Patent Publication Number: US-2017351562-A1

Title: Method for processing at least one piece of information in a networked system

Description:
FIELD 
     The present invention relates to a method for processing at least one information item in a networked system and to a networked system, and to a calculation unit and a computer program for carrying out the method. 
     BACKGROUND INFORMATION 
     When different information sources are networked, for example for the so-called “internet of things,” the result is that data and/or information items that are obtained from external sources are normally regarded as valid directly after they are transferred, and are checked for validity and plausibility only later on in processing. 
     For example, according to the CAN protocol it is a principle of information transfer between two control units of a motor vehicle that the transmitting control unit vouches for the validity of the transmitted data and/or information items. 
     Control units of this kind process large volumes of signals that derive from external sources, for example sensors or interfaces. Those signals are combined during processing steps, and the result is then used for decisions upon software execution or in order to apply control to actuating members. Digital signals (logical zero=invalid, logical one=valid) or discrete status variables (invalid, initialized, . . . , valid), which characterize the validity status, can be used partly in parallel with the variables used for that purpose in the software. 
     During initialization of the control units and in the event of a fault in the external sources (e.g. due to a sensor failure, delays in the interface, etc.), in real-time systems initial and substitute values are typically used for further data processing. 
     It is often not possible to determine, based on the input variables of a control unit, whether or not a signal or a value ascertained in that control unit is trustworthy at the current time, since no information regarding their validity exists for those variables. 
     A need therefore exists to demonstrate ways in which the validity of at least one information item can be taken into consideration upon processing thereof. 
     SUMMARY 
     According to the present invention, an example method for processing at least one information item in a networked system, and a networked system, as well as a calculation unit and a computer program for carrying out the method are provided. Advantageous embodiments are described herein. 
     In order to process at least one information item in a networked system to yield a result, the at least one information item is transferred from at least one source of the system to a receiver of the system. An interim data set having at least two variables is used, of which a first variable is allocated to a value of the at least one information item, and a further variable is allocated to the validity of the value. At least one evaluating step is carried out in the receiver, using the value and the validity, in order to determine a resultant data set having a resultant value and a resultant validity as a result of the processing of the at least one information item. The resultant validity thus makes available a value with which the validity of the resultant value can be assessed. This allows the result to be assessed as to whether or not it is valid, i.e. correct or trustworthy. The validity indicates, for example whether what was intended to be calculated or measured was in fact calculated or measured, or whether or not the information items obtained are also in fact correct. 
     Preferably, in a comparing step, the validity is compared with a minimum value, and the interim data set and/or the resultant data set are determined as a function of the comparison result. This makes it possible to react effectively, in the context of processing, to information items having insufficient validity. 
     Preferably a substitute value is used as a value of the at least one information item for the interim data set if the validity is less than or equal to the minimum value. It is thereby possible, for example, to prevent possibly erroneous values from leading to an undesired result, or to prevent possibly faulty values from being unrestrictedly further processed or forwarded as valid values. The substitute value can advantageously be a reliable standard value for the respective source. Alternatively, it can also be the most recent valid value, or an average of several most recent valid values. 
     The substitute value is preferably a value from a different source having a higher validity. If the validity is too low, information values of further sources are therefore evaluated so as therefore to find a value having a higher validity. 
     According to a further embodiment the resultant value is determined only when the value of the validity is greater than or equal to the minimum value. This ensures that values that are to be categorized as very uncertain, because of their low validity, cannot be further processed and thus lead to incorrect results. 
     According to an embodiment, a confidence value relating to the respective source is allocated by the receiver to the at least one source. A confidence value that does not derive from the source itself, and is thus source-independent, is thus used. Malfunctions of the source itself thus cannot lead to an erroneously high confidence value. 
     According to a further embodiment, the confidence value is used in order to determine the resultant validity. The confidence value is thus incorporated into the resultant validity, so that the resultant validity depends not only on the validity of the value but also on the confidence value of the source. A particularly accurate resultant validity is thus furnished. 
     According to a further embodiment, the validity can have values between one and zero. The value zero can be allocated to an absence of validity, and the value one to a validity verging on certainty. Validity values less than one and greater than zero characterize a lower or unknown validity of the data or of the result. This permits particularly simple processing of the values for the validity. 
