CN117485356B - High-precision positioning fault diagnosis method and system based on risk level evaluation - Google Patents
High-precision positioning fault diagnosis method and system based on risk level evaluation Download PDFInfo
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Classifications
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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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- 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
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/005—Handover processes
- B60W60/0059—Estimation of the risk associated with autonomous or manual driving, e.g. situation too complex, sensor failure or driver incapacity
Abstract
The application provides a high-precision positioning fault diagnosis method and system based on risk level assessment, comprising the following steps: continuously performing fault diagnosis on a positioning algorithm resolving result of the vehicle in the running process of the vehicle so as to obtain a fault diagnosis conclusion; carrying out risk grade assessment according to the fault diagnosis conclusion to obtain a grade assessment conclusion; establishing a positioning state code according to the grade evaluation conclusion; and controlling the vehicle to switch to run in a preset auxiliary driving mode through the positioning state code, wherein the type of the preset auxiliary driving mode corresponds to the positioning state code. The method and the system provided by the application can respond and locate the fault in a grading way, have high information transmission instantaneity, and enhance the robustness, accuracy and safety of the whole auxiliary driving system.
Description
Technical Field
The application mainly relates to the field of intelligent driving, in particular to a high-precision positioning fault diagnosis method and system based on risk level assessment.
Background
Unmanned automobile is a research hotspot at present, the existing intelligent driving technology of mass production landing mainly focuses on the level of L2+, and in high-order navigation assisted driving, intelligent driving algorithms are divided into sensing, positioning and regulation algorithms, wherein the sensing algorithm is upstream, the positioning algorithm is midstream and the regulation algorithm is downstream. Because of the limitations of sensor performance and algorithm technology, the intelligent driving algorithm has own limit and boundary, when meeting the boundary and limit of the algorithm in a special scene, the false auxiliary driving can cause serious driving collision risk, thereby influencing the life safety of drivers and passengers, and therefore, the safety and fault diagnosis research of the intelligent driving algorithm is necessary.
There are a number of deficiencies in the current art in the way of diagnosing high-precision positioning faults. For example, at present, reasonable design of fault diagnosis architecture of a middle positioning algorithm is lacking in intelligent driving, the existing design may depend on each algorithm module to interact with a bottom soft, various fault information is sent to the bottom soft by a sensing, positioning and regulating algorithm, clustering processing is carried out by the bottom soft, a processing result is sent to the regulating algorithm for processing by the bottom soft, and data transmission quantity is large, and instantaneity and accuracy are not enough. In addition, the current intelligent driving algorithm lacks grade definition of faults, and implements a robust auxiliary driving switching function according to faults of different grades. If the robust switching function is not available, the auxiliary driving function is stopped immediately when a fault occurs, so that the user experience is poor, namely false alarm is caused; or when the fault stopping auxiliary driving function needs to be reported, the function is not stopped in time, namely the fault stopping auxiliary driving function is not reported.
Disclosure of Invention
The technical problem to be solved by the method and the system for diagnosing the high-precision positioning faults based on risk level assessment can respond to positioning faults in a grading mode, information transmission is high in instantaneity, and the robustness, accuracy and safety of the whole auxiliary driving system are improved.
In order to solve the technical problems, the application provides a high-precision positioning fault diagnosis method based on risk level evaluation, which comprises the following steps: continuously performing fault diagnosis on a positioning algorithm resolving result of the vehicle in the running process of the vehicle so as to obtain a fault diagnosis conclusion; performing risk grade assessment according to the fault diagnosis conclusion to obtain a grade assessment conclusion; establishing a positioning state code according to the grade evaluation conclusion; and controlling the vehicle to switch to run in a preset auxiliary driving mode or exit from a current auxiliary driving mode through the positioning state code, wherein the type of the preset auxiliary driving mode corresponds to the positioning state code.
Optionally, the step of performing fault diagnosis on the result of the positioning algorithm solution of the vehicle further comprises performing fault diagnosis on a map matching module, a combined navigation module, a wheel type odometer module and/or a fusion positioning algorithm module in the positioning module of the vehicle, and the fault diagnosis comprises general input information fault diagnosis.
