EP3622451A1 - Détermination de la maturité d'un système technique et en particulier d'un véhicule circulant de manière autonome - Google Patents

Détermination de la maturité d'un système technique et en particulier d'un véhicule circulant de manière autonome

Info

Publication number
EP3622451A1
EP3622451A1 EP18720650.3A EP18720650A EP3622451A1 EP 3622451 A1 EP3622451 A1 EP 3622451A1 EP 18720650 A EP18720650 A EP 18720650A EP 3622451 A1 EP3622451 A1 EP 3622451A1
Authority
EP
European Patent Office
Prior art keywords
test
sut
tests
result
environment
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP18720650.3A
Other languages
German (de)
English (en)
Inventor
Holger Naundorf
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Dspace Se & Co Kg
Original Assignee
Dspace GmbH
Dspace Digital Signal Processing and Control Engineering GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Dspace GmbH, Dspace Digital Signal Processing and Control Engineering GmbH filed Critical Dspace GmbH
Publication of EP3622451A1 publication Critical patent/EP3622451A1/fr
Pending legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395—Quality analysis or management
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic networks

Definitions

  • the invention relates to a method and a test system for
  • test coverage Methods for product maturity determination are known from the prior art, in which the product maturity of a technical system is determined by means of test coverage. Under test coverage is here in
  • the ratio of tests performed to the total number of tests executable for the technical system or the ratio of successfully performed tests to the total number of tests that can be performed on the technical system.
  • product maturity is determined by means of test coverage, and proposals are made for improving the test coverage.
  • the object of the invention is to provide a device which further develops the prior art.
  • a method for determining a product maturity by means of tests comprises executing a test case by means of a test environment applied to a test object, and there is no result for at least one test, and the method comprises the steps of setting rules for calculating a probability that a test for which there is no result will be successful or unsuccessful, the rules using as input variables present or expected results of tests and returning probabilities as output variables, calculating the probability that a test for which no result is present, will be successful, by means of at least part of the predetermined rules, as well as representation of the product maturity in dependence of the probabilities calculated in the previous step.
  • An advantage of the method according to the invention is that the product maturity of a technical system is evaluated not only on the basis of already performed tests, but also tests that have not yet been carried out are taken into account in the evaluation. In the event that not all tests are performed, this results in a more complete picture of product maturity, otherwise you will get more meaningful statements about product maturity at an earlier stage, as the tests that are still in the future will also be included in the evaluation. Furthermore, based on this forward-looking consideration, an improved selection of the tests still to be performed and their order can be made. Further, it is advantageous that by means of the method easier to find but meaningful representations of product maturity found and presented can be. Statements about product maturity can simply be made according to the existing criteria, such as: B.
  • test object is an at least partially autonomously driving vehicle, a part of an at least partially autonomously driving vehicle or a functionality of an at least partially autonomously driving vehicle
  • test case is a driving maneuver of the at least partially autonomously driving vehicle, a driving maneuver with the part of the at least partially autonomously driving vehicle or a driving maneuver in which the functionality of an at least partially autonomously driving vehicle is taken into account
  • TE test environment
  • test case or a test environment or a test object in a first and a second version, wherein the second version represents a state of development of the test case or the test environment or the test object, the time of the development of the first version of the test case or Test environment or the test object.
  • the predetermined rules represent a technical or statistical relationship between a first test case, a first test environment or a first test object in the first or second version and a second test case, a second test environment or a second test object in the first or second version.
  • the result of a test may take at least the values "Test Success” (passed) and "Test Failed”.
  • the predetermined rules are automatically created and / or verified by analyzing a database of at least a portion of the tests, including test cases, test environments, test objects, and results.
  • the analysis comprises a static evaluation of relationships of tests, in particular relationships of tests with positive results.
  • a first set of tests is determined using a statistical distribution, with results being or being generated for the first set of tests.
  • the determination of the tests of the first group of tests is based on one or more further static distributions of the test cases, the test environments and / or the test objects.
  • the static distribution and / or one or more of the further static distributions are random distributions.
  • the calculation of the probability that a test for which no Result, will be successful from the static distribution of the tests, the test cases, the test environments, and / or the test objects.
  • the presentation of the product maturity takes place in the form of a numerical, in particular percentage, test coverage or in the form of a, in particular color-coded graphic.
  • one or more criteria are specified and some of the tests for which in the second method step a probability that the test will be successful or unsuccessful have been calculated will be executed or suggested for execution, with the ones to be executed or executed proposed tests meet at least one of the given criteria.
