CN114677779B - Vehicle configuration state monitoring method and device, storage medium and computer equipment - Google Patents
Vehicle configuration state monitoring method and device, storage medium and computer equipment Download PDFInfo
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Abstract
The application provides a vehicle configuration state monitoring method, a device, a storage medium and computer equipment, wherein the method comprises the following steps: acquiring vehicle information of each vehicle; acquiring configuration parameters of each vehicle; the configuration parameters are obtained by self-checking and fed back by each vehicle according to a parameter acquisition task issued in advance; the parameter acquisition task comprises the type of parameters to be acquired of each vehicle; determining a preset baseline configuration corresponding to each vehicle according to the vehicle information of each vehicle; the parameter type in the preset baseline configuration is consistent with the parameter type to be acquired; if any configuration parameter of the vehicle exceeds the parameter limit in the preset baseline configuration corresponding to the vehicle, generating an abnormal prompt task; triggering an abnormality prompt based on the abnormality prompt task; the abnormality prompt is used for prompting abnormal vehicles with abnormal configuration states and abnormal parameters of the abnormal vehicles. The application can realize the monitoring of the configuration state of each vehicle in the motorcade and provides a basis for ensuring the reliable operation of the motorcade for automatic driving.
Description
Technical Field
The present application relates to the field of automatic driving technologies, and in particular, to a method and apparatus for monitoring a vehicle configuration state, a storage medium, and a computer device.
Background
With the development of autopilot technology, the application of autopilot expands from single vehicles to fleets, in which each of the autopilot vehicles is equipped with several sensors and computing units to implement autopilot control. With the change of the scale of the motorcade or the iteration of the upgrading of the software and the hardware of the vehicle, the operation control of the same motorcade can be abnormal, which is not beneficial to the reliable operation of the automatic driving vehicle.
Disclosure of Invention
The embodiment of the application provides a vehicle configuration state monitoring method, a device, a storage medium and computer equipment, which can realize the monitoring of the configuration state of each vehicle in a motorcade and provide a basis for ensuring the reliable operation of the motorcade.
The application provides a vehicle configuration state monitoring method which is applied to a vehicle management platform and comprises the following steps:
Acquiring vehicle information of each vehicle;
Acquiring configuration parameters of each vehicle; the configuration parameters are obtained by self-checking and fed back by the vehicles according to a parameter acquisition task issued in advance; the parameter acquisition task comprises a to-be-acquired parameter type of each vehicle;
Determining a preset baseline configuration corresponding to each vehicle according to the vehicle information of each vehicle; the parameter type in the preset baseline configuration is consistent with the parameter type to be acquired;
if any configuration parameter of the vehicle exceeds parameter limit in preset baseline configuration corresponding to the vehicle, generating an abnormal prompt task;
Triggering an abnormality prompt based on the abnormality prompt task; the abnormality prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
In one embodiment, the vehicle information includes a vehicle model number and a vehicle attribute;
the determining a preset baseline configuration corresponding to each vehicle according to the vehicle information of each vehicle comprises the following steps:
determining a primary baseline configuration corresponding to a vehicle model of each vehicle according to the vehicle model of each vehicle;
Determining a secondary baseline configuration corresponding to the vehicle attribute of each vehicle in the primary baseline configuration according to the vehicle attribute of each vehicle;
And determining the secondary baseline configuration as the preset baseline configuration.
In one embodiment, the vehicle configuration state monitoring method further includes:
responding to a parameter acquisition definition instruction, and generating a parameter acquisition task; the parameter acquisition task is used for indicating each vehicle to preset the type of parameters to be acquired corresponding to the vehicle information of each vehicle;
and sending the parameter acquisition task to each vehicle.
In one embodiment, the vehicle configuration state monitoring method further includes:
responding to the parameter acquisition modification instruction, and generating a parameter acquisition modification task; the parameter acquisition modification task is used for indicating the target vehicle to add and/or delete at least one parameter type to be acquired;
And sending the parameter acquisition modification task to the target vehicle.
In one embodiment, if any configuration parameter of the vehicle exceeds a parameter limit in a corresponding preset baseline configuration, generating an abnormal prompting task includes:
Screening effective parameters in the configuration parameters fed back by each vehicle;
comparing the effective parameters of each vehicle with preset baseline configurations corresponding to each vehicle respectively;
And if any configuration parameter in the effective parameters exceeds the parameter limit in the corresponding preset baseline configuration, generating the abnormal prompting task.
The embodiment of the application also provides a vehicle configuration state monitoring method which is applied to the vehicle and comprises the following steps:
acquiring configuration parameters according to a preset type of parameters to be acquired; the type of the parameters to be acquired is preset according to a parameter acquisition task issued by a vehicle management platform;
Identifying whether the configuration parameters are abnormal or not according to preset baseline configuration issued by the vehicle management platform;
If any configuration parameter exceeds the parameter limit in the corresponding preset baseline configuration, generating an abnormal prompt report;
Uploading the abnormality prompt report to the vehicle management platform; the vehicle management platform is used for triggering an abnormal prompt according to the abnormal prompt report, wherein the abnormal prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
In one embodiment, the vehicle configuration state monitoring method further includes:
uploading vehicle information to the vehicle management platform; the vehicle management platform is used for determining a preset baseline configuration according to the vehicle information;
and acquiring a preset baseline configuration issued by the vehicle management platform.
In one embodiment, the vehicle information includes a vehicle model number and a vehicle attribute;
The vehicle management platform is used for determining a primary baseline configuration according to the vehicle model, determining a secondary baseline configuration corresponding to the vehicle attribute in the primary baseline configuration according to the vehicle attribute, and determining the secondary baseline configuration as the preset baseline configuration to issue.
In one embodiment, the anomaly prompt report includes vehicle information and anomaly parameters; the vehicle management platform is used for associating the abnormal parameters with corresponding vehicles according to the vehicle information.