Optionally, the step of performing fault diagnosis on the result of the positioning algorithm of the vehicle further includes: and acquiring pose output information of the map matching module, the integrated navigation module, the wheel type odometer module and/or the fusion positioning algorithm module, and executing pose jump detection according to the pose output information.
Optionally, the step of performing fault diagnosis on the map matching module further includes performing output offset detection, wherein the output offset detection includes: converting the perceived lane line from a vehicle body coordinate system to a world coordinate system by utilizing the pose output information to project so as to obtain the perceived lane line to be analyzed; and comparing the high-precision map lane line under the world coordinate system with the to-be-analyzed sensing lane line to judge whether the lane line is deviated or not, so as to obtain the fault diagnosis conclusion.
Optionally, the step of performing fault diagnosis on the integrated navigation module further includes performing a longitudinal speed comparison detection and an integrated navigation position consistency detection, wherein the longitudinal speed comparison detection includes: obtaining the fault diagnosis conclusion by comparing the longitudinal speeds of the integrated navigation module and the wheel speed meter of the vehicle under a vehicle body coordinate system; the integrated navigation position consistency detection comprises the steps of obtaining an actual front and rear frame position calculated according to the current running speed of the vehicle and an output front and rear frame position generated by the integrated navigation module after calculation, and comparing the actual front and rear frame position with the output front and rear frame position so as to obtain the fault diagnosis conclusion.
Optionally, the step of performing fault diagnosis on the fused positioning algorithm module further includes performing fused positioning location consistency detection, where the fused positioning location consistency detection includes: calculating a first front frame position and a second frame position according to the output speed provided by the integrated navigation module; outputting a second front frame position and a second rear frame position after resolving through the fusion positioning algorithm module; and comparing whether the first front and rear frame positions and the second front and rear frame positions are consistent to obtain the fault diagnosis conclusion.
Optionally, the step of performing fault diagnosis on the fused positioning algorithm module further includes performing an excess edge detection, where the excess edge detection includes: loading the map lane lines from the map matching module to the fusion positioning algorithm module, and acquiring road edge information; and comparing the current frame calculation result of the fusion positioning algorithm module with the road edge information to judge whether the vehicle exceeds the road edge or not, so as to obtain the fault diagnosis conclusion.
Optionally, the positioning algorithm solution results include positioning position and/or pose results, and the form of the positioning status code includes bits.
Optionally, the level evaluation conclusion includes a normal fault, a serious fault and a fatal fault, the preset driving assistance mode includes a low-order driving assistance mode, a pure vision driving assistance mode and a high-order pilot driving assistance mode, and the positioning status code has a numerical interval of a first gear, a second gear and a third gear from low to high, wherein when the level evaluation conclusion is the normal fault, the positioning status code created according to the level evaluation conclusion is located in the numerical interval of the first gear, and the method further includes controlling the vehicle to travel in the low-order driving assistance mode; when the grade evaluation conclusion is the serious fault, the positioning state code created according to the grade evaluation conclusion is located in a numerical interval of the second gear, and the method further comprises controlling the vehicle to run in the pure vision auxiliary driving mode; and when the grade evaluation conclusion is the fatal fault, the positioning state code created according to the grade evaluation conclusion is located in a numerical interval of the third gear, and the method further comprises controlling the vehicle to run in the high-order pilot-assisted driving mode.
In order to solve the above technical problems, the present application provides a high-precision positioning fault diagnosis system based on risk level evaluation, including: a perception module configured to provide perception information; the positioning module is configured to generate a positioning algorithm resolving result of the vehicle in the running process of the vehicle, obtain a fault diagnosis conclusion and a grade evaluation conclusion according to the fault diagnosis method and establish a positioning state code; and the regulation module is configured to receive the positioning result message from the positioning module and control the vehicle to run in a preset auxiliary driving mode, wherein the positioning result message comprises the positioning algorithm resolving result and the positioning state code, and the type of the preset auxiliary driving mode corresponds to the positioning state code.
