CN114061651B - Automatic driving-based automobile operation information monitoring method and system - Google Patents
Automatic driving-based automobile operation information monitoring method and system Download PDFInfo
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Abstract
The invention discloses an automatic driving-based automobile operation information monitoring method, which comprises the following steps: collecting live monitoring information of the operation of the automobile, obtaining a comparison information set, calculating the discrete degree in the comparison information set, comparing the live monitoring information with the discrete degree, obtaining preliminary abnormal information according to a comparison result, obtaining working condition characteristic parameters corresponding to the preliminary abnormal information, obtaining historical information identical to the working condition characteristic parameters, and obtaining historical abnormal information in the historical information; and obtaining external factor marks attached to the historical abnormal information, receiving the external factor marks corresponding to the preliminary abnormal information, analyzing whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same or not, if so, deducing and outputting the preliminary abnormal information. By adopting the method, the abnormal information can be timely found and processed, meanwhile, the reason for generating the abnormal information can be quickly found, the influence of external factors is fully considered, and the detection of the automobile running information is more accurately and quickly realized.
Description
Technical Field
The invention belongs to the technical field of vehicle signal processing, and particularly relates to an automatic driving-based automobile operation information monitoring method and system.
Background
At present, with the increasing automation and intelligent degree of automobiles, the integrated working components in the automobiles are more and more distributed and more complex, and when the automobiles run, the types and the quantity of the generated running information are more and more because of the working running of various components.
In the prior art, with the increase of operation information of various components and parts and the switching process of different working conditions, abnormal information appearing therein is more and more increased, and if the abnormal information is obvious and is correspondingly displayed on a vehicle-mounted instrument panel, problems can be found and processed by related staff, and the abnormal information which is less obvious or is not correspondingly displayed on the vehicle-mounted instrument panel is not easy to find, so that the abnormal information generated by the operation of the components cannot be found in time, and meanwhile, the cause of the abnormality cannot be solved. In addition, there is a case that when the information is abnormal, the information is required to be removed from the starting abnormality due to various reasons, such as that the automobile cannot be started, the battery is not powered, the controller is damaged, and the like, and if the battery is not powered, the abnormal starting information is required to be removed, so that the waste of human resources is avoided, and the automobile which is not problematic is maintained.
In view of the foregoing, there is a need for a method for accurately determining whether information of an intelligent automobile is abnormal or not, which can solve the above problems.
Disclosure of Invention
The embodiment of the invention aims to provide an automatic driving-based automobile operation information monitoring method and system, and aims to solve the problem that whether information of an intelligent automobile is abnormal or not cannot be accurately judged in the prior art.
In order to solve the technical problems, the invention provides a method for monitoring automobile operation information based on automatic driving, which comprises the following steps:
Collecting live monitoring information of automobile operation, and obtaining a comparison information set which is the same as the information type and the working condition characteristics of the live monitoring information, wherein the working condition characteristics comprise: the working state of the components related to the monitoring information, the environment temperature and humidity of the corresponding components and the like;
calculating the discrete degree in the comparison information set, comparing the live monitoring information with the discrete degree, and analyzing preliminary abnormal information in the live monitoring information according to a comparison result, wherein the preliminary abnormal information is attached with a discrete degree size mark;
acquiring working condition characteristic parameters corresponding to the preliminary abnormal information, and acquiring historical information which is the same as the working condition characteristics in a computer control module, and acquiring historical abnormal information in the historical information;
Obtaining the history abnormal information corresponding to the preliminary abnormal information according to the discrete degree size mark, and obtaining an external factor mark attached to the history abnormal information, wherein the external factor mark is a corresponding mark of an external emergency in a corresponding time period of the history abnormal information;
and receiving an external factor mark corresponding to the preliminary abnormal information, analyzing whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same, deducing that the preliminary abnormal information is abnormal and outputting the preliminary abnormal information when the external factor marks of the preliminary abnormal information and the historical abnormal information are different.
