DE102024004186A1 - control device of a motor vehicle and motor vehicle - Google Patents

Abstract

Described is an operating device of a motor vehicle, with a rotary push button, wherein the rotary push button has at least one touch-sensitive surface, wherein a controller is provided which is designed to process signals from the rotary push button, wherein the touch-sensitive surface is designed to register more than one touch point simultaneously, wherein the controller has a differentiation algorithm which is designed to register whether the multiple touch points originate from a driver's hand or a passenger's hand.

Description

A control device of a motor vehicle and a motor vehicle are described.

Operating devices of a motor vehicle and motor vehicles of the type mentioned above are known in the state of the art.

Rotary push buttons with touch-sensitive surfaces are well known as essential components of human machine interfaces (HMI) in motor vehicles. These controls combine mechanical and touch-sensitive input options to enable intuitive control of vehicle functions. Typically, users can operate the rotary push button by turning, pressing or by touching the surface. Each of these input methods is used to control specific functions, such as scrolling through menus, selecting options or adjusting settings.

The touch-sensitive surface of a rotary push-button controller often recognizes gestures such as swiping, tapping or multi-finger touches, thus supplementing the mechanical operation with another level of interaction. This functionality enables faster and more precise input, especially in complex infotainment systems, without the user having to navigate deep into submenus. These controllers are often positioned centrally in the center console of a vehicle, making them easy to reach for both the driver and the passenger. The combination of haptic feedback and tactile input increases user-friendliness and ensures a safe operating experience, as the driver's attention can largely remain focused on the road.

When operating a human-machine interface in a motor vehicle, different requirements and challenges can arise depending on whether the control device is used by the driver or the passenger. It is particularly problematic if the same content is displayed for both users without taking their respective roles in the vehicle into account. For the driver, this could result in them receiving information that is not directly related to driving the vehicle and distracts their attention from road traffic. This significantly increases the risk of accidents, as the driver may be less attentive to critical traffic situations. The passenger, on the other hand, does not usually need any driving-related information and could be unnecessarily confused by it or perceive the user-friendliness of the interface to be limited.

It would be particularly critical if the driver were confronted with too much or complex information while driving. This could lead to cognitive overload, as processing such information impairs the resources needed to drive the vehicle. An overloaded display or the presentation of irrelevant content can lead to the driver looking at the screen for longer than necessary or making decisions with delay. By making a targeted distinction between driver and passenger and adapting the content accordingly, it is ensured that the driver only receives the information that is essential to him while driving, which significantly increases driving safety.

From the US 2009/0082951 A1 A navigation system is known comprising a user interface for detecting touch inputs. The system determines whether a driver or passenger is operating the navigation system via touch input. If the system determines that the driver is operating the system, an action is initiated (e.g., the user interface is locked, a warning is issued). The navigation system allows a passenger in the vehicle to operate the navigation system while the vehicle is moving. In one aspect, additional or different sensors (e.g., seat sensor, seat belt sensor, infrared sensor) may be used to detect whether a driver or passenger is operating the navigation system while the vehicle is moving.

The disadvantage is that this technology is not suitable for use with rotary push buttons.

The task therefore arises of further developing the operating devices of a motor vehicle and motor vehicles of the type mentioned above in such a way that a safer operation of a motor vehicle is possible.

The object is achieved by an operating device of a motor vehicle according to claim 1 and a motor vehicle according to the independent claim 8. Further embodiments and developments are the subject of the dependent claims.

Described is an operating device of a motor vehicle, with a rotary push button, wherein the rotary push button has at least one touch-sensitive surface, wherein a control is provided which is used for processing of signals from the rotary push button, wherein the touch-sensitive surface is designed to register more than one touch point simultaneously, wherein the controller has a discrimination algorithm which is designed to register whether the plurality of touch points originate from a driver's hand or a passenger's hand.

Recognising whether the driver or the front passenger is using the control device makes it possible to tailor content to the respective user role. For example, safety-relevant information such as directions or warning messages can be shown to the driver, while content such as multimedia options, communication functions or other less critical information is provided to the front passenger. This separation not only improves safety, but also the user experience, as everyone has access to the information that is relevant to them.

In a first further embodiment, it is provided that the touch-sensitive surface is a circumferential ring.

This makes it possible to recognize whether the driver or the passenger is operating the rotary push button in many different handle positions.

In a further refinement, the touch-sensitive surface has a projected capacitive touch sensor.

Capacitive touch sensing, often called Projected Capacitive Touch Technology (PCT), is a capacitive touchscreen technology that is based on the property of human skin as a conductive material that influences electrical fields.

