DE102023000708A1 - Method for operating an electronic computing device in a motor vehicle, computer program product, computer-readable storage medium and electronic computing device - Google Patents

Abstract

The invention relates to a method for operating an electronic computing device (14) of a motor vehicle (12), with the steps: - Specification of a user profile (18) for a user of the motor vehicle (12) for individual use (16) of at least one component (10) of the motor vehicle (12) by means of the electronic computing device (14);- receiving a current usage signal (20, 22) of a current use of at least the component (10) by means of the electronic computing device (14);- determining a similarity value or distance value (24) between the specified individual use and the current use by means of the electronic computing device (14); and- If the determined similarity value or distance value (24) falls below a similarity threshold value or exceeds a distance threshold value (26), generating a synthetic usage signal (28) and providing the synthetic usage signal (28) for further processing by means of the electronic computing device (14). The invention also relates to a computer program product, a computer-readable storage medium and an electronic computing device (14).

Description

The invention relates to a method for operating an electronic computing device in a motor vehicle. The invention also relates to a computer program product, a computer-readable storage medium and an electronic computing device.

Data-driven models in the vehicle environment pose a threat to the individual privacy of the motor vehicle user, since information about their actions flows into the models and can be extracted from them if necessary. In particular, if this information is processed in a personalized way, for example if vehicle interactions are linked to a personal profile of the user and usage models and/or statistical evaluations of the data can be generated or created from these, individual privacy is particularly at risk. So-called privacy protection methods are known from data processing systems. The data generated is deliberately excluded from further processing. For example, there are settings in the browser that enable so-called "in private browsing". Likewise, according to the General Data Protection Regulation (GDPR) or comparable international regulations, the user's permission to process the usage data is required or requested by default.

The CN 103256938A describes a computer-implemented trip planning method comprising accessing one or more target elements of a matrix of travel information, the access being based at least in part on a trip home page and a day of the week. Each accessed item is associated with a probability that indicates how likely it is that the item is the destination where a vehicle trip will end, based at least on the home page and the day of the week. The method also includes selecting a destination from the one or more items that has the highest probability of being the destination at which the vehicle journey will end. The method also includes using the selected destination as the final destination for the corresponding travel planning.

The US11171792B2 describes a method for reporting on in-vehicle media consumption and user interaction with a vehicle. The method includes receiving, by a platform device, raw media and vehicle usage data from a vehicle, the platform device including memory, operational controls, a microprocessor, a memory component, an input/output device, and an operating system installed and running thereon; processing the raw data to remove at least one obfuscation function to analyze at least a portion of personally identifiable information; and generating a report with the processed raw data related to user interaction with the vehicle and media content.

The object of the present invention is to create a method, a computer program product, a computer-readable storage medium and an electronic computing device, by means of which the private sphere of a user in the motor vehicle can be maintained in an improved manner.

This object is achieved by a method, a computer program product, a computer-readable storage medium and an electronic computing device according to the independent patent claims. Advantageous embodiments are specified in the dependent claims.

One aspect of the invention relates to a method for operating an electronic computing device in the motor vehicle. A user profile for the individual use of at least one component of the motor vehicle is specified by means of the electronic computing device. A current usage signal of a current use of at least the component is received by the electronic computing device. A similarity value between the specified individual use and the current use is determined using the electronic computing device. If the determined similarity value falls below a similarity threshold value, i.e. the current usage deviates greatly from normal individual usage, a synthetic usage signal is generated and the synthetic usage signal is provided for further processing by the electronic computing device.

In this way, the synthetic usage signal can be processed further, for example, if no further processing of the current usage signals is desired.

In a motor vehicle, information from many internal and external sensors, for example a camera, microphones, driving dynamics sensors, driver interaction with controls, physiological data of the driver and/or the like is processed and processed in the various control units and/or a vehicle-external data processing point, for example a cloud or a data center. This aggregated information makes it possible to to extract vehicle-specific and, if the information from several vehicles in a vehicle fleet is combined, vehicle group-specific information and to apply it in special data-driven analysis methods, such as statistics, machine learning methods or the like.

Furthermore, the sensor information recorded in the motor vehicle can be clearly assigned to persons, with the persons being identified by a variety of methods, for example by taking pictures, for example from an interior camera, and common methods, for example face recognition, machine vision, in particular computer vision, by personalized vehicle keys or a personal PIN code, can be identified.

