CN115655752B - New energy vehicle automatic test method and device, electronic equipment and storage medium - Google Patents
New energy vehicle automatic test method and device, electronic equipment and storage medium Download PDFInfo
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- CN115655752B CN115655752B CN202211578213.3A CN202211578213A CN115655752B CN 115655752 B CN115655752 B CN 115655752B CN 202211578213 A CN202211578213 A CN 202211578213A CN 115655752 B CN115655752 B CN 115655752B
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Abstract
The application provides a new energy vehicle automatic testing method and device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring initial test data of a target function of the new energy vehicle in a specified test scene; determining target test data of the target function under a plurality of specified test dimensions according to the initial test data; determining a first test result corresponding to the target function under all the specified test dimensions through the target test data; determining the autonomy of the target function under the specified test scene based on first test results corresponding to the target function under all the specified test dimensions; and determining a second test result of the target function under the specified test scene based on the first test result and the autonomy. According to the technical scheme, the vehicle is tested in a multi-scene and multi-dimension mode, and comprehensiveness and practicability of vehicle testing are improved.
Description
Technical Field
The application relates to the technical field of new energy, in particular to a new energy vehicle automatic testing method and device, electronic equipment and a storage medium.
Background
The new energy vehicle is a vehicle type which abandons the traditional fuel mode, and mainly operates by combining a motor, an electric control system and a battery, and because the new energy vehicle has already stepped into the social aspect, the new energy vehicle is necessary to be tested comprehensively and reliably. However, in the related art, a scheme for comprehensively and automatically testing a vehicle is usually set for a conventional fuel vehicle, and a small number of testing methods for a new energy vehicle can only test local functions such as cruising ability of the new energy vehicle, and cannot meet the increasing testing requirements of the new energy vehicle.
Therefore, how to provide a comprehensive and reliable automatic testing mode for new energy vehicles becomes a technical problem to be solved urgently at present.
Disclosure of Invention
The embodiment of the application provides a new energy vehicle automatic test method and device, electronic equipment and a storage medium, and aims to solve the technical problem that the existing vehicle test mode in the related art cannot meet the test requirement of a new energy vehicle.
In a first aspect, an embodiment of the present application provides an automatic new energy vehicle testing method, including: acquiring initial test data of a target function of the new energy vehicle in a specified test scene; determining target test data of the target function under a plurality of specified test dimensions according to the initial test data; determining a first test result corresponding to the target function under all the specified test dimensions through the target test data; determining the autonomy of the target function under the specified test scene based on first test results corresponding to the target function under all the specified test dimensions; and determining a second test result of the target function under the specified test scene based on the first test result and the autonomy.
In the foregoing embodiment of the present application, optionally, the specifying a test scenario includes: one or more of an environmental static perception scene, an intelligent driving scene, an entertainment scene, a vehicle and external interconnection scene, a parking scene, an energy charging scene and a user care scene; the plurality of specified test dimensions includes: interactive items, custom function items, amount of information, execution efficiency and accuracy.
In the above embodiment of the present application, optionally, the determining, according to the initial test data, target test data of the target function under multiple specified test dimensions includes: when the specified test dimensions comprise the interactive items, determining a first parameter corresponding to the interactive items based on the number of the interactive items related to the target function; when the plurality of specified test dimensions comprise the self-defined function items, determining second parameters corresponding to the self-defined function items based on the number of the self-defined function items related to the target function; or determining a second parameter corresponding to the user-defined function item based on the number of the user-defined function items related to the target function and the relative relation between the user-defined range of each user-defined function item and the specified reference range.
In the foregoing embodiment of the present application, optionally, the determining, according to the initial test data, target test data of the target function in a plurality of specified test dimensions includes: when the plurality of specified test dimensions comprise the execution efficiency, determining a third parameter corresponding to the execution efficiency based on the first parameter, the second parameter and a preset execution efficiency calculation rule.
In the foregoing embodiment of the present application, optionally, the determining, based on the first parameter, the second parameter, and a predetermined execution efficiency calculation rule, a third parameter corresponding to the execution efficiency includes: selecting at least one target parameter satisfying a predetermined filtering condition from the first parameter and the second parameter; and determining a third parameter corresponding to the execution efficiency based on the target parameter and a preset execution efficiency coefficient.
In the above embodiment of the present application, optionally, the determining, according to the initial test data, target test data of the target function under multiple specified test dimensions includes: when the plurality of specified test dimensions comprise the information quantity, determining a fourth parameter corresponding to the information quantity based on the multi-level information type related to the target function; when the plurality of specified test dimensions comprise the accuracy, determining a fifth parameter corresponding to the accuracy based on a function execution result corresponding to each of the multi-level information types related to the target function and a fourth parameter corresponding to the information amount.
In the foregoing embodiment of the present application, optionally, the determining, through the target test data, a first test result corresponding to the target function in all the specified test dimensions includes: determining a sixth parameter based on the third parameter, the fifth parameter, and a predetermined basis coefficient of the target function; and determining a first test result corresponding to the target function under all the specified test dimensions based on the first parameter, the second parameter, the fourth parameter and the sixth parameter.
In the foregoing embodiment of the present application, optionally, the determining the autonomy of the target function in the specified test scenario based on the first test result corresponding to the target function in all the specified test dimensions includes: determining the autonomy corresponding to the first test result in a preset autonomy range, and taking the autonomy as the autonomy of the target function in the specified test scene; or selecting the autonomy degree corresponding to each of the first test result, the first parameter, the second parameter, the fourth parameter and the sixth parameter in a preset autonomy degree range, and determining the autonomy degree of the target function in the specified test scene based on the corresponding autonomy degree.
