Method and device for operating vehicle, and vehicle system

Abstract

The embodiment of the invention relates to a method and device for operating a vehicle and a vehicle system. The invention relates to a method for operating a vehicle. In the reading step, a plurality of redundant sensor signals from a plurality of redundant vehicle sensors are read. In the calculation step, a variance is calculated for each sensor signal. In the ascertaining step, a reference signal is ascertained using a sensor signal variance. In the generating step, a sensitivity index is generated for each sensor signal, the variance of the reference signal is divided by the variance of the corresponding sensor signal, and the sensitivity index represents the sensitivity error of the sensor signal. In an execution step, a comparison of the sensitivity indicator with at least one evaluation threshold value is performed to produce an evaluation result for each sensor signal. In the determination step, evaluation parameters of the sensor signal are determined on the basis of the evaluation result. In the providing step, output data containing at least the evaluation parameter is provided for output to the at least one vehicle device via the interface.

Description

TECHNICAL FIELD

[0001] The invention is based on a device or a method according to the invention. The content of the invention also relates to a computer program. BACKGROUND

[0002] Many applications, like autonomous driving (AD) functions, can require the use of reliable sensor signals. Therefore, typically redundant IMU (inertial measurement unit) sensor architectures, like three angular rate sensors mounted on the same printed circuit board, measuring the same physical event, can be used to identify sensor failures by monitoring the signal deviation between the redundant signals. The valid redundant signals are combined (fused) or a selection algorithm is executed to select the best final signal from all possibilities in terms of functional integrity and signal accuracy. These redundant sensor groups can have different characteristics. For example, some sensors can have a larger sensitivity error than others, for example. SUMMARY

[0003] In this context, a method according to the invention, a device using the method, a vehicle system for a vehicle and a corresponding computer program are proposed with the solution presented here. Advantageous extensions and improvements of the device of the invention can be achieved by the measures listed in the dependent claims.

[0004] According to embodiments, in particular a variance-based sensitivity error monitoring for redundant vehicle sensors, for example inertial sensors, can be provided for evaluating the sensor signals and for sensitivity detection by using the variance or signal variance. This can be advantageous for autonomous driving applications or for autonomous driving applications that can require the use of very precise and reliable sensor signals. For example, the precision and reliability of the final signal can be improved in that the sensitivity error level of the sensor signals can be considered when selecting or fusing the final signal for an autonomous driving application. In other words, in particular a monitoring algorithm can be provided that uses the signal variance to identify the sensitivity error of the redundant signals and / or uses this information when deciding or fusing the redundant signals. Here, the precision of the final signal can be improved using those signals that have a smaller error. In general, a safety threshold can be set not only for the offset error but also for the sensitivity deviation. Error patterns determined by the sensitivity can also be monitored in order to react accordingly when the sensitivity error is above a set safety threshold. The reaction can consist, for example, in setting the signal as invalid when a diagnostic threshold is exceeded.

[0005] The invention provides a method for operating a vehicle, wherein the method has the following steps:

[0006] - reading a plurality of redundant sensor signals from a plurality of redundant vehicle sensors of the vehicle via an interface;

[0007] - calculating a variance for each sensor signal, wherein the variance is calculated as a moving variance over a predefined time period;

[0008] - deriving a reference signal by using the variances of the sensor signals;

[0009] - generating a sensitivity index for each sensor signal, wherein for each sensitivity index the variance of the reference signal is divided by the variance of the corresponding sensor signal, wherein the sensitivity index represents a sensitivity error of the sensor signal;

[0010] - performing a comparison of the sensitivity index with at least one evaluation threshold to generate an evaluation result for each sensor signal;

[0011] - determining an evaluation parameter for the sensor signals depending on the evaluation result; and

[0012] - providing output data comprising at least the evaluation parameter for outputting to at least one vehicle device for automated driving by an interface for operating the vehicle.