Compared with the prior art, the method and the device for diagnosing the high-precision positioning faults through risk level assessment, realize the transmission of positioning fault information by adopting special state positioning codes through different response measures to different level faults, have the advantages of extremely low communication bandwidth consumption and high instantaneity, and enhance the robustness, accuracy and safety of the whole auxiliary driving system.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the accompanying drawings:
FIG. 1 is a flow chart of a high-precision localization fault diagnosis method based on risk level assessment according to an embodiment of the present application;
FIG. 2 is a schematic overall technical architecture of a high-precision localization fault diagnosis method based on risk level assessment according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a technical architecture for performing high-precision positioning fault diagnosis on different functional modules in a high-precision positioning fault diagnosis method based on risk level evaluation according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a technical architecture for a message transmission part in a high-precision positioning fault diagnosis method based on risk level evaluation according to an embodiment of the present application; and
FIG. 5 is a block diagram of a high-precision localization fault diagnosis system based on risk level assessment in an embodiment of the present application.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present application, and it is obvious to those skilled in the art that the present application may be applied to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.
As used in this application and in the claims, the terms "a," "an," "the," and/or "the" are not specific to the singular, but may include the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.
The relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present application unless it is specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description. Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but should be considered part of the specification where appropriate. In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
In the description of the present application, it should be understood that, where azimuth terms such as "front, rear, upper, lower, left, right", "transverse, vertical, horizontal", and "top, bottom", etc., indicate azimuth or positional relationships generally based on those shown in the drawings, only for convenience of description and simplification of the description, these azimuth terms do not indicate and imply that the apparatus or elements referred to must have a specific azimuth or be constructed and operated in a specific azimuth, and thus should not be construed as limiting the scope of protection of the present application; the orientation word "inner and outer" refers to inner and outer relative to the contour of the respective component itself.
Spatially relative terms, such as "above … …," "above … …," "upper surface at … …," "above," and the like, may be used herein for ease of description to describe one device or feature's spatial location relative to another device or feature as illustrated in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements described as "above" or "over" other devices or structures would then be oriented "below" or "beneath" the other devices or structures. Thus, the exemplary term "above … …" may include both orientations of "above … …" and "below … …". The device may also be positioned in other different ways (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
In addition, the terms "first", "second", etc. are used to define the components, and are merely for convenience of distinguishing the corresponding components, and unless otherwise stated, the terms have no special meaning, and thus should not be construed as limiting the scope of the present application. Furthermore, although terms used in the present application are selected from publicly known and commonly used terms, some terms mentioned in the specification of the present application may be selected by the applicant at his or her discretion, the detailed meanings of which are described in relevant parts of the description herein. Furthermore, it is required that the present application be understood, not simply by the actual terms used but by the meaning of each term lying within.
The application proposes a high-precision positioning fault diagnosis method (hereinafter referred to as "method 10") based on risk level evaluation with reference to fig. 1, which comprises steps S1-S4. Flowcharts are used in this application to describe the operations performed by systems according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in order precisely. Rather, the various steps may be processed in reverse order or simultaneously. At the same time, other operations are added to or removed from these processes.
Specifically, step S1 includes continuously performing fault diagnosis on a result of a positioning algorithm solution of the vehicle during running of the vehicle to obtain a fault diagnosis conclusion; step S2, carrying out risk grade assessment according to the fault diagnosis conclusion to obtain a grade assessment conclusion; step S3, establishing a positioning state code according to the grade evaluation conclusion; step S4 comprises the step of controlling the vehicle to switch to drive in a preset auxiliary driving mode through the positioning state code, wherein the type of the preset auxiliary driving mode corresponds to the positioning state code. Illustratively, the positioning algorithm solution results include positioning position and/or attitude results, and the form of the positioning status code includes bits for which the software program is applicable, as will be further described below with reference to FIG. 4.
Based on the method 10, FIGS. 2-4 show, respectively, some technical architecture diagrams in a more preferred embodiment based on the method 10. Referring first to fig. 2, a step S1 in the method 10 proposes performing fault diagnosis on a result of a positioning algorithm solution of a vehicle, and in a preferred embodiment shown in fig. 2, the step S1 is specifically implemented to perform fault diagnosis on a map matching module, a combined navigation module, a wheel type odometer module and a fusion positioning algorithm module in a vehicle positioning module respectively. Specifically, in the present embodiment, the accuracy of the high-precision positioning algorithm is in the centimeter level, and the high-precision positioning algorithm can be executed by the above four modules as shown in fig. 2; at the same time, however, the four modules perform the respective module algorithms and also perform the fault diagnosis method of method 10.