Data protection is essential. Data economy and selectivity prevent unnecessary data that does not reflect normal behavior from being processed and used for data-driven analysis methods, which can increase the quality of their statements.

The use of the vehicle is divided into so-called use segments of components, which can each be characterized by a trip with the motor vehicle. During each usage segment, usage characteristics, such as the route, for example start or end, time, people in the vehicle or the like, are taken from the vehicle's various internal and external sensors, such as cameras, microphones, driving dynamics sensors, driver interaction with controls, physiological sensors, assistance system interventions, LIDAR , Radar or the like, in particular as components, recorded in a control unit or an electronic computing device.

The usage characteristics can be time series information, aggregated parameters or values statistically determined over a period of time. In addition, context information, for example route, time of day, weather or the like, can supplement the usage features.

These usage features, which each characterize a usage segment, are referred to below as a data record. This data record is aggregated and stored in the control device or in electronic computing devices and/or data centers.

If the usage characteristics are now recorded during a new/additional usage segment, then these are compared with the already known usage characteristics for earlier usage segments and a similarity value is calculated for them. For example, distances, so-called similarity distances referred to below as distance, can be used in the space of usage features, for example the Euclidean distance, or in projections of the space of usage features onto a space with smaller dimensions. Alternatively or additionally, machine learning methods such as cluster analysis, a one-class classifier, anomaly detection based on a normal model of the usage characteristics or the like can be used to determine a similarity value.

If the determined similarity value is less than a predefined threshold/threshold value and the similarity value thus deviates significantly from the previous usage patterns, this data set can, for example, be discarded automatically or manually after querying the user via a user interface of the motor vehicle, or deliberately used as an additional variation of the normal behavior for data processing. As an additional option, the usage characteristics can also be concealed, which can also be done automatically or manually.

In particular, the similarity value can be updated continuously during the usage segment or the journey and the comparison with the similarity values can also be carried out continuously. This means that during the usage segment the usage features are continuously updated with additional sensor data recorded during usage and continuously calculated on the basis of the similarity values.

Alternatively or additionally, the user can switch off the use of the usage features before the usage segment/before the start of the journey, especially if his planned usage deviates from his normal behavior.

To disguise the usage characteristics, these usage characteristics from the aggregation of the historical usage characteristics are used or statistically determined from them, which reflect typical normal behavior of the user, which corresponds in particular to the so-called synthetic usage signal.

In particular, in the obfuscation mode, the user characteristics reflecting the normal behavior of the user (e.g. normal routes on the navigation system, synthetic GPS and general telemetry data) can be played in the data-recording system inside the vehicle as well as on-board systems.

In an advantageous further embodiment, the motor vehicle can communicate with a device temporarily coupled to the motor vehicle, for example a smartphone, to transmit the synthetically generated “normal” usage features, for example the GPS information, so that a consistent and disguised usage behavior is present. For example, in a smartphone operated in flight mode, synthetic GPS coordinates of "normal" usage behavior could be transmitted over time.

The method is illustrated in an application example. A person drives to an acquaintance in a luxurious luxury vehicle. The vehicle recognizes that for the current context (Tuesday night) such usage behavior (unknown route) does not correspond to the previously recorded normal usage behavior. Since the person has stored in the vehicle settings that in this case a usage behavior that does not correspond to the standard, this behavior should not be used for data processing, but rather should even be concealed, synthetic data corresponding to normal behavior is used. Corresponding usage characteristics are extracted from normal behavior (“Tuesday night drive to the next gas station with a 5-minute stop and on the direct way back”) and played back to the system in real time. in particular, the telemetry data sent by the vehicle will be modified according to normal usage characteristics. The next day, the journey history of the navigation system only records one trip to the gas station on Tuesday night and one trip to the bakery on Wednesday morning.

According to an advantageous embodiment, the current usage signal is assigned to the user profile when the similarity threshold value is exceeded.

It is also advantageous if, when the similarity threshold value is not reached, the current usage signal is discarded by the electronic computing device or it is suggested to a user that it should be discarded.

Furthermore, it has proven to be advantageous if the current usage signal is replaced by the synthetic user signal when the similarity threshold value is not reached.

The method presented is in particular a computer-implemented method. A further aspect of the invention therefore relates to a computer program product with program code means which cause an electronic computing device to carry out a method according to the preceding aspect when the program code means are processed by the electronic computing device.

