much time and occupies the system performance, and reduces the working efficiency of the automatic driving system.

Disclosure of Invention

The application provides a fault detection method, a fault detection device, a vehicle, a readable storage medium and a program product, which are used for solving the problem that the existing fault processing influences the working efficiency of an automatic driving system.

In a first aspect, an embodiment of the present application provides a fault detection method, which is applied to a vehicle, and the method includes:

acquiring sensor data acquired by a sensor in a vehicle, and preprocessing the sensor data to obtain a preprocessing result, wherein the preprocessing result is used for determining a running path of the vehicle;

when the sensor data are preprocessed, fault detection is carried out on the sensor data in parallel to obtain a fault detection result, and the fault detection result is used for indicating whether a fault exists in the sensor;

and determining a control strategy according to the preprocessing result and the fault detection result, wherein the control strategy is used for the automatic driving of the vehicle.

In one possible design of the first aspect, the acquiring sensor data of the vehicle includes:

and performing read-write operation on the data storage area of the sensor to obtain the sensor data.

In another possible design of the first aspect, before performing the fault detection on the sensor data in parallel, the method further includes:

and when the sensor data is preprocessed, performing read-only operation on the data storage area through a bypass function to obtain the sensor data.

In yet another possible design of the first aspect, the sensor at least includes a camera, and performing fault detection on the sensor data to obtain a fault detection result includes:

acquiring an image to be detected, which is shot by a camera in the sensor;

according to a preset algorithm, carrying out fault detection on the image to be detected, and determining whether a target fault exists in the camera, wherein the target fault comprises at least one of image blurring, image shielding and image freezing;

if the camera has a target fault, obtaining a first fault detection result indicating that the camera works abnormally;

and if the camera does not have the target fault, obtaining a second fault detection result indicating that the camera works normally.

In yet another possible design of the first aspect, the preprocessing the sensor data to obtain a preprocessing result includes:

acquiring perception information perceived by each sensor from the sensor data, wherein the perception information comprises environmental information and vehicle state information;

fusing the perception information of each sensor to obtain fused information;

determining a driving strategy of the vehicle according to the fusion information, wherein the driving strategy comprises following driving, bypassing driving or parking;

and determining a driving path of the vehicle as the preprocessing result according to the driving strategy.

In yet another possible design of the first aspect, the determining a control strategy according to the preprocessing result and the fault detection result includes:

determining that the fault detection result is a first fault detection result or a second fault detection result, wherein the first fault detection result is used for indicating that the sensor has a fault, and the second fault detection result is used for indicating that the sensor does not have a fault;

if the fault detection result is a first fault detection result, determining a first control strategy according to the first fault detection result and the preprocessing result, wherein the first control strategy is used for indicating the vehicle to decelerate and brake;

and if the fault detection result is a second fault detection result, determining a second control strategy according to the second fault detection result and the preprocessing result, wherein the second control strategy is used for indicating the vehicle to continue to run.

In another possible design of the first aspect, after obtaining the fault detection result, the method further includes:

and storing the fault detection result to a preset storage area.

In yet another possible design of the first aspect, before determining the control strategy according to the preprocessing result and the fault detection result, the method further includes:

and reading the fault detection result stored in the preset storage area when the preprocessing result is obtained.

when the fault detection result is stored in a preset storage area, reading the fault detection result stored in the preset storage area;

and preprocessing the sensor data according to the fault detection result to obtain a preprocessing result.

In a second aspect, an embodiment of the present application provides a fault detection apparatus, including:

the system comprises a preprocessing module, a data processing module and a data processing module, wherein the preprocessing module is used for acquiring sensor data acquired by a sensor in a vehicle, preprocessing the sensor data to obtain a preprocessing result, and the preprocessing result is used for determining a driving path of the vehicle;

the fault detection module is used for carrying out fault detection on the sensor data in parallel when the sensor data are preprocessed to obtain a fault detection result, and the fault detection result is used for indicating whether a fault exists in the sensor;

and the strategy determining module is used for determining a control strategy according to the preprocessing result and the fault detection result, and the control strategy is used for the automatic driving of the vehicle.