Further specifically, in this embodiment, when the high-precision positioning algorithm is executed, the above modules are fused and output to obtain a positioning algorithm solution result, and step S1 in the method 10 further performs fault diagnosis based on the positioning algorithm solution result to obtain a fault diagnosis conclusion, where the fault diagnosis conclusion may specifically include a module fault result and fault detailed information as shown in fig. 2. On the basis, fault risk level evaluation is performed and a positioning state code is generated, so that the state switching is determined by a rule state machine, namely, steps S2-S4 shown in FIG. 1 are executed.
Referring more specifically to fig. 3, as described above, the map matching module, the integrated navigation module, the wheel odometer module, and the fused positioning algorithm module (i.e., the fused positioning module in fig. 3) execute the respective algorithms simultaneously with the method 10 shown in fig. 1, that is, the general input information fault diagnosis and the output data fault diagnosis are performed for each module.
First, in terms of general input information fault diagnosis, exemplary, specific fault diagnosis is to set a program running fault in a main program loop section, and check whether each module thread is operating by the traffic of the data flow of each module in a specific time. And for the input part of each module, the detection and check of the time stamp and the data of each input source can be performed. As shown in fig. 3, in the method 10, when performing the fault diagnosis operation in step S1, input verification may be performed on the high-precision map, the perceived lane line, and the integrated navigation in the map matching module, input verification may be performed on the GNSS and the IMU in the integrated navigation module, input verification may be performed on the wheel speed meter and the IMU in the wheel type odometer module, and input verification may be performed on the map matching, the integrated navigation, and the wheel type odometer in the fusion positioning algorithm module. For example, with respect to the wheel odometer in the wheel odometer module, in other embodiments of the present application, a visual odometer, a lidar odometer, and the like can also be used instead, which is not limiting in the present application.
With continued reference to fig. 3, in the output verification portion, the method 10 performs fault diagnosis on the result of the positioning algorithm solution of the vehicle in step S1, specifically includes obtaining pose output information of the map matching module, the integrated navigation module, the wheel-type odometer module, and/or the fusion positioning algorithm module, and performing pose jump detection according to the pose output information.
On this basis, in the present embodiment, the method 10 preferably designs a specific diagnostic algorithm for the output portion of each module. Specifically, the step of performing fault diagnosis on the output part of the map matching module further includes performing output offset detection, where the output offset detection includes converting the perceived lane line from the vehicle body coordinate system to the world coordinate system by using pose output information to perform projection so as to obtain the perceived lane line to be analyzed; and comparing the high-precision map lane line under the world coordinate system with the sensing lane line to be analyzed to judge whether the lane line is deviated or not, so as to obtain a fault diagnosis conclusion.
In this embodiment, the step of performing the fault diagnosis on the output portion of the integrated navigation module further includes performing a longitudinal speed comparison detection and an integrated navigation position consistency detection, wherein the longitudinal speed comparison detection includes obtaining a fault diagnosis conclusion by comparing the longitudinal speeds of the integrated navigation module and a wheel speed meter of the vehicle in a vehicle body coordinate system; the integrated navigation position consistency detection comprises the steps of obtaining the actual front and rear frame positions calculated according to the current running speed of the vehicle and the output front and rear frame positions generated by the integrated navigation module after calculation, and comparing the actual front and rear frame positions with the output front and rear frame positions, so that a fault diagnosis conclusion is obtained.
In this embodiment, the step of performing fault diagnosis on the output portion of the fusion positioning algorithm module further includes performing fusion positioning position consistency detection, where the fusion positioning position consistency detection includes calculating a first front and rear frame position according to an output speed provided by the integrated navigation module; outputting the second front and rear frame positions after resolving through the fusion positioning algorithm module; and comparing whether the first front and rear frame positions are consistent with the second front and rear frame positions to obtain a fault diagnosis conclusion.
