CN116331237B - Control method for automatic driving vehicle - Google Patents

Control method for automatic driving vehicle

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Publication number
CN116331237B
CN116331237B CN202310174788.7A CN202310174788A CN116331237B CN 116331237 B CN116331237 B CN 116331237B CN 202310174788 A CN202310174788 A CN 202310174788A CN 116331237 B CN116331237 B CN 116331237B
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China
Prior art keywords
vehicle
automatic driving
information
driving vehicle
track
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CN116331237A (en
Inventor
李玉峰
卜士洋
王鹏
沈毅
刘俊雲
张浪
张瑰琦
陶士昌
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Zijinshan Laboratory
Purple Mountain Laboratories
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Zijinshan Laboratory
Purple Mountain Laboratories
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Priority to CN202310174788.7A priority Critical patent/CN116331237B/en
Publication of CN116331237A publication Critical patent/CN116331237A/en
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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
    • 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
    • B60W50/029—Adapting to failures or work around with other constraints, e.g. circumvention by avoiding use of failed parts

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)

Abstract

本发明公开了一种自动驾驶车辆的控制方法。其中，该方法包括：获取自动驾驶车辆的异常状态信息，其中，异常状态信息包括：用于表征自动驾驶车辆中的域控制器出现异常的第一状态信息，及用于表征自动驾驶车辆的通信状态出现异常的第二状态信息；基于异常状态信息，确定自动驾驶车辆的异常类型，其中，异常类型包括：域控制器的第一异常类型和数据传输总线的第二异常类型；确定异常类型对应的故障等级，其中，故障等级用于表征异常类型对自动驾驶车辆的正常行驶的影响程度；基于故障等级对应的预设控制方案，控制自动驾驶车辆运行。本发明解决了相关技术无法全面地发现整车故障，并采取相应的控制措施的技术问题。

This invention discloses a control method for an autonomous vehicle. The method includes: acquiring abnormal state information of the autonomous vehicle, wherein the abnormal state information includes: first state information indicating an abnormality in the domain controller of the autonomous vehicle, and second state information indicating an abnormality in the communication state of the autonomous vehicle; determining the abnormality type of the autonomous vehicle based on the abnormal state information, wherein the abnormality type includes: a first abnormality type of the domain controller and a second abnormality type of the data transmission bus; determining the fault level corresponding to the abnormality type, wherein the fault level is used to characterize the degree of impact of the abnormality type on the normal operation of the autonomous vehicle; and controlling the operation of the autonomous vehicle based on a preset control scheme corresponding to the fault level. This invention solves the technical problem that related technologies cannot comprehensively detect vehicle faults and take corresponding control measures.

Description

Control method for automatic driving vehicle
Technical Field
The invention relates to the field of vehicle control, in particular to a control method of an automatic driving vehicle.
Background
With the increasing complexity of the actual application scene of the automatic driving automobile, the safety requirement of people on the automatic driving automobile is higher, the existing automatic driving automobile degradation operation measures mainly focus on the man-vehicle interaction and alarming after abnormal discovery, do not take safety measures for protecting passengers and vehicles in time and autonomously, only focus on a certain module fault, and are too simple for the grading and classifying treatment measures of the fault, so that the riding experience of passengers is greatly discounted, and even the safety of passengers is endangered.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a control method for an automatic driving vehicle, which at least solves the technical problems that the related technology cannot comprehensively discover the faults of the whole vehicle and adopts corresponding control measures.
According to one aspect of the embodiment of the invention, the control method of the automatic driving vehicle comprises the steps of obtaining abnormal state information of the automatic driving vehicle, wherein the abnormal state information comprises first state information used for representing that a domain controller in the automatic driving vehicle is abnormal and second state information used for representing that a communication state of the automatic driving vehicle is abnormal, determining an abnormal type of the automatic driving vehicle based on the abnormal state information, wherein the abnormal type comprises a first abnormal type of the domain controller and a second abnormal type of a data transmission bus, determining a fault grade corresponding to the abnormal type, wherein the fault grade is used for representing the influence degree of the abnormal type on normal running of the automatic driving vehicle, and controlling the automatic driving vehicle to run based on a preset control scheme corresponding to the fault grade.
Optionally, acquiring abnormal state information of the automatic driving vehicle comprises acquiring current state information sent by the domain controller and fault information of an electronic device corresponding to the domain controller in response to the occurrence of abnormality of the domain controller to obtain first state information, and acquiring data transmission state information of a data transmission bus to obtain second state information.
Optionally, determining the fault level corresponding to the abnormality type comprises matching the abnormality type with a plurality of preset abnormality types to obtain a target abnormality type successfully matched with the abnormality type, and determining the preset level corresponding to the target abnormality type as the fault level.
Optionally, in response to failure in matching the abnormality type with a plurality of preset abnormality types, the method further comprises the steps of obtaining a fault reason corresponding to the abnormality type, and evaluating the fault reason to obtain a fault grade corresponding to the abnormality type.
The method comprises the steps of controlling the automatic driving vehicle to run based on a preset control scheme corresponding to a fault level, wherein the automatic driving vehicle is controlled to cut off power supply, controlling the automatic driving vehicle to perform emergency braking, controlling the automatic driving vehicle to perform non-emergency braking, controlling the automatic driving vehicle to stop at the side, controlling the automatic driving vehicle to run to a target stop point to stop, controlling the automatic driving vehicle to stop at a second stop point after completing a current dispatching task, controlling the speed of the automatic driving vehicle to be smaller than a preset value, controlling the automatic driving vehicle to keep in a static state, and controlling the automatic driving vehicle to output alarm information, wherein the alarm information is used for representing that the automatic driving vehicle is abnormal.
The method comprises the steps of obtaining first driving information of an automatic driving vehicle, wherein the first driving information comprises chassis state information, vehicle positioning information, first obstacle information positioned in front of the automatic driving vehicle and navigation route information, generating a vehicle driving track of the automatic driving vehicle at a future moment based on the first driving information and a historical planning track of the automatic driving vehicle, determining an emergency braking mode of the automatic driving vehicle based on the first obstacle information and the vehicle driving track, wherein different emergency braking modes are used for braking the automatic driving vehicle in different braking modes, and controlling the automatic driving vehicle to brake based on the emergency braking mode.
The method comprises the steps of determining an emergency braking mode of an automatic driving vehicle based on first obstacle information and a vehicle driving track, wherein the method comprises the steps of minimizing the vehicle driving track and maximizing deceleration of the automatic driving vehicle to obtain a first emergency braking track of the automatic driving vehicle, obtaining the sum of displacement of the first emergency braking track and parking safety distance of the automatic driving vehicle to obtain a preset distance, determining the emergency braking mode to be the first braking mode in response to the fact that the obstacle distance in the first obstacle information is larger than the preset distance, wherein the first braking mode is used for controlling the automatic driving vehicle to brake according to the vehicle driving track, and determining the emergency braking mode to be the second braking mode in response to the fact that the obstacle distance is smaller than or equal to the preset distance, wherein the second braking mode is used for controlling a brake pedal of the automatic driving vehicle to brake according to different opening degrees.