Further, the method further comprises:
Comparing the live monitoring information with the information in the comparison information set to obtain an information difference value I;
Obtaining a corresponding standard deviation of the comparison information set, and comparing the first information difference value with the standard deviation to obtain a second information difference value;
obtaining interference factors on corresponding working condition characteristics of the live monitoring information, and determining a corresponding error range according to the interference factors, wherein the interference factors are environmental factors influencing the size of the live monitoring information;
And calculating whether the information difference value II is in the error range, and when the information difference value II is not in the error range, the live monitoring information is preliminary abnormal information.
In the above embodiment, the method further includes:
And if the information difference value II is not in the error range, analyzing an information difference value III between the information difference value II and the upper limit and the lower limit of the error range, and determining a corresponding discrete degree size mark according to the size level of the information difference value III.
In the above embodiment, the method further includes:
And sorting the preliminary abnormal information to enable the preliminary abnormal information to be attached with corresponding external factor marks, and outputting the sorted preliminary abnormal information to the computer control module.
In the above embodiment, the method further includes:
And if the external factor mark corresponding to the preliminary abnormal information is not received, judging and outputting the preliminary abnormal information to be abnormal.
In the above embodiment, the method further includes:
and obtaining a corresponding warning level according to the discrete degree size mark, obtaining set early warning information and a corresponding query terminal according to the warning level, and transmitting the early warning information to the query terminal.
The embodiment of the application provides an automatic driving-based automobile running information monitoring system, which comprises the following components:
The collecting module is used for collecting the real-time monitoring information of the computer control module and obtaining a comparison data set which is the same as the information type and the working condition characteristics of the real-time monitoring information, and the working condition characteristics comprise: the working state of the components related to the monitoring information, the environment temperature and humidity of the corresponding components, and the like.
The analysis module is used for analyzing the discrete degree in the comparison information set, comparing the live monitoring information with the discrete degree, and obtaining preliminary abnormal information in the live monitoring information according to a comparison result, wherein the preliminary abnormal information is attached with a discrete degree size mark.
The first acquisition module is used for acquiring working condition characteristic parameters corresponding to the preliminary abnormal information, acquiring historical information which is the same as the working condition characteristic parameters in the computer control module, and acquiring the historical abnormal information in the historical information.
The second obtaining module is configured to obtain the historical anomaly information corresponding to the preliminary anomaly information according to the discrete degree size mark, and obtain an external factor mark attached to the historical anomaly information, where the external factor mark is a corresponding mark of an external anomaly event in a corresponding time period of the historical anomaly information.
The judging module is used for receiving the external factor marks corresponding to the preliminary abnormal information, judging whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same, judging that the preliminary abnormal information is abnormal by different external factor marks of the preliminary abnormal information and the historical abnormal information, and outputting the preliminary abnormal information.
In the above embodiment, the system further includes:
and the contrast module I is used for comparing the live monitoring information with the information in the contrast information set to obtain an information difference value I.
And the contrast module II is used for obtaining the standard deviation corresponding to the contrast information set, and comparing the information difference I with the standard deviation to obtain an information difference II.
The obtaining module III is used for obtaining interference factors on the corresponding working condition characteristics of the live monitoring information and determining a corresponding error range according to the interference factors, wherein the interference factors are environmental factors influencing the size of the live monitoring information.
And the judging module II is used for judging whether the information difference value II is in the error range, and if the information difference value II is not in the error range, the live monitoring information is preliminary abnormal data.