[0013] The vehicle can be a motor vehicle, such as a passenger car, a truck or other commercial vehicle, a robot, etc. The vehicle can be a vehicle for at least partially automated driving or a vehicle for at least partially automated travel. All vehicle sensors can have the same design, the same measured variable and additionally or alternatively the same detection principle. Each vehicle sensor can be configured to output or provide a sensor signal. The method can process a signal value, a signal level, an instantaneous value or a signal waveform of the sensor signal. In the step of reading, the sensor signal can be low-pass filtered. In the step of deriving, the reference signal can be derived as a median of the variances. A sensitivity index can be generated for each sensor signal. An evaluation parameter can be determined for each sensor signal. The vehicle device for automated driving can be a controller, a part of a controller, a plurality of controllers and additionally or alternatively at least one actuator for longitudinal guidance and / or lateral guidance of the vehicle. Automated driving can be understood as at least partially automated driving.

[0014] According to one embodiment, in the step of performing, the at least one evaluation threshold can be adjusted depending on a temperature and additionally or alternatively other physical environmental conditions, or be constant. This implementation provides the advantage that suitable evaluation parameters can be adjusted depending on the actually prevailing conditions.

[0015] In the step of determining, the evaluation parameter determined in the step of determining can comprise, for each sensor signal, a valid state, an invalid state, and additionally or alternatively a weight value relating to a subsequent use of the sensor signal. This embodiment has the advantage that an undesired signal level of a sensor signal can be caused to respond appropriately, so that a sensor signal with a lower reliability can be taken into account less in further processing accordingly.

[0016] In this case, the sensitivity index generated in the step of generating represents, at a magnitude of 1, the absence of a sensitivity error of the corresponding sensor signal, at a magnitude between 0 and 1, a sensitivity error of signal attenuation of the corresponding sensor signal and at a magnitude greater than 1, a sensitivity error of signal enhancement of the corresponding sensor signal. Thus, it can be determined simply and reliably for each sensor signal, depending on the sensitivity index, whether a sensitivity error exists and, if so, its type.

[0017] In addition, the evaluation parameter determined in the step of determining can comprise, for each sensor signal, a valid state, an invalid state, and additionally or alternatively a weight value relating to a subsequent use of the sensor signal. This embodiment has the advantage that an undesired signal level of a sensor signal can be caused to respond appropriately, so that a sensor signal with a lower reliability can be taken into account less in further processing accordingly.

[0018] In addition, a determination rule can be used in the step of determining, according to which the evaluation result is evaluated in terms of a magnitude relationship between the sensitivity index and the at least one evaluation threshold value and additionally or alternatively in terms of a temporal relationship. For example, according to the determination rule, it can be required that the sensitivity index exceeds the at least one evaluation threshold value by a predefined magnitude and additionally or alternatively for a predefined period of time, in order to determine a predefined evaluation parameter of the relevant sensor signal. This embodiment offers the advantage that actually relevant signal deviations can be reliably distinguished and identified from unimportant signal deviations.

[0019] According to one embodiment, a determination rule can be used in the step of determining, according to which a counter is incremented or decremented depending on the evaluation result. In this case, the evaluation parameter can be determined depending on a comparison of the counter with a predefined or adjustable limit value for the accumulation. This embodiment offers the advantage that a history of the sensor signal can be taken into account and thus a reliable decision can be made with regard to the sensor signal quality. In addition, the difference between the current counter and the limit value can be used as an indicator which can be incorporated into the evaluation parameter.

[0020] In the step of providing at least one sensor signal, output data comprising the at least one sensor signal can also be provided. Here, a relevant evaluation parameter can be assigned to each sensor signal. Additionally or alternatively, the sensor signals can be fused into a combined sensor signal by using the evaluation parameter.

[0021] The method can be implemented, for example, in software or hardware or in a mixture of software and hardware, for example in a controller or a device.

[0022] The solution presented here also provides a device which is designed to carry out, to operate or to implement the steps of a variant of the method presented here in a corresponding apparatus. Through these implementation variants of the invention in the form of a device, the tasks presented by the invention can also be solved quickly and efficiently.