The method comprises the steps of obtaining first driving information of an automatic driving vehicle, wherein the driving information comprises chassis state information, vehicle positioning information, first obstacle information positioned in front of the automatic driving vehicle and navigation route information, generating a vehicle driving track of the automatic driving vehicle at a future moment based on the first driving information and a history planning track of the automatic driving vehicle, maximizing the vehicle driving track, minimizing deceleration of the automatic driving vehicle to obtain a second emergency braking track of the automatic driving vehicle, and controlling the automatic driving vehicle to brake based on the second emergency braking track.
The method comprises the steps of obtaining second driving information of an automatic driving vehicle, wherein the second driving information comprises transverse displacement, speed and acceleration, performing track fitting on the automatic driving vehicle based on the second driving information to obtain a motion track of the automatic driving vehicle, obtaining sensing information of the automatic driving vehicle, wherein the sensing information comprises second obstacle information in the transverse direction and lane line information around the automatic driving vehicle, and controlling the automatic driving vehicle to stop by the side based on the sensing information and the motion track.
Optionally, the method further comprises the steps of determining a target fault grade in the fault grades, wherein the target fault grade is higher than other fault grades in the fault grades, and obtaining a control scheme corresponding to the target fault grade to obtain a preset control scheme.
According to another aspect of the embodiment of the invention, a control system of an automatic driving vehicle is further provided, and the control system comprises a state data receiving module and a vehicle control module, wherein the state data receiving module is used for obtaining abnormal state information of the automatic driving vehicle, the abnormal state information comprises first state information used for representing that a domain controller in the automatic driving vehicle is abnormal and second state information used for representing that a communication state of the automatic driving vehicle is abnormal, the fault diagnosis grading module is used for determining an abnormal type of the automatic driving vehicle based on the abnormal state information and determining a fault grade corresponding to the abnormal type, the abnormal type comprises a first abnormal type of the domain controller and a second abnormal type of a data transmission bus, the fault grade is used for representing the influence degree of the abnormal type on normal running of the automatic driving vehicle, and the vehicle control module is used for controlling the automatic driving vehicle to run based on a preset control scheme corresponding to the fault grade.
According to another aspect of the embodiment of the present invention, there is also provided a computer-readable storage medium, the computer-readable storage medium including a stored program, wherein a device in which the computer-readable storage medium is controlled to execute the above-described control method for an autonomous vehicle when the program runs.
According to another aspect of the embodiment of the present invention, there is also provided a processor for running a program, wherein the program executes the control method of the autonomous vehicle.
In the embodiment of the invention, the abnormal state information of the automatic driving vehicle is acquired, the abnormal type of the automatic driving vehicle is determined based on the abnormal state information, then the fault grade corresponding to the abnormal type is determined, the operation of the automatic driving vehicle is controlled based on the preset control scheme corresponding to the fault grade, the abnormal type comprises a first abnormal type of a domain controller and a second abnormal type of a data transmission bus, the fault grade is used for representing the influence degree of the abnormal type on the normal running of the automatic driving vehicle, the abnormal type and the corresponding fault grade of the vehicle are determined by acquiring the abnormal information of the vehicle domain controller and the communication state, and the corresponding control scheme is set based on the fault grade, so that the aims of effectively evaluating various abnormalities found in the operation of the automatic driving vehicle and taking corresponding degradation measures are fulfilled, the whole vehicle fault is comprehensively detected, the technical effects of taking different control schemes for different abnormal types are achieved, and the technical problems that the related technology cannot comprehensively find the whole vehicle fault and take corresponding control measures are solved.
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 specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a method of controlling an autonomous vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an autonomous vehicle downgrade operation system according to an embodiment of the invention;
Fig. 3 is a schematic diagram of a control system for an autonomous vehicle according to an embodiment of the invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention 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 invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
According to an embodiment of the present invention, there is provided a control method of an autonomous vehicle, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical sequence is shown in the flowchart, in some cases the steps shown or described may be performed in a different order than what is shown herein.
Fig. 1 is a flowchart of a control method of an autonomous vehicle according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, obtaining abnormal state information of the automatic driving vehicle, wherein the abnormal state information comprises first state information used for representing that a domain controller in the automatic driving vehicle is abnormal and second state information used for representing that the communication state of the automatic driving vehicle is abnormal.
The domain controller may be a server computer that responds to a security authentication request within a computer network domain for data calculation and overall control functions responsible for the critical functional domains of an autonomous vehicle. The key functional domain of the automatic driving vehicle is obtained according to an electronic and electric architecture of the automatic driving vehicle, and comprises, but not limited to, an automatic driving domain, a chassis domain, a power domain, a vehicle body domain and a network connection domain, wherein the automatic driving domain is responsible for the automatic driving function of the vehicle, the chassis domain is an actuating mechanism of the vehicle, the driving state data of the vehicle can be fed back to an automatic driving system, the power domain manages the energy use state of the vehicle, the vehicle body domain manages the use states of components related to the vehicle, such as a vehicle lamp, a vehicle door, a vehicle window, a windshield wiper and the like, the network connection domain realizes the interconnection of information in the vehicle and the outside of the vehicle, the vehicle and the cloud platform, the vehicle and the vehicle, the road and the vehicle and the human, the vehicle interior network and the like are all-round network-linked, the first state information can be the state information of a domain controller, and the second state information can be the state information of vehicle communication.
In an alternative embodiment, the first status information may be obtained by an electronic control unit (Electronic Control Unit, abbreviated ECU) and a connection sensor, and the second status information may be obtained by data interception.
Step S104, determining an abnormality type of the automatic driving vehicle based on the abnormality state information, wherein the abnormality type comprises a first abnormality type of the domain controller and a second abnormality type of the data transmission bus.
The first exception type can be the exception type of the domain controller, including but not limited to no output data, tampered data, exception of processing results and other unknown exceptions, the ECU exception type and the sensor exception type are determined by a specific product maintenance manual, and the second exception type can be the exception type of the data transmission bus, including but not limited to exceptions such as communication interruption, communication delay, communication link attack and the like.
In an alternative embodiment, the first anomaly type may be determined by the ECU and the connection sensor, and the second anomaly type may be obtained by monitoring the data transmission status of the accessed CAN bus network and ethernet network, receiving network communication status information, and detecting and confirming the communication status anomaly and the specific anomaly type.
Step S106, determining a fault grade corresponding to the abnormal type, wherein the fault grade is used for representing the influence degree of the abnormal type on the normal running of the automatic driving vehicle.