The scheme of the application at least comprises the following beneficial effects:
According to the technical scheme, the automatic driving-based automobile operation information monitoring method and system acquire live monitoring information of the computer control module, and meanwhile obtain a comparison information set with the same information type and working condition characteristics as those of the live monitoring information, wherein the working condition characteristics comprise: the working state of the components related to the monitoring information, the environment temperature and humidity of the corresponding components and the like; calculating the discrete degree of the comparison information set, comparing the live monitoring information with the discrete degree, and obtaining preliminary abnormal information in the live monitoring information by using a comparison result, wherein the preliminary abnormal information is attached with a discrete degree mark; acquiring working components corresponding to the preliminary abnormal information, acquiring historical information of the working components related to the preliminary abnormal information in the computer control module, acquiring the historical abnormal information in the historical information, acquiring the historical abnormal information corresponding to the preliminary abnormal information according to the discrete degree size mark, and acquiring an external factor mark attached to the historical abnormal information, wherein the external factor mark is a corresponding mark of an external emergency in a corresponding time period of the historical abnormal information; and receiving the external factor marks corresponding to the preliminary abnormal information, judging whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same, and judging and outputting the preliminary abnormal information abnormality when the external factor marks of the preliminary abnormal information and the historical abnormal information are different. Therefore, various information in the running process of the automobile can be judged abnormally, the abnormal information can be found timely while the human resources are saved, the subsequent processing of the generation reasons of the abnormal information is facilitated, in addition, whether the abnormal information is caused by sudden external factors or not can be considered when the abnormal information is found, and the abnormal information detection can be completed more specifically.
Drawings
One or more embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings.
Fig. 1 is a flowchart of an automatic driving-based vehicle operation information monitoring method according to an embodiment of the present invention.
Fig. 2 is a block diagram of an automatic driving-based vehicle operation information monitoring system according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the following detailed description of the embodiments of the present application will be given with reference to the accompanying drawings. However, those of ordinary skill in the art will understand that in various embodiments of the present application, numerous technical details have been set forth in order to provide a better understanding of the present application. The claimed application may be practiced without these specific details and with various changes and modifications based on the following embodiments.
Fig. 1 is a schematic flow chart of an automatic driving-based method for monitoring vehicle operation information according to an embodiment of the present application, and as shown in fig. 1, an embodiment of the present application provides an automatic driving-based method for monitoring vehicle operation information, including:
step SA-1, collecting live monitoring information of automobile operation, and obtaining a comparison information set with the same information type and working condition characteristics as those of the live monitoring information, wherein the working condition characteristics comprise: the working state of the components related to the monitoring information, the environment temperature and humidity of the corresponding components, and the like.
Specifically, the live monitoring information of the current running of the automobile can be collected through the computer control module, and can be divided according to the type of the monitoring information, including running parameter information, braking parameter information, safety airbag parameter information, car window parameter information, seat parameter information, air conditioner parameter information and the like, then a comparison information set which is the same as the information type and working condition characteristics of the live monitoring information is obtained, for example, car window lifting process information of the A car is obtained, then the working condition characteristics are the same and refer to main factors affecting the car window lifting process information, namely, the working state of a car window lifter, the environmental temperature and humidity of the environment where the car window lifter is located and the like, and the comparison information set corresponding to the car window lifting process information of the A car comprises the information such as: different vehicles, but the working state of the window lifter and the environment temperature and humidity of the environment where the window lifter is positioned are the same.
And step SA-2, calculating the discrete degree in the comparison information set, comparing the live monitoring information with the discrete degree, and analyzing preliminary abnormal information in the live monitoring information according to a comparison result, wherein the preliminary abnormal information is attached with a discrete degree size mark.
Specifically, the discrete degree of the information in the comparison information set is calculated, wherein the discrete degree can be represented by extremely poor, average difference, standard deviation and the like, the discrete degree of the live monitoring information and the discrete degree in the comparison information set are compared, namely, whether the discrete degree of the live monitoring information reaches the discrete degree of the information in the comparison information set or not is compared with the discrete degree of each piece of the live monitoring information, when the discrete degree of the information in the comparison information set is reached or exceeded, the fact that the size of the live monitoring information deviates is indicated, the existence of preliminary abnormal information in the live monitoring information is judged, meanwhile, the size of the abnormal degree (discrete degree) of the preliminary abnormal information is marked according to the size of the abnormal degree of the preliminary abnormal information, the size of the discrete degree is marked to represent the abnormal degree (discrete degree) of the preliminary abnormal information, and when the preliminary abnormal information is abnormal (the discrete degree is larger), the attached size mark of the discrete degree is larger.
