CN114407910B - Fault processing method, device and storage medium for intelligent driving vehicle - Google Patents
Fault processing method, device and storage medium for intelligent driving vehicle Download PDFInfo
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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
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q1/00—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor
- B60Q1/26—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic
- B60Q1/46—Arrangement of optical signalling or lighting devices, the mounting or supporting thereof or circuits therefor the devices being primarily intended to indicate the vehicle, or parts thereof, or to give signals, to other traffic for giving flashing caution signals during drive, other than signalling change of direction, e.g. flashing the headlights or hazard lights
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q5/00—Arrangement or adaptation of acoustic signal devices
- B60Q5/005—Arrangement or adaptation of acoustic signal devices automatically actuated
- B60Q5/006—Arrangement or adaptation of acoustic signal devices automatically actuated indicating risk of collision between vehicles or with pedestrians
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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
- B60W50/023—Avoiding failures by using redundant parts
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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
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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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
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
- B60W50/16—Tactile feedback to the driver, e.g. vibration or force feedback to the driver on the steering wheel or the accelerator pedal
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- 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
- B60W60/001—Planning or execution of driving tasks
- B60W60/0015—Planning or execution of driving tasks specially adapted for safety
- B60W60/0016—Planning or execution of driving tasks specially adapted for safety of the vehicle or its occupants
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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
- B60W60/0053—Handover processes from vehicle to occupant
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/02—Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures
- B60W50/0205—Diagnosing or detecting failures; Failure detection models
- B60W2050/0215—Sensor drifts or sensor failures
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- 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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- 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
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Abstract
The invention discloses a fault processing method of an intelligent driving vehicle, which comprises the following steps: acquiring operation data of a vehicle; analyzing the operation data to obtain a fault diagnosis result; analyzing the fault diagnosis result to obtain fault information; evaluating the fault information to obtain a fault grade corresponding to the fault; and according to the fault level and the environment information, starting corresponding fault processing measures. According to the fault processing method, the device and the storage medium for the intelligent driving vehicle, when the software and hardware faults of the vehicle are detected, the fault acquisition fault source is analyzed, the fault information is generated, then the fault grade corresponding to the fault acquisition fault is evaluated, and corresponding fault processing measures are started according to the fault grade, the vehicle external environment information, the vehicle internal environment information and the vehicle information. The accuracy of fault grade assessment and the safety of fault treatment measures are improved.
Description
Technical Field
The application relates to the field of intelligent driving, in particular to a fault processing method, device and storage medium for an intelligent driving vehicle.
Background
The intelligent driving vehicle can automatically and safely operate the vehicle in response to various traffic scenes and road conditions under the condition of no active operation of human beings by virtue of the technologies of intelligent environment perception, high-precision positioning, steady decision planning, reliable control and the like. With the rapid development of intelligent driving technology, the intelligent driving technology is applied to more and more vehicles. However, during the running process of the vehicle, the communication network among hardware, software or components of the intelligent driving automobile is inevitably failed, and the safe running of the vehicle is directly affected. When a vehicle breaks down, the intelligent driving vehicle needs to accurately diagnose the fault type of the vehicle, and after the fault occurs, proper measures must be taken to ensure the safety of the vehicle and surrounding vehicles.
In many current intelligent driving vehicle fault handling schemes, the main handling mode is to control the intelligent driving vehicle to brake to a stop when the intelligent driving vehicle fault is detected. This way of handling is simple, but there is a certain risk. For example, under a high-speed working condition, the braking on a traffic lane has a great safety risk, and on an urban road, the traffic jam can be caused by parking on a main road. Therefore, under the condition that the intelligent driving vehicle breaks down, the design of safe and effective treatment measures is crucial, and the safety performance of the intelligent driving vehicle can be obviously improved.
Disclosure of Invention
In order to solve the problems, the invention provides a fault processing method for an intelligent driving vehicle, which enables corresponding fault processing measures according to fault grades, vehicle external environment information, vehicle internal environment information and vehicle information when a vehicle fault is detected. The safety of the vehicle during driving is improved.
The invention provides a fault processing method of an intelligent driving vehicle, which is characterized by comprising the following steps of: acquiring operation data of a vehicle; analyzing the operation data to obtain a fault diagnosis result; analyzing the fault diagnosis result to obtain fault information; evaluating the fault information to obtain a fault grade corresponding to the fault; and according to the fault level and the environment information, starting corresponding fault processing measures.