In an alternative embodiment, the fault level corresponding to the anomaly type may be determined by performing a risk level analysis on each domain controller anomaly (i.e., communication node anomaly) and data transmission state anomaly (i.e., communication state anomaly) obtained by receiving, i.e., analyzing the severity of the consequences that the anomaly may have on the passenger and vehicle state, and then performing a reasonable automated driving vehicle fault severity classification, creating a fault severity level table corresponding to the anomaly type.
Specifically, the failure levels may include, but are not limited to, nine failure levels E0 through E8. Where E0 is the highest failure level, E8 is the lowest failure level, intermediate levels, and so on.
Step S108, controlling the operation of the automatic driving vehicle based on the preset control scheme corresponding to the fault level.
The preset control scheme can be preset in advance, and for different received fault levels, a corresponding vehicle control method is called by combining the current state of the vehicle and the obstacle information in front of the vehicle.
Specifically, when the failure level is E0, it may be considered that the current vehicle is uncontrollable, and the danger is unavoidable, and the power supply of the automatic driving vehicle must be disconnected only by adopting a high-voltage disconnection manner, so as to reduce the injury to the human and vehicle caused by the collision; when the failure level is E1, the vehicle can be considered to be unavoidable in collision or is in a critical condition of collision but controllable, the most urgent braking control mode must be adopted to control the vehicle to stop so as to reduce the damage or avoid collision caused by the collision to the human vehicle, when the failure level is E2, the vehicle can be considered to be controllable, the collision condition exists but can be avoided, the vehicle can be controlled in a non-urgent braking mode to avoid the collision and improve the comfort of the braking process from the passenger angle, when the failure level is E3, the vehicle can be considered to have no automatic driving condition, if the vehicle continues to drive, the vehicle can be considered to be in a side parking mode, and continues to drive after the abnormality is eliminated, when the failure level is E4, the vehicle can be considered to have a short-term automatic driving condition, but can trigger the collision condition after a certain period is exceeded, the vehicle can be controlled to safely reach the point and stop, when the failure level is E5, the vehicle can not immediately be considered to have an automatic driving condition, the vehicle can not be considered to have a task scheduling problem, the vehicle can be controlled to have a task scheduling condition after a certain period is exceeded, the vehicle can be considered to have a safe parking point when the vehicle is stopped, the vehicle is not be completely stopped, and the vehicle can be parked when the vehicle is 6 has a short-term, the vehicle is not have a task is scheduled, and the vehicle is required to be parked when the vehicle is completely stopped, and has a certain condition is completely, and has a safe parking condition is required to be controlled when the vehicle is 6, however, due to the limitation of special driving scenes, the vehicle speed is limited below a certain value, the vehicle is controlled to drive at the limited speed value, when the failure level is E7, the vehicle can be considered to be in a stationary state and has abnormality, the automatic driving function of the vehicle is required to be locked, the vehicle is kept in a stopped state, the locked state of the vehicle is released after the abnormality is eliminated, and when the failure level is E8, the abnormality can be considered to have no influence on the current running state of the vehicle, and only an alarm prompt is made.
In the embodiment of the invention, the abnormal state information of the automatic driving vehicle is acquired, the abnormal type of the automatic driving vehicle is determined based on the abnormal state information, then the fault grade corresponding to the abnormal type is determined, the operation of the automatic driving vehicle is controlled based on the preset control scheme corresponding to the fault grade, the abnormal type comprises a first abnormal type of a domain controller and a second abnormal type of a data transmission bus, the fault grade is used for representing the influence degree of the abnormal type on the normal running of the automatic driving vehicle, the abnormal type and the corresponding fault grade of the vehicle are determined by acquiring the abnormal information of the vehicle domain controller and the communication state, and the corresponding control scheme is set based on the fault grade, so that the aims of effectively evaluating various abnormalities found in the operation of the automatic driving vehicle and taking corresponding degradation measures are fulfilled, the whole vehicle fault is comprehensively detected, the technical effects of taking different control schemes for different abnormal types are achieved, and the technical problems that the related technology cannot comprehensively find the whole vehicle fault and take corresponding control measures are solved.
Optionally, acquiring abnormal state information of the automatic driving vehicle comprises acquiring current state information sent by the domain controller and fault information of an electronic device corresponding to the domain controller in response to the occurrence of abnormality of the domain controller to obtain first state information, and acquiring data transmission state information of a data transmission bus to obtain second state information.
The current state information may be state information of the domain controller in the current working process, the fault information of the electronic device may include, but is not limited to, a fault position and a fault degree, and the data transmission state information may include, but is not limited to, normal and abnormal.
In an alternative embodiment, the current state information sent by the domain controller may be acquired by the ECU and the connection sensor, and the data transmission state information of the data transmission bus may be acquired by data listening.
Optionally, determining the fault level corresponding to the abnormality type comprises matching the abnormality type with a plurality of preset abnormality types to obtain a target abnormality type successfully matched with the abnormality type, and determining the preset level corresponding to the target abnormality type as the fault level.
The preset abnormality types can be types of abnormality of the vehicle preset in advance, the target abnormality types can be preset abnormality types matched with the current abnormality types of the vehicle, the preset levels can be preset fault levels in advance, and nine fault levels can be used for representing the fault levels from E0 to E8.
In an alternative embodiment, the anomaly type and a plurality of preset anomaly types can be matched through a keyword comparison method to obtain a target anomaly type successfully matched with the anomaly type, and a preset grade corresponding to the target anomaly type can be determined to be a fault grade through a table lookup method.
Specifically, according to the acquired first state information and second state information, a fault severity level table is formed after fault risk level evaluation, and abnormal alarm information is generated to the vehicle terminal, and the table can be directly checked for the known abnormality found later to acquire the fault severity level.
Optionally, in response to failure of matching the abnormality type with a plurality of preset abnormality types, the method further comprises obtaining a fault reason corresponding to the abnormality type, and evaluating the fault reason to obtain a fault grade corresponding to the abnormality type.
The cause of the failure may be a factor that causes the vehicle to fail.
It will be appreciated that when an unknown anomaly occurs in the vehicle, then a fault severity level assessment is made based on the fault localization and description, matching the existing fault severity level, and then the anomaly of that type and the corresponding fault level are added to the fault severity level table.
Optionally, the method further comprises the steps of determining a target fault grade in the fault grades, wherein the target fault grade is higher than other fault grades in the fault grades, and obtaining a control scheme corresponding to the target fault grade to obtain a preset control scheme.
The target failure level may be a level corresponding to a failure that the vehicle currently generates.
Specifically, as shown in step S108, different failure levels correspond to different control schemes.