In a third aspect, an embodiment of the present application provides a vehicle, including: a processor, and a memory communicatively coupled to the processor;

the memory stores computer-executable instructions;

the processor executes the computer-executable instructions stored by the memory to implement the methods described above.

In a fourth aspect, the present application provides a readable storage medium, in which computer instructions are stored, and when executed by a processor, the computer instructions are used to implement the method as described above.

In a fifth aspect, the present application provides a program product including computer instructions, which when executed by a processor implement the method described above.

The fault detection method, the fault detection device, the vehicle, the readable storage medium and the program product provided by the embodiment of the application determine the control strategy of the vehicle by paralleling the fault detection of the sensor data with the preprocessing process and integrating the results after obtaining the respective results. The problem that fault detection and preprocessing are serial and take a large amount of time is solved, and the working efficiency of the automatic driving system can be improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application;

fig. 1 is a schematic view of a scenario of a fault detection method according to an embodiment of the present application;

fig. 2 is a schematic flowchart of a first embodiment of a fault detection method according to an embodiment of the present application;

fig. 3 is a schematic flowchart of a second embodiment of a fault detection method according to an embodiment of the present application;

fig. 4 is a schematic structural diagram of a fault detection apparatus provided in an embodiment of the present application;

FIG. 5 is a system diagram of a vehicle according to an embodiment of the present disclosure.

With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Fig. 1 is a schematic view of a scenario of a fault detection method provided in an embodiment of the present application, where the method may be applied to an autonomous vehicle. As shown in fig. 1, during automatic driving, a vehicle 10 needs to collect various information of the vehicle through a series of sensors, such as information of a road where the vehicle is located, information of obstacles existing in the road, and the like. The automatic driving system of the vehicle completes analysis and decision based on the information collected by the sensor, and determines how to control the vehicle to drive subsequently by the control strategy. Therefore, in the process, it is important whether the data collected by the sensor is accurate and reliable. Usually, a plurality of sensors are installed on the vehicle to cooperate with each other, so as to ensure the integrity and reliability of the data to a certain extent. Meanwhile, the automatic driving system can also be provided with a fault detection node to detect the data acquired by the sensor, so that the integrity and the reliability of the data captured by the sensor are further ensured, and powerful support is provided for subsequent analysis and decision.

In the prior art, in the whole work flow, the automatic driving system sets the fault detection node at the forefront of the whole work flow, and the subsequent various analysis decision nodes are all positioned behind the fault detection node and are in series with the fault detection node. Therefore, only after the fault detection node is completed, the subsequent analysis decision node can be carried out. The method mainly considers the condition that data acquired by a sensor is possible to be incomplete and reliable, and the fault detection node is arranged at the forefront end, so that the follow-up analysis decision node can be ensured not to have errors. However, in the practical application process, the probability of the sensor fault is very small, and after the sensor collects data each time, a large amount of time and operation performance of the automatic driving system can be occupied by performing fault detection once, so that the working efficiency of the automatic driving system is reduced.

In order to solve the above problem, in the embodiment of the present application, the failure detection node of the sensor data and the preprocessing process of the sensor data are parallel, and after respective results are obtained, the failure detection node and the preprocessing process are integrated to determine the control strategy of the vehicle. The problem that fault detection and preprocessing are serial and a large amount of fault detection time needs to be spent is solved, and the working efficiency of the automatic driving system can be improved.

The technical solution of the present application will be described in detail below with reference to specific examples. It should be noted that the following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

Fig. 2 is a schematic flow chart of a first embodiment of a fault detection method provided in the embodiment of the present application, where the method may be applied to an automatic driving system of an automobile. Taking an automatic driving system as an execution subject, as shown in fig. 2, the method may specifically include the following steps:

s201, sensor data acquired by a sensor in the vehicle is acquired, and the sensor data is preprocessed to obtain a preprocessing result.

Wherein the preprocessing result is used for determining a driving path of the vehicle.