In one embodiment, the operation data includes operation information of the vehicle software and hardware, connection relation of the vehicle software and hardware and communication links thereof.
In one embodiment, the step of analyzing the operation data to obtain a fault diagnosis result includes: analyzing the working state of the software and the hardware according to the working information of the software and the hardware; and analyzing whether signal transmission between the software and the hardware is normal or not according to the connection relation of the software and the hardware and the communication link of the software and the hardware.
In one embodiment, the step of analyzing the fault diagnosis result to obtain fault information includes: analyzing abnormal discovery time, connection relation and communication link of abnormal software and hardware to obtain fault source of the abnormal software and hardware; and after the false alarm abnormality associated with the fault source is restrained, generating fault information.
In one embodiment, the step of enabling the corresponding fault handling measures according to the fault level and the environmental information includes: judging whether the fault level jeopardizes intelligent driving safety; if yes, judging whether the fault level affects intelligent driving safety parking; if not, restarting the failed software and hardware or starting the standby software and hardware.
In an embodiment, the step of determining whether the failure level affects intelligent driving safety parking includes: reminding a driver to take over the vehicle when the failure level affects intelligent driving safety parking; and when the failure level does not influence intelligent driving safety parking, analyzing the vehicle exterior environment information and the vehicle information to obtain the safety parking position.
In an embodiment, the step of reminding the driver to take over the vehicle comprises the following steps: judging whether the state of the driver meets the takeover condition; if yes, the vehicle is delivered to the driver for taking over; if not, the vehicle is handed over to the remote driving takeover.
In one embodiment, the step of analyzing the vehicle exterior environment information and the vehicle information to obtain the safe parking position includes: the vehicle is controlled to stop at a safe position.
The invention also provides a fault processing device of the intelligent driving vehicle, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the steps of the fault processing method of the intelligent driving vehicle when executing the computer program.
The present invention also provides a storage medium storing a computer program which, when executed by a processor, implements the steps of the fault handling method for an intelligent driving vehicle described above.
According to the fault processing method, the device and the storage medium for the intelligent driving vehicle, when the software and hardware faults of the vehicle are detected, the fault acquisition fault source is analyzed, the fault information is generated, then the fault grade corresponding to the fault acquisition fault is evaluated, and corresponding fault processing measures are started according to the fault grade, the vehicle external environment information, the vehicle internal environment information and the vehicle information. The accuracy of fault grade assessment and the safety of fault treatment measures are improved.
Drawings
Fig. 1 is a flow chart of a fault handling method for an intelligent driving vehicle according to a first embodiment of the present invention;
FIG. 2 is a flow chart of the present invention for analyzing faults of an intelligent driving vehicle;
fig. 3 is a flow chart of a fault handling method of an intelligent driving vehicle according to a second embodiment of the present invention.
Detailed Description
The foregoing and other features, aspects, and advantages of the present invention will become more apparent from the following detailed description of the preferred embodiments, which proceeds with reference to the accompanying drawings. While the invention may be susceptible to further details of embodiments and examples of means and effects for achieving the desired purpose, the drawings are provided for the purpose of reference and illustration only and are not intended to be limiting.
In order to further describe the technical means and effects adopted by the present invention to achieve the preset purpose, the following detailed description of the present invention is given with reference to the accompanying drawings and preferred embodiments.
Fig. 1 is a flow chart of a fault handling method for an intelligent driving vehicle according to a first embodiment of the present invention.
As shown in fig. 1, the fault handling method of the intelligent driving vehicle of the present embodiment includes the steps of:
Step S11: operational data of the vehicle is acquired.
Specifically, the operation data of the vehicle includes the operation information of the software and hardware of the vehicle, the connection relation of the software and the hardware of the vehicle and the communication link thereof.
Step S12: and analyzing the operation data to obtain a fault diagnosis result.
Specifically, the obtained vehicle operation data is analyzed to perform fault diagnosis on the hardware and software of the vehicle, and a fault diagnosis result is obtained. The hard software of the vehicle comprises a sensor, an actuator, a controller and the like.
Specifically, when the sensor is subjected to fault diagnosis, equipment such as a camera, a millimeter wave radar, a laser radar, an inertial navigation device and the like are subjected to electrical diagnosis and signal rationality diagnosis. If the sensor has the function of a software algorithm, fault diagnosis can be carried out on the software algorithm of the sensor.
