CN115471927A - Intelligent vehicle test monitoring system and method and cloud platform - Google Patents

Abstract

According to the vehicle intelligent test monitoring system, the vehicle intelligent test monitoring method and the cloud platform, the brake performance in the vehicle performance test event is evaluated, the historical sample records bound by the first reference brake performance description and each first reference brake performance description in the vehicle performance test event are obtained, and a sample set to be used is set up by combining the first reference brake performance description and the historical sample records in each vehicle performance test event. The different vehicle performance evaluation threads have different evaluation rates and evaluation accuracies, and when the vehicle performance is evaluated, the accuracy of the brake performance evaluation and the evaluation rate are balanced by the adaptive vehicle performance evaluation threads according to the test subjects of the vehicle performance test events, so that the first reference brake performance description and the historical sample records can be efficiently and accurately obtained, and the sample set to be used can be efficiently and accurately set up to obtain the monitoring result in real time to ensure the vehicle test monitoring accuracy.

Description

Intelligent vehicle test monitoring system and method and cloud platform

Technical Field

The application relates to the technical field of vehicle intelligent test and data monitoring, in particular to a vehicle intelligent test monitoring system and method and a cloud platform.

Background

In the conventional technology, a lot of human resources are needed for testing vehicles, and in the process of testing by vehicle testers, the vehicle testers may be in a state of inaccurate testing due to poor attention or the reliability of the test results is affected due to poor mood of the vehicle testers.

At present, the artificial intelligence technology is more and more mature, the application field of the artificial intelligence technology is gradually wide, vehicle testing is included, the artificial intelligence can replace vehicle testing personnel to monitor the vehicle in real time, and therefore the artificial interference can be avoided as far as possible. However, in the process of real-time monitoring the vehicle through artificial intelligence, it is still difficult to ensure the accuracy of the vehicle intelligent test monitoring result to a certain extent.

Disclosure of Invention

In view of this, the application provides a vehicle intelligent test monitoring system, a vehicle intelligent test monitoring method and a cloud platform.

In a first aspect, a vehicle intelligent test monitoring method is provided, and is applied to a vehicle intelligent test monitoring cloud platform, and the method at least includes: obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises vehicle performance test events of not less than one test subject; determining a vehicle performance evaluation thread bound with each vehicle performance test event according to the test theme of each vehicle performance test event, wherein the vehicle performance evaluation threads with differences have different evaluation rates and different evaluation accuracies; evaluating the brake performance in the vehicle performance test event by combining with the vehicle performance evaluation thread bound to each vehicle performance test event to obtain historical sample records and first reference brake performance descriptions in the vehicle performance test event, wherein each historical sample record and each first reference brake performance description have a correlation condition; and combining the first reference brake performance description and the historical sample record in each vehicle performance test event to build a sample set to be used.

In an independently implemented embodiment, the determining the vehicle performance evaluation thread bound to the vehicle performance test event in combination with the test subject of each vehicle performance test event comprises: and on the basis that the vehicle performance test event is test data, determining that the vehicle performance evaluation threads bound by the vehicle performance test event comprise a first evaluation thread.

In an independently implemented embodiment, the determining the vehicle performance test event bound vehicle performance evaluation thread based on the vehicle performance test event being test data comprises a first evaluation thread comprising: on the basis that the vehicle performance test event is test data, determining that vehicle performance evaluation threads bound by the vehicle performance test event comprise a first evaluation thread and a second evaluation thread; wherein the evaluation rate of the first evaluation thread is greater than the evaluation rate of the second evaluation thread, and the accuracy of the first evaluation thread in evaluating the braking performance is less than the accuracy of the second evaluation thread in evaluating the braking performance.

In an independently implemented embodiment, the step of evaluating the brake performance of the vehicle performance test events by the vehicle performance evaluation thread bound with each vehicle performance test event to obtain a historical sample record and a first reference brake performance description of the vehicle performance test events comprises: on the basis that the vehicle performance test event is test data, the brake performance in the test data is evaluated in combination with the first evaluation thread to obtain a first reference brake performance description record bound with the test data, wherein the first reference brake performance description record covers the first reference brake performance description of the brake performance in the test data; for each first reference brake performance description in the brake performance description record, loading the test data into a historical sample record of the first reference brake performance description binding.

In an embodiment of an independent implementation, the evaluating, in combination with the first evaluation thread, the brake performance in the test data to obtain a first reference brake performance profile bound to the test data includes: evaluating the brake performance in the test data by using the first evaluation thread to obtain a first reference brake performance description record bound with the test data; and on the basis that the first reference brake performance description record is abnormal, evaluating the brake performance in the test data by using the second evaluation thread to obtain the first reference brake performance description record bound with the test data.

In an independently implemented embodiment, the determining the vehicle performance evaluation thread bound to the vehicle performance test event in combination with the test subject of each vehicle performance test event comprises: and on the basis that the vehicle performance test event is the test data set, determining that the vehicle performance evaluation threads comprise a third evaluation thread, wherein the evaluation rate of the third evaluation thread is smaller than that of the first evaluation thread and larger than that of the second evaluation thread, and the accuracy of the third evaluation thread in brake performance evaluation is larger than that of the first evaluation thread and smaller than that of the second evaluation thread in brake performance evaluation.

In an independently implemented embodiment, the step of evaluating the brake performance of the vehicle performance test events by the vehicle performance evaluation thread bound with each vehicle performance test event to obtain a historical sample record and a first reference brake performance description of the vehicle performance test events comprises: on the basis that the vehicle performance test event is a test data set, the brake performance in the test data set is evaluated by using the third evaluation thread to obtain a vehicle test data set keyword record of the test data set; determining the matching condition between the brake performance description in the test data set and the keywords in the vehicle test data set by combining the keyword records in the vehicle test data set; and determining a first reference brake performance description and a historical sample record in the test data set according to the matching condition.

In a separately implemented embodiment, the determining a match between the brake performance description in the test data set and the vehicle test data set keyword in conjunction with the vehicle test data set keyword record includes: for each vehicle test data set keyword in the vehicle test data set keyword record, determining the brake performance description bound by the vehicle test data set keyword; and loading the association condition between the brake performance description and the vehicle test data set key word to the matching condition bound by the test data set.