In the above embodiment of the present application, optionally, the determining the autonomy of the target function in the specified test scenario based on the first test result corresponding to the target function in all the specified test dimensions includes: normalizing the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter to obtain a normalized result; constructing a test data matrix based on the normalization processing result, wherein each item of test data in the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter respectively corresponds to one row of the test data matrix, and row elements of each row of the test data matrix are products of single item of test data corresponding to the row and each item of test data which are arranged according to a specified sequence; and determining the product of the rank of the test data matrix and the autonomy degree adjustment coefficient corresponding to the specified test scene as the autonomy degree of the target function in the specified test scene.
In a second aspect, an embodiment of the present application provides an automatic testing device for a new energy vehicle, including: the initial test data acquisition unit is used for acquiring initial test data of a target function of the new energy vehicle in a specified test scene; the initial test data processing unit is used for determining target test data of the target function under a plurality of specified test dimensions according to the initial test data; a first test result obtaining unit, configured to determine, through the target test data, a first test result corresponding to the target function in all the specified test dimensions; the autonomy degree determining unit is used for determining the autonomy degree of the target function under the specified test scene based on first test results corresponding to the target function under all the specified test dimensions; and the second test result acquisition unit is used for determining a second test result of the target function under the specified test scene based on the first test result and the autonomy.
In the above embodiment of the present application, optionally, the specifying a test scenario includes: one or more of an environment static perception scene, an intelligent driving scene, an entertainment scene, a vehicle and external interconnection scene, a parking scene, an energy charging scene and a user care scene; the plurality of specified test dimensions includes: interactive items, custom function items, amount of information, execution efficiency, and accuracy.
In the foregoing embodiment of the present application, optionally, the initial test data processing unit is configured to: when the specified test dimensions comprise the interactive items, determining a first parameter corresponding to the interactive items based on the number of the interactive items related to the target function; when the plurality of specified test dimensions comprise the self-defined function items, determining second parameters corresponding to the self-defined function items based on the number of the self-defined function items related to the target function; or determining a second parameter corresponding to the user-defined function item based on the number of the user-defined function items related to the target function and the relative relation between the user-defined range of each user-defined function item and the specified reference range.
In the above embodiment of the present application, optionally, the initial test data processing unit is configured to: when the plurality of specified test dimensions comprise the execution efficiency, determining a third parameter corresponding to the execution efficiency based on the first parameter, the second parameter and a preset execution efficiency calculation rule.
In the above embodiment of the present application, optionally, the initial test data processing unit is configured to: selecting at least one target parameter satisfying a predetermined screening condition from the first parameter and the second parameter; and determining a third parameter corresponding to the execution efficiency based on the target parameter and a preset execution efficiency coefficient.
In the foregoing embodiment of the present application, optionally, the initial test data processing unit is configured to: when the plurality of specified test dimensions comprise the information amount, determining a fourth parameter corresponding to the information amount based on the multi-level information type related to the target function; when the plurality of specified test dimensions comprise the accuracy, determining a fifth parameter corresponding to the accuracy based on a function execution result corresponding to each of the multi-level information types related to the target function and a fourth parameter corresponding to the information amount.
In the above embodiment of the present application, optionally, the first test result obtaining unit is configured to: determining a sixth parameter based on the third parameter, the fifth parameter, and a predetermined basis coefficient of the target function; and determining a first test result corresponding to the target function under all the specified test dimensions based on the first parameter, the second parameter, the fourth parameter and the sixth parameter.
In the foregoing embodiment of the present application, optionally, the autonomy determining unit is configured to: determining the autonomy corresponding to the first test result in a preset autonomy range, and taking the autonomy as the autonomy of the target function in the specified test scene; or selecting the autonomy degree corresponding to each of the first test result, the first parameter, the second parameter, the fourth parameter and the sixth parameter in a preset autonomy degree range, and determining the autonomy degree of the target function in the specified test scene based on the corresponding autonomy degree.
In the foregoing embodiment of the present application, optionally, the autonomy determining unit is configured to: normalizing the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter to obtain a normalized result; constructing a test data matrix based on the normalization processing result, wherein each item of test data in the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter respectively corresponds to one row of the test data matrix, and row elements of each row of the test data matrix are products of single item of test data corresponding to the row and each item of test data which are arranged according to a specified sequence; and determining the product of the rank of the test data matrix and the autonomy degree adjustment coefficient corresponding to the specified test scene as the autonomy degree of the target function in the specified test scene.
In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being arranged to perform the method of any of the first aspects above.
In a fourth aspect, an embodiment of the present application provides a storage medium storing computer-executable instructions for performing the method flow of any one of the above first aspects.
Above technical scheme, to the technical problem that current vehicle test mode can't satisfy the test demand of new forms of energy vehicle among the correlation technique, can realize that multi-scene multidimension degree tests the vehicle, helps promoting vehicle test's comprehensiveness and practicality, provides new standard and foundation for vehicle test and appraisal, helps all-round understanding the actual conditions of vehicle, has the significance to the security that promotes intelligent driving.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 shows a flow chart of a new energy vehicle automatic testing method according to an embodiment of the present application;
fig. 2 shows a block diagram of an automatic new energy vehicle testing apparatus according to an embodiment of the present application;
FIG. 3 shows a block diagram of an electronic device according to an embodiment of the application.