[0023] To this end, the device can have at least one computing unit for processing signals or data, at least one storage unit for storing signals or data, at least one interface to a sensor or to an actuator for reading sensor signals from the sensor or for outputting data or control signals to the actuator, and / or at least one communication interface for reading or outputting data embedded in a communication protocol. The computing unit can be, for example, a signal processor, a microcontroller or the like, wherein the storage unit can be a flash memory or a magnetic storage unit. The communication interface can be designed to read or output data in a wireless and / or wired connection, wherein a communication interface which can read or output wired data can read this data from or output it to a corresponding data transmission line, for example in an electrical or optical manner.

[0024] The device can currently be understood as an electrical device which processes sensor signals and outputs control and / or data signals therefrom. The device can have an interface which can be implemented in hardware and / or software. In a hardware implementation, the interface can be, for example, part of a so-called ASIC system which contains the various functions of the device. However, the interface can also be a separate integrated circuit or at least partially consist of discrete components. In a software implementation, the interface can be, for example, a software module which exists together with other software modules on a microcontroller.

[0025] The invention also proposes a vehicle system for a vehicle, wherein the vehicle system has the following features:

[0026] Embodiments of the device mentioned here;

[0027] a plurality of redundant vehicle sensors; and

[0028] at least one vehicle apparatus for automated driving, wherein the device is connected in a signal-transmitting manner to the plurality of redundant vehicle sensors and to the at least one vehicle apparatus for automated driving.

[0029] In connection with such a vehicle system, embodiments of the device referred to herein can advantageously be utilized or used for operating the vehicle and especially for providing reliable and accurate sensor signals for the operation of the vehicle.

[0030] It is likewise advantageous that a computer program product or a computer program with program code, which can be stored on a machine-readable carrier or storage medium, for example a semiconductor memory, a hard disk memory or an optical memory, and for carrying out, implementing and / or operating the steps of the method according to one of the above embodiments, especially when the program product or program is executed on a computer or device. BRIEF DESCRIPTION OF DRAWINGS

[0031] Embodiments of the solution proposed herein have been illustrated in the attached drawings and are set forth in more detail in the following description. The drawings show:

[0032] Figure 1 a schematic view of a vehicle with a vehicle system and a device according to embodiments;

[0033] Figure 2 a flow chart showing an embodiment of a method for the operation of a vehicle;

[0034] Figure 3 a functional block diagram showing signal processing in connection with Figure 1 a device and / or Figure 2 a method;

[0035] Figure 4 a schematic view showing signal evaluation in connection with Figure 1 a device and / or Figure 2 a method and / or Figure 3 signal processing; DETAILED DESCRIPTION

[0036] In the following description of preferred embodiments of the application, identical or similar elements shown in the various figures are designated with the same or similar reference numerals, wherein a repeated description of these elements is omitted.

[0037] Figure 1 a schematic view of a vehicle 100 with a vehicle system 101 and a device 110 according to embodiments. The vehicle 100 is a motor vehicle, for example a passenger car, a truck or other commercial vehicle. The vehicle 100 is designed as a vehicle for at least partially autonomous driving or as a vehicle for at least partially automated driving. For the vehicle 100, Figure 1The illustration shows a vehicle system 101, for example, only showing multiple redundant vehicle sensors 102-1, 102-2, 102-N, for example, only showing a vehicle device 106 for autonomous driving or at least partial autonomous driving, and a device 110 or operating device 110 for the operation of the vehicle 100. The vehicle system 101 includes multiple redundant vehicle sensors 102-1, 102-2, 102-N, at least one vehicle device 106 for autonomous driving, and device 110 or operating device 110. Here, device 110 is signal-transmittingly connected to the multiple redundant vehicle sensors 102-1, 102-2, 102-N and to the at least one vehicle device 106 for autonomous driving.

[0038] Although only three vehicle sensors 102-1, 102-2, and 102-N are shown exemplarily in the accompanying drawings, the number of vehicle sensors 102-1, 102-2, and 102-N can be any value N, and N is at least 2. The redundant vehicle sensors 102-1, 102-2, and 102-N all have the same design, the same measurement parameters, and / or the same detection principle. For example, one type of redundant vehicle sensor 102-1, 102-2, and 102-N is an inertial sensor or accelerometer for measuring acceleration values ​​along at least one axis and / or about at least one axis. Each vehicle sensor 102-1, 102-2, and 102-N is designed to output or provide a sensor signal 105. Therefore, vehicle sensors 102-1, 102-2, and 102-N are designed to output or provide multiple or N redundant sensor signals 105, corresponding to the number N of vehicle sensors 102-1, 102-2, and 102-N.