The method comprises the steps of controlling the automatic driving vehicle to run based on a preset control scheme corresponding to a fault level, wherein the automatic driving vehicle is controlled to cut off power supply, controlling the automatic driving vehicle to perform emergency braking, controlling the automatic driving vehicle to perform non-emergency braking, controlling the automatic driving vehicle to stop at the side, controlling the automatic driving vehicle to run to a target stop point to stop, controlling the automatic driving vehicle to stop at a second stop point after completing a current dispatching task, controlling the speed of the automatic driving vehicle to be smaller than a preset value, controlling the automatic driving vehicle to keep in a static state, and controlling the automatic driving vehicle to output alarm information, wherein the alarm information is used for representing that the automatic driving vehicle is abnormal.
The target stop point may be a stop point closest to the current vehicle, the current dispatching task may include, but is not limited to, boarding and disembarking, loading and unloading, or leaving a task point, etc., the second stop point may be a stop point closest to the current dispatching task after the vehicle completes the current dispatching task, and the preset value may be a vehicle speed limited by a special scene.
In an alternative embodiment, the vehicle may be controlled by a vehicle control device to implement the above control scheme, and the warning information may be fed back to the user by an acoustic feedback device, where the acoustic feedback device may be understood as any device capable of implementing acoustic feedback, such as a horn, or other horn-loaded device. The normal traffic notification fed back by the sound feedback device may be a sound with semantics or a sound which is not provided with semantics and can be recognized, for example, the normal notification of the vehicle state is "drop" one sound, and the abnormal notification of the vehicle state is "drop" three sound.
Specifically, the above control scheme corresponds to E0 to E8 for a total of nine failure levels, respectively, as described in step S108.
The method comprises the steps of obtaining first driving information of an automatic driving vehicle, wherein the driving information comprises chassis state information, vehicle positioning information, first obstacle information positioned in front of the automatic driving vehicle and navigation route information, generating a vehicle driving track of the automatic driving vehicle at a future moment based on the first driving information and a historical planning track of the automatic driving vehicle, determining an emergency braking mode of the automatic driving vehicle based on the first obstacle information and the vehicle driving track, wherein different emergency braking modes are used for braking the automatic driving vehicle in different braking modes, and controlling the automatic driving vehicle to brake based on the emergency braking mode.
The chassis state information may be normal or abnormal, the vehicle positioning information may be a current specific positioning of the vehicle, the first obstacle information may be perceived obstacle information in front of the vehicle, the navigation route information may be a specific route for vehicle navigation, the history planning track may be a braking planning track of a vehicle history, and the emergency braking mode may be a mode for controlling the vehicle to perform emergency braking.
In an alternative embodiment, the first travel information of the autonomous vehicle may be obtained by means of a sensor, a positioning system, or the like.
Specifically, generating a vehicle travel track of an autonomous vehicle at a future time includes establishing a vehicle braking track planning method, i.e., a track planning module of a vehicle derating system. According to chassis state information, vehicle positioning information, perceived obstacle information and navigation route information, a braking track of the vehicle in an advanced prediction state is periodically generated by combining a vehicle history planning track, a planning module data receiving and processing timer and a vehicle driving path reference line generator are created, and corresponding processing threads are started. The method comprises the steps of receiving external chassis state information, vehicle positioning information, perceived obstacle information and navigation route information in the scene planner, updating the vehicle state information, perceived fusion information and navigation route information after processing, and calling a map data interface to obtain high-precision map data in a certain range in front of and behind a vehicle according to the latest vehicle state information and navigation route information if the latest navigation route exists, wherein the high-precision map data comprises information such as road information, lane information, intersections, signal lamps, crosswalks, speed limit marks, forbidden stop marks and the like, and generating a reference line set for vehicle running according to the high-precision map data in the local range. If the latest navigation route does not exist, the road map data is updated according to the vehicle advancing direction planned by the reference line generator and a straight line path with a certain range behind the vehicle, a simplified vehicle driving reference line is generated according to the road map data, and the pre-control state of the vehicle is predicted and updated to serve as a track planning starting point according to the current state of the vehicle and the historical planning track, and the control time delay of the vehicle is considered. The method comprises the steps of carrying out track splicing on a planned starting point and a planned track on a vehicle, guaranteeing continuity of the overall planned track and smoothness of vehicle control, generating displacement data and speed data of the vehicle along each reference line by traversing a reference line set according to the current state of the vehicle, obstacle information in front of the vehicle, the planned track information of the previous frame and the planned starting point of the track, planning displacement data of the vehicle along the reference lines, namely carrying out inner coordinate projection on the planned starting point to the corresponding reference line, and intercepting and converting path points on the reference lines as displacement data points in a linear interpolation mode at certain distance intervals.
The method comprises the steps of determining an emergency braking mode of an automatic driving vehicle based on first obstacle information and a vehicle driving track, wherein the method comprises the steps of minimizing the vehicle driving track and maximizing deceleration of the automatic driving vehicle to obtain a first emergency braking track of the automatic driving vehicle, obtaining the sum of displacement of the first emergency braking track and parking safety distance of the automatic driving vehicle to obtain a preset distance, determining the emergency braking mode to be the first braking mode in response to the fact that the obstacle distance in the first obstacle information is larger than the preset distance, wherein the first braking mode is used for controlling the automatic driving vehicle to brake according to the vehicle driving track, and determining the emergency braking mode to be the second braking mode in response to the fact that the obstacle distance is smaller than or equal to the preset distance, wherein the second braking mode is used for controlling a brake pedal of the automatic driving vehicle to brake according to different opening degrees.
The first emergency braking track may be a braking track after the vehicle running track and the deceleration are re-planned, and the preset distance may be understood as a maximum distance between the vehicle, on which the braking track is calculated, and the obstacle after the vehicle is stably stopped.