Detailed Description
For better understanding of the technical solutions of the present application, the following detailed descriptions of the embodiments of the present application are provided with reference to the accompanying drawings.
It should be understood that the embodiments described are only a few embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
Fig. 1 shows a flow chart of a new energy vehicle automatic testing method according to an embodiment of the present application.
As shown in fig. 1, an automatic new energy vehicle testing method according to an embodiment of the present application includes:
and 102, acquiring initial test data of the target function of the new energy vehicle in a specified test scene.
The target function refers to a function to be tested of the new energy vehicle, and the specified test scene refers to a preset scene required by the new energy vehicle test, including but not limited to one or more of an environment static perception scene, an intelligent driving scene, an entertainment scene, a vehicle and external interconnection scene, a parking scene, an energy charging scene and a user care scene. Different specified test scenes correspond to various target functions which can be tested, and the same target function can be tested under different specified test scenes, in other words, the same target function can be tested under a plurality of specified test scenes.
The environmental static perception scene is used for testing the perception capability of the vehicle to the surrounding environment in a static state, for example, a vehicle radar induction function, an environmental modeling perception function and the like can be tested in the environmental static perception scene. The intelligent driving scenario is used to test functions in the vehicle related to autonomous driving and/or assisted driving, such as autonomous braking functions. The entertainment scene is used for testing entertainment-related functions provided by the vehicle, such as video and audio functions of the vehicle. The vehicle and external interconnection scene is used for testing functions related to communication between the vehicle and external equipment, such as a vehicle road coordination function, a navigation function and the like. The parking scene is used for testing functions related to automatic parking and/or autonomous parking of the vehicle, such as a vehicle radar sensing function, a vehicle autonomous parking function and the like. The charging scenario is used to test functions related to the power supply battery of the vehicle, such as battery power supply level, charging control function, charging station information feedback function, and the like. The user care scene refers to some auxiliary functions related to the vehicle user, such as a specific position article detection function, a child lock control function, and the like.
Of course, the test scenario and the target function described in the present application include, but are not limited to, those listed above, and may also be any other function possessed by the new energy vehicle.
And 104, determining target test data of the target function under a plurality of specified test dimensions according to the initial test data.
The plurality of specified test dimensions includes: interactive items, custom function items, amount of information, execution efficiency and accuracy.
Target test data under a plurality of specified test dimensions are obtained through the initial data, namely vehicle test results under the plurality of specified test dimensions are obtained, the test condition of the vehicle is comprehensively shown through the plurality of specified test dimensions, and the comprehensiveness of new energy vehicle test is improved.
The interactive item includes contents related to hardware type interaction and functional type interaction lamps in the vehicle, wherein the hardware type interaction generally refers to interaction units with fixed hardware, such as images, sounds, vibrations, lights, interconnection equipment and the like, the functional type interaction is performed by specific function units of the vehicle, and if one function exists, the function is considered to correspond to one interaction unit, but the functional type interaction needs to be fed back through the hardware type interaction. Generally, the more interactive items of a vehicle, the richer the vehicle functions.
The user-defined function item refers to a function capable of customizing required contents by a user, for example, whether the door opening reminding function is started or not can be set by the user, and for example, the reminding mode of the door opening reminding function can be selected by the user to be a light or a warning sound. It can be understood that the more the user-defined function items of the vehicle are, the wider the user-defined operation range is, the more the vehicle has practicability, and the more the requirements of the user on the function use can be met.
The information amount refers to information provided by the vehicle for the user on specific functions, for example, road condition information, route information, intersection reminding information, mileage information and the like which can be provided by a map system in the vehicle for the user are information amounts, and for example, in the vehicle endurance performance, the information amount refers to information contents such as actual endurance mileage, power consumption and the like. Therefore, different target functions correspond to different information contents. For the same target function, the richer the information amount provided by the target function, the more the driving experience of the user can be improved.
The execution efficiency is equivalent to the evaluation result of the target function expression, and the evaluation result comprises the aspects of the target function integral function expression, the target function sub-function expression, the interactive item expression, the user-defined function item expression and the like, and is used for reflecting whether the target function, the target function sub-function, the interactive item, the user-defined function item and the like are accurate in realization effect and timely in response.
Accuracy is used to reflect the accuracy of the information content. For example, for the article detection reminding function of the vehicle, if the vehicle detects that the mobile phone is left, the user can be reminded that the mobile phone is in the vehicle through the image type interaction item, the mobile phone left is detected to be the information quantity of the target function of the article detection reminding function, the left article is detected to be the mobile phone, and the wrong article is detected to be the other wrong article, so that the information quantity provided by the article detection reminding function is embodied with high accuracy. The evaluation criteria for accuracy differ for different amounts of information. For another example, for the endurance function of the vehicle, the accuracy is represented as the difference between the actual endurance and the standard working condition endurance.
It is necessary to know that there is some overlap of content involved in multiple specified test dimensions, but to focus on evaluating the traits of different aspects of the overlapping content.
More than, mutual item, self-defined function item, information content, a plurality of appointed test dimensions of efficiency of execution and degree of accuracy reflect the speciality in different aspects of vehicle separately, compare in traditional test directly with the test mode of initial test data as evaluation standard, can reflect the concrete performance of vehicle in the dimension of difference more definitely, richened the reflection ability of test result, promoted test practicality.