In an independently implemented embodiment, the evaluating the braking performance in the test data set by using the third evaluation thread to obtain a vehicle test data set keyword record of the test data set includes: and utilizing the third evaluation thread to carry out specific vehicle performance evaluation on the test data set to obtain the vehicle test data set keyword records of the test data set.

In an independently implemented embodiment, the determining the keyword bound brake performance description of the vehicle test data set comprises: performing key description mining on each brake performance evaluated in the vehicle test data set keywords to obtain a brake performance description bound to each brake performance; determining a braking performance description result of the braking performance description; determining a second reference brake performance description in the keywords of the vehicle test data set according to each brake performance description result; and determining the second reference brake performance description as the brake performance description bound by the keyword of the vehicle test data set.

In an independently implemented embodiment, said determining a first reference brake performance description and a historical sample record in said test data set based on said matching comprises: performing discrimination function processing on the brake performance description in the matching condition to obtain a first discrimination result; for each discrimination attribute in the first discrimination result, determining a first reference brake performance description for the discrimination attribute; obtaining a historical sample bound by each brake performance description in the discriminant attribute by combining the matching condition; loading the historical sample of each brake performance description binding to the historical sample record of the first reference brake performance description binding.

In an independently implemented embodiment, the building a sample set to be used in combination with the first reference brake performance description and the historical sample record in each vehicle performance test event includes: loading each first reference brake performance description in each vehicle performance test event to a description cluster to be distinguished; carrying out discrimination function processing on the brake performance description in the description cluster to be discriminated to obtain a second discrimination result; for each discrimination attribute in the second discrimination result, determining a third reference brake performance description for the discrimination attribute; for each brake performance description in the distinguishing attribute, loading a historical sample in the historical sample record bound by each brake performance description into the historical sample record bound by the third reference brake performance description; updating each third reference brake performance description and the historical sample record bound by the third reference brake performance description to the sample set to be used.

In a second aspect, a vehicle intelligent test monitoring system is provided, which includes: the intelligent vehicle testing and monitoring cloud platform is in communication connection with the vehicle; wherein, vehicle intelligent test control cloud platform for: obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises vehicle performance test events of not less than one test subject; determining vehicle performance evaluation threads bound to the vehicle performance test events according to the test subjects of each vehicle performance test event, wherein the different vehicle performance evaluation threads have different evaluation rates and different evaluation accuracies; evaluating the brake performance in the vehicle performance test events by combining with the vehicle performance evaluation thread bound to each vehicle performance test event to obtain historical sample records and first reference brake performance descriptions in the vehicle performance test events, wherein each historical sample record and each first reference brake performance description have a correlation condition; and combining the first reference brake performance description and the historical sample record in each vehicle performance test event to build a sample set to be used.

In a third aspect, a vehicle intelligent test monitoring cloud platform is provided, which includes: a memory for storing a computer program; a processor coupled to the memory for executing the computer program stored by the memory to implement the above-described method.

According to the vehicle intelligent test monitoring system, the vehicle intelligent test monitoring method and the cloud platform, the brake performance in the vehicle performance test events is evaluated by combining each vehicle performance test event in the vehicle performance test event records to be identified with the vehicle performance evaluation thread determined by the test subject of the vehicle performance test events, the historical sample records bound by the first reference brake performance description and each first reference brake performance description in the vehicle performance test events are obtained, and the sample set to be used is set up by combining the first reference brake performance description and the historical sample records in each vehicle performance test event. Therefore, the different vehicle performance evaluation threads have different evaluation rates and evaluation accuracies, so that the accuracy and the evaluation rate of brake performance evaluation can be balanced by the adaptive vehicle performance evaluation threads according to the test subjects of the vehicle performance test events during vehicle performance evaluation, a first reference brake performance description and a historical sample record can be efficiently and accurately obtained, a sample set to be used can be efficiently and accurately constructed, and the searching accuracy during searching of historical samples in the constructed sample set to be used is improved, so that the vehicle intelligent test monitoring results can be rapidly and accurately obtained from a large amount of relevant information, and the accuracy of the vehicle intelligent test monitoring results is guaranteed.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a flowchart of a vehicle intelligent test monitoring method according to an embodiment of the present disclosure.

Fig. 2 is a block diagram of an intelligent vehicle test monitoring device according to an embodiment of the present disclosure.

Fig. 3 is a schematic diagram of a hardware structure of a vehicle intelligent test monitoring cloud platform provided in an embodiment of the present application.

Detailed Description

In order to better understand the technical solutions, the technical solutions of the present application are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.

Referring to fig. 1, a method for monitoring a vehicle intelligent test is shown, which may include the technical solutions described in the following steps 101 to 104.

step101, obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises not less than one vehicle performance test event with a test subject.

For example, the vehicle performance test event to be identified is recorded as a vehicle performance test event or a vehicle performance test event that needs to be subjected to a data profiling process.

The test subjects may include test data, a test data set, and the like, and specifically, the test subjects of the vehicle performance test events included in the vehicle performance test event record may be determined according to actual operating conditions, which is not further limited again.

step102, combining the test subjects of each vehicle performance test event, and determining vehicle performance evaluation threads bound by the vehicle performance test events, wherein the vehicle performance evaluation threads with differences have different evaluation rates and different evaluation accuracies.

For example, the vehicle performance evaluation thread may include at least one of a vehicle performance evaluation thread in conjunction with a brake performance description point, a vehicle performance evaluation thread in conjunction with a global brake performance set, a vehicle performance evaluation thread in conjunction with a CNN thread, and the like, and when the brake performance in the vehicle performance test event is evaluated by using the vehicle performance evaluation thread having a difference, there is a difference in the evaluation rate and the accuracy of the brake performance evaluation.