Specifically, when the fault diagnosis is performed on the actuator, the basic function diagnosis and the performance index related diagnosis are performed on equipment such as a linear control accelerator, a linear control brake, a linear control steering, a linear control gear, lamplight, doors and windows, a loudspeaker and the like. The basic function diagnosis is mainly to judge whether the control command can be correctly responded or not and whether abnormal response occurs when the control command is not updated or not. The performance index related diagnosis includes diagnosis of indexes such as response time, overshoot, settling time, follow-up characteristics and the like.
Specifically, when the controller is subjected to fault diagnosis, electrical diagnosis, running performance diagnosis and basic software running diagnosis are performed on equipment such as an intelligent driving controller, a vehicle machine, a vehicle-mounted computer and the like.
In particular, in one embodiment, a diagnostic is also performed on the communication link of the vehicle. The diagnosis of the communication link is mainly the diagnosis of network communication among the diagnosis sensor, the actuator and the controller, and the diagnosis of whether the signal transmission between the sensors, the actuator and the controller is normal or not.
Specifically, in one embodiment, the intelligent driving basic algorithm and intelligent driving monitoring are also diagnosed. The diagnosis of the intelligent driving basic algorithm mainly aims at the diagnosis of positioning, sensing, predicting, planning and controlling of the intelligent driving core algorithm module, and diagnosis such as diagnosis of input signals and diagnosis of abnormal algorithm operation or not can be carried out in each module. The intelligent driving monitoring algorithm is used for monitoring the running condition of the whole intelligent driving algorithm, and comprises two aspects, namely, monitoring the running state of each node in the intelligent driving algorithm on one hand, monitoring whether the scheduling and running state of each module are abnormal or not, monitoring the basic intelligent driving algorithm on the other hand, and monitoring and diagnosing whether the information such as the planning path and the control instruction calculated by the basic intelligent driving algorithm can ensure that the intelligent driving vehicle runs in a safe state or not.
Step S13: and analyzing the fault diagnosis result to obtain fault information.
Specifically, the abnormal discovery time, connection relation and communication link of abnormal software and hardware are analyzed, the fault source of the abnormal software and hardware is obtained, and fault information is generated after misinformation abnormality associated with the fault source is restrained. The fault is clear and orderly, the fault cause is accurate and the direction is clear, and the problem of undefined diagnosis directivity caused by the associated fault can be effectively solved.
In order to describe step S13 in detail, step S13 is further described below with reference to fig. 2.
As shown in fig. 2, the unit a, the unit B and the unit C are three diagnostic units, which may be an independent controller, an intelligent driving software node or a cloud server software node. The three units have the following characteristics on the signal transmission route that the signals of the A unit can be simultaneously transmitted to the B unit and the C unit, the signals of the B unit can also be transmitted to the C unit, in addition, the three units can independently perform fault diagnosis and feed the diagnosis result back to the fault analysis module, and the fault analysis module calculates final fault information. For example, the B unit first diagnoses that the a unit transmission signal is abnormal and issues the diagnosis result, and then the C unit issues the diagnosis result of the B unit transmission signal abnormality. The fault analysis module can judge that the abnormal faults of the signals sent by the A unit occur firstly and then the abnormal faults of the signals sent by the B unit occur according to the time sequence reported by the diagnosis result. Because the C unit has sent out an abnormality of the a unit transmission signal when diagnosing the B unit transmission signal abnormality, it may be that the a unit transmission signal failure causes a B unit transmission signal abnormality, and then the failure is continuously analyzed to obtain the worst potential result that the failure may cause. However, if the fault analysis module receives the diagnosis result of the abnormal signal sent by the B unit and then receives the diagnosis result of the abnormal signal sent by the a unit, it is unlikely that the fault of the signal sent by the a unit causes the abnormal signal sent by the B unit, and at this time, it is unnecessary to continuously analyze the fault, and the worst potential result possibly caused by the fault is obtained, so that it can be determined that the fault of the abnormal signal sent by both the a unit and the B unit occurs. Because the signals sent by the A unit are received by the B unit and the C unit, when the A unit does not send out the signals for a long time, the B unit and the C unit can diagnose the abnormality of the signal interruption of the A unit and feed the diagnosis results back to the fault analysis module, and the fault analysis module can judge that the two diagnosis results are related to the A unit after receiving the diagnosis results of the signal interruption of the A unit fed back by the B unit and the C unit, the diagnosis results can be unified into the fault of the signal interruption of the A unit and send out the fault information. In a situation that the signals sent by the A unit are abnormal and then the B unit is abnormal, the signals sent by the B unit are abnormal, the C unit can diagnose that the signals sent by the A unit and the B unit are abnormal, and the diagnosis result is fed back to the fault analysis module. The failure of the B unit caused by invalid signals sent by the A unit is an associated failure, and the failure analysis module is required to restrain the failure of the abnormal signals sent by the B unit through the analyzed failure of the abnormal signals sent by the A unit, so that the failure of the abnormal signals sent by the B unit is avoided. Therefore, in this case, the failure analysis module only reports the failure of the signal abnormality of the a unit, and does not report the failure of the signal abnormality of the B unit.
