DE102020204833B4 - Method and device for merging a plurality of signals from an ultrasonic sensor system of a means of transport - Google Patents

Abstract

Method for merging a plurality of signals from an ultrasonic sensor system (30, 35) of a means of transportation (80) comprising the steps:• receiving (100) a first weighting factor for a first signal which represents a first aquaplaning risk value,• receiving (200) a second weighting factor for a second signal, which represents a second aquaplaning risk value,• determining (300) a third weighting factor representing the reciprocal sum of the reciprocal first weighting factor and the reciprocal second weighting factor,• determining (400) a weighted mean value for the first aquaplaning risk value and the second aquaplaning risk value the sum of respective quotients from the first aquaplaning risk value and the first weighting factor, and the second aquaplaning risk value and the second weighting factor, the sum of these quotients being weighted using the third weighting factor,• determining (500) a desired calculated variance for the first aquaplaning risk value and the second aquaplaning risk value on the basis of respective deviations of respective aquaplaning risk values from the weighted average, taking into account the first weighting factor, the second weighting factor and the third weighting factor,• determining a total variance for the first aquaplaning risk value and the second aquaplaning risk value based on the third weighting factor and the weighted variance,• subsequently using the total variance as the weighted variance and• using (600) the weighted mean and the weighted variance to determine a resulting aquaplaning risk condition, the weighted mean representing the merging of the first signal and the second signal.

Description

State of the art

The present invention relates to a method and a device for combining a plurality of signals from an ultrasonic sensor system of a means of transportation.

Means of transportation are known from the prior art, which are provided with one or more ultrasonic sensors for detecting the surroundings of the means of transportation. For this purpose, ultrasonic waves are first emitted into a predefined area of an area surrounding the means of locomotion by means of the ultrasonic sensors. A propagation time of the ultrasonic waves is then determined on the basis of the ultrasonic waves reflected or scattered by the surroundings to the ultrasonic sensors. Finally, based on the propagation time of the ultrasonic waves, a distance between the means of transportation and objects in the vicinity of the means of transportation can be determined. In the prior art, distance information from objects in the vicinity of the means of transportation determined in this way is received and used, for example, by maneuvering assistance systems of the means of transportation (e.g. lane change assistant, parking assistant, etc.).

Furthermore, semi-autonomous and/or autonomous means of transport are known from the prior art, which, to ensure safe driving operation, take into account additional information about the status of roads currently being traveled on (e.g. wetness, bumps in the roadway) when controlling the means of transport.

DE102016221809A1 describes a method for analyzing an unevenness of a roadway for a vehicle, a signal relating to a position and/or movement of the vehicle being detected and the unevenness of the roadway being characterized by evaluating the signal. The signal can be detected, among other things, by means of an ultrasonic sensor. By filtering the signal using a bandpass filter or using a plurality of bandpass filters in one or more frequency ranges, a computationally intensive frequency analysis can be dispensed with and the unevenness of the road can be described using a small amount of data. In addition, a mean value and a variance of the signal can be determined and advantageously used for analyzing the unevenness of the roadway.

DE 10 2018 118 679 A1 describes the communication and avoidance of hazards in a monitored driving environment based on an application of a system for improved target object detection in a vehicle equipped with a laser detection and ranging LIDAR system by simultaneously transmitting multiple lasers at different wavelengths. The lasers are detected and separated by wavelength to reduce acquisition time and/or increase point density. The recorded sensor data are weighted in a suitable manner. Typically, the mean, variance, and standard deviation of resampled data gives the probability of a new object position.

In the unpublished at the time of filing DE 10 2019 210 767 A1 describes how several ultrasound-based wetness values can be fused together using a weighted variance. This type of fusion is suitable for detecting disturbances that have a similarly strong effect on sensors arranged next to one another and for greatly reducing the respective weighting of the sensor values of the affected sensors during the fusion in order to calculate a particularly disturbance-free wetness value.

An actual risk of aquaplaning is fundamentally to be distinguished from a purely wet value of the roadway in that the roadway is wet regardless of the means of transport being driven on, while the risk of aquaplaning only arises when a vehicle moves on the wet roadway. The risk of experiencing aquaplaning depends on various factors. For example, the speed of the vehicle has an impact on the risk of aquaplaning and can be easily adjusted by a driver to reduce the risk. In addition, the drainage properties of the road surface and tires have a significant influence on the risk of aquaplaning. In addition, the static and dynamic tire contact forces related to the tire contact area can have an impact on the risk of aquaplaning.

It is an object of the present invention to provide a method and a device for merging a plurality of signals from an ultrasonic sensor system of a means of locomotion, on the basis of which aquaplaning risk information recorded in particular by the ultrasonic sensor system can be fused. Among other things, this enables to achieve greater reliability for a respective aquaplaning risk detection method in the means of transport.

Disclosure of Invention

To determine the situation-related, for the means of transport individual risk of aquaplaning should be signals, for example, by tire noises are caused, are measured with ultrasonic sensors of the means of transport. These ultrasonic sensors can be part of a parking pilot system, for example. Each individual ultrasonic sensor can calculate an aquaplaning risk value based on a noise level measurement of one or more frequency ranges in such a way that a characteristic value for roadway wetness is determined based on the noise level measurement and an aquaplaning risk value is determined using this characteristic value for roadway wetness, taking into account the current speed of the means of transport and, if necessary, other conditions will. In particular, these ultrasound-based aquaplaning risk values should be merged with one another in such a way that the influence of disruptions is reduced to a minimum.