The method for determining the emergency braking mode of the automatic driving vehicle can comprise the steps of planning speed data of the vehicle along a reference line, and firstly judging whether the speed data need to be re-planned according to projection of a planned track of a previous frame of a planning starting point. If the remaining distance from the projection point to the planned track end pointLess than the first obstacle distance from the vehicle to the frontSubtracting the stopping safety distance from the obstacle after stopping the vehicleI.e.The speed data of the track can be planned along the last frame without re-planning the speed data, and the relative distance between the speed data and the planning starting point is corrected. Otherwise, the speed data is re-planned from the planning starting point, and the speed data is re-planned from the planning starting point according to the three-section S-shaped brake curveState transition to deceleration uniform reductionState, deceleration change rate isWhere s, v and a are vehicle displacement, velocity and acceleration state values,For the initial braking speed to be the same,For the distance travelled after the end of the first phase of the vehicle,For the value of the speed of the vehicle after the end of the first phase,Is the maximum deceleration reached after the end of the first phase of the vehicle and is positive. And then is converted into the uniform deceleration motionA state in whichFor the distance travelled after the end of the second phase of the vehicle,Is the speed value after the second phase of the vehicle is finished. Finally, the speed is increased at a constant speed to be converted intoState, deceleration change rate isWhereinThe driving distance after the third stage of the vehicle is finished, namely the final driving distance of the vehicle along the planned track. In these three phasesTo a known extent, can obtainAnd (3) withConstraint relationship in which,The method comprises the steps of (1) setting a maximum deceleration value in the vehicle accelerator/brake calibration to be not larger than a maximum deceleration value, and finally establishing speed data of the vehicle along a reference line in combination with the vehicle motion process, wherein the time domain state information comprises time, displacement, speed, acceleration, jerk and the like in the vehicle motion process;
According to the planned track of the corresponding reference line, a track evaluation equation and a comprehensive cost function are established by considering curvature change, transverse offset, distance between the track and an obstacle and deviation degree of the track relative to the reference line, the total cost value of each reference line track is calculated, the reference line track with the minimum cost value is selected as a final vehicle running track, the relative time of the track is corrected by combining current timestamp information, and track data is issued at fixed time;
and establishing a brake control method of the vehicle along the planned track, namely a control module of the vehicle degradation running system. According to the generated vehicle running track, combining chassis state information, vehicle positioning information and vehicle accelerator/brake calibration information, periodically generating a vehicle transverse and longitudinal control instruction, and controlling the vehicle to brake along the planned track;
Establishing a vehicle transverse control method based on a linear quadratic optimal control algorithm, establishing a vehicle dynamics equation according to vehicle parameters and longitudinal speed, solving a coefficient matrix A, B in the state equation, discretizing the vehicle continuous state equation, establishing a linear quadratic regulator (Linear Quadratic Regulator, LQR for short) objective function according to the state matrix A, B, enabling the objective function to reach the iteration precision requirement through iterative optimization to obtain an optimal state feedback matrix K, predicting the state parameters of the vehicle at the pre-aiming time point in advance by combining the vehicle state and planning track information at a certain pre-aiming time, comparing the vehicle predicted state with the current state to obtain the transverse control error of the vehicle and the curvature information of the pre-aiming point, calculating a feedforward control output together with the vehicle parameter information and the curvature information of the pre-aiming point, eliminating the steady state error, calculating the steering angle of the final control output according to the state feedback matrix, the transverse control error and the feedforward control output calculated before, and periodically transmitting the steering instruction to the vehicle chassis according to a chassis control protocol so as to control the steering process of the vehicle;
Establishing a vehicle longitudinal control method based on a proportional, integral and derivative (Proportion INTEGRAL DIFFERENTIAL, PID for short) control algorithm of double-loop deviation;
establishing a PID control bottom logic, calculating PID control output according to a PID discretization calculation formula, initializing position PID and speed PID parameters according to control module configuration information, and loading an accelerator/brake calibration table, wherein the calibration table is obtained by carrying out longitudinal dynamics calibration test on a specific vehicle in advance;
A control module timer is established, external chassis state information, vehicle positioning information and track planning information are received at regular time, data verification and overtime receiving processing are carried out, vehicle state data are updated according to the received chassis state information and the received vehicle positioning information, a PID parameter interpolation table is inquired according to the initial braking speed of the planned track, and position PID and speed PID control parameters under specific initial braking speeds are set to obtain optimal control parameters under different initial braking speeds. The PID parameter interpolation table is obtained by adjusting position PID and speed PID of different initial braking speeds of a specific vehicle in advance, and the state parameters of the vehicle after the pre-aiming time are predicted in advance by combining the vehicle state and planning track information in a certain pre-aiming time, and the predicted state of the vehicle is compared with the current state to obtain the longitudinal control error of the vehicle. And calculating and outputting the error value through a position PID and a speed PID to obtain an acceleration control output value, and obtaining the acceleration final output through acceleration gradient compensation and control dead zone acceleration correction. The corresponding throttle/brake command value is obtained by inquiring a throttle/brake calibration table, and the unique brake or throttle opening is obtained through throttle/brake singularity processing. Finally, according to a chassis control protocol, the opening instruction is periodically sent to the chassis of the vehicle, so that the longitudinal acceleration or deceleration process of the vehicle is controlled;
And establishing a sectional pressure type brake control method. When the distance between the first obstacle and the front of the vehicle is smaller than the limit braking distance When the parking safety distance is added, the maximum opening type emergency braking is adopted for parking, whereinFor the current vehicle speed,G is the ground friction coefficient and g is the gravitational acceleration. When the distance between the obstacles is greater than the distance required by stable parking and the parking safety distance, a certain small brake opening is adopted to perform stable braking of the vehicle. When the obstacle distance is greater than the limit braking distance plus the parking safety distance and less than the stable parking distance plus the parking safety distance, the Time-To-Collision (TTC) graded braking is performed by adopting a Time-To-safety distance model based on Time distance, namely when the vehicle collides with the front vehicleWhen the device is in a non-operating state,When a certain moderate brake opening degree is adopted to perform partial braking,When the full braking of the maximum braking opening degree is performed, wherein T= (d-d 0)/V, d is the obstacle distance, d0 is the parking safety distance, V is the vehicle speed,、And the vehicle stationary brake opening value and part of the brake opening value are obtained by real vehicle testing.
A vehicle control method for emergency braking and stopping is established. Firstly, a planning module outputs a final emergency braking planning track by taking the maximum braking deceleration value and the minimum planning track displacement as constraint conditions, and then the distance between the vehicle and a front obstacle is judgedDistance of safety of parkingAnd final displacement of emergency brake planning track(I.e., the distance required for smooth stopping as described above), ifAnd if not, the control module adopts the sectional pressure type emergency braking to stop.
The method comprises the steps of obtaining first driving information of an automatic driving vehicle, wherein the driving information comprises chassis state information, vehicle positioning information, first obstacle information positioned in front of the automatic driving vehicle and navigation route information, generating a vehicle driving track of the automatic driving vehicle at a future moment based on the first driving information and a history planning track of the automatic driving vehicle, maximizing the vehicle driving track, minimizing deceleration of the automatic driving vehicle to obtain a second emergency braking track of the automatic driving vehicle, and controlling the automatic driving vehicle to brake based on the second emergency braking track.
The chassis state information may be normal or abnormal, the vehicle positioning information may be a current specific positioning of the vehicle, the first obstacle information may be perceived obstacle information in front of the vehicle, the navigation route information may be a specific route of vehicle navigation, the history planning track may be a braking planning track of vehicle history, the emergency braking mode may be a mode of controlling the vehicle to perform emergency braking, and the second emergency braking track may be a braking track after rescheduling the vehicle driving track and the deceleration.
In an alternative embodiment, the first travel information of the autonomous vehicle may be obtained by means of a sensor, a positioning system, or the like.
Specifically, controlling the autonomous vehicle to perform non-emergency braking may include outputting, by the planning module, a final emergency braking planned trajectory with the maximized planned trajectory displacement and the minimized braking deceleration value as constraints, and then controlling, by the control module, the vehicle to perform non-emergency braking along the planned trajectory.