Furthermore, the invention also relates to a computer-readable storage medium with the computer program product according to the preceding aspect.

Yet another aspect of the invention relates to an electronic computing device, the electronic computing device being designed to carry out a method according to the preceding aspect. In particular, the method is carried out using the electronic computing device.

The electronic computing device has, for example, processors, circuits, in particular integrated circuits, and other electronic components in order to be able to carry out corresponding method steps.

Advantageous configurations of the method are to be regarded as advantageous configurations of the computer program product, the computer-readable storage medium and the electronic computing device.

Furthermore, the invention also relates to a motor vehicle with an electronic computing device according to the preceding aspect.

Further advantages, features and details of the invention result from the following description of preferred exemplary embodiments and from the drawings. The features and combinations of features mentioned above in the description and the features and combinations of features mentioned below in the description of the figures and/or shown alone in the figures can be used not only in the combination specified in each case, but also in other combinations or on their own, without going beyond the scope of the leave invention.

• 1 eine schematische Ansicht zur Erzeugung eines Nutzerprofils gemäß einer Ausführungsform des Verfahrens;
• 2 ein schematisches Blockschaltbild gemäß einer Ausführungsform einer elektronischen Recheneinrichtung; und
• 3 ein schematisches Ablaufdiagramm gemäß einer Ausführungsform des Verfahrens.

show:

• 1 a schematic view for generating a user profile according to an embodiment of the method;
• 2 a schematic block diagram according to an embodiment of an electronic computing device; and
• 3 a schematic flow chart according to an embodiment of the method.

Elements that are the same or have the same function are provided with the same reference symbols in the figures.

1 shows a schematic view according to an embodiment of the method. In particular, three diagrams A, B and C are shown. The 1 shows an example of a two-dimensional representation of the generally multidimensional use of components 10 of a motor vehicle 12 ( 2 ). Each marker or each cross represents a usage feature, in particular the use of a component 10, for a usage segment, for example a trip of motor vehicle 10.

In particular, a method for operating an electronic computing device 14 ( 2 ) is proposed, in which a user profile 18 for individual use 16 of at least one component 10 of motor vehicle 10 is specified by means of electronic computing device 14 . A current usage signal 20, 22 of a current usage of at least the component 10 is received by the electronic computing device 14. A similarity value is determined from a distance value 24 between the specified individual usage 16 and the current usage by the electronic computing device 14. If a similarity value falls below a similarity threshold value, or if the distance threshold value 26 is exceeded by the determined distance value 24, a synthetic usage signal 28 ( 2 ) and the provision of the synthetic usage signal 28 for further processing by means of the electronic computing device 14.

In particular, the figure part 1A shows that on the basis of the components 10 from the set of usage segments belonging to a motor vehicle 12, normal behavior, in particular the user profile 18, can be defined, i.e. an area in which all elements of the set are located that are used in the User profile 18, in particular by the component 10, are used. It goes without saying that the user profile 18 can also include a large number of different uses of different components 10 .

The figure part 1B of 1 Figure 12 again shows that the features belonging to a new/additional usage segment can be inside, which is represented by a circle, or outside, which is represented by the asterisk. In other words, the 1B current usage behavior with a first usage signal 20, which is within user profile 18, and a current second usage signal 22, which is outside of usage profile 18, and in particular also falls below the similarity threshold or exceeds a distance threshold 26.

If the new current usage signals 20, 22 are outside, then in particular the similarity value, for example the inverse distance from a limit characterizing normal behavior, the minimum similarity value for designating a usage as similar being within the limit, or alternatively the distance value 24, where the maximum distance value is within the limit. If the similarity value is less than the predefined similarity threshold value, or if the distance value 24 is greater than the predefined distance threshold value 26, then the data set can be discarded automatically or manually, for example, or released deliberately.

Part 1C of the figure shows, in particular, an additional option which enables the use features to be concealed. For this purpose, those usage features are used which correspond to the current second usage signal 22 and are replaced with new synthetic usage features or new synthetic usage signals 28 . These are in particular contained in the usage profile 18 and have, for example, the smallest distance from the current second usage signal 22 .