In the present embodiment, various sensors such as a camera, a laser radar, a millimeter wave radar, an ultrasonic radar, a gyroscope, and an accelerometer may be provided on the vehicle, and for example, one or more sensors may be provided for each of the same types. The multiple sensors can ensure that information is acquired more comprehensively and completely, and when one sensor breaks down, the other sensors can continue to complete data acquisition to a certain extent.

The same situation may exist in the information collected by different types of sensors, for example, the millimeter wave radar and the laser radar both sense the size, position, advancing direction and speed information of another vehicle on the road at the same time. At the moment, the information acquired by the two sensors can be fused by an automatic driving system, so that the consistency of time and space of the same vehicle in different types of sensors on the road is ensured.

The sensor data may include, for example, ambient information and vehicle state information. The surrounding environment information includes, among other things, the shape, direction, curvature, gradient, lane, traffic sign, signal light, and the position, size, heading direction, and speed of other vehicles or pedestrians of the road. The vehicle state information includes the forward speed, acceleration, steering angle, vehicle body position and posture, etc. of the vehicle itself.

In this embodiment, the data collected by the sensor may be stored in a data storage area, or may be directly transmitted to a processor connected thereto, and the processor directly preprocesses the sensor data.

Illustratively, the preprocessing mainly comprises four nodes, namely a perception node, a fusion node, a decision node and a planning node. The sensing nodes mainly sense the environment, the information of the vehicle and the surrounding environment. The fusion node is mainly used for fusing and unifying data collected by various sensors of different types. The decision node mainly plays the role of a driver, serves as the brain of the whole automatic driving system, and decides the subsequent driving strategy of the vehicle according to the collected information. Such as which road to pick, whether to change lanes, whether to follow, whether to detour, whether to park, etc. The planning node is mainly used for planning a reasonable driving path for the vehicle. According to the scope of path planning, the method can be divided into global path planning and local path planning. Global route planning refers to planning a global route from the current position of the vehicle to a destination with knowledge of a global map. The local path planning means planning a safe and smooth driving path in real time under the conditions of changing lanes, turning, avoiding obstacles and the like according to the information (road and obstacle information) sensed by the environment.

S202, when the sensor data are preprocessed, fault detection is conducted on the sensor data in parallel, and a fault detection result is obtained.

Wherein the fault detection result is used for indicating whether the sensor has a fault.

In this embodiment, the processors of the autopilot system may be multithreaded and parallel, and may also be used to perform fault detection on sensor data in parallel when preprocessing the sensors. In the parallel processing process, because the number of nodes involved in the preprocessing is large, and the node behind the fault detection node is one, usually the fault detection is completed first to obtain a fault detection result, and the preprocessing is completed later. I.e. the result of the preprocessing is coming out later with respect to the fault detection result.

The fault detection mainly comprises running a series of algorithms, such as a perception algorithm, and judging whether a sensor has a fault after a series of complex operations, for example, a camera is shielded.

For example, after the failure detection result is obtained, the failure detection result may be stored in a preset storage area. If the processor is performing preprocessing (for example, the processor is also located at a decision node), the processor can select two different processing modes at this time, the first mode is that when the fault detection result is stored in a preset area, the fault detection result is directly read from the preset storage area, preprocessing of the sensor data is assisted according to the fault detection result, a preprocessing result is obtained, and finally, a control strategy of the vehicle is determined directly according to the preprocessing result. And the other method is that after the preprocessing is finished to obtain the preprocessing result, the fault detection result in the preset storage area is read, and then the preprocessing result and the fault detection result are integrated to analyze to obtain the control strategy of the vehicle.

And S203, determining a control strategy according to the preprocessing result and the fault detection result.

Wherein the control strategy is used for automatic driving of the vehicle.

In this embodiment, after the preprocessing, a control node is further provided, where the control node mainly controls steering, driving, and braking of the vehicle, and further may include control of a turn light, a horn, a door window, and the like.