The vehicle performance evaluation thread bound to the vehicle performance test event is a brake data processing thread for evaluating the brake performance in the vehicle performance test event, and the vehicle performance evaluation thread bound to the vehicle performance test event can be determined according to the test subject of the vehicle performance test event. For example, for a vehicle performance test event of a test data category and a vehicle performance test event of a test data set category, there may be a vehicle performance evaluation thread bound to each other. In the specific implementation process, the vehicle performance evaluation thread bound by the test subjects with differences can be determined according to the actual operation conditions, and no further limitation is made again.

step103, combining the vehicle performance evaluation threads bound to each vehicle performance test event, evaluating the brake performance in the vehicle performance test event to obtain a history sample record and a first reference brake performance description in the vehicle performance test event, wherein each history sample record and each first reference brake performance description have a correlation condition.

For example, the historical sample in the historical sample record may be a vehicle reference sample covering the reference braking performance associated with the first reference braking performance description bound to the historical sample record, and may include, but is not limited to, at least one of test data covering the reference braking performance, a test data set keyword covering the reference braking performance, and the like. The first reference brake performance description may represent the reference brake performance covered by each historical sample in the historical sample record.

For example, when the vehicle performance test event is test data, the vehicle performance evaluation may be performed on the test data by using a vehicle performance evaluation thread bound to the test data set, so as to obtain the reference brake performance contained in the test data and the brake performance description bound to each reference brake performance. Since each brake performance description corresponds to a reference brake performance covered in the test data, i.e. each brake performance description is used to characterize a reference brake performance in the test data, each brake performance description in the test data may be determined as a first reference brake performance description in the test data, which is understood as a historical sample loaded into the historical sample record bound to each first reference brake performance description.

For another example, when the vehicle performance test event is a test data set, the vehicle performance evaluation may be performed on the test data set through a vehicle performance evaluation thread bound to the test data set, so as to obtain the reference braking performance covered in the test data set, the braking performance description bound to each reference braking performance, and the test data set keywords covering the reference braking performance. Since each brake performance description corresponds to one of the reference brake performances covered in the test data set, that is, each brake performance description is used for representing one of the reference brake performances in the test data set, each brake performance description in the test data set can be determined as a first reference brake performance description in the test data set, and for each first reference brake performance description, each test data set keyword that covers the reference brake performance represented by the brake performance description in the test data set is used as a history sample and loaded into the history sample record bound by each first reference brake performance description.

step104, combining the first reference brake performance description and the historical sample record in each vehicle performance test event, and building a sample set to be used.

For example, the set of samples to be used may be used to store brake performance descriptions and historical sample records bound to each brake performance description. According to the brake performance description, the corresponding historical sample records can be searched in the sample set to be used.

The vehicle intelligent test monitoring method provided by the embodiment of the disclosure evaluates the brake performance in the vehicle performance test event by combining each vehicle performance test event in the vehicle performance test event record to be identified with the vehicle performance evaluation thread determined by the test subject of the vehicle performance test event to obtain the historical sample record bound by the first reference brake performance description and each first reference brake performance description in the vehicle performance test event, and builds the sample set to be used by combining the first reference brake performance description and the historical sample record in each vehicle performance test event. In this way, the vehicle performance evaluation threads with the differences have the different evaluation rates and the different evaluation accuracies, so that the accuracy and the evaluation rate of the brake performance evaluation can be balanced by the adaptive vehicle performance evaluation threads according to the test subjects of the vehicle performance test events during the vehicle performance evaluation, the first reference brake performance description and the historical sample records can be efficiently and accurately obtained, and the sample set to be used can be efficiently and accurately constructed. Furthermore, the searching precision when the built samples to be used are searched for historical samples in a centralized mode can be improved, and therefore the intelligent vehicle test monitoring result can be obtained quickly and accurately from a large amount of relevant information.

The embodiment of the disclosure provides an intelligent vehicle test monitoring method, which comprises the following steps.

step201, obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises vehicle performance test events with not less than one test subject.

Step201 corresponds to step101, and in the implementation process, reference may be made to the implementation steps of step 101.

step202, determining a vehicle performance evaluation thread bound with the vehicle performance test events by combining the test subjects of each vehicle performance test event; the vehicle performance evaluation threads bound by the vehicle performance test events are determined to comprise a first evaluation thread on the basis that the vehicle performance test events are the test data.

For example, the first evaluation thread may be a vehicle performance evaluation thread that is randomly appropriate for the test data, a vehicle performance evaluation thread that includes a CNN thread, a vehicle performance evaluation thread, and the like.

In an alternative embodiment, the first evaluation thread may be a vehicle performance evaluation thread with low difficulty, high performance, but low accuracy of brake performance evaluation, which has a high demand for brake performance in the test data to be evaluated, but at a high evaluation rate.

In an alternative embodiment, the first evaluation thread has a higher difficulty level, but a lower working efficiency, but a higher accuracy of the brake performance evaluation, and has a higher demand for the brake performance in the test data to be evaluated, but at a higher evaluation rate.

step203, combining the vehicle performance evaluation threads bound to each vehicle performance test event, evaluating the brake performance in the vehicle performance test event to obtain a history sample record and a first reference brake performance description in the vehicle performance test event, wherein each history sample record and each first reference brake performance description have a correlation condition.

step204, combining the first reference brake performance description and the historical sample record in each vehicle performance test event, and building a sample set to be used.

Illustratively, step203 and step204 correspond to step103 and step104, and in the implementation process, reference may be made to the implementation steps of step103 and step 104.

In an alternative embodiment, step202 may comprise: on the basis that the vehicle performance test event is test data, determining that vehicle performance evaluation threads bound to the vehicle performance test event comprise a first evaluation thread and a second evaluation thread; wherein the evaluation rate of the first evaluation thread is greater than the evaluation rate of the second evaluation thread, and the accuracy of the first evaluation thread in evaluating the braking performance is less than the accuracy of the second evaluation thread in evaluating the braking performance.

Illustratively, the second evaluation thread has a lower evaluation rate than the first evaluation thread, but the second evaluation thread evaluates the braking performance more accurately than the first evaluation thread. In a specific implementation, the first evaluation thread and the second evaluation thread may be adapted vehicle performance evaluation threads that randomly meet the accuracy requirements of the evaluation rate and the brake performance evaluation, and the adapted first evaluation thread and second evaluation thread are determined according to the actual operating conditions, and are not further limited again.