[0039] Device 110 or operating device 110 includes a reading device 112, a computing device 113, a seeking device 114, a computing device 116, an execution device 118, a determining device 120, and a providing device 122. Device 110 also includes an input interface 111 and an output interface 124. Device 110 is connected to multiple vehicle sensors 102-1, 102-2, and 102-N via the input interface 111 for signal transmission. Device 110 is connected to vehicle device 106 via the output interface 124 for signal transmission. The input interface 111 and the output interface 124 can be physically implemented as separate interfaces or combined interfaces.

[0040] Input device 112 is designed to read multiple or N redundant sensor signals 105 from vehicle sensors 102-1, 102-2, 102-N via input interface 111. Furthermore, input device 112 is designed to forward sensor signals 105 to all other devices of device 110 as needed.

[0041] The computing device 113 is designed to compute a variance Var for each sensor signal 105. More specifically, the computing device 113 is designed to compute the variance Var as a sliding variance over a predefined time period.

[0042] The deriving device 114 is designed to derive the reference signal 115 by using the variances Var of the sensor signals 105. Furthermore, the deriving device 114 is designed to forward the reference signal 115 to the at least generating device 116.

[0043] The generating device 116 is arranged to generate a sensitivity index 117 for each sensor signal 105. To generate each sensitivity index 117, the generating device 116 is designed to divide the variance of the reference signal 115 by the variance Var of the corresponding sensor signal 105. The thus generated sensitivity index 117 represents a sensitivity error of the sensor signal 105. Furthermore, the generating device 116 is designed to forward the sensitivity index 117 to the at least performing device 118. In particular, the sensitivity index 117 here represents a non-existing sensitivity error at a magnitude of 1, a sensitivity error of a signal attenuation at a magnitude between 0 and 1, and a sensitivity error of a signal enhancement of the corresponding sensor signal 105 at a magnitude greater than 1.

[0044] The performing device 118 is designed to perform a comparison of the sensitivity index 117 with at least one evaluation threshold in order to generate an evaluation result 119 for each sensor signal 105. The performing device 118 is also designed to forward the evaluation result 119 to the at least determining device 120. According to one embodiment, the performing device 118 is designed to adjust or change the at least one evaluation threshold depending on the temperature and / or other physical environmental conditions. Alternatively, the performing device 118 is designed to keep the at least one evaluation threshold constant. Additionally or alternatively, the performing device 118 is designed to compare the sensitivity index 117 with a first evaluation threshold and with a second evaluation threshold for this purpose. Here, the first evaluation threshold is related to a signal enhancement and the second evaluation threshold is related to a signal attenuation. These thresholds will be discussed in more detail with reference to the subsequent figures.

[0045] The determining device 120 is designed to determine an evaluation parameter 121 of the sensor signals 105 from the evaluation result 119. Furthermore, the determining device 120 is designed to forward the evaluation parameter 121 to the providing device 122. The evaluation parameter 121 comprises, for example, for each sensor signal 105, a valid state, an invalid state and / or a weighting value which is relevant for or used for a subsequent use of the sensor signal 105. According to one embodiment, the determining device 120 is designed to determine the evaluation parameter 121 using a determination rule according to which the evaluation result 119 is evaluated in terms of a magnitude relationship and / or a time relationship between the sensitivity indicator 117 and at least one evaluation threshold. Additionally or alternatively, for this purpose the determining device 120 is designed to determine the evaluation parameter 121 using a determination rule according to which a counter is incremented or decremented depending on the evaluation result 119. Here, the determining device 120 is designed to determine the evaluation parameter 121 from a comparison of the counter with a predefined or adjustable limit value for the accumulation.