The method comprises the steps of obtaining second driving information of an automatic driving vehicle, wherein the second driving information comprises transverse displacement, speed and acceleration, performing track fitting on the automatic driving vehicle based on the second driving information to obtain a motion track of the automatic driving vehicle, obtaining sensing information of the automatic driving vehicle, wherein the sensing information comprises second obstacle information in the transverse direction and lane line information around the automatic driving vehicle, and controlling the automatic driving vehicle to stop by the side based on the sensing information and the motion track.
The second obstacle information may be a position, a size, etc. of the perceived obstacle in the lateral direction of the vehicle, and the lane line information may be the number and specific positions of the lane lines.
In an alternative embodiment, the second travel information of the autonomous vehicle may be acquired by a displacement sensor, a speed sensor and an acceleration sensor.
The method comprises the following steps of controlling an automatic driving vehicle to stop by side, wherein a planning module utilizes a penta-order polynomial to fit a longitudinal track of the vehicle according to a vehicle kinematic model and the starting and ending states of the vehicle, namely transverse and longitudinal displacement, speed and acceleration values, of the vehicle to execute the by-side stopping task in a French coordinate systemAnd a transverse trackWherein the longitudinal trajectoryIs a function of time, transverse trajectoryIs a function of the longitudinal displacement, determined by a kinematic model of the vehicle. Then convert the transverse trackAs a function of timeObtaining a transverse and longitudinal time domain motion track of the vehicle;
And calling a transverse and longitudinal controller of the control module to control the vehicle to stop along the planned track, wherein the obstacle information of the vehicle on the side is also required to be introduced in the process, and if no obstacle exists on the side within the range of the transverse track, the vehicle is controlled to run along the planned track. If an obstacle exists, calculating a TTC value of the obstacle from a transverse track control point by using a safe distance model based on a time interval, if the TTC value is larger than the relative time of the transverse track control point, normally controlling the vehicle to run along a planned track, and if the TTC value is smaller than or equal to the relative time of the transverse track control point and the change trend is gradually reduced, sending a lane keeping signal by a transverse controller;
The planning module receives the lane keeping signal, actively requests lane center line information of a certain distance before and after a lane where a current vehicle is located to the high-precision map data service, and if the request response fails, the lane center line information is formed by the left and right lane line information of the lane where the current vehicle is located perceived by the vehicle. The lane central line information is used as a reference line, a uniform speed running track along the reference line is generated, and meanwhile, the control module controls the vehicle to run along the track;
When the TTC value of the obstacle on the side perceived by the vehicle is larger than a certain threshold value and the change trend is gradually increased, the vehicle re-executes the side parking task.
The method further comprises the step of establishing a vehicle control method for stopping at a nearby station. The planning module firstly obtains a passing point which is preset on a navigation route and is closest to the current position of the vehicle as a planned terminal point, if the passing point is not needed, the navigation route terminal point is used as a planned track terminal point, a parking track close to the nearest passing point is established based on the planned track terminal point, and then the control module controls the vehicle to brake along the track.
And establishing a vehicle control method for stopping the vehicle after the execution of the dispatching task. Firstly, acquiring the execution state of a planning module on a current planning task, if the task is still in execution, controlling a vehicle to run along the planning track of the current planning task by a control module, and if the planning module has already executed the task, planning a vehicle braking track by the planning module by taking an undriven route of the vehicle along a navigation route by a fixed distance as a reference line, and controlling the vehicle to brake along the track by the control module.
And establishing a speed-limiting driving vehicle control method. The speed-limiting running of the vehicle is realized by considering the speed control of the vehicle under the normal running condition along the navigation route, namely the speed value in the speed data of the vehicle along the reference line of the planning module is changed into a constant value, the displacement is increased at a constant speed along time, the acceleration and the jerk are both zero, the planning module outputs a constant-speed movement track of the vehicle along the navigation route, and then the control module controls the vehicle to carry out speed-limiting running along the planned track.
A vehicle control method is established that keeps waiting in a stopped state. When the vehicle is in a stop state, if abnormality is found through system state monitoring, the driving mode of the vehicle is kept in a locking state of an emergency mode, the vehicle is in a parking state and locked, and when the abnormality of the system disappears, the locking state of the vehicle is canceled.
An intermediate state machine for vehicle mode task switching is established. When the automatic driving system finds abnormality to perform degradation operation, the state machine selects a corresponding vehicle control method according to the fault severity level to control the vehicle to brake and park. Meanwhile, in the execution process of a certain vehicle control task, when an abnormal type with higher severity level needs to be executed, the state machine is used for task switching, a matched track planning method and a vehicle control method are called, an automatic driving control instruction is generated and sent to a vehicle chassis, and the vehicle is controlled to perform corresponding actions.
Fig. 2 is a schematic diagram of an automatic driving vehicle degradation running system according to an embodiment of the present invention, and as shown in fig. 2, the device mainly includes a status data receiving module, configured to obtain status information of a key domain controller connected to the system, status information of an ECU to which the domain controller belongs, status information of a sensor to which the domain controller belongs, and status information of data bus communication. The method comprises the steps that a module preferentially acquires the state information of a key domain controller and bus communication, and the state information of an ECU under the abnormal domain controller and the state information of a sensor connected with the abnormal domain controller are received and screened only when the key domain controller is abnormal, wherein the state abnormality of the domain controller comprises an ECU fault and a sensor fault, and the state abnormality of the bus communication comprises a communication terminal, communication delay and network attack.
The fault diagnosis grading module is used for carrying out corresponding fault severity evaluation grading according to the specific abnormal type of each key domain controller or the abnormal type of the data bus communication and outputting the highest fault severity grade and the fault code of the corresponding abnormal type. When evaluating and grading faults of the key domain controllers, the operation states of the redundant backup domain controllers are considered, the fault severity of the functional domain is evaluated to be higher only when all controllers of the corresponding functional domain are abnormal, otherwise, the fault severity is lower, and the fault grades can be divided into nine fault grades from E0 to E8.
The vehicle control module is used for executing a specific vehicle control method and a fault warning method according to the highest fault severity level and fault code output by the fault diagnosis grading module and combining with an automatic driving vehicle degradation operation strategy, generating a vehicle control instruction, sending the vehicle control instruction to the vehicle drive-by-wire chassis, controlling the vehicle to perform corresponding actions, including controlling the vehicle to perform emergency braking (grading pressure type emergency braking and emergency braking along a planned track) through a task state machine, stopping at a nearby site, stopping at a dispatching task, limiting speed, keeping a stopping state, prompting only a fault, and controlling the vehicle drive-by-wire chassis through a transverse controller and a longitudinal controller of the track planner.
Example 2
According to another aspect of the embodiments of the present invention, there is further provided a control system for an autonomous vehicle, where the system may execute the control method for an autonomous vehicle in the foregoing embodiment 1, and the specific implementation and application scenario in this embodiment are the same as those in the foregoing embodiment 1, and are not described herein.