In an alternative embodiment, step203 may specifically include the following steps.

step2031, on the basis that the vehicle performance test event is test data, and in combination with the first evaluation thread, the brake performance in the test data is evaluated to obtain a first reference brake performance description record bound with the test data, wherein the first reference brake performance description record covers the first reference brake performance description of the brake performance in the test data.

For example, the first reference brake performance profile of the test data binding covers the first reference brake performance profile of each brake performance in the test data. And evaluating the brake performance in the test data by combining the first evaluation thread, so that the brake performance covered in the test data and the brake performance description bound to each brake performance can be obtained.

step2032, for each first reference brake performance description in the brake performance description records, loading the test data to historical sample records of the first reference brake performance description binding.

For example, each brake performance description in the test data may be determined as a first reference brake performance description in the test data, and the test data may be loaded as a history sample into a history sample record bound to each first reference brake performance description, since each brake performance description corresponds to one brake performance covered in the test data, that is, each brake performance description may characterize one brake performance in the test data.

In an alternative embodiment, the content described in step2031 may specifically include the following steps.

step2031a, utilizing the first evaluation thread to evaluate the brake performance in the test data, and obtaining a first reference brake performance description record bound with the test data.

step2031b, on the basis that the first reference brake performance description record is abnormal, utilizing the second evaluation thread to evaluate the brake performance in the test data, and obtaining the first reference brake performance description record bound by the test data.

Illustratively, when the first reference brake performance profile is not present, it indicates that no brake performance was evaluated on the test data using the first evaluation thread. Compared with the first evaluation thread, the difficulty degree of the second evaluation thread is high, the accuracy of brake performance evaluation is high, when the brake performance is not evaluated by the first evaluation thread, and the brake performance missed by the first evaluation thread can be evaluated when the brake performance in the test data is evaluated by the second evaluation thread, so that the accuracy of brake performance evaluation can be ensured.

The vehicle intelligent test monitoring method provided by the embodiment of the disclosure evaluates the brake performance in the test data by using the first evaluation thread to obtain the brake performance description in the test data, so that the evaluation speed and the evaluation precision when the vehicle performance evaluation is performed on the test data can be effectively ensured, the reliability of the test data in the history sample record bound with the first reference brake performance description in the to-be-used sample set is improved, and the completeness of searching the test data through the brake performance description in the to-be-used sample set is further improved. In addition, when the brake performance in the test data is evaluated by using the first evaluation thread, and when the evaluated first reference brake performance description record does not exist, the brake performance in the test data can be evaluated again by using the second evaluation thread with the accuracy of the brake performance higher than that of the first evaluation thread, so that the evaluation rate of the first evaluation thread is high, the accuracy of the brake performance evaluated by the second evaluation thread is high, and the brake performance missed by the first evaluation thread can be evaluated, therefore, the evaluation rate and the accuracy of the brake performance evaluated can be better balanced when the vehicle performance evaluation is performed on the test data, so that the precision of the test data in the historical sample record bound with the first reference brake performance description in the to-be-used sample set and the rate of building the to-be-used sample set are further improved, and the integrity of searching the test data through the brake performance description in the to-be-used sample set can be further improved.

The embodiment of the disclosure provides a vehicle intelligent test monitoring method, which comprises the following steps.

step301, obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises not less than one vehicle performance test event with a test subject.

Illustratively, step301 corresponds to step101, and in the implementation process, reference may be made to the implementation steps of step 101.

step302, determining a vehicle performance evaluation thread bound with the vehicle performance test events by combining the test subjects of each vehicle performance test event; and on the basis that the vehicle performance test event is the test data set, determining that the vehicle performance evaluation threads comprise a third evaluation thread, wherein the evaluation rate of the third evaluation thread is smaller than the evaluation rate of the first evaluation thread and larger than the evaluation rate of the second evaluation thread, and the accuracy of the third evaluation thread in evaluating the braking performance is larger than the accuracy of the first evaluation thread in evaluating the braking performance and smaller than the accuracy of the second evaluation thread in evaluating the braking performance.

For example, since the braking performance in the test data set is not generally in a particularly perfect state, and the test data set includes several test dimensions, the evaluation of the braking performance in the test data set requires evaluation of all the several test dimensions, and therefore, the vehicle performance evaluation thread used for evaluating the braking performance in the test data set requires high accuracy and high evaluation rate for evaluating the braking performance. Therefore, the third evaluation thread needs to meet: the evaluation rate is less than the evaluation rate of the first evaluation thread and greater than the evaluation rate of the second evaluation thread, and the accuracy of the brake performance is evaluated more than the accuracy of the brake performance evaluated by the first evaluation thread and less than the accuracy of the brake performance evaluated by the second evaluation thread.

The first evaluation thread may be a vehicle performance evaluation thread having low difficulty and high workability, but low accuracy of brake performance evaluation, and having a high demand on brake performance in the test data to be evaluated. The second evaluation thread is a vehicle performance evaluation thread with high difficulty, low working efficiency and high brake performance evaluation accuracy, and has high requirement on the brake performance in the test data to be evaluated.

step303, combining the vehicle performance evaluation threads bound to each vehicle performance test event, evaluating the brake performance in the vehicle performance test event to obtain a history sample record and a first reference brake performance description in the vehicle performance test event, wherein an association condition exists between each history sample record and each first reference brake performance description.

step304, combining the first reference brake performance description and the historical sample record in each vehicle performance test event, and building a sample set to be used.

For example, step303 and step304 correspond to step103 and step104, and in the implementation process, reference may be made to the implementation steps of step103 and step 104.

In an alternative embodiment, the content described in step303 may specifically include the following steps.

step3031, on the basis that the vehicle performance test event is a test data set, utilizing the third evaluation thread to evaluate the brake performance in the test data set, and obtaining the vehicle test data set keyword record of the test data set.