In one possible design, each of the specified test dimensions corresponds to its own unique target test data calculation.
And when the interactive items are interacted, determining a first parameter corresponding to the interactive items based on the number of the interactive items related to the target function. The more interactive items of the vehicle, the richer the vehicle functions, and therefore, the first parameter can be determined based on the number of the interactive items as the target test data corresponding to the dimension of the interactive items.
In one possible design, a predetermined set of interaction items may be set, and each interaction item may be set to correspond to a value of credit uniformly, whereby the product of the number of interaction items involved in the target function and the value of credit may be used as the first parameter.
In another possible design, a respective corresponding scoring value is set for each interactive item in the predetermined set of interactive items, and thus, the sum of the scoring values of all interactive items can be calculated as the first parameter according to the number of interactive items involved in the target function.
For the user-defined function item, in one possible design, based on the number of the user-defined function items related to the target function, determining a second parameter corresponding to the user-defined function item.
The target function can be set according to the first parameter, and the target function can be set according to the first parameter. Or setting a respective corresponding score value for each self-defined function item in a preset self-defined function item set, and thus calculating the sum of the score values of all the self-defined function items as a second parameter according to the number of the self-defined function items related to the target function.
For the user-defined function items, in another possible design, based on the number of the user-defined function items related to the target function and the relative relationship between the user-defined range of each user-defined function item and the specified reference range, determining a second parameter corresponding to the user-defined function item.
The more the user-defined function items of the vehicle are, the wider the user-defined operation range is, and the more the vehicle can meet the requirements of users on function use. Therefore, a specified reference range can be set for each self-defined function item, the relative relationship between the actual self-defined range of the self-defined function item under the target function and the specified reference range reflects the relative size between the actual self-defined range and the specified reference range and the coverage of the self-defined range on the specified reference range, and the larger the actual self-defined range is relative to the specified reference range, the higher the coverage on the specified reference range is, which indicates that the user requirement level which can be met by the actual self-defined range is higher. Thus, the number of the self-defined function items related to the target function and the relative relationship between the self-defined range of the self-defined function items and the specified reference range can be comprehensively considered to determine the second parameter.
Specifically, the product of the number of each user-defined function item under the target function and the score value of the user-defined item can be obtained, then a relative value reflecting the relative relationship between the actual user-defined range of each user-defined function item and the specified reference range is obtained, and the products and the relative values obtained by all the user-defined function items are added to be used as the second parameter.
For the execution efficiency, a third parameter corresponding to the execution efficiency may be determined based on the first parameter, the second parameter, and a predetermined execution efficiency calculation rule. Wherein the predetermined execution efficiency calculation rule is to select at least one target parameter satisfying a predetermined filtering condition from the first parameter and the second parameter; and determining a third parameter corresponding to the execution efficiency based on the target parameter and a preset execution efficiency coefficient. Wherein the predetermined screening condition includes, but is not limited to, taking the maximum value or taking the average value of the first parameter and the second parameter.
In one possible design, the third parameter may be the product of the target parameter and a preset execution efficiency coefficient.
For the information amount, a fourth parameter corresponding to the information amount may be determined based on the multi-level information type related to the target function. Since the amount of information provided by the same target function is richer and the driving experience of the user can be improved, the multi-level information types related to the target function need to be determined when the amount of information is calculated.
For example, for the target function of the vehicle temperature feedback function, the vehicle temperature feedback function has two modes of portable device feedback connected with the vehicle and vehicle self feedback, the two modes respectively have corresponding temperature expression results, and the two modes and the two expression results are four first-level information types. The sub-function of forecasting temperature information in the temperature expression result includes three second-level information types of forecasting one-day temperature, forecasting one-week temperature and forecasting real-time temperature.
In one possible design, different scores may be set for each level of information type, and the sum of the scores corresponding to the multiple information types at each level is used as the fourth parameter.
For the accuracy, a fifth parameter corresponding to the accuracy is determined based on a function execution result corresponding to each of the multi-level information types related to the target function and a fourth parameter corresponding to the information amount.
The accuracy is used for reflecting the accuracy of the information amount, and therefore, the function execution result corresponding to each of the multi-level information types related to the target function can be used as an adjustment basis for the fourth parameter of the information amount to obtain the fifth parameter.
In one possible design, the adjustment coefficient may be set to a specified value if the function execution results corresponding to the respective multi-level information types related to the target function are completely accurate, and the adjustment coefficient may be set to a product of the specified value and a ratio of the completely accurate function execution results in all the function execution results if the function execution results corresponding to the respective multi-level information types related to the target function are partially erroneous. Finally, the product of the fourth parameter and the adjustment coefficient is used as the fifth parameter.
Therefore, a reasonable test data processing mode is provided for each appointed test dimension, reasonable target test data are obtained and used as test results of each appointed test dimension, the specific conditions of the vehicle can be comprehensively reflected in a multi-dimensional mode through the test results of each appointed test dimension, and the comprehensiveness and the reasonability of the test are improved.
And 106, determining first test results corresponding to all the specified test dimensions of the target function according to the target test data.
Specifically, a sixth parameter is determined based on the third parameter, the fifth parameter and a predetermined basis coefficient of the target function; and determining a first test result corresponding to the target function under all the specified test dimensions based on the first parameter, the second parameter, the fourth parameter and the sixth parameter.