[0046] The providing device 122 is designed to provide output data 125 which comprises at least the evaluation parameter 121 for output to an output interface 124 of at least one vehicle device 106 for the automated driving of the vehicle 100. According to one embodiment, the providing device 122 is designed to provide output data 125 which also comprises at least one sensor signal 105. Here, the providing device 122 is designed to assign a respective evaluation parameter 121 to each sensor signal 105. Additionally or alternatively, for this purpose the providing device 122 is designed to fuse the sensor signals 105 into a combined sensor signal by using the evaluation parameters 121.

[0047] Figure 2 A flowchart of an embodiment of a method 210 for the operation of a vehicle is shown. The method 210 for the operation can be performed in conjunction with or using the device in Figure 1 or a similar device. The method 210 for the operation can also be implemented to operate the vehicle in Figure 1 or a similar vehicle. The method 210 for the operation comprises a step 212 of reading, a step 213 of calculating, a step 214 of deriving, a step 216 of generating, a step 218 of executing, a step 220 of determining and a step 222 of providing.

[0048] In a reading step 212, a plurality of redundant sensor signals is read from a plurality of redundant vehicle sensors of the vehicle via the interface. Subsequently, in a computing step 213, a variance is computed for each sensor signal, in particular as a sliding variance over a predefined time period. Subsequently, in a deriving step 214, a reference signal is derived by using the variances of the sensor signals. Subsequently, in a generating step 216, a sensitivity indicator representing a sensitivity error of the sensor signal is generated for each sensor signal, wherein for each sensitivity indicator the variance of the reference signal is divided by the variance of the corresponding sensor signal. Subsequently, in a performing step 218, a comparison of the sensitivity indicators with at least one evaluation threshold is performed to generate an evaluation result for each sensor signal. Subsequently, in a determining step 220, an evaluation parameter of the sensor signals is determined depending on the evaluation results. Finally, in a providing step 222, output data comprising at least the evaluation parameter is provided for outputting to at least one vehicle device for automated driving via the interface in order to operate the vehicle.

[0049] With reference to the above figures, the sensitivity indicator 117 is again discussed in other words and summarized. It is assumed that each signal S and each sensor signal 105 can be modeled as follows: S = k * Sref + Offset. Here, k represents a sensitivity error of the signal S; for example, k = 1.1 means an enhancement error of the signal S of 10%. The offset is a "constant" error that the signal can have. It is noted that in this model the reference signal Sref or the reference signal 115 is considered as an error-free ideal signal. By considering this model, the variance Var of the signal, and subsequently k 2 the factor or sensitivity index 117, as follows, for example for the first signal S1, is calculated as follows: S1 = k * Sref + Offset1; Var(S1) = Var(k * Sref + Offset1); Var(S1) = k2Var(Sref). It is noted that the offset between the signals does not affect the variance, which means: k 2 = Var(Sref) / Var(S1). Here, k can be used as an approximation of the sensitivity error (proportional error) of S1 with respect to Sref. It is noted here that in implementations, k 2 can be used as the sensitivity indicator 117 to avoid square root calculations. Thus, k 2 the factor is used as the sensitivity indicator 117, in particular, in order to identify a sensitivity error of the signal or each sensor signal 105. If the calculated k 2 factor or sensitivity indicator 117 is here 1, this means that there is no sensitivity error in the signal. Whereas k 2 the factor or sensitivity indicator 117 is between 0 and 1, this shows an attenuation of the signal. If this factor or sensitivity indicator 117 is greater than 1, an enhancement error of the signal can be assumed.