Illustratively, each vehicle test data set keyword in the test data set is included in the vehicle test data set keyword record. The vehicle test data set key words are test data set key words bound by referring to vehicles in the test data set. In a specific implementation process, the key word information of the reference vehicle in the test data set can be marked by combining a brake performance detection technology, and according to the marked key word information, the vehicle test data set key word bound with the reference vehicle in the test data set can be determined, and the adaptive brake performance recording mode can be screened according to the actual operation condition to record the brake performance in the test data set, so that the vehicle test data set key word record is obtained.

In an alternative embodiment, a third evaluation thread may be utilized to perform a vehicle-specific performance evaluation on the test data set, resulting in vehicle test data set keyword records for the test data set. For example, the brake performance descriptions in the test data set may be specifically extracted through the third evaluation thread, the brake performance records may be realized by specifically comparing the brake performance descriptions in each group, and the test data set keyword bound to each vehicle in the test data set may be determined according to the result of the brake performance record, so as to obtain the vehicle test data set keyword record of the test data set. In an alternative embodiment, the vehicle performance evaluation may be performed on a number of test data sets according to a number of specific criteria, to obtain the vehicle test data set keyword records of the test data sets.

In an alternative embodiment, keywords may be tested for each particular vehicle when multiple instances of the same keyword occur in the test data set.

step3032, combining the vehicle test data set keyword record to determine the matching condition between the brake performance description in the test data set and the vehicle test data set keyword.

Illustratively, each vehicle test data set keyword in the vehicle test data set keyword record corresponds to a reference vehicle. The matching condition between the brake performance description and the vehicle test data set keyword is the matching condition between the vehicle test data set keyword and the brake performance description of the reference vehicle which represents the binding of the vehicle test data set keyword. In a specific implementation process, according to the brake performance description of the reference vehicle in each group of the vehicle test data set keywords, the brake performance description which can represent the reference vehicle is determined, and then the matching condition between the brake performance description and the vehicle test data set keywords can be determined.

step3033, determining a first reference brake performance description and a historical sample record in the test data set according to the matching condition.

For example, the history sample record in the test data set includes a vehicle test data set keyword corresponding to the same reference vehicle in the test data set, and the reference vehicle and the history sample record may also be bound. The first reference brake performance description may represent a brake performance description of a reference vehicle to which the history sample record is bound.

In a specific implementation process, if the brake performance descriptions bound to the keywords of each vehicle test data set in the history sample record are consistent, the brake performance description may be determined as a first reference brake performance description bound to the history sample record. If the brake performance descriptions bound to the keywords of the vehicle test data sets in the history sample records are different, the brake performance description of the reference vehicle can be determined according to the brake performance description bound to the keywords of the vehicle test data sets, and the brake performance description is used as a first reference brake performance description bound to the history sample records. The first reference brake performance description bound to the historical sample record may be determined in a manner that screens adaptations to actual operating conditions, again without further limitation.

In an alternative embodiment, the content described in step3032 may specifically include the following steps.

step3032a, determining the brake performance description bound by the vehicle test data set keywords for each vehicle test data set keyword in the vehicle test data set keyword records.

For example, the brake performance description bound by the vehicle test data set keyword may be determined according to the brake performance description of the reference vehicle in each group of the vehicle test data set keyword. In a specific implementation process, the brake performance description bound by the vehicle test data set keyword may be one of the brake performance descriptions of the reference vehicle in each group of the vehicle test data set keyword, or may be a first brake performance description generated by combining the brake performance descriptions of the reference vehicle in each group, which is not further limited again.

step3032b, loading the association condition between the brake performance description and the vehicle test data set key word to the matching condition bound by the test data set.

In an alternative embodiment, what is described in step3032a above may specifically include the following: performing key description mining on each braking performance evaluated in the vehicle test data set keywords to obtain a braking performance description bound to each braking performance; determining a braking performance description result of the braking performance description; determining a second reference brake performance description in the vehicle test data set keyword according to each brake performance description result; and determining the second reference brake performance description as the brake performance description bound by the keyword of the vehicle test data set.

For example, the braking performance description result may be calculated by at least one of a braking distance of the braking performance, a friction coefficient of the braking performance, an automatic reliability of the braking performance, an accuracy of vehicle performance evaluation, and the like. And determining a second reference brake performance description according to the brake performance description result, so that the non-brake performance description in the keywords of the vehicle test data set can be eliminated, the possibility of building the non-brake performance reference into the brake performance reference is weakened, and the possibility of occurrence of brake performance association abnormity when the to-be-used sample set is searched according to the brake performance description is weakened. The second reference brake performance description may be the brake performance description that best results from the brake performance descriptions evaluated in the vehicle test data set keywords. In a specific implementation, the statistical manner of the brake performance description result may be determined according to the actual operation condition, and the manner of determining the second reference brake performance description according to the brake performance description result may be determined, again without further limitation.

In an alternative embodiment, the content described in step3033 may specifically include the following steps.

step3033a, performing discriminant function processing on the brake performance description in the matching situation to obtain a first discriminant result.

For example, by performing discriminant function processing on the brake performance descriptions in the matching case, a plurality of vehicle test data set keywords displayed in the test data set by the same reference vehicle can be extracted. In a specific implementation process, the brake performance description may be subjected to discriminant function processing by using randomly adapted AI intelligence.

step3033b, for each discriminant attribute in the first discriminant result, determining a first reference brake performance description for the discriminant attribute.

For example, the first reference brake performance description may represent the brake performance description of the distinguishing attribute, may be a brake performance description bound to a distinguishing center of the distinguishing attribute, and may also be a brake performance description with the best splice in the distinguishing attribute. In a specific implementation, the adapted first reference brake performance description may be determined according to actual operating conditions, again without further limitation.

step3033c, combining the matching condition to obtain a historical sample of each brake performance description binding in the discriminant attribute.

step3033d, loading the historical sample of each brake performance description binding to the historical sample record of the first reference brake performance description binding.

The vehicle intelligent test monitoring method provided by the embodiment of the disclosure evaluates the brake performance in the test data set by using the third evaluation thread to obtain the brake performance description in the test data set, so that the accuracy of the brake performance evaluation of the third evaluation thread is higher than that of the first evaluation thread and the evaluation rate is higher than that of the second evaluation thread, so that the evaluation rate and the evaluation precision of the vehicle performance evaluation of the test data set can be effectively ensured, the reliability of the test data set keywords in the historical sample record bound with the first reference brake performance description in the to-be-used sample set can be improved, and the reliability of the search of the test data set keywords through the brake performance description in the to-be-used sample set can be improved.