In one possible design, a product of the third parameter and the fifth parameter is calculated, and the product is added to a predetermined basic coefficient of the target function to obtain a sixth parameter. The sixth parameter is used for reflecting the vehicle capability level reflected by combining the execution efficiency and the accuracy of the vehicle.
In one possible design, a sum of the first parameter, the second parameter, the fourth parameter, and the sixth parameter is set as a first test result, with the first test result reflecting a combined level of capability of the vehicle in a plurality of specified test dimensions.
In another possible design, a base score may be set for the vehicle, and a sum of the first parameter, the second parameter, the fourth parameter, and the sixth parameter is used as an adjustment value for the base score to obtain a first test result.
And 108, determining the autonomy of the target function in the specified test scene based on the first test results corresponding to the target function in all the specified test dimensions.
The autonomy degree is used for reflecting the degree of intellectualization of the vehicle, and in particular, in one possible design, the autonomy degree corresponding to the first test result can be determined within a preset autonomy degree range and is used as the autonomy degree of the target function in the specified test scene. The range of the preset autonomy degree corresponds to the range of the first test result, and the value corresponding to the actual first test result in the range of the preset autonomy degree is used as the autonomy degree of the target function in the specified test scene.
In another possible design, the autonomy degree corresponding to each of the first test result, the first parameter, the second parameter, the fourth parameter and the sixth parameter is selected within a predetermined autonomy degree range, and the autonomy degree of the target function in the specified test scenario is determined based on the corresponding autonomy degree. The autonomy degree of the vehicle under each specified test dimension and the comprehensive autonomy degree of the vehicle under all the specified test dimensions can be evaluated respectively, and then the autonomy degree of the target function under the specified test scene is calculated based on the autonomy degrees.
The sum or the average value of the autonomy degrees corresponding to the vehicles in each specified test dimension can be set as the autonomy degree of the target function in the specified test scene.
In yet another possible design, the autonomy is calculated by: and normalizing the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter to obtain a normalized result.
The normalization processing can convert data of different magnitudes to the same magnitude, so that after the normalization processing is performed on the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter, the multiple items of test data are adjusted to the same magnitude, and the difference of the performance levels of the vehicle under the specified test dimension represented by the vehicle or under the synthesis of the multiple items of specified test dimensions represented by the vehicle can be reflected under the same magnitude.
Then, a test data matrix is constructed based on the normalization processing result, wherein each item of test data in the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter respectively corresponds to one row of the test data matrix, and row elements of each row of the test data matrix are products of single items of test data corresponding to the row and each item of test data, which are arranged according to a specified sequence.
In other words, each element of the test data matrix is a product of at least two of the normalization processing results, and thus each element of the test data matrix represents a performance level of the vehicle comprehensively reflected by at least two of the normalization processing results, that is, the elements in the test data matrix reflect comprehensive performance results of any of the seven items of execution efficiency and accuracy, the first test result, and the interaction item, the custom function item, the information amount, the execution efficiency, and the accuracy. Therefore, the rank of the test data matrix can reflect the overall test performance of the vehicle in seven aspects of the comprehensive performance result of the execution efficiency and the accuracy, the first test result, the interaction item, the self-defined function item, the information quantity, the execution efficiency and the accuracy.
And finally, determining the product of the rank of the test data matrix and the autonomy adjusting coefficient corresponding to the specified test scene as the autonomy of the target function in the specified test scene. The requirements of each specified test scene on the intelligent level of the vehicle are different, so that an autonomy adjusting coefficient for reflecting the required intelligent level of the vehicle can be set for each specified test scene based on the requirement difference of each specified test scene on the intelligent level of the vehicle. And adjusting the rank of the test data matrix based on the autonomy degree adjusting coefficient to obtain the final autonomy degree. Therefore, the final degree of autonomy not only reflects the intelligent level of the vehicle in the test performance in the seven aspects, but also reflects the intelligent level of the vehicle in the specified test scene of the current test, and a reliable data base is laid for the acquisition of the subsequent final test result.
And step 110, determining a second test result of the target function under the specified test scene based on the first test result and the autonomy.
And determining the final test result of the vehicle in the specified test scene according to the comprehensive performance result of the vehicle in each specified test dimension and the vehicle intelligence level reflected by the comprehensive performance result.
Through the technical scheme, for each appointed test scene, comprehensive evaluation can be carried out from a plurality of appointed test dimensions such as interactive items, self-defined function items, information quantity, execution efficiency and accuracy, and a final vehicle test result is obtained by combining the vehicle intelligentization level reflected by the plurality of appointed test dimensions.
The multi-designation test scenario and multi-designation test dimensions of the present application are exemplified by the following examples.
First, a test result of a vehicle radar sensing function or an environmental modeling sensing function of a vehicle can be obtained in an environmental static sensing scene.
The interactive items of the target function in the scene comprise feedback actions of the vehicle during testing of various scenes, such as image graphic and sound prompt; the self-defined function item comprises whether function setting items related to automatic driving are abundant or not; the information amount comprises items which can pass through in the test road scene; the execution efficiency comprises the passing time of various test road scenes in a high-speed environment; accuracy includes testing the road scene for situations where the autonomous driving function exits or a driver situation is required to take over.
Secondly, a test result of the driving assistance function of the vehicle is obtained in the intelligent driving scene.