In this embodiment, the control node needs to select a control strategy according to the preprocessing result and the fault detection result to realize control over the vehicle. The fault detection result indicates whether the sensor has a fault, and when the sensor has a fault or does not have a fault, the finally obtained control strategies are different. For example, when a sensor fails, the resulting control strategy may be indicative of vehicle deceleration or braking. When the sensor is not in fault, the obtained control strategy may indicate that the vehicle accelerates or keeps running at a normal speed, that is, the control node may obtain a desired speed, a desired steering angle and the like from the planning node in the preprocessing, control the vehicle according to the desired speed and the desired steering angle, and finally realize automatic driving.

According to the embodiment of the application, the parallel processing capacity of the processor is utilized, the sensor data is preprocessed, meanwhile, synchronous parallel fault detection is carried out, the influence of the fault detection node on the preprocessed nodes can be avoided, and the working efficiency of the automatic driving system is improved.

In some embodiments, the processor of the autonomous driving system may retrieve the sensor data from the data storage area via a read-write operation prior to performing the preprocessing. That is, the sensors on the vehicle will store the collected information in the data storage area in advance.

In this embodiment, the read-write operation may cause the processor to write data into the data storage area in addition to causing the processor to read sensor data from the data storage area.

Further, in some embodiments, while the processor obtains the sensor data from the data storage area through read-write operation and performs preprocessing, the processor may perform read-only operation on the data storage area through a bypass function (bypass) to obtain the sensor data to perform fault detection in parallel.

According to the embodiment of the application, the read-only operation is carried out through the bypass function to obtain the sensor data to carry out fault detection, and through the bypass function, data copying can be avoided, and unnecessary performance loss is reduced. The read-only operation can prevent the original data in the storage area from being tampered.

For example, in some embodiments, if the sensor includes a camera, the step S202 of "performing fault detection on the sensor data to obtain a fault detection result" may specifically be implemented by the following steps:

acquiring an image to be detected, which is shot by a camera in a sensor;

according to a preset algorithm, carrying out fault detection on an image to be detected, and determining whether a target fault exists in a camera;

Wherein the target fault comprises at least one of image blurring, image blocking and image freezing. The image freezing means that the image shot by the camera is fixed as an image, if the camera is in video recording, the content of the video recording is the same as the time, and the image is the same image.

In this embodiment, the preset algorithm may be some image processing algorithms, for example, when performing fault detection on an image to be detected, it may be detected first whether all images to be detected are the same image, and if all the images are the same image, it may be determined that an image freezing fault exists in the camera.

In some embodiments, the "preprocessing the sensor data to obtain the preprocessing node" in the step S201 may specifically be implemented by the following steps:

acquiring perception information perceived by each sensor from sensor data;

fusing the perception information of each sensor to obtain fused information;

determining a driving strategy of the vehicle according to the fusion information;

and determining the driving path of the vehicle as a preprocessing result according to the driving strategy.

The perception information comprises environmental information and vehicle state information, and the driving strategy comprises following driving, bypassing driving or parking.

In this embodiment, the sensing information sensed by the different types of sensors may be different or the same. For example, a camera and a lidar, as two different types of sensors, may sense information such as the size and position of the same vehicle in front of the vehicle. Therefore, information sensed by the two sensors needs to be fused and unified to obtain fused information.

For example, the driving strategy may further include lane selection, lane change or not, and the like. For example, when the automatic driving system finds that an obstacle exists in front of the vehicle after fusing the perception information, the driving strategy is determined to be lane change. The automatic driving system controls the vehicle to turn according to the lane changing strategy, so that the lane changing purpose is achieved.

According to the embodiment of the application, the driving path of the vehicle can be determined by preprocessing the sensor data such as sensing, fusion, decision and planning, the automatic driving system can be ensured to normally operate when the sensor data is not subjected to fault detection, and the parallel fault detection and preprocessing are realized.

In some embodiments, the step S203 may be further implemented by:

determining that the fault detection result is a first fault detection result or a second fault detection result;

if the fault detection result is the first fault detection result, determining a first control strategy according to the first fault detection result and the preprocessing result;

and if the fault detection result is a second fault detection result, determining a second control strategy according to the second fault detection result and the preprocessing result.