In one embodiment, the vehicle configuration state monitoring method further includes:
And when a parameter acquisition modification task issued by the vehicle management platform is received, adding and/or deleting at least one parameter type to be acquired according to the parameter acquisition modification task.
The embodiment of the application also provides a vehicle configuration state monitoring device which is applied to the vehicle management platform and comprises the following components:
The information acquisition module is used for acquiring vehicle information of each vehicle;
The parameter acquisition module is used for acquiring configuration parameters of each vehicle; the configuration parameters are obtained by self-checking and fed back by the vehicles according to a parameter acquisition task issued in advance; the parameter acquisition task comprises a to-be-acquired parameter type of each vehicle;
The base line determining module is used for determining preset base line configuration corresponding to each vehicle according to the vehicle information of each vehicle; the parameter type in the preset baseline configuration is consistent with the parameter type to be acquired;
The abnormal prompt task generation module is used for generating an abnormal prompt task when any configuration parameter of the vehicle exceeds parameter limit in preset baseline configuration corresponding to the vehicle;
The prompt triggering module is used for triggering an abnormal prompt based on the abnormal prompt task; the abnormality prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
The embodiment of the application also provides a vehicle configuration state monitoring device, which is applied to a vehicle and comprises:
the parameter acquisition module is used for acquiring configuration parameters according to a preset parameter type to be acquired; the type of the parameters to be acquired is preset according to a parameter acquisition task issued by a vehicle management platform;
The abnormality identification module is used for identifying whether the configuration parameters are abnormal or not according to preset baseline configuration issued by the vehicle management platform;
the report generation module is used for generating an abnormal prompt report when any configuration parameter exceeds the parameter limit in the corresponding preset baseline configuration;
The report uploading module is used for uploading the abnormal prompt report to the vehicle management platform; the vehicle management platform is used for triggering an abnormal prompt according to the abnormal prompt report, wherein the abnormal prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
Embodiments of the present application also provide a storage medium having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the vehicle configuration status monitoring method as described in any of the embodiments above.
The embodiment of the application also provides computer equipment, which comprises: one or more processors, and memory;
The memory has stored therein computer readable instructions which, when executed by the one or more processors, perform the steps of the vehicle configuration status monitoring method as described in any of the embodiments above.
From the above technical solutions, the embodiment of the present application has the following advantages:
according to the vehicle configuration state monitoring method, device, storage medium and computer equipment, the configuration of the parameter acquisition task is realized through the vehicle management platform, the type of parameters to be monitored is defined, the configuration parameters of the vehicle are judged abnormally according to the preset baseline configuration matched with different vehicles, and when any configuration parameter of any vehicle does not meet the parameter limit in the preset baseline configuration, the abnormal prompt is triggered, so that operation and maintenance personnel can perform manual detection and adjustment in time, the efficiency of monitoring the configuration parameters is improved, and the reliability of the automatic driving vehicle is improved.
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In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the application, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a diagram of an application environment for a vehicle configuration status monitoring method in one embodiment;
FIG. 2 is a flow chart of a vehicle configuration status monitoring method in one embodiment;
FIG. 3 is a flowchart illustrating steps for determining a preset baseline configuration for each vehicle based on vehicle information for each vehicle, according to one embodiment;
FIG. 4 is a flowchart illustrating steps further included in the vehicle configuration status monitoring method according to one embodiment;
FIG. 5 is a flowchart illustrating steps further included in the vehicle configuration status monitoring method according to one embodiment;
FIG. 6 is a flowchart illustrating a task anomaly notification step if any configuration parameter of a vehicle exceeds a parameter limit in a corresponding preset baseline configuration;
FIG. 7 is a flow chart of a method for monitoring vehicle configuration status in another embodiment;
FIG. 8 is a flowchart illustrating steps further included in the vehicle configuration status monitoring method according to one embodiment;
FIG. 9 is a block diagram showing a configuration of a vehicle configuration state monitoring device in one embodiment;
FIG. 10 is a block diagram showing a configuration of a vehicle configuration state monitoring device according to another embodiment;
FIG. 11 is an internal block diagram of a computer device, in one embodiment.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The vehicle configuration state monitoring method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the vehicle 101 communicates with the vehicle management platform 102 via a network. The data storage system may store data that the vehicle management platform 102 needs to process. The data storage system may be integrated on the vehicle management platform 102 or may be located on a cloud or other network server. The vehicle management platform 102 may be implemented by a stand-alone server or a server cluster including a plurality of servers.
As shown in fig. 2, the present application provides a vehicle configuration status monitoring method applied to the vehicle management platform 102 in fig. 1, the method includes steps S201-S205, wherein:
in step S201, vehicle information of each vehicle is acquired.
The vehicle information is identity information of the vehicle, and a specific vehicle can be positioned in a vehicle team according to the vehicle information.
Step S202, obtaining configuration parameters of each vehicle.
The configuration parameters are obtained by self-checking and fed back by each vehicle according to a parameter acquisition task issued in advance; the parameter acquisition task includes a type of parameter to be acquired for each vehicle.
In one embodiment, the parameter collection task issued to each vehicle may be different, and the vehicle management platform issues the parameter collection task corresponding to each vehicle according to the vehicle information of each vehicle. In another embodiment, the parameter acquisition task issued to each vehicle may be the same, but includes a plurality of subtasks corresponding to different vehicle information, and when each vehicle receives the parameter acquisition task, the type of the parameter to be acquired is determined according to the subtasks corresponding to the vehicle information.
In one embodiment, the vehicle may collect the configuration parameters according to a preset period, or may trigger collection according to a collection instruction sent by the vehicle management platform. In one embodiment, the vehicle may collect configuration parameter uploads after each host start-up.