According to a first aspect of the present invention, a method for merging a plurality of signals from an ultrasonic sensor system of a means of transportation is proposed. The means of locomotion can be, for example, a road vehicle (e.g. motorcycle, passenger car, van, truck) or a rail vehicle or an aircraft/plane and/or a watercraft.

In a first step of the method according to the invention, an evaluation unit according to the invention receives a first weighting factor for a first signal, which represents a first aquaplaning risk value. In a second step of the method according to the invention, a second weighting factor for a second signal, which represents a second aquaplaning risk value, is received by means of the evaluation unit according to the invention. The first signal and the second signal can be generated by different ultrasonic sensors or by one and the same ultrasonic sensor of the means of transportation. In addition, the first signal and the second signal can each represent different or identical frequency ranges and/or measurement times of the ultrasonic sensor system. Preferably 2 to 8 different frequency ranges and particularly preferably 3 to 4 different frequency ranges can be detected per ultrasonic sensor. Furthermore, the first signal and the second signal can be determined on the basis of received noise levels of an ultrasonic sensor and/or diffuse ground echoes of a previously transmitted ultrasonic excitation signal. The first and second aquaplaning risk values represented by the first signal and the second signal can be determined on the basis of a suitable algorithm which is set up to determine respective values for a currently existing aquaplaning risk on the basis of the measured values generated by the ultrasonic sensor system. For this purpose, characteristic noise levels present in the measured values can be classified in degrees of wetness that correspond to these. The degrees of wetness together with other parameters, such as the current speed of the means of transport, result in aquaplaning risk values that represent the current aquaplaning risk. The first weighting factor and/or the second weighting factor can be determined in different ways depending on the application context of the method according to the invention described here. The application context should be understood to mean different merging levels for the respective aquaplaning risk values. In other words, the method according to the invention can be used, for example, in a first merging stage, the first signal, the second signal and possibly further signals, which are generated, for example, by one and the same ultrasonic sensor (e.g. in different frequency ranges of the ultrasonic sensor and/or measured at successive measurement times) sensor-related, while in a second merging stage a plurality of sensor-related fused aquaplaning risk values of a plurality of ultrasonic sensors of the means of locomotion can be fused so that a result of the second merging stage can represent an aquaplaning risk value for the entire means of locomotion. Alternatively, it is also conceivable to merge aquaplaning risk values from a plurality of predefined groups of ultrasonic sensors of the means of transportation in the second merging stage, which can then be merged in an additional third merging stage to form an aquaplaning risk value for the entire means of transportation. In addition, it is also conceivable to use other suitable fusion stages in connection with the method according to the invention. It should be noted that in the first merging stage, aquaplaning risk values originating from only one ultrasonic sensor cannot necessarily be merged; instead, in the first merging stage, for example, all aquaplaning risk values of a respective frequency range of a plurality of ultrasonic sensors (i.e. from all ultrasonic sensors of the means of transport or from all ultrasonic sensors a respective group) are merged. In addition, any other combinations of frequency ranges and/or ultrasonic sensors and/or measurement times are conceivable in principle.

The result, which represents a current risk of aquaplaning, can be displayed to a driver, for example, so that if the risk of aquaplaning is too high, he can reduce the speed and thus also the risk of aquaplaning. In addition, for example, the maximum speed of the cruise control of a driving assistance function of the means of transport or of an autonomously driving means of transport if the risk of aquaplaning is too high and the distance to the vehicle in front can be increased. In addition, vehicle stabilization systems such as ESP can be prepared for the increased probability of an imminent stabilization intervention and safety systems such as belt tensioners can be activated to reduce the consequences of an accident due to aquaplaning.

bestimmt werden.The method according to the invention enables the different merging stages to be implemented, preferably on the basis of a multiple implementation of the method according to the invention, with the respective results of a respective preceding merging stage being able to flow into a subsequent iteration run (ie the subsequent merging stage) of the method according to the invention as input variables in the form of respective aquaplaning risk values and respective weighting factors . In this context, it should be noted that the weighting factors that flow into the first merging stage can preferably be predefined weighting factors for the respective ultrasonic sensors and/or frequency ranges of the ultrasonic sensors, which can be determined or learned, for example, during a development phase of the means of transportation. The weighting factors determined in this way can be stored, for example, in a memory unit that is linked to the evaluation unit in terms of information technology and can basically represent a value for an expected quality or reliability of the respective signals. In this way, signals that are rather unsuitable for determining the risk of aquaplaning (e.g. due to a fault-prone arrangement position of the ultrasonic sensors corresponding to the unsuitable signals) can permanently flow into the merger with a correspondingly lower weighting factor, while more suitable signals have a correspondingly larger weighting factor using a correspondingly higher weighting factor Can influence an overall result of the aquaplaning risk determination. In each merging stage following the first merging stage, preferably no predefined weighting factors are included in the method according to the invention, since the result of the first merging stage always depends on current measured values or boundary conditions and is therefore dynamic. For the purpose of a simplified description, the first merging stage is based on a merging of sensor-related aquaplaning risk values (ie a merging of aquaplaning risk values of an individual ultrasonic sensor), without thereby restricting the method according to the invention to this variant. Correspondingly, sensor-related indices or designations of variables used below also do not represent a restriction to this variant, but can also be transferred and applied in a suitable manner to the above-mentioned further possible combinations for merging aquaplaning risk values. The respective predefined weighting factors that flow into the first merging stage can preferably be based on signal-related variances (hereinafter also referred to as "individual variances"). ${\sigma }_i^2$

to be determined.