Further, the step of performing fault diagnosis on the fused positioning algorithm module further includes performing an excess edge detection, where the excess edge detection includes: loading the map lane lines from the map matching module to the fusion positioning algorithm module, and acquiring road edge information; and comparing the current frame resolving result of the fusion positioning algorithm module with the road edge information to judge whether the vehicle exceeds the road edge or not, thereby obtaining a fault diagnosis conclusion.
Referring back to fig. 2, in this embodiment, the method 10 preferably performs a fault risk level assessment on each type of fault generated by each module, where the level assessment conclusion includes a fatal fault, a serious fault, and a general fault. In the method, when risk level evaluation is performed according to the fault diagnosis conclusion, corresponding adjustment and setting can be performed according to actual conditions and application scenes. By way of example, the fault diagnosis conclusion and the rating evaluation conclusion may be corresponded with reference to some of the principles listed below. For example, the fatal fault may be a program operation fault in general input information fault diagnosis, such as the fault of general input information fault diagnosis that was previously determined by the general input information fault diagnosis, such as the map matching module, the integrated navigation module, the wheel odometer module, and the fusion positioning algorithm module, with reference to fig. 3; the serious faults are the excess road edge detection faults determined by the excess road edge detection in the fusion positioning algorithm module or the pose jump detection faults determined by the pose jump detection of the fusion positioning algorithm module; the common faults include all other faults such as an output offset detection fault determined by output offset detection, a longitudinal speed comparison detection fault determined by longitudinal speed comparison detection, a combined navigation position consistency detection fault determined by combined navigation position consistency detection, and the like.
On the basis, the preset auxiliary driving modes comprise a low-order auxiliary driving mode, a pure vision auxiliary driving mode and a high-order pilot auxiliary driving mode. Corresponding to the setting, the positioning state code has numerical intervals of a first gear, a second gear and a third gear from low to high. For example, when the positioning status code is 21-50, the first gear is positioned, namely, the fatal fault interval, when the positioning status code is 51-100, the second gear is positioned, namely, the serious fault interval, and when the positioning status code is 101-200, the first gear is positioned, namely, the ordinary fault interval. In this embodiment, when the positioning status code is 1-20, it indicates that the vehicle is in a status of normal running without failure at this time.
In this embodiment, when the locating status code included in the locating result message received by the regulation module is in the value interval of 21-50, that is, when the level evaluation conclusion is a fatal fault, it means that the fault is serious, the method 10 executes step S4 to control the vehicle to exit all the auxiliary driving functions, and restarts the domain controller or restarts the locating process.
Further, when the level evaluation conclusion is a serious fault, which means that the fault is serious, the positioning status code created according to the level evaluation conclusion is located in the numerical range of the second gear, that is, 51-100, at this time, the method 10 executes step S4 to further control the vehicle to run in the low-order auxiliary driving mode, and at this time, the vehicle will run in the low-order auxiliary driving mode for a period of time, and the high-order auxiliary driving mode cannot be restarted until the state of the vehicle returns to a normal period of time and the recovery condition is satisfied.
When the grade evaluation conclusion is a common fault, the fault is in a controllable range, and the positioning state code created according to the grade evaluation conclusion is located in a numerical range of a third gear, namely 101-200. At this time, the method 10 executes step S4 to control the vehicle to run in the pure vision auxiliary mode instead of the higher-order auxiliary mode, and maintains the running for a period of time, the switching process is not perceived by the occupant, and after the failure is recovered, the background is automatically switched back to the higher-order pilot auxiliary driving mode.
In this embodiment, the fusion module is the final output module that is the positioning algorithm module. Referring to fig. 4, in this embodiment, it is preferable to design the positioning status code to use a software program bit form so that the corresponding positioning fault code information can be directly carried according to the difference of the numerical intervals, and the positioning algorithm transmits the positioning result message to the rule control algorithm in real time, and simultaneously includes the positioning position and posture result (i.e. the positioning algorithm resolving result) and the positioning status code information, so as to play a role in fault real-time transmission. For example, if the message queue is set to be transmitted once for t, the time for the rule algorithm to receive the positioning fault information is equal to t. The output frequency of the positioning algorithm to the regulation algorithm is 100hz, namely 10ms is one frame, the real-time performance of the positioning algorithm on the positioning output is very high, and the vehicle can generally run for more than 40 meters at high speed for 1 s. When the architecture is adopted, the control algorithm can quickly respond when the positioning algorithm fails, and can remind a driver to take over the vehicle in time while taking urgent measures.