In one embodiment, the configuration parameters to be collected may include hardware parameters, firmware parameters, operating system parameters, software parameters, or other vehicle software parameters and hardware parameters of the autopilot server. Specifically, the hardware parameters of the autopilot domain server may include a CPU model, a CPU core number, a memory size, a memory slot arrangement, a hardware model, and the like. Firmware parameters may include BIOS (Basic Input Output System ) versions, CPU or memory motherboard configuration parameters, sensor firmware versions, etc. Operating system parameters may include OS version, kernel version, system level configuration, etc. The software parameters may include autopilot system base parameters.
Step S203, determining a preset baseline configuration corresponding to each vehicle according to the vehicle information of each vehicle.
The parameter type in the preset baseline configuration is consistent with the parameter type to be acquired.
For different vehicles, the condition that software versions or partial hardware is inconsistent may exist, so that a plurality of baseline configurations can be preset to correspond to different vehicle information, and the normal work of each vehicle is not affected on the premise that the control of each vehicle in a vehicle team can be reliably realized. When the vehicle management platform selects a preset baseline configuration to issue, the baseline configuration matched with each vehicle is respectively selected from a plurality of preset baseline configurations according to the vehicle information of each vehicle to be issued as the preset baseline configuration.
In one embodiment, where the vehicle information includes vehicle types, a baseline configuration may be preset for one or more vehicle types as desired.
Step S204, if any configuration parameter of the vehicle exceeds the parameter limit in the preset baseline configuration corresponding to the vehicle, generating an abnormal prompt task.
The parameter limit in the preset baseline configuration may be a specific parameter, and if a certain configuration parameter of the vehicle is inconsistent with a corresponding parameter in the preset baseline configuration, the parameter limit is considered to be exceeded; in one embodiment, the parameter limit in the preset baseline configuration may also be a parameter range or regular expression, and the parameter limit is considered to be exceeded only if the parameter range is not met or the regular expression is not satisfied.
Step S205, triggering an anomaly prompt based on the anomaly prompt task.
The abnormal prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
The abnormal prompt can be performed through a front end interface of the vehicle management platform to inform operation and maintenance personnel of which vehicle in the vehicle team is abnormal and specific abnormal parameters of the abnormal vehicle, so that the operation and maintenance personnel can quickly locate the abnormal vehicle to perform abnormal analysis, and if the operation and maintenance personnel are required to debug or maintain, the abnormal vehicle can be quickly processed.
In another embodiment, the abnormality prompt may send a prompt to the terminal of the operation and maintenance personnel through the vehicle management platform, so that the operation and maintenance personnel can learn the abnormality information in time.
According to the vehicle configuration state monitoring method, the configuration of the parameter acquisition task is realized through the vehicle management platform, the types of parameters to be monitored are defined, the configuration parameters of the vehicles are judged abnormally according to the preset base line configuration matched with different vehicles, and when any configuration parameter of any vehicle does not meet the parameter limit in the preset base line configuration, the abnormal prompt is triggered, so that operation and maintenance personnel can perform manual detection and adjustment in time, the efficiency of monitoring the configuration parameters is improved, and the reliability of the automatic driving vehicle is improved.
In one embodiment, the vehicle information includes a vehicle model and a vehicle attribute, and as shown in fig. 3, determining a preset baseline configuration corresponding to each vehicle according to the vehicle information of each vehicle includes steps S301 to S303, where:
step S301, a primary baseline configuration corresponding to a vehicle model of each vehicle is determined according to the vehicle model of each vehicle.
Wherein the primary baseline is configured to correspond to a primary configuration classification of the vehicle model.
Step S302, determining a secondary baseline configuration corresponding to the vehicle attribute of each vehicle in the primary baseline configuration according to the vehicle attribute of each vehicle.
The vehicle attribute refers to the working attribute of each vehicle in a vehicle team, such as a test vehicle, an operation vehicle, an all-unmanned vehicle and the like; the secondary baseline is configured as a baseline corresponding to the vehicle attribute.
Step S303, determining the secondary baseline configuration as a preset baseline configuration.
The secondary baseline configuration is determined as a preset baseline configuration for comparison with configuration parameters of the vehicle feedback with corresponding vehicle information.
Because the requirements of configuration parameters may be different when the vehicles of the same model are engaged in different working attributes, when vehicles with multiple working attributes exist in a motorcade, the baseline configuration can be divided according to the vehicle attributes, the flexibility is higher, and the reliable operation of each vehicle in the motorcade can be ensured. In some embodiments, the vehicle information may also include other attributes, and one skilled in the art may preset more baseline configurations based on other attributes as desired.
In one embodiment, as shown in fig. 4, the vehicle configuration status monitoring method further includes steps S401 to S402, wherein:
in step S401, a parameter acquisition task is generated in response to the parameter acquisition definition instruction.
The parameter acquisition task is used for indicating each vehicle to preset the type of parameters to be acquired corresponding to the vehicle information of each vehicle. The parameter acquisition definition instruction is input to the vehicle management platform by an operation and maintenance personnel and comprises a trigger instruction of the type of the parameter to be acquired, which is matched with different vehicle information.
Step S402, a parameter acquisition task is sent to each vehicle.
In this embodiment, the types of parameters to be collected of different vehicles can be defined manually, so that the flexibility is high, the parameters can be defined according to the running condition of a fleet, and unified management can be realized.
In one embodiment, as shown in fig. 5, the vehicle configuration status monitoring method further includes steps S501-S502, wherein:
In step S501, a parameter acquisition modification task is generated in response to the parameter acquisition modification instruction.
The parameter acquisition modification task is used for indicating the target vehicle to add and/or delete at least one parameter type to be acquired. The parameter acquisition modification instruction is input to the vehicle management platform by an operation and maintenance person, the types of parameters to be acquired, which are required to be added or deleted, of the vehicles corresponding to at least one type of vehicle information are for example corresponding to a type A vehicle, the types of the original parameters to be acquired are a type, b type and c type, the type d of the parameters to be acquired is required to be added for the type A vehicle, the operation and maintenance person inputs the parameter acquisition modification instruction, and the vehicle management platform generates a parameter acquisition modification task for indicating all the type A vehicles to be added with the type d of the parameters to be acquired.