  • At least one of the predetermined criteria is above or below a threshold for the probability that the test will be successful or unsuccessful.
  • a weighting is assigned to a test case (TC), a test environment (TE), a test object (SUT) or a combination of at least two elements from test case (TC), test environment (TE) and test object (SUT) and the weighting is taken into account in calculating the likelihood that a test for which no result will be successful or unsuccessful in the second step and / or in the presentation of the product maturity in the last step.
  • a threshold value of the product maturity is determined and, if the threshold for product maturity is exceeded, the test object (SUT) is released for a further development step.
  • test object is assigned to a class of test objects (SUT), in particular by means of a level of the degree of automation, and the threshold value of the product maturity is defined as a function of the assigned class.
  • SUT class of test objects
  • the object is also achieved by a test system for testing a technical system, wherein the test system carries out one of the methods described above.
  • Figure 1 shows schematically the composition of a test
  • Test environment TE
  • test case TC
  • test object SUT
  • FIG. 2 schematically shows the relationships between test (1)
  • Test environment TE
  • test case TC
  • test object SUT
  • result of the test TR
  • FIG. 3 schematically shows the storage or storage of
  • FIG. 4 schematically shows the prediction of results (TR)
  • FIG. 5 schematically shows the prediction of results (TR)
  • Figure 6 is a tabular representation of results of tests
  • Figure 7 is a tabular representation of predicted
  • Results of test (1) schematically the derivation of rules (5) from the in a data storage (3) stored or stored tests (1) and results of tests (TR).
  • schematic representation of an at least partially autonomously driving vehicle schematic representation of a classification into levels of different degrees of automation in at least partially autonomously driving vehicles.
  • a test (1) comprises at least one test environment (TE) from a possible plurality of test environments (TE), one test case (TC) from a possible plurality of test cases (TC) and one test object ("system under test”).
  • TE test environment
  • TC test case
  • TC test case
  • SUT test object
  • the aim of the maturity determination of a technical system is to evaluate product characteristics such as performance, reliability or user-friendliness. From this it follows whether a next stage, a so-called milestone, has been reached in the development of the technical system. The final milestone in most cases is the release of the product for sale or delivery of the product.
  • test cases There is, among other things, on the functionality to be tested and the objectives to be achieved for safety and reliability
  • HIL tests hardware-in-the-loop tests
  • test cases can be developed on the HIL test environments (usually special real-time computers)
  • An example of such a test tool is the software product AutomationDesk from dSPACE
  • simulation environments so-called offline simulators, are also used, some of which can be executed on commercially available PCs.
  • TE test environments
  • HIL offline simulator
  • test (1) test environment (TE), test object (SUT) and result (TR) of a test (1) are shown schematically.
  • data are collected which represent, at least partially, a result (TR) of the test (1) or from which a result (TR) of the test (1) can be derived.
  • TR result of the test (1)
  • TC test case
  • TE test environment
  • SUT test object
  • TR test results
  • results (TR) are assigned to the test (1) in order to be able to understand the conditions of the corresponding test execution in the later evaluation of the test results (TR).
  • Typical results (TR) of tests (1) are "passed” and "failed". Since the use of the English terms "passed” and "failed" in the environment of testing and test administration are more common, they are also used in the following.
  • the technical system to be tested is a control device for an automobile
  • the test object (SUT) is typically a prototype of this control device which is connected to an HIL simulator.
  • the HIL simulator and the executable test software will then provide one Test environment (TE).
  • TE Test environment
  • the exact configuration of the HIL simulator is relevant for the traceability and reproducibility of the tests (1) and is defined as a test environment (TE).
  • Changes to the hardware or software of the HIL simulator result in a new test environment (TE).
  • TE test environment
  • TC test case
  • SUT test object
  • TR results of the test (1) are stored and for the purpose of traceability with the test (1 ) connected.
  • This data is preferably stored in a database and managed by a test management tool with connection to the database.
  • a test management tool is the SYNECT software from dSPACE.
  • the depiction in FIG. 3 schematically shows the storage or storage of test cases (TC) and test objects (SUT) in a data storage system (3).
  • the data storage can be a file system, a database or another, known from the prior art, electronic data storage. It is also possible that in the data storage only representatives of the actual test cases (TC) or test objects (SUT) or references to the actual test cases (TC) or test objects (SUT) are stored. This is e.g. useful or even necessary if the test objects are not electronically available data but physically present objects (eg electronic devices). From the stored test cases (TC) and test objects (SUT) different tests (1) can then be generated by distribution to one or more test environments (TE).
  • TE test environments
  • FIG. 4 schematically shows the determination according to the invention of expected test results (TR).
  • TR expected test results
  • the former shows dashed rather than solid lines in the figures.
  • Rules (5) are used to calculate the test results (TR) and assigned probabilities. These rules (5) can be specified by the user or created automatically by evaluating existing databases.