Step S14: and evaluating the fault information to obtain a fault grade corresponding to the fault.
Specifically, the fault level is evaluated according to the influence degree of the fault on the vehicle driving performance, the influence degree of the fault on the whole system and the participants and the worst potential result caused by the fault when the fault information is evaluated.
Specifically, in one embodiment, the fault level is also evaluated according to the influence degree of the fault on the intelligent driving performance of the vehicle when the fault information is evaluated.
Specifically, in one embodiment, the failure classes may be classified into four classes, primary failure, secondary failure, tertiary failure, and quaternary failure, with the primary failure being most severe and the quaternary failure having the least impact. The first-order failure is a major failure of the intelligent driving vehicle, which may adversely affect the normal operation of the system for performing intelligent driving immediately, and vehicle control by the intelligent driving system is not possible. A secondary failure indicates that the intelligent driving system capability is degraded, but does not affect the ability of the system to perform controlled remedial maneuvers in the degraded state. The third level of failure is less severe than the second level of failure, and although not affecting current intelligent drivability, the failure increases the likelihood of a more severe failure, which is then unknown, either immediately or at a later time. Such as failure of a primary actuator with only one backup substitute, after which the backup substitute can continue to be used without affecting the current intelligent driving capability. But because of this failure, if the backup replacement also fails, a major failure, i.e., a primary failure, results. Four-level faults refer to faults that have no or very little impact on intelligent drivability.
Step S15: according to the fault level and the environment information, corresponding fault processing measures are started
Specifically, after the fault level is obtained, corresponding fault handling measures are started according to factors such as surrounding natural environment, surrounding traffic environment, current fault level, running state of the vehicle at the moment and driver state. Wherein the processing measures can be one or a plurality of processing measures to face faults with different complexity. Further processing measures include enabling alternate sensors and/or actuators and/or controllers, restarting hardware and software, alerting the driver to take over, alerting the vehicle outsider and the vehicle, controlling the vehicle to stop to a safe position, and handing the vehicle over to a remote drive take over.
In particular, in one embodiment, for intelligent driving software or controller related faults, an attempt may be made to eliminate the fault by a software restart or a hardware restart. The intelligent driving vehicle has faults in the intelligent driving process, and the driver can be reminded to take over the control right of the vehicle by means of sound, vibration and the like so as to ensure safe driving of the vehicle. Meanwhile, the current vehicle is characterized by the measures of lighting a hazard alarm flash lamp, a horn sound and the like, so that surrounding pedestrians and vehicles are reminded of paying attention to safety. When a hardware fault of the vehicle is detected, but the intelligent driving capability of the vehicle also meets the requirement of operating the vehicle, the vehicle is operated to be stopped at a safe position, and the safety position needs to comprehensively consider factors such as natural environment, traffic environment and the like around the vehicle. If the current traffic is less congested, a position where roadsides can safely park may be selected for a safe seat position. If the current traffic jam occurs, the movement is slow, and the stop at a certain position of the own lane is a safe position at the moment. If the safe parking position cannot be found, the speed of the vehicle is reduced, the distance between the vehicle and the front vehicle is increased, the vehicle continues to run on the lane, and then the current traffic flow and the surrounding environment information are re-evaluated after a certain time interval, so that the safe parking position is found. Therefore, the driving safety of the vehicle is considered under the condition of not causing traffic jam.