Step S502, a parameter acquisition modification task is sent to the target vehicle.
And sending the parameter acquisition modification task to a target vehicle needing to modify the type of the parameter to be acquired. The target vehicle can be a specific vehicle or a type of vehicle, and the operation and maintenance personnel can select the target vehicle through parameter acquisition and modification instructions.
The embodiment can flexibly realize unified configuration for different vehicle teams or types of parameters to be collected of different vehicles directly through the vehicle management platform without single vehicle debugging.
In one embodiment, as shown in fig. 6, if any configuration parameter of the vehicle exceeds a parameter limit in a corresponding preset baseline configuration, an abnormality notification task is generated, including steps S601-S603, in which:
in step S601, valid parameters in the configuration parameters fed back by each vehicle are screened out.
The effective parameters refer to configuration parameters remained after screening according to a preset screening mechanism.
For example, when the vehicle feeds back the configuration parameters, partial parameters in the uploaded report may be incomplete due to network problems, and the incomplete parameters cannot be used and need to be removed; in some embodiments, there may be a failure of the vehicle to update the type of parameter to be acquired in time, which results in acquisition of some configuration parameters that do not need to be acquired, and rejection of some parameters is also required, and the remaining parameters after being screened by various screening mechanisms are the effective parameters of each vehicle.
Step S602, comparing the effective parameters of each vehicle with the preset baseline configuration corresponding to each vehicle.
Step S603, if any configuration parameter in the effective parameters exceeds the parameter limit in the corresponding preset baseline configuration, generating an abnormal prompt task.
In the embodiment, the configuration parameters fed back by the vehicle are effectively screened, the screened effective parameters are compared with the preset baseline configuration corresponding to the vehicle to which the effective parameters belong, whether the abnormality exists or not is judged, the accuracy of monitoring the configuration parameters can be further ensured, and the abnormal identification result is prevented from being influenced by invalid parameters.
In one embodiment, the vehicle management platform screens out vehicles needing to be subjected to abnormality monitoring according to the vehicle attribute of each vehicle, compares the configuration parameters fed back by the screened vehicles with the corresponding preset baseline configuration, and generates an abnormality prompt task if abnormality occurs. The test vehicle is an exemplary vehicle that does not require anomaly monitoring, and after the test vehicle is screened out by the vehicle attribute, the remaining vehicles are anomaly monitored.
As shown in fig. 7, the embodiment of the present application further provides a vehicle configuration status monitoring method, which is applied to the vehicle in fig. 1, and the method includes steps S701-S704, wherein:
step S701, collecting configuration parameters according to a preset parameter type to be collected.
The type of the parameters to be acquired is preset according to the parameter acquisition task issued by the vehicle management platform.
In one embodiment, the vehicle may collect the configuration parameters according to a preset period, or may trigger collection according to a collection instruction sent by the vehicle management platform. In one embodiment, the vehicle may collect configuration parameter uploads after each host start-up.
Step S702, whether the configuration parameters are abnormal or not is identified according to the preset baseline configuration issued by the vehicle management platform.
The parameter type in the preset baseline configuration is consistent with the parameter type to be acquired.
In step S703, if any configuration parameter exceeds the parameter limit in the corresponding preset baseline configuration, an abnormality notification report is generated.
The parameter limit in the preset baseline configuration may be a specific parameter, and if a certain configuration parameter of the vehicle is inconsistent with a corresponding parameter in the preset baseline configuration, the parameter limit is considered to be exceeded; in one embodiment, the parameter limit in the preset baseline configuration may also be a parameter range or regular expression, and the parameter limit is considered to be exceeded only if the parameter range is not met or the regular expression is not satisfied.
Step S704, uploading the abnormality notification report to the vehicle management platform.
The vehicle management platform is used for triggering an abnormal prompt according to the abnormal prompt report, wherein the abnormal prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
The abnormal prompt can be performed through a front end interface of the vehicle management platform to inform operation and maintenance personnel of which vehicle in the vehicle team is abnormal and specific abnormal parameters of the abnormal vehicle, so that the operation and maintenance personnel can quickly locate the abnormal vehicle to perform abnormal analysis, and if the operation and maintenance personnel are required to debug or maintain, the abnormal vehicle can be quickly processed.
In another embodiment, the abnormality prompt may send a prompt to the terminal of the operation and maintenance personnel through the vehicle management platform, so that the operation and maintenance personnel can learn the abnormality information in time.
According to the vehicle configuration state monitoring method, the configuration of the parameter acquisition task is realized through the vehicle management platform, the types of parameters to be monitored are defined, preset baseline configuration is issued for different vehicles, the vehicle carries out abnormality judgment on the configuration parameters of the vehicle according to the preset baseline configuration, an abnormality prompt report is generated when abnormality is found and is uploaded to the vehicle management platform, and the vehicle management platform triggers the abnormality prompt according to the abnormality prompt report, so that operation and maintenance personnel can carry out manual detection and adjustment in time, the efficiency of monitoring the configuration parameters is improved, and the reliability of the automatic driving vehicle is improved.
In one embodiment, the anomaly prompt report includes vehicle information and anomaly parameters; the vehicle management platform is used for associating the abnormal parameters with the corresponding vehicles according to the vehicle information.
In one embodiment, as shown in fig. 8, the vehicle configuration status monitoring method further includes steps S801 to S802:
Step S801, the vehicle information is uploaded to the vehicle management platform.
The vehicle management platform is used for determining a preset baseline configuration according to vehicle information.
Step S802, a preset baseline configuration issued by a vehicle management platform is obtained.