And step SA-3, obtaining working condition characteristic parameters corresponding to the preliminary abnormal information, and obtaining historical information which is the same as the working condition characteristics in the computer control module, and obtaining the historical abnormal information in the historical information.
Specifically, the working condition characteristic parameters corresponding to the preliminary abnormal information are obtained, for example, if the braking information of the braking pedal of the vehicle is the preliminary abnormal information, the working condition characteristic parameters corresponding to the braking pedal of the vehicle are obtained, the historical working information of the braking pedal of the vehicle is obtained through the computer control module, then the historical abnormal information in the historical information is obtained, the historical abnormal information can be the historical information containing the abnormal mark in the computer control module, in the historical information, if the information is abnormal, the abnormal mark can be correspondingly added, and the abnormal information can be intuitively found when the information is conveniently found in the computer control module.
And step SA-4, obtaining the history abnormal information corresponding to the preliminary abnormal information according to the discrete degree size mark, and obtaining an external factor mark attached to the history abnormal information, wherein the external factor mark is a corresponding mark of an external emergency in a corresponding time period of the history abnormal information.
Specifically, the history abnormal information corresponding to the preliminary abnormal information is obtained according to the discrete degree size mark, wherein when the discrete degree size mark of the preliminary abnormal information is larger, the discrete degree of the corresponding history abnormal information is also larger, namely, the discrete degree (information abnormal degree) of the preliminary abnormal information is the same as that of the history abnormal information, the discrete degree (information abnormal degree) of the preliminary abnormal information is corresponding to the discrete degree of the history abnormal information, after the corresponding history abnormal information is obtained, whether the history abnormal information is attached with an external factor mark is analyzed, if attached, the external factor mark attached to the history abnormal information is obtained, wherein when the history abnormal information occurs, the external factor mark attached to the history abnormal information is possibly generated due to the ageing of a component, line faults and the like, namely, the internal cause of the component, and the information caused by the reasons such as sudden rise and fall of the ambient temperature, the external shock and the like of the working of the component, namely, the external factor is generated when the history abnormal information caused by the external factor appears, and the computer control module generates the corresponding external factor mark and correspondingly stores the external factor mark when the history abnormal information is recorded.
And step SA-5, receiving the external factor marks corresponding to the preliminary abnormal information, analyzing whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same, deducing that the preliminary abnormal information is abnormal and outputting the preliminary abnormal information when the external factor marks of the preliminary abnormal information and the historical abnormal information are different.
Specifically, the external factor marks corresponding to the preliminary abnormal information are received, whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same or not is judged, for example, when the external factor marks of the preliminary abnormal information and the historical abnormal information are different due to reasons such as sudden rising and falling of air temperature, the condition that the historical abnormal information is abnormal is judged and output because the external factor marks corresponding to the preliminary abnormal information are not only external factors but also internal reasons or because the external factor marks corresponding to the preliminary abnormal information are empty is indicated.
In addition, if the external factor mark corresponding to the preliminary abnormal information is not received, the abnormal reason of the preliminary abnormal information is indicated to be due to the internal reason, the preliminary abnormal information is directly judged and output, the abnormal reason of the preliminary abnormal information is conveniently and rapidly found, the preliminary abnormal information is timely repaired, and larger loss is avoided.