In addition, a third evaluation thread may be utilized to perform a vehicle-specific performance evaluation on the test data set to obtain a vehicle test data set keyword record of the test data set. In this way, brake performance records are made using a particular brake performance description-by-brake performance description comparison. Furthermore, the vehicle performance evaluation can be specifically carried out on a plurality of test data sets in a large batch, so that the vehicle performance evaluation speed of the test data sets can be effectively improved.

The embodiment of the disclosure provides a vehicle intelligent test monitoring method, and the content described in the method specifically comprises the following steps.

step401, obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises not less than one vehicle performance test event with a test subject.

step402, determining a vehicle performance evaluation thread bound with the vehicle performance test events by combining the test subjects of each vehicle performance test event; wherein the vehicle performance evaluation threads with differences have different evaluation rates and evaluation accuracies.

step403, combining the vehicle performance evaluation threads bound to each vehicle performance test event, evaluating the brake performance in the vehicle performance test event to obtain a history sample record and a first reference brake performance description in the vehicle performance test event, where there is an association between each history sample record and each first reference brake performance description.

For example, step401 to step403 correspond to step101 to step103, and in the implementation process, the specific implementation steps of step101 to step103 may be referred to.

step404, loading each first reference brake performance description in each vehicle performance test event to a description cluster to be discriminated.

And step405, performing discriminant function processing on the brake performance description in the description cluster to be discriminated to obtain a second discrimination result.

step406, for each discrimination attribute in the second discrimination result, a third reference brake performance description of the discrimination attribute is determined.

For example, the third reference brake performance description may represent a brake performance description of the discriminant attribute, and may be a brake performance description of a discriminant focus binding of the discriminant attribute. In a specific implementation, the adapted third reference brake performance description may be determined according to actual operating conditions, and is not further limited again.

step407, for each brake performance description in the discriminant attribute, loading a historical sample in the historical sample record bound by each brake performance description into a historical sample record bound by a third reference brake performance description.

step408, updating the historical sample record of each third reference brake performance description and the binding of the third reference brake performance description to the sample set to be used.

According to the vehicle intelligent test monitoring method provided by the embodiment of the disclosure, the discriminant function processing is performed on each first reference brake performance description in each vehicle performance test event, so that historical samples corresponding to the same reference vehicle in the vehicle performance test events with differences can be clustered into one historical sample record, and the association condition between the clustered historical sample record and the third reference brake performance description is built. In this way, the number of the built braking performance descriptions in the to-be-used sample set can be weakened, so that the searching speed of the braking performance descriptions in searching the historical samples in the to-be-used sample set can be increased, and the accuracy and the integrity of the braking performance description data can be improved.

In this embodiment, the method may include the following.

step501, obtaining the search data of the vehicle to be searched.

step502, combining the searched data, obtains the brake performance description of the vehicle to be searched.

For example, since the search data can extract the vehicle to be searched, in combination with the search data, the brake performance description of the vehicle to be searched can be obtained.

step503, searching the brake performance description in a sample set to be used which is set up in advance to obtain a search result, wherein the sample set to be used is set up in advance by using the vehicle intelligent test monitoring method provided by the embodiment of the disclosure.

For example, the search result includes a history sample related to the vehicle to be searched, and may include, but is not limited to, at least one of test data covering the vehicle to be searched, a keyword of the test data set, and the like. In a specific implementation process, the braking performance description may be searched by using a randomly adapted search method supported by the sample set to be used, and is not further limited again.

In an alternative embodiment, step502 may comprise: and on the basis that the search data is the brake performance data, carrying out key description mining on the brake performance data to obtain the brake performance description of the vehicle to be searched. For example, the brake performance data may be subjected to key description mining by using a randomly adapted key description mining thread, which is not further limited again.

In an alternative embodiment, step502 may comprise: and on the basis that the search data is a brake performance label, searching a previously established brake performance description set according to the brake performance label to obtain the brake performance description bound to the vehicle to be searched. Illustratively, the brake performance label is a label in a brake performance description set previously built by the vehicle to be searched. In an alternative embodiment, the brake performance label may also be a label for a brake performance description centralized brake performance description.

On the basis, please refer to fig. 2 in combination, an intelligent testing and monitoring device 200 for a vehicle is provided, which is applied to an intelligent testing and monitoring system for a vehicle, and the device includes:

an evaluation thread determining module 210, configured to obtain a vehicle performance test event record to be identified; the vehicle performance test event record comprises vehicle performance test events of not less than one test subject; determining vehicle performance evaluation threads bound to the vehicle performance test events according to the test subjects of each vehicle performance test event, wherein the different vehicle performance evaluation threads have different evaluation rates and different evaluation accuracies;

the sample record building module 220 is configured to evaluate the brake performance in the vehicle performance test event in combination with the vehicle performance evaluation thread bound to each vehicle performance test event to obtain a historical sample record and a first reference brake performance description in the vehicle performance test event, where each historical sample record and each first reference brake performance description have a correlation therebetween; and combining the first reference brake performance description and the historical sample record in each vehicle performance test event to build a sample set to be used.

The method provided by the embodiment of the application can be executed in a vehicle intelligent test monitoring cloud platform, computer equipment or a similar computing device. By taking the operation on the vehicle intelligent test monitoring cloud platform as an example, fig. 3 is a hardware structure block diagram of the vehicle intelligent test monitoring cloud platform implementing the beidou signal capturing method in the weak signal environment according to the embodiment of the application. As shown in fig. 3, the vehicle intelligent test monitoring cloud platform 300 may include one or more (only one shown in fig. 3) processors 310 (the processors 310 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 320 for storing data. It can be understood by those skilled in the art that the structure shown in fig. 3 is only an illustration, and does not limit the structure of the above-mentioned vehicle intelligent test monitoring cloud platform. For example, vehicle smart test monitoring cloud platform 300 may also include more or fewer components than shown in FIG. 3, or have a different configuration than shown in FIG. 3.