When the vehicle management platform selects a preset baseline configuration to issue, the baseline configuration matched with each vehicle is respectively selected from a plurality of preset baseline configurations according to the vehicle information of each vehicle to be issued as the preset baseline configuration. For different vehicles, the condition that software versions or partial hardware is inconsistent may exist, so that a plurality of baseline configurations can be preset to correspond to different vehicle information, and the normal work of each vehicle is not affected on the premise that the control of each vehicle in a vehicle team can be reliably realized.
In one embodiment, the vehicle information includes a vehicle model number and a vehicle attribute. The vehicle management platform is used for determining primary baseline configuration according to the vehicle model, determining secondary baseline configuration corresponding to the vehicle attribute in the primary baseline configuration according to the vehicle attribute, and determining the secondary baseline configuration as preset baseline configuration for issuing.
Wherein the primary baseline is configured to correspond to a primary configuration classification of the vehicle model. The vehicle attribute refers to the working attribute of each vehicle in a vehicle team, such as a test vehicle, an operation vehicle, an all-unmanned vehicle and the like; the secondary baseline is the baseline configuration corresponding to the attribute of the vehicle, the secondary baseline configuration is determined to be the preset baseline configuration and is sent to the corresponding vehicle for each vehicle to carry out anomaly identification on the configuration parameters of the vehicle.
Because the requirements of configuration parameters may be different when the vehicles of the same model are engaged in different working attributes, when vehicles with multiple working attributes exist in a motorcade, the baseline configuration can be divided according to the vehicle attributes, the flexibility is higher, and the reliable operation of each vehicle in the motorcade can be ensured. In some embodiments, the vehicle information may also include other attributes, and one skilled in the art may preset more baseline configurations based on other attributes as desired.
In one embodiment, the vehicle configuration state monitoring method further includes:
When a parameter acquisition modification task issued by the vehicle management platform is received, adding and/or deleting at least one parameter type to be acquired according to the parameter acquisition modification task.
The parameter acquisition modification task is used for indicating the target vehicle to add and/or delete at least one parameter type to be acquired. The parameter acquisition modification instruction is input to the vehicle management platform by an operation and maintenance person, the types of parameters to be acquired, which are required to be added or deleted, of the vehicles corresponding to at least one type of vehicle information are for example corresponding to a type A vehicle, the types of the original parameters to be acquired are a type, b type and c type, the type d of the parameters to be acquired is required to be added for the type A vehicle, the operation and maintenance person inputs the parameter acquisition modification instruction, and the vehicle management platform generates a parameter acquisition modification task for indicating all the type A vehicles to be added with the type d of the parameters to be acquired.
The embodiment can flexibly realize unified configuration for different vehicle teams or types of parameters to be collected of different vehicles directly through the vehicle management platform without single vehicle debugging.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
The text processing device provided by the embodiment of the application is described below, and the text processing device described below and the text processing method described above can be referred to correspondingly.
As shown in fig. 9, the embodiment of the present application further provides a vehicle configuration status monitoring device 900, which is applied to a vehicle management platform, and the device includes:
An information acquisition module 901 for acquiring vehicle information of each vehicle;
A parameter obtaining module 902, configured to obtain configuration parameters of each vehicle; the configuration parameters are obtained by self-checking and fed back by each vehicle according to a parameter acquisition task issued in advance; the parameter acquisition task comprises the type of parameters to be acquired of each vehicle;
A baseline determination module 903, configured to determine a preset baseline configuration corresponding to each vehicle according to vehicle information of each vehicle; the parameter type in the preset baseline configuration is consistent with the parameter type to be acquired;
an abnormal prompt task generating module 904, configured to generate an abnormal prompt task when an arbitrary configuration parameter of the vehicle exceeds a parameter limit in a preset baseline configuration corresponding to the vehicle;
A prompt triggering module 905, configured to trigger an abnormal prompt based on the abnormal prompt task; the abnormality prompt is used for prompting abnormal vehicles with abnormal configuration states and abnormal parameters of the abnormal vehicles.
In one embodiment, the vehicle information includes a vehicle model number and a vehicle attribute; the baseline determination module includes:
A first-level baseline determination unit configured to determine a first-level baseline configuration corresponding to a vehicle model of each vehicle according to the vehicle model of each vehicle;
a secondary baseline determination unit for determining a secondary baseline configuration corresponding to the vehicle attribute of each vehicle in the primary baseline configuration according to the vehicle attribute of each vehicle;
And the baseline determination unit is used for determining the secondary baseline configuration as a preset baseline configuration.
In one embodiment, the vehicle configuration status monitoring apparatus 900 further includes:
The first task generating module is used for responding to the parameter acquisition definition instruction and generating a parameter acquisition task; the parameter acquisition task is used for indicating each vehicle to preset the type of parameters to be acquired corresponding to the vehicle information of each vehicle;
And the first task sending module is used for sending the parameter acquisition task to each vehicle.
In one embodiment, the vehicle configuration status monitoring apparatus 900 further includes:
The second task generating module is used for responding to the parameter acquisition modification instruction and generating a parameter acquisition modification task; the parameter acquisition modification task is used for indicating the target vehicle to add and/or delete at least one parameter type to be acquired;
And the second task sending module is used for sending the parameter acquisition modification task to the target vehicle.
In one embodiment, the exception prompting task generating module includes:
The effective parameter screening unit is used for screening effective parameters in the configuration parameters fed back by each vehicle;
A parameter comparison unit for comparing the effective parameters of each vehicle with preset baseline configurations corresponding to each vehicle, respectively;
the abnormal prompt task generating unit is used for generating an abnormal prompt task when any configuration parameter in the effective parameters exceeds the parameter limit in the corresponding preset baseline configuration.