The first fault detection result is used for indicating that the sensor has a fault, the second fault detection result is used for indicating that the sensor does not have a fault, the first control strategy is used for indicating that the vehicle decelerates and brakes, and the second control strategy is used for indicating that the vehicle continues to run.

In this embodiment, if the fault detection result indicates that the sensor has a fault, the automatic driving system executes a predetermined fault processing procedure at the control node after obtaining the preprocessing result. For example, when a camera is found to have a fault, the control node may get a first control strategy of deceleration or braking.

If the fault detection result indicates that the sensor has no fault, after the automatic driving system obtains the preprocessing result, a normal control process is executed at the control node, for example, according to the expected speed and the expected steering angle in the preprocessed planning node, and then according to the expected speed and the expected steering speed, a second control strategy is obtained to control the vehicle to run.

According to the embodiment of the application, different fault detection results are obtained, and then different control strategies are determined according to the preprocessing result and the different fault detection results, so that the fault detection and the preprocessing can be performed in parallel, and the working efficiency of the automatic driving system is improved.

Fig. 3 is a schematic flow diagram of a second embodiment of the fault detection method provided in the embodiment of the present application, and as shown in fig. 3, a preprocessing process involves four nodes, namely a sensing node 31, a fusion node 32, a decision node 33, and a planning node 34. These nodes in the preprocessing process may serve as the primary function of the autopilot system, while the fault detection node 35 serves as a bypass function.

The sensor data can be acquired through read-write operation before being preprocessed. While the fault detection node 35, which functions as a bypass, can only read sensor data by read-only operation.

In this embodiment, each node in the preprocessing and the failure detection node 35 may be in parallel, wherein the failure detection node stores the failure detection result in the preset storage area after completing the failure detection of the sensor data. When the last planning node in the preprocessing is completed, the fault detection result in the preset storage area is read, and then the control node 36 is entered. Different control strategies are selected by the control node 36 based on the fault detection result and the preprocessing result.

The following are embodiments of the apparatus of the present application that may be used to perform embodiments of the method of the present application. For details which are not disclosed in the embodiments of the apparatus of the present application, reference is made to the embodiments of the method of the present application.

Fig. 4 is a schematic structural diagram of a fault detection device according to an embodiment of the present application, where the fault detection device may be integrated on a processor of an automatic driving system, or may be independent of the processor and cooperate with the processor to implement the technical solution of the present application. As shown in fig. 4, the fault detection apparatus 40 includes a preprocessing module 41, a fault detection module 42, and a policy determination module 43.

The preprocessing module 41 is configured to acquire sensor data acquired by a sensor in a vehicle, and preprocess the sensor data to obtain a preprocessing result. The fault detection module 42 is configured to perform fault detection on the sensor data in parallel when the sensor data is preprocessed, so as to obtain a fault detection result. The strategy determining module 43 is configured to determine a control strategy according to the preprocessing result and the fault detection result.

The preprocessing result is used for determining a running path of the vehicle, the fault detection result is used for indicating whether the sensor has a fault, and the control strategy is used for automatically driving the vehicle.

In some embodiments, the preprocessing module 41 may be specifically configured to perform read/write operations on a data storage area of the sensor to obtain sensor data.

Optionally, in some embodiments, the fault detection apparatus further includes a read-only module, configured to perform read-only operation on the data storage area through the bypass function when the sensor data is preprocessed, so as to obtain the sensor data.

In some embodiments, if the sensor includes a camera, the fault detection module may be specifically configured to:

acquiring an image to be detected, which is shot by a camera in a sensor;

Wherein the target fault comprises at least one of image blurring, image blocking and image freezing.

In some embodiments, the preprocessing module may be specifically configured to:

acquiring perception information perceived by each sensor from sensor data;

fusing the perception information of each sensor to obtain fused information;

In some embodiments, the policy determination module may be specifically configured to:

In some embodiments, the fault handling apparatus further includes a storage module, configured to store the fault detection result in a preset storage area.