wobei ${\sigma }_{s,r}^2$

eine sensorbezogene Varianz und ${\sigma }_i^2$

die signalbezogene Varianz repräsentieren. Der Index r kennzeichnet die Berechnung auf Basis der jeweiligen reziproken Werte.In a third step of the method according to the invention, a third weighting factor representing the reciprocal sum of the reciprocal first weighting factor and the reciprocal second weighting factor is determined by means of the evaluation unit. This can preferably be done on the basis of the following formula: $${\sigma }_{s,\mathrm{right}}^2=\frac{1}{{\sum }_i\frac{1}{{\mathrm{<figure-callout\; id="2"\; label="\sigma \; i"\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">\sigma </figure-callout>}}_i^{}}}$$

in which ${\sigma }_{s,\mathrm{right}}^2$

a sensor-related variance and ${\mathrm{<figure-callout\; id="2"\; label="\sigma \; i"\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">\sigma </figure-callout>}}_i^{}$

represent the signal-related variance. The index r identifies the calculation based on the respective reciprocal values.

wobei µ_s den gewichteten Mittelwert und µ_i die jeweiligen Aquaplaningrisikowerte repräsentieren.In a fourth step of the method according to the invention, the evaluation unit is used to determine a weighted average for the first aquaplaning risk value and the second aquaplaning risk value from the sum of the respective quotients of the first aquaplaning risk value and the first weighting factor, and the second aquaplaning risk value and the second weighting factor, with the sum of these Quotient is weighted by the third weighting factor. This can preferably be done on the basis of the following formula: $${\mu }_s={\sigma }_{s,\mathrm{right}}^2{\displaystyle \sum _i\frac{{\mu }_i}{{\sigma }_i^2}}$$

where µ _s represents the weighted average and µ _i represents the respective aquaplaning risk values.

wobei ${\sigma }_{s,\pi }^2$

die gewichtete Varianz bezogen auf den jeweiligen Ultraschallsensor repräsentiert.In a fifth step of the method according to the invention, a weighted variance for the first aquaplaning risk value and the second aquaplaning risk value is determined by means of the evaluation unit on the basis of respective deviations of respective aquaplaning risk values from the weighted average, taking into account the first weighting factor, the second weighting factor and the third weighting factor. This can preferably be done on the basis of the following formula: $${\sigma }_{s,\mathrm{<figure-callout\; id="2"\; label="w"\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">w</figure-callout>}}^2={\sigma }_{s,\mathrm{right}}^2{\displaystyle \sum _i\frac{{\left({\mu }_i-{\mu }_s\right)}^2}{{\mathrm{<figure-callout\; id="2"\; label="\sigma \; i"\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">\sigma </figure-callout>}}_i^{}}}$$

in which ${\sigma }_{s,\mathrm{<figure-callout\; id="2"\; label="\pi "\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">\pi </figure-callout>}}^2$

represents the weighted variance related to the respective ultrasonic sensor.

In a sixth step of the method according to the invention, the weighted mean value and the weighted variance are used to determine a resulting aquaplaning risk state, the weighted mean value representing the merging of the first signal and the second signal. As described above, using the results of the sixth method step can also mean performing the method described again using the results of the method as input variables for the subsequent iteration of the method. Alternatively, an improved aquaplaning risk determination can already be achieved on the basis of the results of the first merging stage.

It should be pointed out that the preferred calculation rules mentioned above are not intended to represent any restriction of the method according to the invention to their specific configuration. Instead, it is also conceivable to use calculation rules that deviate from the calculation rules mentioned above, as long as the basic principle of the method according to the invention is retained on their basis. In addition, it is also conceivable, instead of the variances used above (or the standard deviations derived therefrom), to also use scattering parameters that deviate from them in connection with the method according to the invention.

The dependent claims show preferred developments of the invention.

wobei σ² die Gesamtvarianz repräsentiert. Die Gesamtvarianz σ² wird dann groß, wenn alle individuellen Varianzen ${\sigma }_i^2$

aufgrund eines Messrauschens groß sind. Sie wird aber auch dann groß, wenn die individuellen Varianzen ${\sigma }_i^2$

σ² aufgrund des Messrauschens klein sind, während sich die Aquaplaningrisikowerte µ_i stark unterscheiden. Allerdings kann die Gesamtvarianz σ² auch klein werden, wenn einer der Messwerte stark von anderen Messwerten abweichen sollte, während für diesen Messwert eine hohe Varianz aufgrund des Messrauschens bestimmt wurde.In a preferred embodiment of the present invention, a total variance for the first aquaplaning risk value and the second aquaplaning risk value is determined by the evaluation unit in an additional method step on the basis of the third weighting factor and the weighted variance. In a further additional method step, this total variance is then used as the weighted variance in the means of transportation. These method steps are preferably carried out between the respective fusion stages in order, among other things, to avoid potential divisions by zero. The total variance can preferably be calculated on the basis of the following formula: $${\mathrm{<figure-callout\; id="2"\; label="\sigma "\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">\sigma </figure-callout>}}^2={\sigma }_{s,\mathrm{right}}^2+{\sigma }_{s,\mathrm{<figure-callout\; id="2"\; label="w"\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">w</figure-callout>}}^2$$

where σ ² represents the total variance. The total variance σ ² becomes large when all individual variances ${\sigma }_i^{}$${}_2^{}$

are large due to measurement noise. However, it also becomes large when the individual variances ${\sigma }_i^{}$${}_2^{}$