     The confidence value(s) of the source can furthermore analogously have values between one and zero. The value zero can be allocated to an absence of validity, and the value one to a confidence verging on certainty. This permits particularly simple processing of the confidence values. 
     In terms of the validity of the result, this means that low validity values close to zero occur when data sources with an unknown origin for the original data or an unclear data source state are used, or because the data source itself has evaluated the validity of the transmitted values to be less than one. High validity values of one or close to one, on the other hand, occur when known sources with a good knowledge of the state, i.e. a high confidence value for the data source, are used, and because the data source itself has evaluated the validity of the transmitted values to be one or very close to one. 
     A networked system, for example an electrical system of a motor vehicle, has as a calculation unit a control unit that is configured to carry out, in particular by programmed execution, a method according to the present invention. At least one source can be embodied as a sensor of a motor vehicle. The processing reliability of information items in a vehicle electrical system can be appreciably increased with such a system, so that the electrical system is, for example, less sensitive to electromagnetic interference signals and/or to a failure or malfunctions of components of the electrical system, e.g. sensors. Improvements are therefore achieved specifically in the safety-relevant sector of motor vehicle electrical systems. 
     Implementation of the method in the form of software is also advantageous, since this entails particularly low cost, especially if an executing control unit is also used for further tasks and is therefore present in any case. Suitable data media for furnishing the computer program are, in particular, diskettes, hard drives, flash memories, EEPROMs, CD-ROM, DVDs, and many others. Downloading of a program via computer networks (internet, intranet, etc.) is also possible. 
     Further advantages and embodiments of the present invention are described below and are shown in the figures. 
     It is understood that the features discussed above and those yet to be explained below are usable not only in the respective combination indicated but also in other combinations or in isolation, without departing from the scope of the present invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present invention is schematically depicted in the figures on the basis of an exemple embodiment, and is described below with reference to figures. 
         FIG. 1  schematically depicts a networked system in which information items are processed to yield results. 
         FIG. 2  shows a value curve or signal curve for a first value of a first source, and a value curve for the first validity of the first value. 
         FIG. 3  shows a value curve or signal curve for a second value of a second source, and a value curve for the second validity of the second value. 
         FIG. 4  shows a curve for a resultant value and a curve for a resultant validity. 
     
    
    
       FIG. 1  depicts a networked system  2  for processing information items, which in the present exemplifying embodiment has a plurality of sources  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  and a receiver  6 . 
     DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS 
     In the present exemplifying embodiment, sources  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  can be intelligent or smart sensors or interfaces of an electrical system of a motor vehicle, while receiver  6  can be a control unit or a portion of a control unit of the motor vehicle. 
     From the respective sensors  4   1 ,  4   2 ,  4   3 , . . . ,  4   n , respective information items I 1 , I 2 , I 3 , . . . , I n  are transferred to control unit  6 , the respective information items I 1 , I 2 , I 3 , . . . , I n  each having a value x 1 , x 2 , x 3 , . . . , x n , for example a measured value of a sensor. 
     According to the embodiment shown, the respective validities v 1 , v 2 , v 3 , . . . , v n  relating to the values x 1 , x 2 , x 3 , . . . , x n  of information items I 1 , I 2 , I 3 , . . . , I n  are also transferred from the respective sensors  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  to control unit  6 . Information items I 1 , I 2 , I 3 , . . . , I n  can have a vector format. 
     While values x 1 , x 2 , x 3 , . . . , x n  corresponding to sensors  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  can assume any values, for example in accordance with the measurement range of a sensor, the validities v 1 , v 2 , v 3 , . . . , v n  can assume, for example, values between zero and one. The value zero can be allocated to an unknown or low validity v 1 , v 2 , v 3 , . . . , v n , and the value one to a validity v 1 , v 2 , v 3 , . . . , v n  verging on certainty. The validity v 1 , v 2 , v 3 , . . . , v n  indicates here whether, for example, what was intended to be measured was in fact measured, or whether or not the information items I 1 , I 2 , I 3 , . . . , I n  obtained are in fact correct or derive from a trustworthy source. 
     Sensors  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  can be embodied, for example, as intelligent or smart sensors or interfaces, and can have a self-diagnosis function or plausibility checking function. Sensors  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  can thus, for example, detect their own malfunction or recognize implausible values. Alternatively or additionally, sensors  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  can be embodied for a measured data evaluation that checks a series of measured values in terms of plausibility, for example whether the measured values fluctuate excessively within a predetermined time interval, or whether multiple values are plausible with respect to one another. 