As shown in fig. 10, an embodiment of the present application further provides a vehicle configuration status monitoring device 1000, applied to a vehicle, where the device includes:
The parameter acquisition module 1001 is configured to acquire configuration parameters according to a preset type of parameters to be acquired; the type of the parameters to be acquired is preset according to the parameter acquisition task issued by the vehicle management platform;
the abnormality identification module 1002 is configured to identify whether an abnormality exists in the configuration parameters according to a preset baseline configuration issued by the vehicle management platform;
A report generating module 1003, configured to generate an exception prompt report when any configuration parameter exceeds a parameter limit in a corresponding preset baseline configuration;
A report uploading module 1004, configured to upload the abnormality alert report to the vehicle management platform; the vehicle management platform is used for triggering an abnormal prompt according to the abnormal prompt report, wherein the abnormal prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
In one embodiment, the vehicle configuration status monitoring apparatus 1000 further includes:
The vehicle information uploading module is used for uploading the vehicle information to the vehicle management platform; the vehicle management platform is used for determining preset baseline configuration according to vehicle information;
The baseline configuration acquisition module is used for acquiring preset baseline configuration issued by the vehicle management platform.
In one embodiment, the vehicle configuration status monitoring apparatus 1000 further includes:
The acquisition type modification module is used for adding and/or deleting at least one parameter type to be acquired according to the parameter acquisition modification task when the parameter acquisition modification task issued by the vehicle management platform is received.
The respective modules in the above-described vehicle configuration state monitoring device may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, the present application also provides a storage medium having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the vehicle configuration status monitoring method as set forth in any of the above embodiments.
In one embodiment, the present application also provides a computer device having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the vehicle configuration status monitoring method as described in any of the above embodiments.
In one embodiment, a computer device is provided, which may be a server or a terminal, and the internal structure thereof may be as shown in fig. 11. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing data. The network interface of the computer device is used for communicating with an external device through a network connection. The computer program is executed by a processor to implement a vehicle configuration status monitoring method.
It will be appreciated by those skilled in the art that the structure shown in FIG. 11 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magneto-resistive random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (PHASE CHANGE Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise. Also, the term "and/or" as used in this specification includes any and all combinations of the associated listed items.
In the present specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and may be combined according to needs, and the same similar parts may be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (11)
1. A vehicle configuration status monitoring method, applied to a vehicle management platform, the method comprising:
Acquiring vehicle information of each vehicle; the vehicle information comprises a vehicle model and a vehicle attribute;
Acquiring configuration parameters of each vehicle; the configuration parameters are obtained by self-checking and fed back by the vehicles according to a parameter acquisition task issued in advance; the parameter acquisition task comprises a to-be-acquired parameter type of each vehicle;
Determining a preset baseline configuration corresponding to each vehicle according to the vehicle information of each vehicle; the parameter type in the preset baseline configuration is consistent with the parameter type to be acquired;
if any configuration parameter of the vehicle exceeds parameter limit in preset baseline configuration corresponding to the vehicle, generating an abnormal prompt task;
triggering an abnormality prompt based on the abnormality prompt task; the abnormal prompt is used for prompting abnormal vehicles with abnormal configuration states and abnormal parameters of the abnormal vehicles;
wherein the determining the preset baseline configuration corresponding to each vehicle according to the vehicle information of each vehicle comprises:
determining a primary baseline configuration corresponding to a vehicle model of each vehicle according to the vehicle model of each vehicle; the primary baseline is configured to correspond to a primary configuration classification of a vehicle model;
Determining a secondary baseline configuration corresponding to the vehicle attribute of each vehicle in the primary baseline configuration according to the vehicle attribute of each vehicle; the vehicle attribute refers to the working attribute of each vehicle in an automatic driving motorcade;
And determining the secondary baseline configuration as the preset baseline configuration.
2. The vehicle configuration state monitoring method according to claim 1, characterized by further comprising:
responding to a parameter acquisition definition instruction, and generating a parameter acquisition task; the parameter acquisition task is used for indicating each vehicle to preset the type of parameters to be acquired corresponding to the vehicle information of each vehicle;
and sending the parameter acquisition task to each vehicle.
3. The vehicle configuration state monitoring method according to claim 2, characterized by further comprising:
responding to the parameter acquisition modification instruction, and generating a parameter acquisition modification task; the parameter acquisition modification task is used for indicating the target vehicle to add and/or delete at least one parameter type to be acquired;
And sending the parameter acquisition modification task to the target vehicle.
4. The vehicle configuration status monitoring method according to claim 1, wherein generating an abnormality notification task if any configuration parameter of the vehicle exceeds a parameter limit in a corresponding preset baseline configuration, comprises:
Screening effective parameters in the configuration parameters fed back by each vehicle;
comparing the effective parameters of each vehicle with preset baseline configurations corresponding to each vehicle respectively;
And if any configuration parameter in the effective parameters exceeds the parameter limit in the corresponding preset baseline configuration, generating the abnormal prompting task.
5. A vehicle configuration status monitoring method, characterized by being applied to a vehicle, the method comprising:
Uploading vehicle information to the vehicle management platform; the vehicle information comprises a vehicle model and a vehicle attribute; the vehicle management platform is used for determining a primary baseline configuration according to the vehicle model, determining a secondary baseline configuration corresponding to the vehicle attribute in the primary baseline configuration according to the vehicle attribute, and determining the secondary baseline configuration as a preset baseline configuration to issue; the primary baseline is configured to correspond to a primary configuration classification of a vehicle model; the vehicle attribute is the working attribute of each vehicle in an automatic driving motorcade;
Acquiring a preset baseline configuration issued by the vehicle management platform;
acquiring configuration parameters according to a preset type of parameters to be acquired; the type of the parameters to be acquired is preset according to a parameter acquisition task issued by a vehicle management platform;
Identifying whether the configuration parameters are abnormal or not according to preset baseline configuration issued by the vehicle management platform;
If any configuration parameter exceeds the parameter limit in the corresponding preset baseline configuration, generating an abnormal prompt report;
Uploading the abnormality prompt report to the vehicle management platform; the vehicle management platform is used for triggering an abnormal prompt according to the abnormal prompt report, wherein the abnormal prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
6. The vehicle configuration status monitoring method according to claim 5, wherein the abnormality notification report includes vehicle information and abnormality parameters; the vehicle management platform is used for associating the abnormal parameters with corresponding vehicles according to the vehicle information.