The interactive items of the target function in the scene comprise feedback actions of the vehicle during testing of various scenes, such as image graphic and sound prompt; the self-defined function items comprise whether function setting items related to automatic driving are rich or not; the information amount comprises items which can pass through in the test road scene; the execution efficiency comprises the passing time of various test road scenes in a high-speed environment; accuracy includes testing the road scene for situations where the autonomous driving function exits or a driver situation is required to take over.
Third, a test result of a linking function of an entertainment device of a vehicle is obtained in an entertainment scene.
The interactive items of the target function in the scene comprise vehicle-mounted entertainment hardware, content and three-party entertainment equipment supporting connection; the self-defining function items comprise content items for supporting self-definition of the vehicle and the three-party connecting equipment; the information amount includes the number of devices; the execution efficiency comprises the response and compatibility of the test equipment for different entertainment forms, and the equipment conforms to the requirements of entertainment contents; accuracy includes different entertainment types of different devices for the vehicle, whether the various functions of the device are in normal use, etc.
And fourthly, acquiring a test result of the vehicle road cooperative function of the vehicle in a scene of interconnection between the vehicle and the outside.
The interactive items of the target function in the scene comprise hardware type interaction and functional type interaction units, such as image and modeling type interaction, and vehicle networking/V2X communication capacity; the self-defined function items comprise function items for providing related function settings; the information amount comprises information types such as environment roads supported by the vehicle; the execution efficiency comprises whether the vehicle-road cooperative information is fed back in time or not, whether the driver is effectively helped to obtain the road environment information during the test or not and the like; accuracy includes whether any amount of information of the environment is accurate.
Fifthly, a test result of the autonomous parking function of the vehicle is obtained in a parking scene.
Wherein, the interactive item of the target function in the scene comprises a hardware type interactive unit; the self-defined function item comprises self-defined content of the self-defined parking function; the information quantity comprises parking space identification, parking space objects and the like; the execution efficiency includes whether to execute according to the functions of the vehicle, test different parking times and the like; the accuracy includes the performance according to the functions of the vehicle, and the parking problem, such as collision, warehouse skew and the like.
And sixthly, acquiring a test result of the information feedback function of the charging station of the vehicle in the charging scene.
The interactive items of the target function in the scene comprise a vehicle machine, interconnection equipment and the like; the user-defined function items comprise the information feedback user-defined viewing capability of the energy charging station, and the richer the information is, the stronger the user-defined capability is; the information amount comprises specific information types of the charging stations which can be fed back; the execution efficiency comprises whether the information of the charging station is updated in real time, such as the number of the remaining vacant sites and the like; the accuracy includes whether the various information feedbacks are accurate or not.
And seventhly, acquiring a test result of the object detection reminding function of the vehicle in the user care scene.
The interactive items of the target function in the scene comprise a reminding mode and supported equipment; the self-defining function items comprise reminding strength, detection time setting and the like; the amount of information includes supported device or item types, quantities, etc.; the execution efficiency comprises whether the article detection reminding is timely and accurate or not, or the detection response capability is customized according to a user, and the like; accuracy includes whether the device, item type, quantity, etc. is identified accurately, etc.
Of course, in the actual test, the test content in each specified test scenario and specified test dimension includes, but is not limited to, the above content, and may also be any item that meets the actual test requirement.
Fig. 2 shows a block diagram of an automatic new energy vehicle testing apparatus according to an embodiment of the present application.
As shown in fig. 2, an automatic new energy vehicle testing apparatus 200 according to an embodiment of the present application includes: the initial test data acquisition unit 202 is configured to acquire initial test data of a target function of the new energy vehicle in a specified test scene; an initial test data processing unit 204, configured to determine, according to the initial test data, target test data of the target function in multiple specified test dimensions; a first test result obtaining unit 206, configured to determine, according to the target test data, first test results corresponding to all the specified test dimensions for the target function; the autonomy determining unit 208 is configured to determine autonomy of the target function in the specified test scenario based on first test results corresponding to all the specified test dimensions of the target function; a second test result obtaining unit 210, configured to determine, based on the first test result and the autonomy, a second test result of the target function in the specified test scenario.
In the foregoing embodiment of the present application, optionally, the specifying a test scenario includes: one or more of an environment static perception scene, an intelligent driving scene, an entertainment scene, a vehicle and external interconnection scene, a parking scene, an energy charging scene and a user care scene; the plurality of specified test dimensions includes: interactive items, custom function items, amount of information, execution efficiency and accuracy.
In the above embodiment of the present application, optionally, the initial test data processing unit 204 is configured to: when the specified test dimensions comprise the interactive items, determining a first parameter corresponding to the interactive items based on the number of the interactive items related to the target function; when the plurality of specified test dimensions comprise the self-defined function items, determining second parameters corresponding to the self-defined function items based on the number of the self-defined function items related to the target function; or determining a second parameter corresponding to the user-defined function item based on the number of the user-defined function items related to the target function and the relative relation between the user-defined range of each user-defined function item and the specified reference range.
In the above embodiment of the present application, optionally, the initial test data processing unit 204 is configured to: when the plurality of specified test dimensions comprise the execution efficiency, determining a third parameter corresponding to the execution efficiency based on the first parameter, the second parameter and a preset execution efficiency calculation rule.
In the above embodiment of the present application, optionally, the initial test data processing unit 204 is configured to: selecting at least one target parameter satisfying a predetermined filtering condition from the first parameter and the second parameter; and determining a third parameter corresponding to the execution efficiency based on the target parameter and a preset execution efficiency coefficient.