2 shows a schematic block diagram according to an embodiment of the motor vehicle 12 with the electronic computing device 14. In particular, internal or external sensors 30 are shown, which are processed in a processing step 32 in the electronic computing device 14. For example, these can be processed in an aggregated or statistical manner, with this relating in particular to temporal sensor information. Corresponding context information 34 can also be provided, this in turn being used to determine the usage signals 20, 22. In particular, the similarity value or a distance value 24 can be determined in a calculation module 36 . Should this be greater than the similarity threshold value or smaller than the distance threshold value 26, the data can be stored accordingly in a memory device 38. If the similarity value is less than the similarity threshold or the distance value 24 is greater than the distance threshold 26, automatic rejection, manual rejection, conscious release or even concealment can be enabled, which is shown here with block 40.

3 shows a schematic flow chart according to an embodiment of the method. The method begins in a first step S1. In a second step S2, context information 34 is determined on the basis of an inter NEN tap or external tap of the sensors 30 in the motor vehicle 12. The current usage signals 20, 22 can then in turn be created. In a third step S3, the similarity value or distance value 24 is calculated and a check is made as to whether the similarity value is less than or greater than the similarity threshold value, or whether the distance value 24 is less than or greater than the distance threshold value 26. If the similarity value is greater or the distance value is smaller than the similarity threshold value or distance threshold value 26, a transition is made to a fourth step S4 and the current usage signal 20, 22 is stored in the data set. Starting from the fourth step S4, a transition can be made to a fifth step S5 and the method can be ended.

Starting from the third step S3, if the similarity value is less than the similarity threshold value or the distance value 24 is greater than the distance threshold value 26, a transition is made to a sixth step S6. A query is created as to whether automatic or manual discarding is provided. If an automatic discard is provided, then starting from the sixth step S6 there is a transition to the fifth step S5.

If manual discarding is intended, then in a seventh step S7 the query for a deliberate release takes place. If a conscious release by the user is intended, starting from the seventh step S7, there is a transition to the fourth step S4. If conscious release is not intended, then there is a transition to an eighth step S8, in which the person is asked, for example, whether concealment is intended. If no veiling is provided, starting from the eighth step S8, there is a transition to the fifth step S5. If obfuscation is provided, starting from the eighth step S8 there is a transition to a ninth step S9, wherein the synthetic usage signal 28 can be used and the synthetic usage signal 28 can be reflected in the motor vehicle 10 and externally. Starting from the ninth step S9, the fifth step S5 can again be started.

reference list

10

component

12

motor vehicle

14

electronic computing device

16

User profile individual use

18

user profile

20

current first usage signal

22

current second usage signal

24

similarity value

26

similarity threshold

28

synthetic usage signal

30

sensors

32

processing step

34

context information

36

calculation module

38

storage device

40

block

S1 to S9

steps of the procedure

QUOTES INCLUDED IN DESCRIPTION

This list of documents cited by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent Literature Cited

• CN 103256938A [0003]
• US 11171792 B2 [0004]

Claims (7)

Method for operating an electronic computing device (14) of a motor vehicle (12), with the steps: - Specification of a user profile (18) for a user of the motor vehicle (12) for individual use (16) of at least one component (10) of the motor vehicle (12) by means of the electronic computing device (14); - Receiving a current usage signal (20, 22) of a current usage of at least the component (10) by means of the electronic computing device (14); - determining a similarity value or a distance value (24) between the specified individual use and the current use by means of the electronic computing device (14); and - If the determined similarity value or distance value (24) falls below a similarity threshold value or exceeds a distance threshold value (26), generating a synthetic usage signal (28) and providing the synthetic usage signal (28) for further processing by means of the electronic computing device (14). procedure after claim 1 , characterized in that when the similarity threshold value is exceeded or a distance threshold value (26) is not reached, the current usage signal (20, 22) is assigned to the user profile (18). procedure after claim 1 or 2 , characterized in that when the similarity threshold value is not reached or the distance threshold value (26) is exceeded, the current usage signal (20, 22) is discarded by the electronic computing device (14) or a user is suggested to discard it. Method according to one of the preceding claims, characterized in that when the similarity threshold value is not reached or a distance threshold value (26) is exceeded, the current usage signal (20, 22) is replaced by the synthetic user signal (28). Computer program product with program code means which cause an electronic computing device (14) to do so when the program code means are processed by the electronic computing device (14), a method according to one of Claims 1 until 4 to perform. Computer-readable storage medium containing a computer program product claim 5 . Electronic computing device (14), wherein the electronic computing device (14) for performing a method according to one of Claims 1 until 4 is trained.

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