σ ² are small due to the measurement noise, while the aquaplaning risk values µ _i differ greatly. However, the total variance σ ² can also be small if one of the measured values deviates significantly from other measured values, while a high variance was determined for this measured value due to the measurement noise.

wobei α den vierten Gewichtungsfaktor repräsentiert. Wird der Faktor α groß gewählt, dann bewirken potentiell einwirkende Störungen eine starke Erhöhung der Gesamtvarianz σ². Dadurch kann bei einer anschließenden Fusion mehrerer Aquaplaningrisikowerte der Einfluss der jeweils gestörten Ultraschallsensoren besonders gut reduziert werden. Wird der Faktor α hingegen klein gewählt, dann bewirken zufällige Unterschiede zwischen Signalen aufgrund des Messrauschens nur eine geringe Erhöhung der Gesamtvarianz σ². Dadurch kann bei einer anschließenden Fusion mehrerer Aquaplaningrisikowerte entsprechend der Einfluss des Messrauschens reduziert werden. Um einen geeigneten Kompromiss zwischen einer guten Erkennung von Störungen und einer guten Reduzierung des Messrauschens zu erreichen, kann der Faktor α bevorzugt in einem Bereich zwischen 0,2 und 10 und insbesondere bevorzugt in einem Bereich zwischen 1 und 2 gewählt werden. Die Wahl des Faktors α kann darüber hinaus bevorzugt für jeden Ultraschallsensor individuell festgelegt werden.In a further advantageous embodiment of the present invention, the weighted variance is weighted with a fourth weighting factor before the determination of the total variance by means of the evaluation unit. This can preferably be done on the basis of the following formula: $${\mathrm{<figure-callout\; id="2"\; label="\sigma "\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">\sigma </figure-callout>}}^2={\sigma }_{s,\mathrm{right}}^2+a{\sigma }_{s,\mathrm{<figure-callout\; id="2"\; label="\pi "\; filenames="DE102020204833B4\_0014.png"\; state="\{\{state\}\}">\pi </figure-callout>}}^2$$

where α represents the fourth weighting factor. If the factor α is chosen to be large, then potentially influencing disturbances cause a strong increase in the total variance σ ² . As a result, in the event of a subsequent fusion of a number of aquaplaning risk values, the influence of the respective faulty ultrasonic sensors can be reduced particularly well. On the other hand, if the factor α is chosen to be small, then random differences between signals cause only a small increase in the total variance σ ² due to the measurement noise. As a result, the influence of the measurement noise can be correspondingly reduced in the event of a subsequent fusion of several aquaplaning risk values. In order to achieve a suitable compromise between a good detection of disturbances and a good reduction in the measurement noise, the factor α can preferably be selected in a range between 0.2 and 10 and particularly preferably in a range between 1 and 2. In addition, the selection of the factor α can preferably be determined individually for each ultrasonic sensor.

In a further advantageous embodiment of the present invention, the first signal and the second signal are generated by a predefined group of ultrasonic sensors and a weighted mean value assigned to the group and a weighted variance assigned to the group are determined across all ultrasonic sensors of the predefined group. As described above, the ultrasonic sensors of the means of locomotion can be assigned to a plurality of groups, it being possible for each ultrasonic sensor of the means of locomotion to be assigned to one, several or none of the groups. For the assignment of respective ultrasonic sensors to respective groups, ultrasonic sensors lying next to each other locally can preferably be used can be selected for a respective group assignment. This can be of particular advantage since interference affecting the ultrasonic sensors often has a locally limited effect on adjacent ultrasonic sensors and/or on individual adjacent and/or overlapping groups. All aquaplaning risk scores from groups affected by disturbances should preferably be given a small weight in the calculation of the merged aquaplaning risk score across multiple groups. Measurements for which it is known that a high variance is to be expected due to measurement noise or disturbances should accordingly be weighted less when calculating the variance of the merged aquaplaning risk value. Disturbances which, on the other hand, do not lead to an increased value for the variance, but which can have different effects on different ultrasonic sensors, should advantageously lead to a calculation of a large value for the variance. For this reason, the calculations for the group-related aquaplaning risk values and the group-related variances can be carried out analogously to the calculation steps described above for the individual ultrasonic sensors. Preferably, between 2 and 4 adjacent ultrasonic sensors can be assigned to a common group without thereby restricting the number in terms of the method according to the invention. As already mentioned, it can also be advantageous to assign one or more ultrasonic sensors to more than one group. As a result, an overlapping of groups can be achieved, as a result of which the probability can be increased that one or more groups of the means of transportation will remain undisturbed during disruptions that occur and can thereby generate an aquaplaning risk value with a low variance. Alternatively, for example, 5 or 6 ultrasonic sensors (or more) can also be assigned to a respective group, in which case each ultrasonic sensor can preferably be assigned to three groups so that the effects of disturbances can continue to be clearly delimited.