[0050] Figure 3 a device and / or a method in Figure 1 a device and / or a method in Figure 2 A functional block diagram 300 of the signal processing related to a device and / or a method in is shown. Here N sensor signals 105 are shown, here exemplarily only three sensor signals 105-1, 105-2 and 105-3 of three sensors, a low pass filter 312 (20 Hz) for low pass filtering the sensor signals 105-1, 105-2 and 105-3, a computing means 113 for computing the variances Var1, Var2 and Var3 or a corresponding variance Var for each sensor signal 105-1, 105-2 and 105-3, e.g. within a time window of 250 ms, an extracting means 114 for extracting the reference signal 115, in particular as a median, a combination block for threshold comparison and evaluation, including a generating means 116, an executing means 118, a determining means 120 and a providing means 122, wherein the output signal from the combination block for threshold comparison and evaluation is an output data 125, here e.g. including three evaluation parameters 121-1, 121-2 and 121-3 related to the sensor signal validity, and three sensitivity error estimates 321-1, 321-2 and 321-3 for the sensor signals, and for condition computation by using additional information 332, e.g. temperature and / or other physical environmental conditions, and for activating / deactivating the block 334 for the threshold comparison and evaluation block.

[0051] In other words, Figure 3 The main functional modules or main flow of the sensitivity monitoring are shown. First, the redundant sensor signals 105-1, 105-2 and 105-3 (in this example only three signals are considered) are low pass filtered by means of a low pass filter 312 to mainly eliminate noise which the signals can have. Subsequently, a sliding variance window is computed for each signal by means of a computing means 113. From all available variances Var1, Var2 and Var3, a reference signal 115 is computed by means of an extracting means 114, e.g. a median. Each signal variance Var1, Var2 and Var3 is used in a combination block for threshold comparison and evaluation together with the variance of the reference signal. Here, a sensitivity index or factor k 2 is computed for each sensor signal 105-1, 105-2 and 105-3 based on the variances Var1, Var2 and Var3. This factor or sensitivity index is compared to a threshold or evaluation threshold to determine whether at least one of the sensor signals 105-1, 105-2 and 105-3 should be set to invalid. The sensitivity index or k 2The factors can be used to estimate the actual sensitivity error of the sensor signals 105-1, 105-2 and 105-3; see for this the sensitivity error estimates 321-1, 321-2 and 321-3.

[0052] Figure 4 A schematic diagram 400 is shown which is related to the signal evaluation of the device and / or the method in Figure 1 and / or the signal processing in Figure 2 and / or the signal processing in Figure 3 . Figure 4 In the left side of the diagram in Figure 4 In the right side of the diagram in

[0053] In the functional block diagram the combination block for threshold comparison and evaluation in Figure 3 is shown in more detail. The variances Var1, Var2 and Var3 and the reference signal 115 are shown as input signals of the generating means 116; the sensitivity indicators 117-1, 117-2 and 117-3 are shown as output signals of the generating means 116 and as input signals of the common block comprising the performing means 118 and the determining means 120; and the evaluation parameters 121-1, 121-2 and 121-3 are shown as output signals of the common block. In addition, the additional information 332 and the calibration parameters 432, e.g. the threshold values, are shown as further input signals of the common block.

[0054] In the diagram, the time t is plotted on the horizontal axis in each diagram section, wherein the sensitivity indicators 117 are plotted on the vertical axis in the first diagram section and the evaluation thresholds 418A and 418B are plotted, and wherein in the second diagram section the counters 417 according to the comparison of the sensitivity indicators 117 with the evaluation thresholds 418A and 418B are plotted on the vertical axis and the limits 420X are plotted.

[0055] In other words, Figure 4 The k 2 factors or sensitivity indicators 117 are compared with the thresholds or evaluation thresholds 418A and 418B. The first evaluation threshold 418A (AmpThd) for identifying a larger enhancement and the second evaluation threshold 418B (AttThd) for identifying a larger attenuation can be constant or a function of the environment or context, e.g. the temperature. If k 2If the factor or sensitivity indicator 117 exceeds the range defined by the evaluation thresholds 418A and 418B (AmpThd and AttThd), the counter 417 is incremented or, respectively, increased. If the sensitivity indicator 117 is within the range, the counter 417 is decremented or, respectively, decreased. If the counter 417 reaches a limit value 420X or a counter threshold (Thd_Counter), as symbolically shown for example in the figure, the respective sensor signal can be set to be invalid. It should be noted that the sensitivity indicator 117 and the counter value 417 can be used in the fusion of the final signal to reduce the evaluation of sensor signals with sensitivity errors.