According to the fault processing method for the intelligent driving vehicle, when the software and hardware faults of the vehicle are detected, the fault acquisition fault source is analyzed, fault information is generated, then the fault grade corresponding to the fault information acquisition fault is evaluated, and corresponding fault processing measures are started according to the fault grade, the vehicle exterior environment information, the vehicle interior environment information and the vehicle information. The accuracy of fault grade assessment and the safety of fault treatment measures are improved.
Fig. 3 is a flow chart of a fault handling method of an intelligent driving vehicle according to a second embodiment of the present invention.
As shown in fig. 3, the fault handling method of the intelligent driving vehicle of the present embodiment includes the steps of:
step S151: and judging whether the fault level jeopardizes intelligent driving safety.
Specifically, when the failure level jeopardizes intelligent driving safety, step S153 is entered: and judging whether the fault level influences intelligent driving safety parking. When the failure level does not jeopardize the intelligent driving safety, step S152 is entered: restarting the failed hardware and software or enabling the spare hardware and software.
Specifically, when the failure level affects the intelligent driving safety stop, step S156 is entered: the driver is alerted to take over the vehicle. When the failure level does not affect the intelligent driving safety stop, the step S154 is entered: and analyzing the vehicle exterior environment information and the vehicle information to obtain the safe parking position.
Specifically, in one embodiment, when the safe parking position is obtained, factors such as the natural environment and the traffic environment around the vehicle are comprehensively considered. If the current traffic is less congested, a position where roadsides can safely park can be selected as a safe parking position. If the current traffic jam occurs, the current traffic jam moves slowly, and a certain safe position of the current lane is taken as a safe parking position at the moment. If the safe parking position cannot be found, the speed of the vehicle is reduced, the distance between the vehicle and the front vehicle is increased, the vehicle continues to run on the lane, and then the current traffic flow and the surrounding environment information are re-evaluated after a certain time interval, so that the safe parking position is found. After the safe parking position is acquired, the process proceeds to step S155: and controlling the vehicle to stop at a safe position.
Specifically, when reminding a driver to take over the vehicle, the driver can be reminded to take over the control right of the vehicle by means of sound, vibration and the like, and meanwhile, the current vehicle is characterized by means of measures such as a hazard alarm flash lamp, a loudspeaker and the like, so that surrounding pedestrians and vehicles are reminded of paying attention to safety. After the alert is issued, the process proceeds to step S157: and judging whether the state of the driver meets the takeover condition.
Specifically, in one embodiment, in determining whether the driver status satisfies the takeover condition, in acquiring in-vehicle information, detecting whether the driver has an emergency situation and detecting whether the driving action of the driver has a potential safety hazard, and in detecting that the driver has no emergency situation and the driving action has no potential safety hazard, determining that the driver status can satisfy the takeover condition. When the coma of the driver, the sudden illness of the driver and the potential safety hazard of the driving action are detected, the condition that the state of the driver cannot meet the takeover condition is judged.
Specifically, when it is determined that the driving state can satisfy the takeover condition, the process advances to step S159: the vehicle is taken over by the driver. When it is determined that the driver state cannot satisfy the takeover condition, the flow proceeds to step S158: the vehicle is handed over to the remote drive take over.
The invention also provides a fault processing device of the intelligent driving vehicle, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the steps of the fault processing method of the intelligent driving vehicle when executing the computer program.
The present invention also provides a storage medium storing a computer program which, when executed by a processor, implements the steps of the security verification method described above.
According to the fault processing method, the device and the storage medium for the intelligent driving vehicle, when the software and hardware faults of the vehicle are detected, the fault acquisition fault source is analyzed, the fault information is generated, then the fault grade corresponding to the fault acquisition fault is evaluated, and corresponding fault processing measures are started according to the fault grade, the vehicle external environment information, the vehicle internal environment information and the vehicle information. The accuracy of fault grade assessment and the safety of fault treatment measures are improved.
The present invention is not limited to the above-mentioned embodiments, but is capable of modification and variation in all aspects, including all obvious modifications and equivalents, which fall within the scope of the present invention.