In a further advantageous embodiment of the present invention, the evaluation unit is used to determine a weighted mean value assigned to the means of transport and a weighted variance assigned to the means of transport for the first aquaplaning risk value and for the second aquaplaning risk value, with the first aquaplaning risk value and the second aquaplaning risk value having a weighted mean and a weighted Represent variance for a respective ultrasonic sensor or a weighted average and a weighted variance for a respective group of ultrasonic sensors of the means of transport. As described above, the values relating to the means of transport can be calculated analogously to the method according to the invention described above. The variance calculated for the means of transportation can be used in particular as an indicator for the reliability of the aquaplaning risk determination for the entire means of transportation.

In a further advantageous embodiment of the present invention, the weighted mean value assigned to the means of transportation and the weighted variance assigned to the means of transportation are additionally determined on the basis of an aquaplaning risk value of a sensor system that differs from the ultrasonic sensor system of the means of transportation. This deviating sensor system can be, for example, a camera and/or a lidar sensor and/or a satellite-based positioning system (due to a changed multipath propagation with different degrees of wetness), the output signals of which are preferably pre-processed in such a way that they are given respective weighted mean values and weighted values in accordance with the method according to the invention Variances for respective aquaplaning risk values of the ultrasonic sensors can be merged.

In a further advantageous embodiment of the present invention, the weighted mean value and the weighted variance are additionally determined based on third aquaplaning risk values and/or based on a weighted mean value of the third aquaplaning risk values and a weighted variance of the third aquaplaning risk values. The third aquaplaning risk values and/or the weighted mean values and weighted variances based thereon can be determined on the basis of a further ultrasonic sensor of the means of transportation. Alternatively or additionally, these can also be determined on the basis of a wetness value provided by another means of transportation (crowd sourcing) and/or by an external server. In other words, aquaplaning risk values that were determined using wetness values determined outside of the means of transportation can be merged with a respective result of a respectively corresponding merging stage of the means of transportation, which may result in a further improvement in the reliability of the aquaplaning risk determination.

In a further advantageous embodiment of the present invention, the first weighting factor and/or the second weighting factor represent speed-dependent and/or degree-of-wetness-dependent and/or thermal measurement noise-dependent values, which are determined in particular from a predefined characteristic map can be told. The reliability of the aquaplaning risk determination can be correspondingly further increased by this additional consideration of the above-mentioned influencing variables on the aquaplaning risk determination. The influencing variables mentioned above can preferably be determined during a development phase and/or a training phase for the means of transportation and stored, for example, in the storage unit connected to the evaluation unit.

According to a further advantageous embodiment of the present invention, ultrasonic sensors that are arranged at the front of the means of locomotion, viewed in the direction of travel of the means of locomotion, are considered separately from ultrasonic sensors that are arranged at the rear of the means of locomotion, viewed in the direction of travel of the means of locomotion. A front merged aquaplaning risk value is thus determined by means of the front ultrasonic sensors and a rear merged aquaplaning risk value is determined by means of the rear ultrasonic sensors. The front merged aquaplaning risk value can be assigned in particular to a front axle of the means of locomotion, the rear merged aquaplaning risk value can be assigned in particular to a rear axle of the means of locomotion. This embodiment of the invention has the advantage that it is possible to react in good time to a sudden change in the wetness of the roadway. In such a case, for example with a large puddle of water on the road, the front merged aquaplaning risk value can already indicate an increased aquaplaning risk at a time when the wheels of the rear axle are still on a dry road, i.e. the rear aquaplaning risk value is determined to be significantly lower than the first aquaplaning risk value.

The tire noises of the front axle can be dominant for the noises measured by the ultrasonic sensors. Depending on the axle spacing and the speed of the means of transport, such a change in the risk of aquaplaning has a delayed effect on the tire noise that is generated by the rear axle and measured with the rear ultrasonic sensors. So that this delay in the merging of the first and second aquaplaning risk values of the front and rear ultrasonic sensors is not mistaken for a malfunction, the sensor values of the front ultrasonic sensors can be delayed by a dead time element, with the dead time or the delay being selected in particular as a function of the current speed will. Due to this delay, a sudden change in the risk of aquaplaning acts synchronously on the rear and front delayed ultrasonic sensor values, as a result of which disturbances during such a change in the risk of aquaplaning have less of an impact on the fusion.

In a particularly advantageous embodiment of the present invention, in the case of a means of transportation with at least four wheels, individual fused aquaplaning values are determined for each wheel. This information can be used, for example, by an ESP control of the means of transport, so that the driving dynamics control can better estimate the coefficient of friction of the individual wheels and thus the developing vehicle dynamics.

In order to output a risk of aquaplaning suitable for a driver or for the cruise control, the merged aquaplaning risk values can be filtered over a longer period of time. For example, a driver's reaction time to aquaplaning risk information can be 0.2 to 1 second. In order to prevent incorrect information due to measurement noise, it can therefore be beneficial to filter the aquaplaning risk values, e.g. over 0.2 to 1 second. The fusion equations described above can be used for filtering a plurality of aquaplaning risk values determined in succession over time. For example, a fusion filter with an infinite impulse response (IIR filter) can be implemented by weighting or offsetting the output of the fusion filter and feeding it back as an input. Alternatively, a fusion filter with a finite impulse response (FIR filter) can be implemented by fusing a certain number of the input values last calculated with one another.