     In the present exemplifying embodiment a CAN bus system is used to transfer the information items I 1 , I 2 , I 3 , . . . , I n  and validities v 1 , v 2 , v 3 , . . . , v n  from sensors  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  to control unit  6 . 
     In addition to processing of the information items, the latter can also be displayed to a user or driver of the vehicle, for example on a display device. If the information items are made available on a display device, then in addition to the useful information item I the allocated validity value of the information item can additionally be displayed. If the information is organized in a sequenced list, the presentation can be organized by descending validity, so that information items having the highest validity are displayed first, and those having the lowest validity are displayed last. 
     Vehicle electrical system  2 , sensors  4   1 ,  4   2 ,  4   3 , . . . ,  4   n , and/or control unit  6  have hardware and software components for this purpose and in order to process information items I 1 , I 2 , I 3 , . . . , I n . 
     Control unit  6  creates and uses an interim data set ZD having at least two variables. Of the two variables, a first variable is allocated to the value x 1 , x 2 , x 3 , . . . , x n  of the respective information item I 1 , I 2 , I 3 , . . . , I n , while a further variable is allocated to the validity v 1 , v 2 , v 3 , . . . , v n  of the respective value x 1 , x 2 , x 3 , . . . , x n . The interim data set ZD can have a vector format. 
     Control unit  6  is embodied or configured to execute an evaluating step so that, using values x 1 , x 2 , x 3 , . . . , x n  and their validities v 1 , v 2 , v 3 , . . . , v n , a resultant data set ED having a resultant value x E  and a resultant validity x E  are determined as a result. The resultant data set ED can have a vector format. 
     The evaluating step can encompass, for example, carrying out calculation operations using scalar variables, for example an addition involving the values x 1 , x 2 , and their validities v 1 , v 2 , of sensors  4   1 ,  4   2 : 
         I   1   ⊕I   2 =( x   1   ,v   1 )⊕( x   2   ,v   2 )=( x   1   +x   2   ,v   1   *v   2 ).
 
     In the context of addition, the values x 1 , x 2  are thus added, and their validities v 1 , v 2 , whose value is between zero and one, are multiplied, so that the value of the resultant validity v E  is always between zero and one. 
     The calculation operations can also encompass a multiplication involving the values x 1 , x 2 , and their validities v 1 , v 2 , of sensors  4   1 ,  4   2 : 
         I   1     I   2 =( x   1   ,v   1 ) ( x   2   ,v   2 )=( x   1   *x   2   ,v   1   *v   2 ). 
     In the context of multiplication, the values x 1 , x 2  are thus multiplied, and their validities v 1 , v 2 , whose value is between zero and one in this case as well, are multiplied, so that here as well, the value of the resultant validity v E  is always between zero and one. 
     According to further preferred embodiments, the information items I 1 , I 2 , I 3 , . . . , I n  can additionally have one or more further elements and can have, for example, the following vector format: 
         I   n =( x   n   ,v   n   ,q   n   ,s   x   ,n   x   ,r   x ), 
     where q n  can be a confidence value relating to the respective source, e.g., relating to a known source, a sensor value, an information item from a third-party source (e.g., government information, company information), etc., or a value between zero for an unknown source and one for a trustworthy source. A confidence value q 1 , q 2 , q 3 , . . . , q n  is thus allocated by the receiver of the respective source  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  and is used to determine the resultant validity v E . 
     The evaluating step can encompass, for example, any calculation operations, for example any mathematical functions relating to the values x 1 , x 2 , . . . , x n  and their validities v 1 , v 2 , . . . , v n  and confidence values q 1 , q 2 , . . . , q n  of sources  4   1 ,  4   2 ,  4   3 , . . . ,  4   n . The result represents a resultant value x e  as a function f x  of input values x 1 , x 2 , . . . , x n  and of their validities v 1 , v 2 , . . . , v n  confidence values q 1 , q 2 , . . . , q n , and a resultant validity v e  as a function f v  of the input validities v 1 , v 2 , . . . , v n  and confidence values q 1 , q 2 , . . . , q n : 
         F ( I   1   ,I   2   , . . . ,I   n )= F (( x   1   ,v   1   ,q   1 ),( x   2   ,v   2   ,q   2 ), . . . ,( x   n   ,v   n   ,q   n ))==( f   x ( x   1   ,v   1   ,q   1   ,x   2   ,v   2   ,q   2   , . . . ,x   n   ,v   n   ,q   n ), f   v   x ( x   1   ,v   1   ,q   1   ,x   2   ,v   2   ,q   2   , . . . ,x   n   ,v   n   ,q   n )) 
     In addition, s x  can assume, for example, values which denote respective information items I 1 , I 2 , I 3 , . . . , I n  that are obtained for the first time, obtained several times, confirmed by further sources, calculated, and/or valid. 