Claims (8)
1. A fault handling method for an intelligent driving vehicle, the method comprising:
Acquiring operation data of a vehicle;
Analyzing the operation data to obtain a fault diagnosis result;
Analyzing the fault diagnosis result, obtaining a fault source of abnormal software and hardware, and generating fault information after suppressing false alarm abnormality associated with the fault source;
Evaluating the fault information to obtain a fault grade corresponding to the fault;
According to the fault level and the environment information, corresponding fault processing measures are started;
And enabling corresponding fault processing measures according to the fault level and the environment information, wherein the enabling of the corresponding fault processing measures comprises at least one of the following:
restarting the failed software and hardware or starting the spare software and hardware when the failure level does not jeopardize the intelligent driving safety;
Reminding a driver to take over the vehicle when the intelligent driving safety is compromised by the fault level and the intelligent driving safety is affected by the fault level;
When the intelligent driving safety is endangered by the fault level and the intelligent driving safety parking is not influenced by the fault level, if the traffic environment information outside the vehicle is no traffic jam, taking the position where the roadside can safely park as a safe parking position;
when the fault level jeopardizes intelligent driving safety and the fault level does not influence intelligent driving safety parking, if the traffic environment information outside the vehicle is traffic jam, taking the safety position in the current lane as the safety parking position at the moment;
And when the fault level endangers the intelligent driving safety and the fault level does not influence the intelligent driving safety parking, if the traffic environment information outside the vehicle is traffic jam and the safe parking position cannot be found in the current lane, the vehicle speed is reduced, the distance between the vehicle and the front vehicle is increased, the vehicle continues to run in the current lane, and after a preset time interval, the safe parking position is found again according to the traffic environment information outside the vehicle.
2. The fault handling method of an intelligent driving vehicle according to claim 1, wherein the operation data includes operation information of the vehicle software and hardware, connection relation of the vehicle software and hardware, and communication links thereof.
3. The fault handling method of an intelligent drive vehicle according to claim 1, wherein the step of analyzing the operation data to obtain a fault diagnosis result includes:
Analyzing the working state of the software and the hardware according to the working information of the software and the hardware;
And analyzing whether signal transmission between the software and the hardware is normal or not according to the connection relation of the software and the hardware and the communication link of the software and the hardware.
4. The method for processing a fault of an intelligent driving vehicle according to claim 1, wherein the step of analyzing the fault diagnosis result, obtaining a fault source of abnormal software and hardware, suppressing a false alarm abnormality associated with the fault source, and generating fault information includes:
And analyzing the abnormal discovery time, connection relation and communication link of the abnormal software and hardware to obtain the fault source of the abnormal software and hardware.
5. The method for handling a fault in an intelligently driven vehicle according to claim 1, wherein the step of reminding the driver to take over the vehicle when the fault level jeopardizes intelligent driving safety and the fault level affects intelligent driving safety parking, then comprises:
Judging whether the state of the driver meets the takeover condition;
If yes, the vehicle is delivered to the driver for taking over;
if not, the vehicle is handed over to the remote driving takeover.
6. The fault handling method for an intelligent driven vehicle of claim 1, wherein the method further comprises:
and after the safe parking position is acquired, controlling the vehicle to park at the safe position.
7. A fault handling device for an intelligent drive vehicle comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, carries out the steps of the fault handling method for an intelligent drive vehicle according to any one of claims 1 to 6.
8. A storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the fault handling method of an intelligent driving vehicle according to any one of claims 1 to 6.
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| CN111824173A (en) * | 2019-04-11 | 2020-10-27 | 上海汽车集团股份有限公司 | Grading processing method and device suitable for faults of intelligent driving system |
| CN111976727A (en) * | 2019-05-21 | 2020-11-24 | 华为技术有限公司 | Automatic driving grade adjusting method and related equipment |
| CN113183978A (en) * | 2021-06-01 | 2021-07-30 | 西安主函数智能科技有限公司 | Fault diagnosis method and safety protection method for line control system of automatic driving engineering vehicle |
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| CN111891134B (en) * | 2019-05-06 | 2022-09-30 | 北京百度网讯科技有限公司 | Automatic driving processing system, system on chip and method for monitoring processing module |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111824173A (en) * | 2019-04-11 | 2020-10-27 | 上海汽车集团股份有限公司 | Grading processing method and device suitable for faults of intelligent driving system |
| CN111976727A (en) * | 2019-05-21 | 2020-11-24 | 华为技术有限公司 | Automatic driving grade adjusting method and related equipment |
| CN113183978A (en) * | 2021-06-01 | 2021-07-30 | 西安主函数智能科技有限公司 | Fault diagnosis method and safety protection method for line control system of automatic driving engineering vehicle |
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