Fig. 3 is a schematic diagram of a control system of an autonomous vehicle according to an embodiment of the present invention, as shown in fig. 3, the system includes a status data receiving module 302 configured to obtain abnormal status information of the autonomous vehicle, where the abnormal status information includes first status information for indicating that a domain controller in the autonomous vehicle is abnormal and second status information for indicating that a communication status of the autonomous vehicle is abnormal, a fault diagnosis ranking module 304 configured to determine an abnormal type of the autonomous vehicle based on the abnormal status information and determine a fault level corresponding to the abnormal type, where the abnormal type includes a first abnormal type of the domain controller and a second abnormal type of a data transmission bus, the fault level is configured to indicate an influence degree of the abnormal type on normal running of the autonomous vehicle, and a vehicle control module 306 configured to control the autonomous vehicle based on a preset control scheme corresponding to the fault level.
The state data receiving module 302 includes a first obtaining unit configured to obtain, in response to occurrence of an abnormality in the domain controller, current state information sent by the domain controller and fault information of an electronic device corresponding to the domain controller, to obtain first state information, and a second obtaining unit configured to obtain data transmission state information of the data transmission bus, to obtain second state information.
The fault diagnosis grading module 304 includes a type matching unit for matching the anomaly type with a plurality of preset anomaly types to obtain a target anomaly type successfully matched with the anomaly type, and a grade determining unit for determining a preset grade corresponding to the target anomaly type as a fault grade.
In response to failure in matching the abnormality type with the plurality of preset abnormality types, the fault diagnosis and classification module 304 further includes a cause obtaining unit configured to obtain a fault cause corresponding to the abnormality type, and a fault evaluation unit configured to evaluate the fault cause to obtain a fault level corresponding to the abnormality type.
The vehicle control module 306 includes a power control unit for controlling the power supply of the autonomous vehicle to be disconnected, a first brake control unit for controlling the autonomous vehicle to perform emergency braking, a second brake control unit for controlling the autonomous vehicle to perform non-emergency braking, a first parking control unit for controlling the autonomous vehicle to park alongside, a second parking control unit for controlling the autonomous vehicle to travel to a target parking point for parking, a third parking control unit for controlling the autonomous vehicle to travel to the second parking point for parking after completing the current dispatching task, a speed control unit for controlling the speed of the autonomous vehicle to be less than a preset value, a vehicle state control unit for controlling the autonomous vehicle to maintain a stationary state, and an information output unit for controlling the autonomous vehicle to output warning information, wherein the warning information is used for representing that the autonomous vehicle is abnormal.
The first brake control unit comprises a first acquisition subunit, a system determination subunit and a first control subunit, wherein the first acquisition subunit is used for acquiring first running information of the automatic driving vehicle, the first running information comprises chassis state information, vehicle positioning information, first obstacle information positioned in front of the automatic driving vehicle and navigation route information, the first generation subunit is used for generating a vehicle running track of the automatic driving vehicle at a future moment based on the first running information and a historical planning track of the automatic driving vehicle, the system determination subunit is used for determining an emergency braking mode of the automatic driving vehicle to be tight based on the first obstacle information and the vehicle running track, different emergency braking modes are used for braking the automatic driving vehicle, and the first control subunit is used for controlling the automatic driving vehicle to brake based on the emergency braking mode.
The system determination subunit may be configured to minimize a vehicle driving track and maximize a deceleration of the autonomous vehicle to obtain a first emergency braking track of the autonomous vehicle, obtain a sum of a displacement of the first emergency braking track and a parking safety distance of the autonomous vehicle to obtain a preset distance, determine, in response to an obstacle distance in the first obstacle information being greater than the preset distance, that an emergency braking mode is a first braking mode, wherein the first braking mode is used to control the autonomous vehicle to brake according to the vehicle driving track, and determine, in response to the obstacle distance being less than or equal to the preset distance, that the emergency braking mode is a second braking mode, wherein the second braking mode is used to control a brake pedal of the autonomous vehicle to brake according to a plurality of different openings.
The second brake control unit comprises a second acquisition subunit, a second generation subunit and a second control subunit, wherein the second acquisition subunit is used for acquiring first running information of the automatic driving vehicle, the running information comprises chassis state information, vehicle positioning information, first obstacle information positioned in front of the automatic driving vehicle and navigation route information, the second generation subunit is used for generating a vehicle running track of the automatic driving vehicle at a future time based on the first running information and a history planning track of the automatic driving vehicle, the first track acquisition subunit is used for maximizing the vehicle running track and minimizing the deceleration of the automatic driving vehicle to obtain a second emergency braking track of the automatic driving vehicle, and the second control subunit is used for controlling the automatic driving vehicle to brake based on the second emergency braking track.
The first parking control unit comprises a fourth acquisition subunit, a second track acquisition subunit and a perception information acquisition subunit, wherein the fourth acquisition subunit is used for acquiring second driving information of the automatic driving vehicle, the second driving information comprises transverse displacement, speed and acceleration, the second track acquisition subunit is used for carrying out track fitting on the automatic driving vehicle based on the second driving information to obtain a motion track of the automatic driving vehicle, the perception information acquisition subunit is used for acquiring perception information of the automatic driving vehicle, the perception information comprises second obstacle information in the transverse direction and lane line information around the automatic driving vehicle, and the third control subunit is used for controlling the automatic driving vehicle to stop by the side based on the perception information and the motion track.
The device further comprises a grade determining module and a scheme obtaining module, wherein the grade determining module is used for determining a target fault grade in the fault grades, the target fault grade is higher than other fault grades in the fault grades, and the scheme obtaining module is used for obtaining a control scheme corresponding to the target fault grade and obtaining a preset control scheme.
Example 3
According to another aspect of the embodiment of the present invention, there is also provided a computer-readable storage medium, the computer-readable storage medium including a stored program, wherein a device in which the computer-readable storage medium is controlled to execute the above-described control method for an autonomous vehicle when the program runs.