In the above embodiment of the present application, optionally, the initial test data processing unit 204 is configured to: when the plurality of specified test dimensions comprise the information quantity, determining a fourth parameter corresponding to the information quantity based on the multi-level information type related to the target function; when the plurality of specified test dimensions comprise the accuracy, determining a fifth parameter corresponding to the accuracy based on a function execution result corresponding to each of the multi-level information types related to the target function and a fourth parameter corresponding to the information amount.
In the above embodiment of the present application, optionally, the first test result obtaining unit 206 is configured to: determining a sixth parameter based on the third parameter, the fifth parameter, and a predetermined basis coefficient for the target function; and determining a first test result corresponding to the target function under all the specified test dimensions based on the first parameter, the second parameter, the fourth parameter and the sixth parameter.
In the above embodiment of the present application, optionally, the autonomy determining unit 208 is configured to: determining the autonomy degree corresponding to the first test result in a preset autonomy degree range, and taking the autonomy degree as the autonomy degree of the target function in the specified test scene; or selecting the autonomy degree corresponding to each of the first test result, the first parameter, the second parameter, the fourth parameter and the sixth parameter in a preset autonomy degree range, and determining the autonomy degree of the target function in the specified test scene based on the corresponding autonomy degree.
In the foregoing embodiment of the present application, optionally, the autonomy determining unit 208 is configured to: normalizing the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter to obtain a normalized result; constructing a test data matrix based on the normalization processing result, wherein each item of test data in the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter respectively corresponds to one row of the test data matrix, and row elements of each row of the test data matrix are products of single item of test data corresponding to the row and each item of test data which are arranged according to a specified sequence; and determining the product of the rank of the test data matrix and the autonomy degree adjustment coefficient corresponding to the specified test scene as the autonomy degree of the target function in the specified test scene.
The automatic testing device 200 for the new energy vehicle uses the solution described in any of the above embodiments, and therefore, all the technical effects described above are achieved, and details are not repeated herein.
FIG. 3 shows a block diagram of an electronic device according to an embodiment of the application.
As shown in FIG. 3, an electronic device 300 of one embodiment of the present application includes at least one memory 302; and a processor 304 communicatively coupled to the at least one memory 302; wherein the memory stores instructions executable by the at least one processor 304, the instructions being configured to perform the scheme described in any of the above embodiments. Therefore, the electronic device 300 has the same technical effects as any of the above embodiments, and will not be described herein again.
The electronic device of the embodiments of the present application exists in various forms, including but not limited to:
(1) Mobile communication devices, which are characterized by mobile communication functions and are primarily targeted at providing voice and data communications. Such terminals include smart phones (e.g., iphones), multimedia phones, functional phones, and low-end phones, among others.
(2) The ultra-mobile personal computer equipment belongs to the category of personal computers, has calculation and processing functions and generally has the characteristic of mobile internet access. Such terminals include PDA, MID, and UMPC devices, such as ipads.
(3) Portable entertainment devices such devices may display and play multimedia content. Such devices include audio and video players (e.g., ipods), handheld game consoles, electronic books, as well as smart toys and portable car navigation devices.
(4) The server is similar to a general computer architecture, but has higher requirements on processing capacity, stability, reliability, safety, expandability, manageability and the like because of the need of providing high-reliability service.
(5) And other electronic devices with data interaction functions.
In addition, a storage medium is provided in an embodiment of the present application, and stores computer-executable instructions for executing the method flow described in any of the above embodiments.
The technical scheme of this application has been explained in detail in combination with the drawing above, and the technical scheme of this application, the multi-scene multidimension degree is tested the vehicle, helps promoting vehicle test's comprehensiveness and practicality, provides new standard and foundation for vehicle evaluation, helps all-round understanding the actual conditions of vehicle, has the significance to promoting the security of intelligent driving.
It should be understood that the term "and/or" as used herein is merely a relationship that describes an associated object, meaning that three relationships may exist, e.g., a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter associated objects are in an "or" relationship.
It should be understood that although the terms first, second, etc. may be used to describe parameters in the embodiments of the present application, these parameters should not be limited to these terms. These terms are only used to distinguish one parameter from another. For example, a first parameter may also be referred to as a second parameter, and similarly, a second parameter may also be referred to as a first parameter, without departing from the scope of embodiments of the present application.