According to a second aspect of the present invention, a device for combining a plurality of signals from an ultrasonic sensor system of a means of transportation is proposed. The device includes an evaluation unit with a data input and a data output, it being possible for the evaluation unit to be connected by means of the data input and by means of the data output, in particular to an on-board network of the means of transport. Furthermore, the evaluation unit can be connected in terms of information technology to an internal and/or external storage unit, in which data received and/or calculated by the evaluation unit can be stored for subsequent processing. The evaluation unit can be designed, for example, as an ASIC, FPGA, processor, digital signal processor, microcontroller, or the like, and can be set up in connection with a computer program to carry out the method steps according to the invention described above.

In connection with the data input, the evaluation unit is set up to receive a first weighting factor for a first signal, wel ches representing a first aquaplaning risk value and receiving a second weighting factor for a second signal representing a second aquaplaning risk value. Furthermore, the evaluation unit is set up to determine a third weighting factor representing the reciprocal sum of the reciprocal first weighting factor and the reciprocal second weighting factor, a weighted mean value for the first aquaplaning risk value and the second aquaplaning risk value from the sum of respective quotients from the first aquaplaning risk value and the first weighting factor, and to determine the second aquaplaning risk value and the second weighting factor, with the sum of these quotients being weighted using the third weighting factor and a weighted variance for the first aquaplaning risk value and the second aquaplaning risk value based on respective deviations of respective aquaplaning risk values from the weighted average, taking into account the first weighting factor, the to determine the second weighting factor and the third weighting factor. In connection with the data output, the evaluation unit is set up to use the weighted mean value and the weighted variance to determine a resulting risk of aquaplaning, the weighted mean value representing the merging of the first signal and the second signal. In this context it should be pointed out that the result of the method according to the invention, as described above, can be fed to one or more further merging stages in the form of a further iteration of the method according to the invention, whereby the result output at the data output via the data input of the evaluation unit within the evaluation unit itself can be further processed. In such a case, the data output and the data input can be understood, for example, as writing and reading memory access within the evaluation unit itself. Alternatively or additionally, a respective result of the method according to the invention can also be transmitted to one or more recipients of the result by means of the data output via the vehicle electrical system of the means of transport.

character list

• 1 ein Flussdiagramm veranschaulichend Schritte eines Ausführungsbeispiels eines erfindungsgemäßen Verfahrens;
• 2 eine schematische Übersicht einer erfindungsgemäßen Vorrichtung in Verbindung mit einem Fortbewegungsmittel;
• 3 eine grafische Darstellung eines Rechenbeispiels für die Fusion mehrerer Aquaplaningrisikowerte ohne äußere Störung, und
• 4 eine grafische Darstellung eines Rechenbeispiels für die Fusion mehrerer Aquaplaningrisikowerte mit äußerer Störung.

Exemplary embodiments of the invention are described in detail below with reference to the accompanying drawings. show:

• 1 a flow chart illustrating steps of an embodiment of a method according to the invention;
• 2 a schematic overview of a device according to the invention in connection with a means of locomotion;
• 3 a graphical representation of a calculation example for the fusion of several aquaplaning risk values without external interference, and
• 4 a graphical representation of a calculation example for the fusion of several aquaplaning risk values with an external disturbance.

Embodiments of the invention

1 shows a flow chart illustrating steps of an embodiment of a method according to the invention for merging a plurality of signals of an ultrasonic sensor system of a means of transportation. In step 100, an evaluation unit according to the invention, which is a microcontroller here, receives a first weighting factor for a first signal, which represents a first aquaplaning risk value. The first signal is generated on the basis of a measurement in a first frequency range of an ultrasonic sensor of the means of transportation. In step 200, the evaluation unit according to the invention receives a second weighting factor for a second signal, which represents a second aquaplaning risk value. The second signal is generated on the basis of a measurement in a second frequency range, which differs from the first frequency range, of the ultrasonic sensor of the means of transportation. In step 300, a third weighting factor representing the reciprocal sum of the reciprocal first weighting factor and the reciprocal second weighting factor is determined. In step 400, a weighted mean value, related to the ultrasonic sensor, for the first aquaplaning risk value and the second aquaplaning risk value is determined from the sum of the respective quotients of the first aquaplaning risk value and the first weighting factor, and the second aquaplaning risk value and the second weighting factor, with the sum of these quotients being calculated using the third weighting factor is weighted. In step 500, a weighted variance related to the ultrasonic sensor for the first aquaplaning risk value and the second aquaplaning risk value is determined on the basis of respective deviations of respective aquaplaning risk values from the weighted average, taking into account the first weighting factor, the second weighting factor and the third weighting factor. In step 600, the sensor-related weighted mean and the sensor-related weighted variance are used to determine a resulting aquaplaning risk condition. For this purpose, a weighted sensor-related total variance is determined on the basis of the sensor-related weighted variance, on the basis of the third weighting factor and on the basis of a fourth weighting factor. The sensor-related weighted mean and total sensor-related variance are then used to calculate a plurality of weighted means and to merge weighted total variances of a plurality of ultrasonic sensors analogously to the method described above to form respective values related to the means of transportation.