7. The vehicle configuration state monitoring method according to claim 5, characterized by further comprising:
And when a parameter acquisition modification task issued by the vehicle management platform is received, adding and/or deleting at least one parameter type to be acquired according to the parameter acquisition modification task.
8. A vehicle configuration status monitoring device for use with a vehicle management platform, the device comprising:
the information acquisition module is used for acquiring vehicle information of each vehicle; the vehicle information comprises a vehicle model and a vehicle attribute;
The parameter acquisition module is used for acquiring configuration parameters of each vehicle; the configuration parameters are obtained by self-checking and fed back by the vehicles according to a parameter acquisition task issued in advance; the parameter acquisition task comprises a to-be-acquired parameter type of each vehicle;
The base line determining module is used for determining preset base line configuration corresponding to each vehicle according to the vehicle information of each vehicle; the parameter type in the preset baseline configuration is consistent with the parameter type to be acquired;
The abnormal prompt task generation module is used for generating an abnormal prompt task when any configuration parameter of the vehicle exceeds parameter limit in preset baseline configuration corresponding to the vehicle;
The prompt triggering module is used for triggering an abnormal prompt based on the abnormal prompt task; the abnormal prompt is used for prompting abnormal vehicles with abnormal configuration states and abnormal parameters of the abnormal vehicles;
The baseline determination module includes:
A first-level baseline determination unit configured to determine a first-level baseline configuration corresponding to a vehicle model of each vehicle according to the vehicle model of each vehicle; the primary baseline is configured to correspond to a primary configuration classification of a vehicle model;
A secondary baseline determination unit for determining a secondary baseline configuration corresponding to the vehicle attribute of each vehicle in the primary baseline configuration according to the vehicle attribute of each vehicle; the vehicle attribute refers to the working attribute of each vehicle in an automatic driving motorcade;
And the baseline determination unit is used for determining the secondary baseline configuration as a preset baseline configuration.
9. A vehicle configuration state monitoring device, characterized by being applied to a vehicle, comprising:
The vehicle information uploading module is used for uploading the vehicle information to the vehicle management platform; the vehicle information comprises a vehicle model and a vehicle attribute; the vehicle management platform is used for determining a primary baseline configuration according to the vehicle model, determining a secondary baseline configuration corresponding to the vehicle attribute in the primary baseline configuration according to the vehicle attribute, and determining the secondary baseline configuration as a preset baseline configuration to issue; the primary baseline is configured to correspond to a primary configuration classification of a vehicle model; the vehicle attribute is the working attribute of each vehicle in an automatic driving motorcade;
The baseline configuration acquisition module is used for acquiring preset baseline configuration issued by the vehicle management platform;
the parameter acquisition module is used for acquiring configuration parameters according to a preset parameter type to be acquired; the type of the parameters to be acquired is preset according to a parameter acquisition task issued by a vehicle management platform;
The abnormality identification module is used for identifying whether the configuration parameters are abnormal or not according to preset baseline configuration issued by the vehicle management platform;
the report generation module is used for generating an abnormal prompt report when any configuration parameter exceeds the parameter limit in the corresponding preset baseline configuration;
The report uploading module is used for uploading the abnormal prompt report to the vehicle management platform; the vehicle management platform is used for triggering an abnormal prompt according to the abnormal prompt report, wherein the abnormal prompt is used for prompting an abnormal vehicle with abnormal configuration state and abnormal parameters of the abnormal vehicle.
10. A storage medium, characterized by: the storage medium having stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the vehicle configuration status monitoring method of any of claims 1-4 or 5-7.
11. A computer device, comprising: one or more processors, and memory;
The memory has stored therein computer readable instructions which, when executed by the one or more processors, perform the steps of the vehicle configuration status monitoring method of any of claims 1-4 or 5-7.