The embodiment of the application provides an automatic driving-based automobile operation information monitoring method, which is used for collecting live monitoring information of automobile operation and obtaining a comparison information set with the same information type and working condition characteristics as those of the live monitoring information, wherein the working condition characteristics comprise: the working state of the components related to the monitoring information and the environmental temperature and humidity of the corresponding components; calculating the discrete degree in the comparison information set, comparing the live monitoring information with the discrete degree, and obtaining preliminary abnormal information in the live monitoring information according to the comparison result, wherein the preliminary abnormal information is attached with a discrete degree mark; acquiring working condition characteristic parameters corresponding to the preliminary abnormal information, and acquiring historical information which is the same as the working condition characteristic parameters in the computer control module, and acquiring historical abnormal information in the historical information; obtaining historical abnormal information corresponding to the preliminary abnormal information according to the discrete degree size mark, and judging whether the historical abnormal information is attached with an external factor mark, wherein the external factor mark is a corresponding mark of an external emergency in a corresponding time period of the historical abnormal information; and receiving the external factor marks corresponding to the preliminary abnormal information, judging whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same, and determining and outputting the preliminary abnormal information abnormality when the external factor marks of the preliminary abnormal information and the historical abnormal information are different. The method has the advantages that the information collected by the computer control module can be subjected to anomaly analysis, the anomaly information can be found timely while the labor cost is saved, the reasons for generating the anomaly information can be found conveniently and rapidly, in addition, when the anomaly information is monitored, whether the anomaly information is caused by the emergency external factors can be analyzed, and the anomaly information detection can be realized more accurately.
On the basis of the above embodiment, the method for monitoring the running information of the automobile based on automatic driving further includes:
Comparing the live monitoring information with the information in the comparison information set to obtain an information difference value I;
Obtaining a corresponding standard deviation of the comparison information set, and comparing the first information difference value with the standard deviation to obtain a second information difference value;
obtaining interference factors on corresponding working condition characteristics of the live monitoring information, and determining a corresponding error range according to the interference factors, wherein the interference factors are environmental factors influencing the size of the live monitoring information;
And calculating whether the information difference value II is in the error range, and when the information difference value II is not in the error range, the live monitoring information is preliminary abnormal information.
In the embodiment of the application, the live monitoring information is compared with the information of the same type in the comparison information set, the difference between the live monitoring information and the information of the same type in the comparison information set is calculated to obtain a first information difference, then the corresponding standard deviation of the information in the comparison information set is calculated, the first information difference is compared with the standard deviation to obtain a second information difference, wherein the second information difference represents the discrete condition that the difference between the two information (the live monitoring information and the information of the same type in the comparison information set) is compared with the standard deviation, after the second information difference is calculated, the interference factors on the corresponding working condition characteristics of the live monitoring information are obtained, the interference factors can be used for example, the temperature and humidity of the working environment of the component, the vibration impact on the component and the like can generate interference information on the monitoring information, then the upper limit value and the lower limit value of the corresponding error range are calculated according to the influence degree of the interference factors, then whether the second information difference is in the error range is judged, and when the second information difference is not in the error range, the live monitoring information is the primary abnormal information is indicated. Specific steps may be, for example: the rotation speed of a vehicle engine corresponding to 80Km/h of the vehicle is 2050 revolutions, the average value of the information of the same type in the comparison information set is 2000 revolutions, the information difference value is 50 revolutions, then the standard deviation corresponding to the comparison information set is calculated, the standard deviation value is 20, the information difference value is 30, then interference factors on working condition characteristics corresponding to the live monitoring information are obtained, the standard deviation error range is confirmed to be +/-50 by means of parameters such as temperature and humidity of the working environment of the components and vibration impact generated on the components, the information difference value is in the error range, the live monitoring information is not primary abnormal information, and when the error range is +/-10, the information difference value is not in the error range, and the live monitoring information is primary abnormal information.
According to the embodiment of the application, the discrete information (preliminary abnormal information) in the live monitoring information is obtained by calculating the corresponding standard deviation of the comparison information set, the live monitoring information and the information in the comparison information set, and interference factors can be considered in calculation, so that the calculation result of the preliminary abnormal information is more accurate, and the judgment result of the relative abnormal information in the subsequent step is more accurate.
On the basis of the above embodiment, the method for monitoring the running information of the automobile based on automatic driving further includes:
And if the information difference value II is not in the error range, analyzing an information difference value III between the information difference value II and the upper limit and the lower limit of the error range, and determining a corresponding discrete degree size mark according to the size level of the information difference value III.