The memory 320 may be configured to store a computer program, for example, a software program and a module of application software, such as a computer program corresponding to the beidou signal capturing method in a weak signal environment in the embodiment of the present application, and the processor 310 executes various functional applications and data processing by running the computer program stored in the memory 320, so as to implement the foregoing method. The memory 320 may include high speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 320 may further include memory remotely located from processor 310, which may be connected to vehicle intelligent test monitoring cloud platform 300 over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

On the basis, the vehicle intelligent test monitoring system is further provided, and comprises: the intelligent vehicle testing and monitoring cloud platform is in communication connection with the vehicle;

wherein, vehicle intelligent test control cloud platform for: obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises vehicle performance test events of not less than one test subject; determining a vehicle performance evaluation thread bound with each vehicle performance test event according to the test theme of each vehicle performance test event, wherein the vehicle performance evaluation threads with differences have different evaluation rates and different evaluation accuracies; evaluating the brake performance in the vehicle performance test event by combining with the vehicle performance evaluation thread bound to each vehicle performance test event to obtain historical sample records and first reference brake performance descriptions in the vehicle performance test event, wherein each historical sample record and each first reference brake performance description have a correlation condition; and combining the first reference brake performance description and the historical sample record in each vehicle performance test event to build a sample set to be used.

On the basis of the above, there is also provided a computer-readable storage medium on which a computer program is stored, which when executed implements the above-described method.

In summary, based on the above scheme, the brake performance in the vehicle performance test event is evaluated in combination with the vehicle performance evaluation thread determined by the test theme of the vehicle performance test event for each vehicle performance test event in the vehicle performance test event record to be identified, so as to obtain a historical sample record bound by the first reference brake performance description and each first reference brake performance description in the vehicle performance test event, and a sample set to be used is constructed in combination with the first reference brake performance description and the historical sample record in each vehicle performance test event. In this way, the vehicle performance evaluation threads with the differences have the different evaluation rates and the different evaluation accuracies, so that the accuracy and the evaluation rate of the brake performance evaluation can be balanced by the adaptive vehicle performance evaluation threads according to the test subjects of the vehicle performance test events during the vehicle performance evaluation, the first reference brake performance description and the historical sample records can be efficiently and accurately obtained, and the sample set to be used can be efficiently and accurately constructed. Furthermore, the searching precision of the built samples to be used for searching the historical samples in a centralized manner can be improved, so that the intelligent vehicle test monitoring result can be quickly and accurately obtained from a large amount of relevant information.

It should be appreciated that the system and its modules shown above may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, for example such code provided on a carrier medium such as a diskette, CD-or DVD-ROM, programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of the present application may be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, for example, or by a combination of the above hardware circuits and software (e.g., firmware).

It is to be noted that different embodiments may produce different advantages, and in different embodiments, any one or combination of the above advantages may be produced, or any other advantages may be obtained.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered as illustrative only and not limiting of the application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, though not expressly described herein. Such alterations, modifications, and improvements are intended to be suggested herein and are intended to be within the spirit and scope of the exemplary embodiments of this application.

Also, this application uses specific language to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, certain features, structures, or characteristics may be combined as suitable in one or more embodiments of the application.

Moreover, those skilled in the art will appreciate that aspects of the present application may be illustrated and described in terms of several patentable species or situations, including any new and useful combination of processes, machines, manufacture, or materials, or any new and useful improvement thereon. Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

The computer storage medium may comprise a propagated data signal with the computer program code embodied therewith, for example, on baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, etc., or any suitable combination. A computer storage medium may be any computer-readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code on a computer storage medium may be propagated over any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for operation of various portions of the present application may be written in any one or more programming languages, including an object oriented programming language such as Java, scala, smalltalk, eiffel, JADE, emerald, C + +, C #, VB.NET, python, and the like, a conventional programming language such as C, visual Basic, fortran 2003, perl, COBOL 2002, PHP, ABAP, a dynamic programming language such as Python, ruby, and Groovy, or other programming languages, and the like. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order in which elements and sequences of the processes described herein are processed, the use of alphanumeric characters, or the use of other designations, is not intended to limit the order of the processes and methods described herein, unless explicitly claimed. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the numbers allow for variation in flexibility. Accordingly, in some embodiments, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit-preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

Each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, and the like, cited in this application is hereby incorporated by reference in its entirety. Except where the application is filed in a manner inconsistent or contrary to the present disclosure, and except where the claim is filed in its broadest scope (whether present or later appended to the application) as well. It is noted that the descriptions, definitions and/or use of terms in this application shall control if they are inconsistent or contrary to the statements and/or uses of the present application in the material attached to this application.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present application. Other variations are also possible within the scope of the present application. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the present application can be viewed as being consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to only those embodiments explicitly described and depicted herein.

The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art to which the present application pertains. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of the present application shall be included in the scope of the claims of the present application.

Claims (10)

1. The vehicle intelligent test monitoring method is applied to a vehicle intelligent test monitoring cloud platform, and at least comprises the following steps:

obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises vehicle performance test events of not less than one test subject;

determining vehicle performance evaluation threads bound to the vehicle performance test events according to the test subjects of each vehicle performance test event, wherein the different vehicle performance evaluation threads have different evaluation rates and different evaluation accuracies;

evaluating the brake performance in the vehicle performance test events by combining with the vehicle performance evaluation thread bound to each vehicle performance test event to obtain historical sample records and first reference brake performance descriptions in the vehicle performance test events, wherein each historical sample record and each first reference brake performance description have a correlation condition;

and combining the first reference brake performance description and the historical sample record in each vehicle performance test event to build a sample set to be used.

2. The method of claim 1, wherein determining the vehicle performance evaluation thread to which the vehicle performance test event is bound in connection with the test topic for each vehicle performance test event comprises: and on the basis that the vehicle performance test event is test data, determining that the vehicle performance evaluation threads bound by the vehicle performance test event comprise a first evaluation thread.