  • An example of such a rule is that a test (1) comprising a test object (SUT) in a third version (V3) provides 99% of the same test result (TR) as a test (1) comprising the same test object (SUT) in a second version (V2) if test environment (TE) and test case (TC) are the same for both tests (1).
  • TR expected test results
  • the expected result of the test comprising version 2 (V2) of the test object (SUT) is calculated by means of a rule (5) from the present test result (TR) of the test (1) comprising version 1 (VI) of the test object (SUT) and the expected result of the test comprising version 3 (V3) of the test object (SUT) is calculated by means of a rule (5) from the expected test result (TR) of test (1) comprising version 2 (V2) of the test object (SUT).
  • the probability of the expected test result (TR) from the previous calculation is taken into account. An example of this is given if in the previous example to FIG.
  • the result (TR) of the test (1) comprising the test object (SUT) in version 2 (V2) is not present but in an analogous manner from an existing test result (TR ) of a test (1) comprising the test object (SUT) in version 1 (VI), with a probability of 99%.
  • the calculation of the test result (TR) for test (1) comprising the test object (SUT) in version 3 (V3) by means of the same rule (5) also results in the test result (TR) for the test (1) comprising the Test object (SUT) in version 3 (V3) 99% equal to the test result (TR) for test (1), comprising the test object (SUT) in version 2 (V2).
  • FIG. 6 shows tabular results (TR) of tests (1).
  • FIG. 5 shows by way of example a database stored in a data storage system (3).
  • the product maturity of version 3 of the test object (SUT) is shown in tabular form and analogously to the tables in FIG.
  • the individual fields of the table contain, according to the method of the invention, calculated expected results of the illustrated test (1), as well as the correspondingly calculated associated probabilities. It is readily apparent that the representation determined by means of the invention and shown in FIG. 7 gives a significantly better, because more complete, overview of the product maturity of the test object (SUT) in version 3 than the comparable representation in the lower third of FIG.
  • the fields of the table can also be displayed in color or in addition to the textual contents. Typically, green is used for tests (1) with the result passed and red for tests (1) with the result faiied. To represent the probabilities it is additionally possible to vary the hue or the color intensity of the green and red fields.
  • test objects SUT
  • the test environments TE1, TE2, TE3
  • the test cases could be HIL simulators with different software configurations , which different vehicle types represent.
  • the test cases TC1, TC2, TC3) could be, for example, the prevention of window closing (TC1), the emergency opening of the window in an accident (TC2), and the automatic closing of the window when the car is locked.
  • the product maturity resulting according to the invention, as shown in FIG. 7, can now be used for different conclusions, depending on the criterion of evaluation and status in development.
  • the lack of positive test results for the test case TC3 can lead to it being executed again or possibly after any improvement in the corresponding functionality. It could also be decided that the current development milestone (eg, safety-related tests with over 90% probability passed) has been achieved and the next stage of development is being addressed.
  • FIG. 8 schematically shows an automatic derivation of the rules (5), represented by the filled-in arrow, from a database, stored in a data storage system (3), comprising tests (1) and test results (TR). As shown in FIG. 2, the test results (TR) are assigned to tests (1).
  • the automatic derivation can be z. B. create one or more rules (5) from a common correlation.
  • test (1) comprising a specific combination of test case (TC) and test object (SUT) is associated with a result (TR) percentage more frequently than a predefined threshold and from this the rule (5) is derived it will be that other tests (1) comprising the same combination of test case (TC) and test object (SUT) with a probability equal to the threshold will have the same result (TR) as the previously determined tests (1).
  • At least partially or even fully autonomous vehicles have one or more sensors for collecting data, in particular data about the environment of the vehicle. Additionally, such vehicles typically have one or more interfaces to communicate with their environment. The figure Figure 9 illustrates this schematically. Typical sensors are radar, Lidar- or optical camera sensors, with which the environment is detected. The data exchange is usually realized via mobile radio standards (eg 4G or 5G). Furthermore, satellite-based systems (eg GPS) are frequently used for determining the position.
  • Level 0 stands for a system without assistance systems, in which all driving maneuvers, especially steering, acceleration and braking emanate only from the driver.
  • Level 1 is referred to as assisted driving, as either steering or acceleration and braking are done automatically at times.
  • Known systems are z.
  • ACC Adaptive Cruise Control
  • level 2 the system temporarily performs both steering, acceleration and braking tasks.
  • This level of automation is called semi-automated driving. In levels 1 and 2, the driver must be able to intervene at any time so that he can take full control of the vehicle again at any time.
  • High Automated Driving is Level 3.
  • the vehicle drives automatically and the driver merely represents a fallback position if the system can not cope with a traffic situation.
  • the system will in such cases prompt the driver to intervene and to perform driving maneuvers appropriate to the traffic situation.
  • This is the Driver given a finite but beyond the typical human reaction time period. Therefore, the driver can temporarily turn his attention away from the traffic.
  • levels 4 and 5 the automated system takes complete control and the driver no longer has to intervene. Whereby in Level 4 this may only apply in certain traffic situations (eg motorway driving), while at Level 5 the vehicle can cope with any traffic situation and thus practical driving without driver can be on the way.