By adopting the architecture, the method 10 realizes the function of fault interaction between the positioning state code and the regulation algorithm, and avoids processing and transmission through other functional modules such as bottom software and the like in the prior art, so that the communication bandwidth consumption is extremely low and the instantaneity is high. And meanwhile, no extra hardware cost is needed, and the fault locating architecture is detected, defined and realized at the software level.
Still another aspect of the present application proposes a high-precision localization fault diagnosis system 20 based on risk level assessment, including a perception module 21 configured to provide perception information; a positioning module 22 configured to generate a positioning algorithm solution result of the vehicle during the running of the vehicle, and obtain a fault diagnosis conclusion, a grade evaluation conclusion and create a positioning status code according to the fault diagnosis method of any embodiment of the present application; and a regulation module 23 configured to receive the positioning result message from the positioning module and control the vehicle to run in the preset auxiliary driving mode, wherein the positioning result message includes a positioning algorithm resolving result and a positioning status code, and the type of the preset auxiliary driving mode corresponds to the positioning status code. According to fig. 5, it can be seen that the fault diagnosis method disclosed by the application is comprehensively integrated in the information transmission process among the sensing module 21, the positioning module 22 and the regulation module 23, and on the premise that high-cost upgrading and changing are not required to be introduced into the existing software and hardware framework, the robustness, accuracy and safety of the whole auxiliary driving system can be effectively improved by virtue of real-time positioning state code following transmission. For further details regarding fig. 5, reference may be made to the foregoing description of the fault diagnosis method set forth in the present application, which is not repeated here.
While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing application disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements, and adaptations of the present application may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be suggested within this application, and are therefore within the spirit and scope of the exemplary embodiments of this application.
Meanwhile, the present application uses specific words to describe embodiments of the present application. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the present application. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the present application may be combined as suitable.
Likewise, it should be noted that in order to simplify the presentation disclosed herein and thereby aid in understanding one or more application embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure. This method of disclosure, however, is not intended to imply that more features than are presented in the claims are required for the subject application. Indeed, less than all of the features of a single embodiment disclosed above.
In some embodiments, numbers describing the components, number of attributes are used, it being understood that such numbers being used in the description of embodiments are modified in some examples by the modifier "about," approximately, "or" substantially. Unless otherwise indicated, "about," "approximately," or "substantially" indicate that the number allows for a 20% variation. Accordingly, in some embodiments, numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and employ a method for preserving the general number of digits. Although the numerical ranges and parameters set forth herein are approximations that may be employed in some embodiments to confirm the breadth of the range, in particular embodiments, the setting of such numerical values is as precise as possible.
While the present application has been described with reference to the present specific embodiments, those of ordinary skill in the art will recognize that the above embodiments are for illustrative purposes only, and that various equivalent changes or substitutions can be made without departing from the spirit of the present application, and therefore, all changes and modifications to the embodiments described above are intended to be within the scope of the claims of the present application.