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Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102331760A (en) * | 2011-07-15 | 2012-01-25 | 深圳市路畅科技有限公司 | Method and system for remotely diagnosing vehicle failure in real time |
| CN103455020A (en) * | 2012-05-28 | 2013-12-18 | 哈尔滨工业大学深圳研究生院 | Intelligent cloud-detection service system and intelligent cloud-detection service method for vehicle conditions |
| CN103578160A (en) * | 2012-07-31 | 2014-02-12 | 同济大学 | Vehicle monitoring system based on vehicle-mounted wireless data recorder |
| CN108375974A (en) * | 2018-05-21 | 2018-08-07 | 上海星融汽车科技有限公司 | It is a kind of to be used to remotely record, analysis, diagnose, the method and system of maintenance vehicle failure |
| CN108881267A (en) * | 2018-06-29 | 2018-11-23 | 百度在线网络技术（北京）有限公司 | Vehicle abnormality detection method, car-mounted terminal, server and storage medium |
| WO2019142474A1 (en) * | 2018-01-22 | 2019-07-25 | パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカ | Data analysis device and program |
| CN110460669A (en) * | 2019-08-16 | 2019-11-15 | 广州亚美信息科技有限公司 | A kind of car accident detection alarm method based on car networking intelligent terminal |
| CN110912992A (en) * | 2019-11-22 | 2020-03-24 | 深圳市元征科技股份有限公司 | Diagnostic data transmission method, device, equipment and system |
| CN110989555A (en) * | 2019-12-06 | 2020-04-10 | 深圳市元征科技股份有限公司 | Vehicle diagnosis and alarm method, device and system |
| CN111583624A (en) * | 2019-02-19 | 2020-08-25 | 上海博泰悦臻网络技术服务有限公司 | Motorcade combination method and system based on information sharing, sharing platform and vehicle |
| CN112380045A (en) * | 2020-12-03 | 2021-02-19 | 安徽江淮汽车集团股份有限公司 | Vehicle abnormality detection method, device, equipment and storage medium |
| CN112673406A (en) * | 2020-05-29 | 2021-04-16 | 华为技术有限公司 | Method and terminal device for identifying abnormal vehicle parameters in vehicle queue |
| CN113242143A (en) * | 2021-04-25 | 2021-08-10 | 东风汽车集团股份有限公司 | Vehicle remote parameter configuration method, vehicle-mounted remote processor and vehicle networking system |
| CN113259210A (en) * | 2021-07-16 | 2021-08-13 | 南斗六星系统集成有限公司 | Intelligent testing system for car networking terminal |
| CN113740077A (en) * | 2021-09-13 | 2021-12-03 | 广州文远知行科技有限公司 | Vehicle chassis testing method, device, equipment and storage medium |
| CN113961386A (en) * | 2021-10-27 | 2022-01-21 | 奇瑞商用车（安徽）有限公司 | Automatic management method for software version of whole vehicle |
| CN114115170A (en) * | 2021-09-29 | 2022-03-01 | 江铃汽车股份有限公司 | Method and device for determining vehicle configuration module and after-sale diagnostic apparatus |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017165284A1 (en) * | 2016-03-25 | 2017-09-28 | Cummins Inc. | Systems and methods of adjusting operating parameters of a vehicle based on vehicle duty cycles |
| US10382466B2 (en) * | 2017-03-03 | 2019-08-13 | Hitachi, Ltd. | Cooperative cloud-edge vehicle anomaly detection |
| US10510194B2 (en) * | 2017-06-12 | 2019-12-17 | Ford Global Technologies, Llc | Cloud-based connectivity energy budget manager |
| CN108227680B (en) * | 2018-01-19 | 2021-03-05 | 深圳市道通科技股份有限公司 | Automobile diagnostic instrument, operation system method thereof and automobile diagnostic system |
| US11235778B2 (en) * | 2018-01-24 | 2022-02-01 | Clearpath Robotics Inc. | Systems and methods for maintaining vehicle state information |
| US20200184744A1 (en) * | 2018-12-11 | 2020-06-11 | Snap-On Incorporated | Vehicle Scan Tool Configured to Receive Automated Initialization Requests |
| JP7459634B2 (en) * | 2020-04-13 | 2024-04-02 | マツダ株式会社 | Driver Abnormality Judgment System |
-
2022
- 2022-03-30 CN CN202210324922.2A patent/CN114677779B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102331760A (en) * | 2011-07-15 | 2012-01-25 | 深圳市路畅科技有限公司 | Method and system for remotely diagnosing vehicle failure in real time |
| CN103455020A (en) * | 2012-05-28 | 2013-12-18 | 哈尔滨工业大学深圳研究生院 | Intelligent cloud-detection service system and intelligent cloud-detection service method for vehicle conditions |
| CN103578160A (en) * | 2012-07-31 | 2014-02-12 | 同济大学 | Vehicle monitoring system based on vehicle-mounted wireless data recorder |
| WO2019142474A1 (en) * | 2018-01-22 | 2019-07-25 | パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカ | Data analysis device and program |
| CN108375974A (en) * | 2018-05-21 | 2018-08-07 | 上海星融汽车科技有限公司 | It is a kind of to be used to remotely record, analysis, diagnose, the method and system of maintenance vehicle failure |
| CN108881267A (en) * | 2018-06-29 | 2018-11-23 | 百度在线网络技术（北京）有限公司 | Vehicle abnormality detection method, car-mounted terminal, server and storage medium |
| CN111583624A (en) * | 2019-02-19 | 2020-08-25 | 上海博泰悦臻网络技术服务有限公司 | Motorcade combination method and system based on information sharing, sharing platform and vehicle |
| CN110460669A (en) * | 2019-08-16 | 2019-11-15 | 广州亚美信息科技有限公司 | A kind of car accident detection alarm method based on car networking intelligent terminal |
| CN110912992A (en) * | 2019-11-22 | 2020-03-24 | 深圳市元征科技股份有限公司 | Diagnostic data transmission method, device, equipment and system |
| CN110989555A (en) * | 2019-12-06 | 2020-04-10 | 深圳市元征科技股份有限公司 | Vehicle diagnosis and alarm method, device and system |
| CN112673406A (en) * | 2020-05-29 | 2021-04-16 | 华为技术有限公司 | Method and terminal device for identifying abnormal vehicle parameters in vehicle queue |
| CN112380045A (en) * | 2020-12-03 | 2021-02-19 | 安徽江淮汽车集团股份有限公司 | Vehicle abnormality detection method, device, equipment and storage medium |
| CN113242143A (en) * | 2021-04-25 | 2021-08-10 | 东风汽车集团股份有限公司 | Vehicle remote parameter configuration method, vehicle-mounted remote processor and vehicle networking system |
| CN113259210A (en) * | 2021-07-16 | 2021-08-13 | 南斗六星系统集成有限公司 | Intelligent testing system for car networking terminal |
| CN113740077A (en) * | 2021-09-13 | 2021-12-03 | 广州文远知行科技有限公司 | Vehicle chassis testing method, device, equipment and storage medium |
| CN114115170A (en) * | 2021-09-29 | 2022-03-01 | 江铃汽车股份有限公司 | Method and device for determining vehicle configuration module and after-sale diagnostic apparatus |
| CN113961386A (en) * | 2021-10-27 | 2022-01-21 | 奇瑞商用车（安徽）有限公司 | Automatic management method for software version of whole vehicle |
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|---|---|
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