Example 4
According to another aspect of the embodiment of the present invention, there is also provided a processor for running a program, wherein the program executes the control method of the autonomous vehicle.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, 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 through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. 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 the embodiments of the present invention 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 computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. The storage medium includes a U disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, etc. which can store the program code.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims (11)

1. A control method of an autonomous vehicle, characterized by comprising:
Acquiring abnormal state information of the automatic driving vehicle, wherein the abnormal state information comprises first state information used for representing that a domain controller in the automatic driving vehicle is abnormal and second state information used for representing that the communication state of the automatic driving vehicle is abnormal;
Determining an abnormality type of the autonomous vehicle based on the abnormality status information, wherein the abnormality type includes a first abnormality type of the domain controller and a second abnormality type of a data transmission bus;
Determining a fault grade corresponding to the abnormal type, wherein the fault grade is used for representing the influence degree of the abnormal type on the normal running of the automatic driving vehicle, and determining by comparing keywords of the abnormal type with a preset abnormal type and/or evaluating and determining the fault cause of the abnormal type;
Controlling the operation of the automatic driving vehicle based on a preset control scheme corresponding to the fault level;
The method further comprises the steps of obtaining first running information of the automatic driving vehicle under the condition that a preset control scheme corresponding to the fault level is used for controlling the automatic driving vehicle to conduct emergency braking, wherein the first running information comprises chassis state information, vehicle positioning information, first obstacle information and navigation route information, the first obstacle information is located in front of the automatic driving vehicle, an emergency braking mode is determined to be a first braking mode based on the first running information and a historical planning track of the automatic driving vehicle, the historical planning track is a braking planning track of the automatic driving vehicle at a future time, the vehicle running track is minimized, the deceleration of the automatic driving vehicle is maximized, a first emergency braking track of the automatic driving vehicle is obtained, the sum of the displacement of the first emergency braking track and the parking safety distance of the automatic driving vehicle is obtained, the first braking mode is determined to be a first braking mode based on the fact that the distance of the first obstacle information is larger than the preset distance, the first braking mode is determined to be a second braking mode, the first braking mode is used for controlling the automatic driving vehicle to conduct braking according to the fact that the first braking mode is not equal to the first braking mode, and the first braking mode is not equal to the second braking mode is determined to the first braking mode.
2. The method of claim 1, wherein obtaining abnormal state information of the autonomous vehicle comprises:
Responding to the occurrence of abnormality of the domain controller, acquiring current state information sent by the domain controller and fault information of an electronic device corresponding to the domain controller, and obtaining the first state information;
and acquiring data transmission state information of the data transmission bus to obtain the second state information.
3. The method of claim 1, wherein determining the fault level for the anomaly type comprises:
matching the anomaly type with a plurality of preset anomaly types to obtain a target anomaly type successfully matched with the anomaly type;
and determining a preset grade corresponding to the target abnormal type as the fault grade.
4. A method according to claim 3, wherein in response to the anomaly type failing to match a plurality of preset anomaly types, the method further comprises:
Acquiring a fault reason corresponding to the abnormal type;
and evaluating the fault reasons to obtain fault grades corresponding to the abnormal types.
5. The method according to claim 1, wherein the method further comprises:
Determining a target fault level in the fault levels, wherein the target fault level is higher than other fault levels in the fault levels;
And obtaining a control scheme corresponding to the target fault level to obtain the preset control scheme.
6. The method of claim 1, wherein controlling the autonomous vehicle operation based on the preset control scheme corresponding to the fault level comprises one of:
controlling a power supply disconnection of the autonomous vehicle;
Controlling the automatic driving vehicle to perform emergency braking;
controlling the automatic driving vehicle to perform non-emergency braking;
controlling the automatic driving vehicle to stop by side;
controlling the automatic driving vehicle to run to a target stop point for stopping;
after the automatic driving vehicle is controlled to finish the current dispatching task, the automatic driving vehicle is driven to a second stopping point for stopping;
Controlling the speed of the automatic driving vehicle to be smaller than a preset value;
Controlling the autonomous vehicle to remain stationary;
And controlling the automatic driving vehicle to output alarm information, wherein the alarm information is used for representing that the automatic driving vehicle is abnormal.
7. The method of claim 6, wherein controlling the autonomous vehicle to perform non-emergency braking comprises:
Acquiring first driving information of the automatic driving vehicle, wherein the driving information comprises chassis state information, vehicle positioning information, first obstacle information positioned in front of the automatic driving vehicle and navigation route information;
Generating a vehicle travel track of the autonomous vehicle at a future time based on the first travel information and the historical planned track of the autonomous vehicle;
Maximizing the vehicle driving track and minimizing the deceleration of the automatic driving vehicle to obtain a second emergency braking track of the automatic driving vehicle;
And controlling the automatic driving vehicle to brake based on the second emergency braking track.
8. The method of claim 6, wherein controlling the autonomous vehicle to park alongside comprises:
Acquiring second driving information of the automatic driving vehicle, wherein the second driving information comprises transverse displacement, speed and acceleration;
performing track fitting on the automatic driving vehicle based on the second driving information to obtain a motion track of the automatic driving vehicle;
The perception information of the automatic driving vehicle is acquired, wherein the perception information comprises second barrier information in the transverse direction and lane line information around the automatic driving vehicle;
and controlling the automatic driving vehicle to stop by side based on the perception information and the motion trail.
9. A control system for an autonomous vehicle, comprising:
The state data receiving module is used for acquiring abnormal state information of the automatic driving vehicle, wherein the abnormal state information comprises first state information used for representing that a domain controller in the automatic driving vehicle is abnormal and second state information used for representing that the communication state of the automatic driving vehicle is abnormal;
The fault diagnosis grading module is used for determining the abnormal type of the automatic driving vehicle based on the abnormal state information and determining a fault grade corresponding to the abnormal type, wherein the abnormal type comprises a first abnormal type of the domain controller and a second abnormal type of a data transmission bus, the fault grade is used for representing the influence degree of the abnormal type on the normal running of the automatic driving vehicle, and the fault grade is determined by comparing keywords of the abnormal type with a preset abnormal type and/or evaluating and determining the fault reason of the abnormal type;
the vehicle control module is used for controlling the automatic driving vehicle to run based on a preset control scheme corresponding to the fault level;
The system is further used for acquiring first driving information of the automatic driving vehicle under the condition that a preset control scheme corresponding to the fault level is used for controlling the automatic driving vehicle to conduct emergency braking, wherein the first driving information comprises chassis state information, vehicle positioning information, first obstacle information and navigation route information, the first obstacle information is located in front of the automatic driving vehicle, an emergency braking mode is determined to be a first braking mode based on the first driving information and a historical planning track of the automatic driving vehicle, the historical planning track is a braking planning track of the automatic driving vehicle at a future moment, the vehicle driving track is minimized, the deceleration of the automatic driving vehicle is maximized, a first emergency braking track of the automatic driving vehicle is obtained, the sum of the displacement of the first emergency braking track and the parking safety distance of the automatic driving vehicle is obtained, the first braking mode is determined to be a first braking mode based on the fact that the distance in the first obstacle information is larger than the preset distance, the first braking mode is controlled to be the automatic braking mode, the first braking mode is determined to be the automatic braking mode, the first braking mode is controlled to be the first braking mode is not used for controlling the automatic driving vehicle, and the second braking mode is determined to be the same as the first braking mode, and the opening degree is not equal to the first braking mode.
10. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the program when run controls a device in which the computer readable storage medium is located to perform the method according to any one of claims 1 to 8.
11. A processor for running a program, wherein the program when run performs the method of any one of claims 1 to 8.
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