The word "if" as used herein may be interpreted as "at 8230; \8230;" or "when 8230; \8230;" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrases "if determined" or "if detected (a stated condition or event)" may be interpreted as "when determined" or "in response to a determination" or "when detected (a stated condition or event)" or "in response to a detection (a stated condition or event)", depending on the context.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer-readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a Processor (Processor) to execute some steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (8)
1. An automatic testing method for a new energy vehicle is characterized by comprising the following steps:
acquiring initial test data of a target function of the new energy vehicle in a specified test scene;
determining target test data of the target function under a plurality of specified test dimensions according to the initial test data;
determining a first test result corresponding to the target function under all the specified test dimensions through the target test data;
determining the autonomy of the target function under the specified test scene based on first test results corresponding to the target function under all the specified test dimensions;
determining a second test result of the target function under the specified test scene based on the first test result and the autonomy degree;
the specified test scenario includes: one or more of an environment static perception scene, an intelligent driving scene, an entertainment scene, a vehicle and external interconnection scene, a parking scene, an energy charging scene and a user care scene;
the plurality of specified test dimensions includes: a plurality of items among interactive items, custom function items, information amount, execution efficiency, and accuracy;
the determining target test data of the target function under a plurality of specified test dimensions according to the initial test data comprises:
when the specified test dimensions comprise the interactive items, determining a first parameter corresponding to the interactive items based on the number of the interactive items related to the target function;
and
when a plurality of the specified test dimensions include the softkey,
determining a second parameter corresponding to the user-defined function item based on the number of the user-defined function items related to the target function; alternatively, the first and second liquid crystal display panels may be,
determining a second parameter corresponding to the user-defined function item based on the number of the user-defined function items related to the target function and the relative relation between the user-defined range of each user-defined function item and the specified reference range;
when the plurality of specified test dimensions comprise the execution efficiency, determining a third parameter corresponding to the execution efficiency based on the first parameter, the second parameter and a preset execution efficiency calculation rule;
the determining a third parameter corresponding to the execution efficiency based on the first parameter, the second parameter and a predetermined execution efficiency calculation rule includes:
selecting at least one target parameter satisfying a predetermined filtering condition from the first parameter and the second parameter;
and determining a third parameter corresponding to the execution efficiency based on the target parameter and a preset execution efficiency coefficient.
2. The method for automatically testing the new energy vehicle according to claim 1, wherein the determining target test data of the target function under a plurality of specified test dimensions according to the initial test data comprises:
when the plurality of specified test dimensions comprise the information quantity, determining a fourth parameter corresponding to the information quantity based on the multi-level information type related to the target function;
when the plurality of specified test dimensions comprise the accuracy, determining a fifth parameter corresponding to the accuracy based on a function execution result corresponding to each of the multi-level information types related to the target function and a fourth parameter corresponding to the information amount.
3. The method for automatically testing the new energy vehicle according to claim 2, wherein the determining, through the target test data, first test results corresponding to the target functions in all the specified test dimensions comprises:
determining a sixth parameter based on the third parameter, the fifth parameter, and a predetermined basis coefficient for the target function;
and determining a first test result corresponding to the target function under all the specified test dimensions based on the first parameter, the second parameter, the fourth parameter and the sixth parameter.
4. The method for automatically testing the new energy vehicle according to claim 3, wherein the determining the autonomy of the target function under the specified test scene based on the first test result of the target function under all the specified test dimensions comprises:
determining the autonomy corresponding to the first test result in a preset autonomy range, and taking the autonomy as the autonomy of the target function in the specified test scene; alternatively, the first and second electrodes may be,
and selecting the autonomy degree corresponding to each of the first test result, the first parameter, the second parameter, the fourth parameter and the sixth parameter in a preset autonomy degree range, and determining the autonomy degree of the target function in the specified test scene based on the corresponding autonomy degree.
5. The method for automatically testing the new energy vehicle according to claim 3, wherein the determining the autonomy of the target function under the specified test scene based on the first test result of the target function under all the specified test dimensions comprises:
normalizing the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter to obtain a normalized result;
constructing a test data matrix based on the normalization processing result, wherein,
each item of test data in the first test result, the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter, and the sixth parameter corresponds to one row of the test data matrix, and row elements of each row of the test data matrix are products of single item of test data corresponding to the row and each item of test data arranged according to a specified sequence;
and determining the product of the rank of the test data matrix and the autonomy degree adjustment coefficient corresponding to the specified test scene as the autonomy degree of the target function in the specified test scene.
6. The utility model provides a new forms of energy vehicle automatic testing arrangement which characterized in that includes:
the initial test data acquisition unit is used for acquiring initial test data of a target function of the new energy vehicle in a specified test scene;
the initial test data processing unit is used for determining target test data of the target function under a plurality of specified test dimensions according to the initial test data;
a first test result obtaining unit, configured to determine, through the target test data, a first test result corresponding to the target function in all the specified test dimensions; and
the autonomy degree determining unit is used for determining the autonomy degree of the target function under the specified test scene based on first test results corresponding to the target function under all the specified test dimensions;
a second test result obtaining unit, configured to determine, based on the first test result and the autonomy, a second test result of the target function in the specified test scenario;
the specified test scenario includes: one or more of an environmental static perception scene, an intelligent driving scene, an entertainment scene, a vehicle and external interconnection scene, a parking scene, an energy charging scene and a user care scene; the plurality of specified test dimensions includes: interactive items, custom function items, information quantity, execution efficiency and accuracy;
the initial test data processing unit is configured to: when the specified test dimensions comprise the interactive items, determining a first parameter corresponding to the interactive items based on the number of the interactive items related to the target function; when the plurality of specified test dimensions comprise the self-defined function items, determining second parameters corresponding to the self-defined function items based on the number of the self-defined function items related to the target function; or determining a second parameter corresponding to the user-defined function item based on the number of the user-defined function items related to the target function and the relative relation between the user-defined range of each user-defined function item and the specified reference range; when the plurality of specified test dimensions comprise the execution efficiency, determining a third parameter corresponding to the execution efficiency based on the first parameter, the second parameter and a preset execution efficiency calculation rule;
wherein at least one target parameter satisfying a predetermined filtering condition is selected among the first parameter and the second parameter; and determining a third parameter corresponding to the execution efficiency based on the target parameter and a preset execution efficiency coefficient.
7. An electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor and arranged to perform the method of any of claims 1 to 5.
8. A storage medium having stored thereon computer-executable instructions for performing the method of any one of claims 1 to 5.
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