In some embodiments, the fault handling apparatus further includes a result reading module, configured to read the fault detection result stored in the preset storage area when the preprocessing result is obtained.

In some embodiments, the fault handling apparatus further includes a result obtaining module, configured to:

when the fault detection result is stored in the preset storage area, reading the fault detection result stored in the preset storage area;

The apparatus provided in the embodiment of the present application may be used to execute the method in the embodiments shown in fig. 2 to fig. 3, and the implementation principle and the technical effect are similar, which are not described herein again.

It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the preprocessing module may be a processing element that is separately set up, or may be implemented by being integrated into a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and the function of the preprocessing module may be called and executed by a processing element of the apparatus. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element here may be an integrated circuit with signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions according to the embodiments of the present application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium.

FIG. 5 is a system diagram of a vehicle according to an embodiment of the present disclosure. As shown in fig. 5, the vehicle includes: at least one processor 51, memory 52, bus 53, and communication interface 54.

Wherein: the processor 51, the communication interface 54 and the memory 52 communicate with each other via the bus 53.

A communication interface 54 for communicating with other devices. The communication interface 54 includes a communication interface for data transmission and a display interface or an operation interface for human-computer interaction.

The processor 51 is configured to execute the computer-executable instructions stored in the memory 52, and may specifically execute the relevant steps in the method described in the foregoing embodiment.

The processor 51 may be a central processing unit, or an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement an embodiment of the present invention. The one or more processors that the vehicle may include, may be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.

And a memory 52 for storing computer-executable instructions. Illustratively, the memory 52 may also store sensor data and fault detection results. The memory may comprise high speed RAM memory and may also include non-volatile memory, such as at least one disk memory.

The present embodiment also provides a readable storage medium, in which computer instructions are stored, and when the computer instructions are executed by at least one processor of the vehicle, the vehicle executes the fault detection method provided by the above various embodiments.

The present embodiments also provide a program product comprising computer instructions stored in a readable storage medium. The computer instructions may be read from a readable storage medium by at least one processor of the vehicle, and execution of the computer instructions by the at least one processor causes the vehicle to implement the fault detection methods provided by the various embodiments described above.

In the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship; in the formula, the character "/" indicates that the preceding and following related objects are in a relationship of "division". "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.

It is to be understood that the various numerical references referred to in the embodiments of the present application are merely for convenience of description and distinction and are not intended to limit the scope of the embodiments of the present application. In the embodiment of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiment of the present application.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A fault detection method, applied to a vehicle, the method comprising:

2. The method of claim 1, wherein the acquiring sensor data of the vehicle comprises:

3. The method of claim 2, wherein prior to the parallel fault detection of the sensor data, further comprising:

4. The method according to claim 1, wherein the sensor comprises at least a camera, and the performing fault detection on the sensor data to obtain a fault detection result comprises:

acquiring an image to be detected, which is shot by a camera in the sensor;

5. The method of claim 1, wherein the preprocessing the sensor data to obtain a preprocessed result comprises:

fusing the perception information of each sensor to obtain fused information;

6. The method of claim 1, wherein determining a control strategy based on the preprocessing result and the fault detection result comprises:

7. The method of claim 1, wherein after obtaining the fault detection result, further comprising:

and storing the fault detection result to a preset storage area.

8. The method of claim 7, wherein before determining a control strategy based on the preprocessing result and the fault detection result, further comprising:

9. The method of claim 7, wherein before determining a control strategy based on the preprocessing result and the fault detection result, further comprising:

10. A fault detection device, comprising:

11. A vehicle, characterized by comprising: a processor, and a memory communicatively coupled to the processor;

the memory stores computer-executable instructions;

the processor executes computer-executable instructions stored by the memory to implement the method of any of claims 1-9.

12. A readable storage medium having stored therein computer instructions, which when executed by a processor, are adapted to implement the method of any one of claims 1-9.

13. A program product comprising computer instructions, characterized in that the computer instructions, when executed by a processor, implement the method of any of claims 1-9.