     In addition, n x  can denote the number of utilized sources  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  which was used in order to determine the resultant validity v E . 
     Lastly, r x  can denote the number of sub-steps, having evaluating steps and optionally further processing steps, that were carried out starting from information items I 1 , I 2 , I 3 , . . . , I n  up to the current result. 
     Receiver  6  can furthermore be embodied to carry out a comparing step, for example before the evaluating step. In the comparing step, a value of one of the validities v 1 , v 2 , v 3 , . . . , v n  is compared with a minimum value. The evaluating step for determining the resultant value x E  is performed only when the value of the validity v 1 , v 2 , v 3 , . . . , v n  is greater than or equal to the minimum value. The comparing step ensures that, for example, a value x 1  that is to be categorized as very uncertain, based on its low validity v 1 , is not further processed and thus cannot lead to incorrect results. 
     In this case a fault signal can be generated, or the method is continued or repeated using a substitute value (e.g., standard value, average, moving average of earlier values having sufficient validity, etc.), as described below. For example, receiver  6  can be embodied to carry out a supplementing step, for example before the evaluating step but after the comparing step, the supplementing step being executed, for example, when the value of one of the validities v 1 , v 2 , v 3 , . . . , v n  is less than or equal to the minimum value, i.e. is to be categorized as very uncertain. In the supplementing step, further information items I 1 , I 2 , I 3 , . . . , I n  from further sources  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  are read in by receiver  6 , or transferred to receiver  6  from the further sources  4   1 ,  4   2 ,  4   3 , . . . ,  4   n , and then evaluated by receiver  6  in order to determine a further validity v 1 , v 2 , v 3 , . . . , v n  for the values x 1 , x 2 , x 3 , . . . , x n  that were read in or transferred. 
     What can possibly be achieved by way of the supplementing step is that the value of the further validity v 1 , v 2 , v 3 , . . . , v n  is greater than the threshold value, so that the resultant value x E  is then also determined. 
     The evaluating step and the optional comparing steps and supplementing steps can be sub-steps of a method, having multiple steps, for processing information items  4   1 ,  4   2 ,  4   3 , . . . ,  4   n  in a networked system  2  to yield a result. Interim resultant data sets having interim resultant values and interim resultant validities can be created during each sub-step and are updated again in the subsequent sub-step. 
     Lastly, receiver  6  can be embodied to create a sequenced information item list. The sequenced information item list IL has a plurality of data sets, each data set having a value x n  and the validity v n  thereof: 
       IL={( x   1   ,v   1 ),( x   2   ,v   2 ), . . . ,( x   n   ,v   n )} 
     The data sets can be disposed in the sequenced information list IL, for example, in accordance with the magnitudes of the values of the respective validity v 1 , v 2 , v 3 , . . . , v n . The value x 1  having the highest validity v 1  is thus in first place, followed by the value x 2  having the second-highest validity v 2 , and so forth. 
     A sequenced information list IL of this kind can be created in particular when, for one of the values x n , its validity v n  is greater than or equal to the minimum value, and that value x n  with its validity v n  would therefore not be taken into account in further processing. 
     For example, the sequenced information list IL with its individual data sets (i.e. value x n  and validity v n ) can be displayed to a user in accordance with its validity, for example in a sequence that begins with the value x n  having the highest validity v n , followed by the value x 2  having the second-highest validity v 2 , and so forth. 
     A method sequence will now be explained with additional reference to  FIGS. 2 to 4 . 
       FIG. 2  shows a curve m 1  for measured values as captured by sensor  4   1 . This is, for example, a sensor having its own measured value conditioning system (smart sensor), which performs a filtration of the measured value curve, for example a smoothing, and, in the example shown, outputs the smoothed curve for first values x 1 . The sensor can be, for example, a rotation angle measuring device that outputs a normalized measured signal [−1, . . . , +1], for example in accordance with a sine relationship. 