2 shows a schematic overview of a device according to the invention in connection with a means of locomotion 80. The means of locomotion 80 comprises an evaluation unit 10 according to the invention, which is a microcontroller here and which is connected to an on-board network of the means of locomotion 80 by means of a data input 12 and by means of a data output 14 in terms of information technology. The means of transport 80 also includes a first ultrasonic sensor 30 , a second ultrasonic sensor 35 and a plurality of further ultrasonic sensors 50 , which are each connected to the evaluation unit 10 in terms of information technology via the on-board network of the means of transport 80 . A first subset of the ultrasonic sensors 30 , 35 and 50 is assigned to a first ultrasonic sensor group 40 and a second subset of the ultrasonic sensors 30 , 35 and 50 is assigned to a second ultrasonic sensor group 45 . The evaluation unit 10 is additionally connected in terms of information technology to an external storage unit 20, in which data received and processed by the evaluation unit 10 are stored. In addition, a computer program is stored in the memory unit 20, which is set up to execute method steps according to the invention described above. The evaluation unit 10 is also connected in terms of information technology to a camera 70 of the means of transport 80 and is set up to fuse an output signal from the camera 70 with respective measurement signals from the ultrasonic sensors 30, 35 and 50 for determining the risk of aquaplaning in the means of transport 80 using the computer program in a suitable manner. Furthermore, the evaluation unit 10 is connected in terms of information technology via the data output 14 to a control device 60 of the means of transportation 80, which is set up to use a result of the method according to the invention transmitted by the evaluation unit 10 to the control device 60 in the means of transportation 80.

3 FIG. 7 shows a diagram 700 of several measurements 1-4 of an aquaplaning risk value and a resulting amalgamated aquaplaning risk value 5 without external interference according to an exemplary embodiment of the invention. The aquaplaning risk value is plotted on the x-axis and the associated probability density on the y-axis. The aquaplaning risk values are given as percentage values in this example.

In the calculation example shown, the merged aquaplaning risk value 5 was determined at 25%, the standard deviations caused by the measurement noise for the first signal 1 at 17.5%, the values for the second signal 2 and the third signal 3 at 25% each % and the value of the fourth signal 4 is chosen to be 37.5%. The mean value of the merged aquaplaning risk value without disruption (corresponds to the maximum value of the probability density) corresponds to approx. 25%. The standard deviation σ (distance between inflection point and high point) corresponds to approx. 10%.

4 FIG. 8 shows a diagram 800 of several measurements 1′-4′ of an aquaplaning risk value and a resulting amalgamated aquaplaning risk value 5′ with an external disturbance according to a further exemplary embodiment of the invention. The aquaplaning risk value is again plotted on the x-axis and the associated probability density on the y-axis. The aquaplaning risk values are also given as percentage values in this example.

The interference is selected in such a way that for the first signal 1' an increase of 75% points, the signals 2' and 3' increases of 50% points compared to the undisturbed measurement ( 3 ) and for the value 4' causes an increase of 25% points. The mean value of the merged aquaplaning risk value 5' without considering the disruption (this corresponds to the maximum value of the probability density function) is approximately 60%. The deviation from the actually selected aquaplaning risk value of 25% is very large, but the calculated standard deviation of around 20% is also significantly larger than the merged value of 5 without a fault. In a subsequent fusion of the disturbed aquaplaning risk value with an aquaplaning risk value of an undisturbed ultrasonic sensor, the value of the undisturbed ultrasonic sensor is weighted much more heavily due to its lower standard deviation, as a result of which the influence of the malfunctioning ultrasonic sensor can be significantly reduced.

The following advantages in particular are achieved by the invention:

The fusion of several values of an ultrasonic sensor with the help of the weighted variance has the advantage that disturbances that have different effects on the aquaplaning risk values lead to a high calculated variance for the fused value and thus the fused value of the ultrasonic sensor in the further fusion with values of other ultrasonic sensors that are not disturbed are weighted less heavily. This makes the fusion insensitive to disturbances.

The fusion initially within an ultrasonic sensor and the subsequent fusion of a few adjacent ultrasonic sensors within a group and the subsequent fusion of several groups has the advantage that disturbances, which do not have different effects on the aquaplaning risk values of individual ultrasonic sensors, but instead have different effects on neighboring ultrasonic sensors lead to a high calculated variance for the fused value of the zone and as a result the fused value of the zone is weighted less heavily in the further fusion with values of zones that are not disturbed. This makes the fusion insensitive to disturbances that could not be detected or not sufficiently detected by the affected ultrasonic sensors themselves.

The quality of the merged aquaplaning risk value can be read from the calculated variance.

The calibration of the function can be automated to a high degree. In this way, the parameters of the aquaplaning risk value and the variance maps can be calculated from measurements from a few driving tests. very different and large disturbances have a small influence on the calculated aquaplaning risk value and the aquaplaning risk can still be calculated dynamically and accurately.