[0056] If an embodiment contains a “and / or” connection between a first feature and a second feature, it is to be understood that according to one implementation the embodiment has both the first feature and the second feature; and according to another implementation the embodiment has either only the first feature or only the second feature.

Claims

1. A method (210) for operating a vehicle (100), wherein the method (210) has the following steps: - reading (212) a plurality of redundant sensor signals (105) from a plurality of redundant vehicle sensors (102-1, 102-2, 102-N) of the vehicle (100) by means of an interface (111); - calculating (213) a variance (Var) for each sensor signal of the sensor signals (105), wherein the variance (Var) is calculated as a sliding variance over a predefined time period; - deriving (214) a reference signal (115) by using the variances (Var) of the sensor signals (105); - generating (216) a sensitivity index (117) for each sensor signal of the sensor signals (105), wherein for each sensitivity index (117) the variance (Var) of the reference signal (115) is divided by the variance (Var) of the corresponding sensor signal of the sensor signals (105), wherein the sensitivity index (117) represents a sensitivity error of the sensor signal (105); - performing (218) a comparison of the sensitivity index (117) with at least one evaluation threshold (418A, 418B) to generate an evaluation result (119) for each sensor signal of the sensor signals (105); - determining (220) an evaluation parameter (121) of the sensor signals (105) depending on the evaluation result (119); and - providing (222) output data (125) comprising at least the evaluation parameter (121) for outputting to at least one vehicle device (106) for autonomous driving by means of an interface (124) in order to operate the vehicle (100).

2. The method (210) of claim 1, wherein In the step of performing (218), the at least one evaluation threshold (418A, 418B) is set depending on a temperature and / or other physical environmental conditions or is constant.

3. The method (210) according to any one of the preceding claims, characterized by, In the step of performing (218), the sensitivity index (117) is compared with a first evaluation threshold (418A) and with a second evaluation threshold (418B), wherein the first evaluation threshold (418A) is related to a signal enhancement and wherein the second evaluation threshold (418B) is related to a signal attenuation.

4. The method (210) according to any one of the preceding claims, characterized by, The sensitivity index (117) generated in the step of generating (216) represents a non-existing sensitivity error of the corresponding sensor signal (105) at a magnitude of 1, a signal attenuation of the corresponding sensor signal (105) at a magnitude between 0 and 1 and a signal enhancement of the corresponding sensor signal (105) at a magnitude greater than 1.

5. The method (210) according to any of the preceding claims, characterized by, The evaluation parameter (121) determined in the step of determining (220) comprises for each sensor signal (105) a valid state, an invalid state and / or a weight value related to a subsequent use of the sensor signal (105).

6. The method (210) according to any one of the preceding claims, characterized by, In the step of determining (220), a determination rule is used according to which the evaluation result (119) is evaluated in relation to a magnitude relationship and / or a time relationship between the sensitivity indicator (117) and the at least one evaluation threshold (418A, 418B).

7. The method (210) according to any of the preceding claims, characterized by, In the step of determining (220), a determination rule is used according to which a counter (417) is incremented or decremented depending on the evaluation result (119), wherein the evaluation parameter (121) is determined depending on a comparison of the counter (417) with a predefined or adjustable limit value (420X) for the accumulation.

8. The method (210) according to any one of the preceding claims, characterized by, In the step of providing (222), output data (125) is provided which comprises at least one of the sensor signals (105), wherein each sensor signal (105) is assigned a respective evaluation parameter (121), and / or wherein the sensor signals (105) are fused into a combined sensor signal by using the evaluation parameters (121).

9. A device (110) which is set up to carry out and / or to conduct the steps of the method (210) according to any one of the preceding claims in the respective units (112, 113, 114, 116, 118, 120, 122; 312, 334).

10. A vehicle system (101) for a vehicle (100), wherein the vehicle system (101) has the following features: - the device (110) according to claim 9; - a plurality of redundant vehicle sensors (102-1, 102-2, 102-N); and - at least one vehicle means for automated driving (106), wherein the device (110) is in signal-transmitting connection with the plurality of redundant vehicle sensors and with the at least one vehicle means for automated driving (106).

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