In the embodiment of the application, if the information difference value III is not in the error range, the live monitoring information is indicated to be preliminary abnormal information, then the discrete degree of the preliminary abnormal information is calculated by the information difference value III between the information difference value II and the upper limit and the lower limit of the error range according to the abnormal degree of the preliminary abnormal information, and then the discrete degree size mark is correspondingly determined.
According to the embodiment of the application, the corresponding discrete degree size mark is obtained by calculating the second information difference value and the upper limit and the lower limit of the error range, and the standard of the discrete degree size mark can clearly show the discrete degree size of the preliminary abnormal information, so that the subsequent information abnormal judgment is facilitated.
On the basis of the above embodiment, the method for monitoring the running information of the automobile based on automatic driving further includes:
And sorting the preliminary abnormal information to enable the preliminary abnormal information to be attached with corresponding external factor marks, and outputting the sorted preliminary abnormal information to the computer control module.
In the embodiment of the application, after the preliminary abnormal information is judged and outputted to be abnormal, the external factor corresponding to the preliminary abnormal information is marked, the tidied preliminary abnormal information is outputted to the computer control module, and the information of the computer control module is updated, so that the information in the computer control module can be attached with the corresponding external factor mark, thereby being convenient for the subsequent judgment of whether the information is abnormal or not and the reason of the abnormality.
According to the embodiment of the application, the information of the computer control module is updated, so that the information in the computer control module can be attached with corresponding external factor marks, and the information abnormality and the cause of the abnormality can be obviously obtained when the information analysis is carried out later.
On the basis of the above embodiment, the method for monitoring the running information of the automobile based on automatic driving further includes:
and obtaining a corresponding warning level according to the discrete degree size mark, obtaining set early warning information and a corresponding query terminal according to the warning level, and transmitting the early warning information to the query terminal.
In the embodiment of the application, corresponding warning levels are obtained according to the discrete level marks, namely, the corresponding warning levels are determined according to the abnormal level of the live monitoring information, then, the set early warning information and the corresponding query terminal are obtained according to the warning levels, generally, the higher the warning level is, the more urgent the corresponding early warning information content is, the higher the corresponding query terminal management authority is, the higher the related staff level is, and then, the early warning information is transmitted to the corresponding query terminal, so that related staff can timely know the abnormal level, and the corresponding problem generation reason of the live monitoring information is processed.
According to the embodiment of the application, the early warning information of the corresponding level is transmitted to the query terminal of the corresponding level, so that related staff can timely process the problem generation reasons corresponding to the live monitoring information.
Fig. 2 is a schematic diagram of an automatic driving-based vehicle operation information monitoring system according to an embodiment of the present application, including:
The collection module SB-1 is used for collecting live monitoring information of the computer control module and obtaining a comparison data set which is the same as the information type and the working condition characteristics of the live monitoring information, and the working condition characteristics comprise: the working state of the components related to the monitoring information, the environment temperature and humidity of the corresponding components, and the like.
And the analysis module SB-2 is used for analyzing the discrete degree in the comparison information set, comparing the live monitoring information with the discrete degree, and obtaining preliminary abnormal information in the live monitoring information according to a comparison result, wherein the preliminary abnormal information is attached with a discrete degree size mark.
The acquisition module SB-3 is used for acquiring working condition characteristic parameters corresponding to the preliminary abnormal information, acquiring historical information which is the same as the working condition characteristic parameters in the computer control module and acquiring the historical abnormal information in the historical information.
The obtaining module II SB-4 is used for obtaining the historical abnormal information corresponding to the preliminary abnormal information according to the discrete degree size mark, and obtaining an external factor mark attached to the historical abnormal information, wherein the external factor mark is a corresponding mark of an external abnormal event in a corresponding time period of the historical abnormal information.
And the judging module SB-5 is used for receiving the external factor marks corresponding to the preliminary abnormal information, judging whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same, judging whether the external factor marks of the preliminary abnormal information and the historical abnormal information are different, and outputting the preliminary abnormal information to be abnormal.