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Abstract

Selon l'objet de l'invention, la revendication concerne un procédé permettant de déterminer la maturité d'un produit au moyen de tests, un test comprenant l'exécution d'un scénario de test au moyen d'un environnement de test appliqué à un objet de test et aucun résultat n'étant obtenu pour au moins un test, le procédé comprenant les étapes d'élaboration des règles pour calculer une probabilité de réussite ou d'échec pour un test dont le résultat est inexistant, les règles s'appliquant aux résultats de tests obtenus ou attendus en tant que valeurs d'entrée et retournant des probabilités en tant que valeurs de sortie et comprenant le calcul de la probabilité qu'un test, dont le résultat est inexistant, sera réussi en appliquant au moins partiellement les règles prédéterminées et la détermination de la maturité du produit selon les probabilités obtenues au cours de l'étape précédente.
EP18720650.3A 2017-05-09 2018-05-08 Détermination de la maturité d'un système technique et en particulier d'un véhicule circulant de manière autonome Pending EP3622451A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP17170127.9A EP3401849A1 (fr) 2017-05-09 2017-05-09 Détermination de la maturité de produit d'un système technique
PCT/EP2018/061759 WO2018206522A1 (fr) 2017-05-09 2018-05-08 Détermination de la maturité d'un système technique et en particulier d'un véhicule circulant de manière autonome

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EP3622451A1 true EP3622451A1 (fr) 2020-03-18

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EP17170127.9A Ceased EP3401849A1 (fr) 2017-05-09 2017-05-09 Détermination de la maturité de produit d'un système technique
EP18720650.3A Pending EP3622451A1 (fr) 2017-05-09 2018-05-08 Détermination de la maturité d'un système technique et en particulier d'un véhicule circulant de manière autonome

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US (1) US20200074375A1 (fr)
EP (2) EP3401849A1 (fr)
CN (1) CN110603546A (fr)
WO (1) WO2018206522A1 (fr)

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DE102022134027A1 (de) * 2022-12-20 2024-06-20 Dspace Gmbh Computer-implementiertes Verfahren zum Bestimmen Algorithmusversions-kompatibler Test- und/oder Simulationsdaten und entsprechendes System

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US20200074375A1 (en) 2020-03-05
EP3401849A1 (fr) 2018-11-14
CN110603546A (zh) 2019-12-20
WO2018206522A1 (fr) 2018-11-15

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