       FIG. 2  furthermore shows a curve v 1  for the validity of values x 1 . A validity v, which describes the certainty or accuracy of the value, is allocated by sensor  4   1  to each value x that is to be outputted. The validity is between zero (uncertain) and one (certain), and can be ascertained by the sensor, for example, based on internal testing routines. 
     What is depicted is that at the beginning, sensor  4   1  requires a first minimum time period M 1 , for example until a first zero crossing or the like, in order to furnish the first information item I 1 . Sensor  4   1  accordingly outputs at the beginning, during the time span M 1 , the value x 1 =0 and validity v 1 =0. Also depicted is the fact that during a later time span T 1 , an uncertainty exists in the measured value conditioning, and sensor  4   1  accordingly reduces the validity to v 1 =0.3. 
     The values x 1  and validities v 1  are transferred from sensor  4   1  to control unit  6 . In the control unit, an interim data set ZD is created therefrom for further processing. Control unit  6  is furthermore embodied to carry out a comparing step before the evaluating step. In the comparing step, the validity v 1  is compared with a minimum value that, in the present example, is equal to more than 0.3. If the validity does not exceed the minimum value, then in accordance with the embodiment depicted here, calculation occurs in the control unit using a substitute value x E1 =0. This can be, for example, a reliable standard value for the respective sensor. It is thereby possible to prevent possibly erroneous values from leading to an undesired result. 
       FIG. 3  depicts a similar case for a sensor  4   2  having a curve m 2  for measured values, a curve x 2  for second values, and a curve v 2  for second validities of the first value x 1 . 
     What is depicted is that at the beginning, sensor  4   2  requires a second minimum time period M 2  in order to furnish the second information item I 1 . Sensor  4   2  accordingly outputs at the beginning, during the time span M 2 , the value x 2 =1 and validity v 2 =0. Also depicted is the fact that during a later time span T 2 , an uncertainty exists in the measured value conditioning, and sensor  4   2  accordingly reduces the validity to v 2 =0.9. 
     The values x 2  and validities v 2  are transferred from sensor  4   2  to control unit  6 . In the control unit, an interim data set ZD is created therefrom for further processing. Control unit  6  is furthermore embodied to carry out a comparing step before the evaluating step. In the comparing step, the validity v 2  is compared with a minimum value that, in the present example, is equal to more than 0.9. If the validity does not exceed the minimum value, then in accordance with the embodiment depicted here, calculation occurs in the control unit using a substitute value x E2 =1. This can be, for example, a reliable standard value for the respective sensor. It can also be the most recent valid value or an average of several most recent valid values. 
     Control unit  6  is embodied or configured to perform an evaluating step in order to determine, using the values x 1  and x 2  or the respective substitute values x E1  and x E2  (the alternatives are represented by x (E)i ) and their validities v 1  and v 2 , as a result of multiplying the two information items I 1  and I 2 , a resultant data set ED having a resultant value x E  and a resultant validity v E . An evaluating step of this kind is illustrated in  FIG. 4 , in which a multiplication of the values x 1  and x 2  is carried out. 
     Conventionally, the product x 1 *x 2  would be calculated for this purpose. According to the embodiment of the invention which is presented, however, the validity is taken into consideration, as follows: 
         I   1     I   2 =( x   (E)1   ,v   1 ) ( x   (E)2   ,v   2 )=( x   (E)1   *x   (E)2   ,v   1   *v   2 ). 
     It is evident that the resultant validity v E , constituting the product of validities v 1 , v 2 , is reduced, i.e. is less than one, during the first minimum time period M 1 , the second minimum time period M 2 , the first time interval T 1 , and the second time interval T 2 , while between the second minimum time period M 2  and the first time interval T 1 , between the first time interval T 1  and the second time interval T 2 , and after the second time interval T 2 , the resultant validity v E  is one. 
     The resultant value x E  is thus reliable and trustworthy between the second minimum time period M 2  and the first time interval T 1  and after the first time interval T 1 , and not trustworthy (v e =0) or partly trustworthy (0&lt;v e &lt;1) in the other time intervals. 
     What is therefore available with the resultant validity v E  is a value with which the validity of the resultant value x E  can be assessed. The resultant validity v E  indicates the trustworthiness of the processing result in the control unit.