In one embodiment, the system may further comprise:
and the contrast module I is used for comparing the live monitoring information with the information in the contrast information set to obtain an information difference value I.
And the contrast module II is used for obtaining the standard deviation corresponding to the contrast information set, and comparing the information difference I with the standard deviation to obtain an information difference II.
The obtaining module III is used for obtaining interference factors on the corresponding working condition characteristics of the live monitoring information and determining a corresponding error range according to the interference factors, wherein the interference factors are environmental factors influencing the size of the live monitoring information.
And the judging module II is used for judging whether the information difference value II is in the error range, and if the information difference value II is not in the error range, the live monitoring information is preliminary abnormal data.
In one embodiment, the system may further comprise:
And the analysis module II is used for analyzing an information difference III between the information difference II and the upper limit and the lower limit of the error range if the information difference II is not in the error range, and determining a corresponding discrete degree size mark according to the size level of the information difference III.
In one embodiment, the system may further comprise:
the marking module is used for marking the preliminary abnormal information to enable the preliminary abnormal information to be marked by corresponding external factors, and outputting the marked preliminary abnormal information to the computer control module.
In one embodiment, the system may further comprise:
And the output module is used for judging and outputting the abnormality of the preliminary abnormality information when the external factor mark corresponding to the preliminary abnormality information is not received.
In one embodiment, the system may further comprise:
And the alarm module is used for obtaining a corresponding alarm level according to the discrete degree size mark, obtaining set early warning information and a corresponding query terminal according to the alarm level, and transmitting the early warning information to the query terminal.
For specific limitations regarding the autopilot-based vehicle operation information monitoring system, reference may be made to the above limitations regarding the autopilot-based vehicle operation information monitoring method, and no further description is given here. The modules in the automatic driving-based vehicle operation information monitoring system can be all or partially implemented by software, hardware and combinations 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.
The foregoing is merely an embodiment of the present application, and a specific structure and characteristics of common knowledge in the art, which are well known in the scheme, are not described herein, so that a person of ordinary skill in the art knows all the prior art in the application date or before the priority date, can know all the prior art in the field, and has the capability of applying the conventional experimental means before the date, and a person of ordinary skill in the art can complete and implement the present embodiment in combination with his own capability in the light of the present application, and some typical known structures or known methods should not be an obstacle for a person of ordinary skill in the art to implement the present application. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present application, and these should also be considered as the scope of the present application, which does not affect the effect of the implementation of the present application and the utility of the patent. The protection scope of the present application is subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (7)
1. An automatic driving-based automobile operation information monitoring method is characterized by comprising the following steps:
Collecting live monitoring information of automobile operation, and obtaining a comparison information set which is the same as the information type and the working condition characteristics of the live monitoring information, wherein the working condition characteristics comprise: the working state of the components related to the monitoring information, the environment temperature and humidity of the corresponding components and the like;
Calculating the discrete degree in the comparison information set, comparing the live monitoring information with the discrete degree, and analyzing preliminary abnormal information in the live monitoring information according to a comparison result, wherein the preliminary abnormal information is attached with a discrete degree size mark; comprising the following steps:
Comparing the live monitoring information with the information in the comparison information set to obtain an information difference value I;
Obtaining a corresponding standard deviation of the comparison information set, and comparing the first information difference value with the standard deviation to obtain a second information difference value;
obtaining interference factors on corresponding working condition characteristics of the live monitoring information, and determining a corresponding error range according to the interference factors, wherein the interference factors are environmental factors influencing the size of the live monitoring information;
Calculating whether the information difference value II is in the error range or not, and if the information difference value II is not in the error range, determining that the live monitoring information is preliminary abnormal information;
Acquiring working condition characteristic parameters corresponding to the preliminary abnormal information, and acquiring historical information which is the same as the working condition characteristic parameters in a computer control module, wherein the historical abnormal information in the historical information is acquired;
Obtaining the history abnormal information corresponding to the preliminary abnormal information according to the discrete degree size mark, and obtaining an external factor mark attached to the history abnormal information, wherein the external factor mark is a corresponding mark of an external emergency in a corresponding time period of the history abnormal information;
and receiving an external factor mark corresponding to the preliminary abnormal information, analyzing whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same, deducing that the preliminary abnormal information is abnormal and outputting the preliminary abnormal information when the external factor marks of the preliminary abnormal information and the historical abnormal information are different.