Claims (4)
1. The high-precision positioning fault diagnosis method based on risk level evaluation is characterized by comprising the following steps of:
continuously performing fault diagnosis on a positioning algorithm resolving result of the vehicle to obtain a fault diagnosis conclusion in the running process of the vehicle, wherein the fault diagnosis comprises a map matching module, a combined navigation module, a wheel type odometer module and a fusion positioning algorithm module in a positioning module of the vehicle;
performing risk grade assessment according to the fault diagnosis conclusion to obtain a grade assessment conclusion;
establishing a positioning state code according to the grade evaluation conclusion; and
the vehicle is controlled to switch to run in a preset auxiliary driving mode or exit from a current auxiliary driving mode through the positioning state code, wherein the type of the preset auxiliary driving mode corresponds to the positioning state code;
wherein,
the step of performing fault diagnosis on the map matching module further includes performing output offset detection, wherein the output offset detection includes:
the method comprises the steps of obtaining pose output information of a map matching module, converting a perceived lane line from a vehicle body coordinate system to a world coordinate system by utilizing the pose output information, and projecting to obtain a perceived lane line to be analyzed; and
comparing the high-precision map lane line under the world coordinate system with the to-be-analyzed sensing lane line to judge whether the lane line is deviated or not, so as to obtain the fault diagnosis conclusion;
the step of performing fault diagnosis on the integrated navigation module further comprises performing a longitudinal speed comparison detection and an integrated navigation position consistency detection, wherein,
the longitudinal speed comparison detection includes: obtaining the fault diagnosis conclusion by comparing the longitudinal speeds of the integrated navigation module and the wheel speed meter of the vehicle under a vehicle body coordinate system;
the integrated navigation position consistency detection comprises the following steps: acquiring an actual front and rear frame position calculated according to the current running speed of the vehicle and an output front and rear frame position generated by the integrated navigation module after calculation, and comparing the actual front and rear frame position with the output front and rear frame position so as to obtain the fault diagnosis conclusion;
the step of performing fault diagnosis on the fusion positioning algorithm module further includes performing fusion positioning position consistency detection, where the fusion positioning position consistency detection includes:
calculating a first front frame position and a second frame position according to the output speed provided by the integrated navigation module;
acquiring the position of a second front frame and a second back frame which are output by the fusion positioning algorithm module after being resolved; and
comparing whether the first front and rear frame positions are consistent with the second front and rear frame positions to obtain the fault diagnosis conclusion;
the step of performing fault diagnosis on the fusion positioning algorithm module further comprises the step of executing excess road edge detection, wherein the excess road edge detection comprises the following steps:
loading the map lane lines from the map matching module to the fusion positioning algorithm module, and acquiring road edge information;
comparing the current frame calculation result of the fusion positioning algorithm module with the road edge information to judge whether the vehicle exceeds the road edge or not, so as to obtain the fault diagnosis conclusion;
the level evaluation conclusion includes a general fault, a serious fault, and a fatal fault, the preset driving assistance mode includes a low-order driving assistance mode, a pure visual driving assistance mode, and a high-order pilot driving assistance mode, and the positioning status code has numerical intervals of a first gear, a second gear, and a third gear from low to high, wherein,
when the grade evaluation conclusion is the fatal fault, the positioning state code created according to the grade evaluation conclusion is located in a numerical interval of the first gear, and the method further comprises controlling the vehicle to exit from the current auxiliary driving mode for driving;
when the grade evaluation conclusion is the serious fault, the positioning state code created according to the grade evaluation conclusion is located in a numerical interval of the second gear, and the method further comprises controlling the vehicle to run in the low-order auxiliary driving mode; and
when the grade evaluation conclusion is the common fault, the positioning state code created according to the grade evaluation conclusion is located in the numerical interval of the third gear, and the method further comprises controlling the vehicle to run in the pure vision auxiliary driving mode and/or the high-order pilot auxiliary driving mode.
2. The fault diagnosis method according to claim 1, wherein the step of performing fault diagnosis on the result of the localization algorithm solution of the vehicle further comprises: and acquiring pose output information of the map matching module, the integrated navigation module, the wheel type odometer module and the fusion positioning algorithm module, and executing corresponding pose jump detection according to the pose output information.
3. The fault diagnosis method according to claim 1, wherein the positioning algorithm solution results comprise positioning position and/or posture results, and the form of the positioning status code comprises bits.
4. A high-precision localization fault diagnosis system based on risk level assessment for implementing the fault diagnosis method as claimed in any one of claims 1 to 3, comprising:
a perception module configured to provide perception information;
the positioning module is configured to generate a positioning algorithm resolving result of the vehicle in the running process of the vehicle, obtain a fault diagnosis conclusion and a grade evaluation conclusion and establish a positioning state code; and
the regulation module is configured to receive a positioning result message from the positioning module and control the vehicle to run in a preset auxiliary driving mode, wherein the positioning result message comprises a positioning algorithm resolving result and the positioning state code, and the type of the preset auxiliary driving mode corresponds to the positioning state code.
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