Claims (12)

Method for merging a plurality of signals from an ultrasonic sensor system (30, 35) of a means of transportation (80), comprising the steps: • Receiving (100) a first weighting factor for a first signal, which represents a first aquaplaning risk value, • receiving (200) a second weighting factor for a second signal, which represents a second aquaplaning risk value, • determining (300) a third weighting factor representing the reciprocal sum of the reciprocal first weighting factor and the reciprocal second weighting factor, • determining (400) a weighted mean value for the first aquaplaning risk value and the second aquaplaning risk value from the sum of respective quotients of the first aquaplaning risk value and the first weighting factor, and the second aquaplaning risk value and the second weighting factor, the sum of these quotients being weighted using the third weighting factor , • determining (500) a weighted variance for the first aquaplaning risk value and the second aquaplaning risk value on the basis of respective deviations of respective aquaplaning risk values from the weighted average, taking into account the first weighting factor, the second weighting factor and the third weighting factor, • determining a total variance for the first aquaplaning risk value and the second aquaplaning risk value based on the third weighting factor and the weighted variance, • subsequently using the total variance as the weighted variance and • Using (600) the weighted mean and the weighted variance to determine a resulting aquaplaning risk condition, the weighted mean representing the merging of the first signal and the second signal. procedure after claim 1 , The first signal and the second signal being generated • by different ultrasonic sensors (30, 35), or • by one and the same ultrasonic sensor (30), the ultrasonic sensor system (30, 35) of the means of transportation (80). A method according to any one of the preceding claims, wherein the first signal and the second signal are respectively different or identical • frequency ranges, and/or • Represent measurement times of the ultrasonic sensors (30, 35), and / or based on • noise levels, and/or • diffuse ground echoes of a previously transmitted ultrasonic excitation signal are determined. procedure after claim 1 , where the weighted variance is weighted by a fourth weighting factor before determining the total variance. Method according to any one of the preceding claims, wherein • the first signal and the second signal are generated by a predefined group (40) of ultrasonic sensors (30, 35), and • a weighted mean value assigned to the group (40) and a weighted variance assigned to the group (40) are determined across all ultrasonic sensors (30, 35) of the predefined group (40). procedure after claim 5 , wherein a front merged aquaplaning risk value is determined by means of ultrasonic sensors which are arranged at the front of the means of locomotion (80) as seen in the direction of travel of the means of locomotion (80) and with ultrasonic sensors which are arranged at the rear of the means of locomotion (80) as seen in the direction of travel of the means of locomotion (80) are arranged, a rear merged aquaplaning risk value is determined, with the front merged aqua planing risk value is assigned in particular to a front axle of the means of transportation (80) and the rear merged aquaplaning risk value is assigned in particular to a rear axle of the means of transportation (80). procedure after claim 5 or 6 , with a front aquaplaning risk value being merged with a rear aquaplaning risk value, with the signals generated by means of ultrasonic sensors, which are arranged at the front of the means of transport, seen in the direction of travel of the means of transport (80), before the fusion, in particular by a dead time element, compared to signals which by means of ultrasonic sensors, which are arranged at the rear of the means of locomotion (80), viewed in the direction of travel of the means of locomotion (80), the delay being selected in particular as a function of the current speed of the means of locomotion (80). Method according to any one of the preceding claims, wherein • a weighted mean value assigned to the means of transportation (80) and a weighted variance assigned to the means of transportation (80) are determined for the first aquaplaning risk value and for the second aquaplaning risk value, and • the first aquaplaning risk value and the second aquaplaning risk value ◯ a weighted mean value and a weighted variance for a respective ultrasonic sensor (30, 35), or ◯ represent a weighted mean and a weighted variance for a respective group (40) of ultrasonic sensors (30, 35) of the means of transportation (80). procedure after claim 6 , wherein the weighted mean value assigned to the means of transportation (80) and the weighted variance assigned to the means of transportation (80) are additionally determined on the basis of an aquaplaning risk value of a sensor system (70) that differs from the ultrasonic sensors (30, 35) of the means of transportation (80). A method according to any one of the preceding claims, wherein the weighted mean and the weighted variance are additionally based • third aquaplaning risk values, and/or • a weighted mean value of the third aquaplaning risk values and a weighted variance of the third aquaplaning risk values are determined. Method according to one of the preceding claims, wherein the first weighting factor and/or the second weighting factor • speed-dependent, and/or • depending on the degree of wetness, and/or • represent values dependent on thermal measurement noise, and/or • are determined from a predefined map. Device for merging a plurality of signals from an ultrasonic sensor system of a means of transportation, comprising: • an evaluation unit (10), • a data input (12), and • a data output (14), the evaluation unit (10) being set up, • in connection with the data input (12) ◯ receive a first weighting factor for a first signal representing a first aquaplaning risk value, and ◯ receive a second weighting factor for a second signal representing a second aquaplaning risk value, • determine a third weighting factor representing the reciprocal sum of the reciprocal first weighting factor and the reciprocal second weighting factor, • to determine a weighted average for the first aquaplaning risk value and the second aquaplaning risk value from the sum of respective quotients from the first aquaplaning risk value and the first weighting factor, and the second aquaplaning risk value and the second weighting factor, with the sum of these quotients being weighted using the third weighting factor, • to determine a weighted variance for the first aquaplaning risk value and the second aquaplaning risk value on the basis of respective deviations of respective aquaplaning risk values from the weighted average, taking into account the first weighting factor, the second weighting factor and the third weighting factor, • a total variance for the first aquaplaning risk value and the second aquaplaning risk value based on the third weighting factor and the weighted variance, • subsequently using the total variance as the weighted variance and • in connection with the data output (14), to use the weighted mean and the weighted variance for determining a resulting aquaplaning risk state, the weighted mean representing the fusion of the first signal and the second signal.

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