2. An automatic driving-based vehicle operation information monitoring method according to claim 1, characterized in that: a discrete degree size marker comprising:
And if the information difference value II is not in the error range, analyzing an information difference value III between the information difference value II and the upper limit and the lower limit of the error range, and determining a corresponding discrete degree size mark according to the size level of the information difference value III.
3. An automatic driving-based vehicle operation information monitoring method according to claim 2, characterized in that: after the preliminary abnormality information is determined and output, the method further comprises the steps of:
And sorting the preliminary abnormal information to enable the preliminary abnormal information to be attached with corresponding external factor marks, and outputting the sorted preliminary abnormal information to the computer control module.
4. A method for monitoring vehicle operation information based on automatic driving according to claim 3, characterized in that: the method further comprises the steps of:
and if the external factor mark corresponding to the preliminary abnormal information is not received, deducing and outputting the preliminary abnormal information to be abnormal.
5. The method for monitoring vehicle operation information based on automatic driving according to claim 4, wherein after deducing and outputting the preliminary abnormality information abnormality, further comprising:
and obtaining a corresponding warning level according to the discrete degree size mark, obtaining set early warning information and a corresponding query terminal according to the warning level, and transmitting the early warning information to the query terminal.
6. A monitoring system for an autopilot-based method of monitoring vehicle operating information according to any one of claims 1-5, characterized in that: the system comprises:
The collecting module is used for collecting the real-time monitoring information of the computer control module and obtaining a comparison data set which is the same as the information type and the working condition characteristics of the real-time monitoring information, and the working condition characteristics comprise: the working state of the components related to the monitoring information, the environment temperature and humidity of the corresponding components and the like; the analysis module is used for analyzing the discrete degree in the comparison information set, comparing the live monitoring information with the discrete degree, and obtaining preliminary abnormal information in the live monitoring information according to a comparison result, wherein the preliminary abnormal information is attached with a discrete degree size mark;
The first acquisition module is used for acquiring working condition characteristic parameters corresponding to the preliminary abnormal information, acquiring historical information which is the same as the working condition characteristic parameters in the computer control module, and acquiring historical abnormal information in the historical information;
The second obtaining module is used for obtaining the historical abnormal information corresponding to the preliminary abnormal information according to the discrete degree size mark, and obtaining an external factor mark attached to the historical abnormal information, wherein the external factor mark is a corresponding mark of an external abnormal event in a corresponding time period of the historical abnormal information;
The judging module is used for receiving the external factor marks corresponding to the preliminary abnormal information, judging whether the external factor marks of the preliminary abnormal information and the historical abnormal information are the same, judging that the preliminary abnormal information is abnormal by different external factor marks of the preliminary abnormal information and the historical abnormal information, and outputting the preliminary abnormal information.
7. An autopilot-based automotive information monitoring system in accordance with claim 6 wherein: the system further comprises:
The first comparison module is used for comparing the live monitoring information with the information in the comparison information set to obtain an information difference value I;
The second comparison module is used for obtaining a standard deviation corresponding to the comparison information set, and comparing the first information difference with the standard deviation to obtain a second information difference;
The acquisition module III is used for acquiring interference factors on corresponding working condition characteristics of the live monitoring information and determining a corresponding error range according to the interference factors, wherein the interference factors are environmental factors influencing the size of the live monitoring information;
and the judging module II is used for judging whether the information difference value II is in the error range, and if the information difference value II is not in the error range, the live monitoring information is preliminary abnormal data.
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