3. The method of claim 2, wherein determining the vehicle performance evaluation thread to which the vehicle performance test event binds based on the vehicle performance test event being test data comprises a first evaluation thread comprising:

on the basis that the vehicle performance test event is test data, determining that vehicle performance evaluation threads bound by the vehicle performance test event comprise a first evaluation thread and a second evaluation thread; wherein the evaluation rate of the first evaluation thread is greater than the evaluation rate of the second evaluation thread, and the accuracy of the first evaluation thread in evaluating the braking performance is less than the accuracy of the second evaluation thread in evaluating the braking performance.

4. The method of claim 3, wherein the evaluating the brake performance of the vehicle performance testing events in conjunction with each vehicle performance testing event bound vehicle performance evaluation thread to obtain a historical sample record and a first reference brake performance description of the vehicle performance testing events comprises:

on the basis that the vehicle performance test event is test data, the brake performance in the test data is evaluated in combination with the first evaluation thread to obtain a first reference brake performance description record bound with the test data, wherein the first reference brake performance description record covers the first reference brake performance description of the brake performance in the test data;

for each first reference brake performance description in the brake performance description record, loading the test data into a historical sample record of the first reference brake performance description binding.

5. The method of claim 4, wherein said evaluating the brake performance in the test data in conjunction with the first evaluation thread to obtain a first reference brake performance profile bound by the test data comprises:

evaluating the brake performance in the test data by using the first evaluation thread to obtain a first reference brake performance description record bound with the test data;

and on the basis that the first reference brake performance description record is abnormal, evaluating the brake performance in the test data by using the second evaluation thread to obtain the first reference brake performance description record bound with the test data.

6. The method of claim 5, wherein determining the vehicle performance evaluation thread to which the vehicle performance test event binds in conjunction with the test topic for each vehicle performance test event comprises:

and on the basis that the vehicle performance test event is the test data set, determining that the vehicle performance evaluation thread comprises a third evaluation thread, wherein the evaluation rate of the third evaluation thread is smaller than the evaluation rate of the first evaluation thread and larger than the evaluation rate of the second evaluation thread, and the accuracy of the third evaluation thread in evaluating the braking performance is larger than the accuracy of the first evaluation thread in evaluating the braking performance and smaller than the accuracy of the second evaluation thread in evaluating the braking performance.

7. The method of claim 6, wherein the evaluating the brake performance of the vehicle performance testing events in conjunction with each vehicle performance testing event bound vehicle performance evaluation thread to obtain a historical sample record and a first reference brake performance description of the vehicle performance testing events comprises:

on the basis that the vehicle performance test event is a test data set, the brake performance in the test data set is evaluated by using the third evaluation thread to obtain a vehicle test data set keyword record of the test data set;

determining matching conditions between the brake performance description in the test data set and the vehicle test data set keywords in combination with the vehicle test data set keyword records;

determining a first reference brake performance description and a historical sample record in the test data set according to the matching condition.

8. The method of claim 7, wherein said determining a match between a brake performance description in said test data set and a vehicle test data set keyword in conjunction with said vehicle test data set keyword record comprises:

for each vehicle test data set keyword in the vehicle test data set keyword record, determining the brake performance description bound by the vehicle test data set keyword; loading the association condition between the brake performance description and the vehicle test data set keyword to the matching condition bound by the test data set;

wherein, the evaluating the braking performance in the test data set by using the third evaluation thread to obtain the keyword record of the vehicle test data set of the test data set comprises: performing specific vehicle performance evaluation on the test data set by using the third evaluation thread to obtain a vehicle test data set keyword record of the test data set;

wherein the determining the brake performance description bound by the vehicle test data set keyword comprises:

performing key description mining on each brake performance evaluated in the vehicle test data set keywords to obtain a brake performance description bound to each brake performance; determining a braking performance description result of the braking performance description;

determining a second reference brake performance description in the vehicle test data set keyword according to each brake performance description result;

determining the second reference brake performance description as the brake performance description bound by the key words of the vehicle test data set;

wherein said determining a first reference brake performance description and historical sample record in said test data set based on said matching comprises:

performing discriminant function processing on the brake performance description in the matching condition to obtain a first discriminant result;

for each discrimination attribute in the first discrimination result, determining a first reference brake performance description for the discrimination attribute;

obtaining a historical sample bound by each brake performance description in the discriminant attribute by combining the matching condition;

loading the historical sample of each brake performance description binding to the historical sample record of the first reference brake performance description binding;

the method comprises the following steps of combining a first reference brake performance description and a historical sample record in each vehicle performance test event, and building a sample set to be used, wherein the method comprises the following steps:

loading each first reference brake performance description in each vehicle performance test event to a description cluster to be distinguished;

carrying out discrimination function processing on the brake performance description in the description cluster to be discriminated to obtain a second discrimination result; for each discrimination attribute in the second discrimination result, determining a third reference brake performance description for the discrimination attribute;

for each brake performance description in the distinguishing attribute, loading a historical sample in the historical sample record bound by each brake performance description into the historical sample record bound by the third reference brake performance description;

updating each third reference brake performance description and the historical sample record of the third reference brake performance description binding to the to-be-used sample set.

9. An intelligent test monitoring system for a vehicle, comprising: the intelligent vehicle testing and monitoring cloud platform is in communication connection with the vehicle;

wherein, vehicle intelligent test control cloud platform for: obtaining a vehicle performance test event record to be identified; the vehicle performance test event record comprises vehicle performance test events of not less than one test subject; determining a vehicle performance evaluation thread bound with each vehicle performance test event according to the test theme of each vehicle performance test event, wherein the vehicle performance evaluation threads with differences have different evaluation rates and different evaluation accuracies; evaluating the brake performance in the vehicle performance test event by combining with the vehicle performance evaluation thread bound to each vehicle performance test event to obtain historical sample records and first reference brake performance descriptions in the vehicle performance test event, wherein each historical sample record and each first reference brake performance description have a correlation condition; and building a sample set to be used by combining the first reference brake performance description and the historical sample record in each vehicle performance test event.

10. The utility model provides a vehicle intelligent testing control cloud platform which characterized in that includes:

a memory for storing a computer program;

a processor coupled to the memory for executing the computer program stored by the memory to implement the method of any of claims 1-9.

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