A projected capacitive touchscreen typically consists of a transparent electrode layer embedded under a protective glass layer. This electrode layer creates an electric field across the surface of the screen. Unlike traditional capacitive technology, which only measures the total change in capacitance across the entire surface, PCT technology measures capacitive changes at multiple points simultaneously. This measurement is made possible by a grid of horizontal and vertical conductive lines that form a network of touch-sensitive points. When a conductive object, such as a finger, touches or approaches the electric field, the capacitance at the touch point changes. The technology can precisely calculate the location and intensity of that touch.

A feature of projected capacitive touch technology is the support of multi-touch inputs, which allows multiple touches to be recorded simultaneously.

In addition to recognizing the side of the hand, this also enables functions such as zooming, rotating or scrolling. In addition, the capacitive touch technology is characterized by high precision, sensitivity and robustness. It also works through thin gloves or on slightly damp surfaces and is durable thanks to the protective glass layer.

In a further refinement, it is provided that the discrimination algorithm comprises a neural network which is trained using at least one data set containing contact points of driver's hands and contact points of passenger's hands.

For such a binary classification problem, a neural network with one or more hidden layers is suitable, where the output layer can contain a single neuron with a sigmoid activation function. This function outputs probabilities for the states.

To train the model, a suitable loss function, such as Binary Cross-Entropy Loss, is chosen, which measures the error in the predictions. Algorithms such as Stochastic Gradient Descent or Adam can be used to optimize the weights of the model.

To train the neural network, one can use classified training data, which should be sufficiently large and balanced to ensure an equal representation of both states.

The corresponding training data can include data from the driver's hands and from the passenger's hands, i.e. left or right, right hands or left hands, depending on the position of the driver's seat in the vehicle. Data from hands of different sizes and shapes can be used in order to cover the widest possible spectrum of anatomies. In addition, the training data can contain data on different gripping techniques, for example gripping with a thumb together with one finger, two fingers, three fingers, or four fingers. Furthermore, the data can include gripping entirely or partially on the peripheral ring or on the top. The training data can also include grasping the rotary push button, partially on the peripheral ring and partially on the top, for example on an edge.

Before training, it is useful to prepare the data. This includes normalizing the values (for example, to a range between 0 and 1) and, if necessary, generating additional data variants using techniques such as data augmentation. The dataset is then split into training, validation and test data to evaluate the model's performance over time.

During training, inputs are processed through the network (forward propagation), the error is calculated, and backpropagation adjusts the model's weights to minimize the error. This process is repeated over many runs, called epochs, with the input data often split into smaller batches to increase efficiency. After each epoch, the model is checked using validation data to ensure that it not only handles the training data well, but also new data. Metrics such as accuracy, precision, or the F1 score are used for this.

After training is complete, the model is evaluated on a separate test dataset to assess its generalization ability. Finally, if the model is successful, it can be used to reliably assign new inputs to one of the two states. If performance is not satisfactory, the model's hyperparameters (such as the learning rate or the number of layers) can be adjusted and the training process repeated until the desired results are achieved.

In a further refinement, the discrimination algorithm is designed to distinguish a touch of a thumb from a touch of a finger.

This can be achieved, among other things, by detecting the size of the print, as a thumb print is usually larger than a finger print. The position of the thumb print is also usually clear, as the thumb is usually further away from the other fingers when gripping a rotary push button than the other fingers are from each other.

In a further further embodiment, it is provided that a display device is provided which is designed to display a content, wherein the content depends on whether the rotary push button is operated by a driver's hand or a passenger's hand.

A first independent subject matter relates to a motor vehicle with an operating device of the type described above.

Further advantages, features and details emerge from the following description, in which - if necessary with reference to the drawing - at least one embodiment is described in detail. Identical, similar and/or functionally identical parts are provided with the same reference numerals.

• 1 ein Kraftfahrzeug mit einer Bedieneinrichtung;
• 2 ein Koordinatensystem mit erkannten Fingern einer Beifahrerhand, sowie
• 3 ein Klassifikator zur Unterscheidung von Fahrerhänden und Beifahrerhänden.

They show schematically:

• 1 a motor vehicle with an operating device;
• 2 a coordinate system with recognized fingers of a passenger hand, as well as
• 3 a classifier to distinguish between driver's hands and passenger's hands.

1 shows schematically a motor vehicle 2 with an operating device 4.

The operating device 4 has a rotary push button 6, which has a top side 6.1 and a peripheral ring 6.2. The top side 6.1 and peripheral ring 6.2 are designed to be touch-sensitive and each have surfaces that are capable of multi-touch recognition and are based on PCT technology, for example. The rotary push button 6 is arranged on a center console 6.3.

The operating device 4 further comprises a display device 8 which displays a content 8.1. The operating device 4 is controlled by a controller 10 which implements a differentiation algorithm 10.1 which can distinguish between operation of the rotary push button 6 with a right hand 12 and operation of the rotary push button 6 with a left hand 14.

The upper side 6.1 and the peripheral ring 6.2 of the rotary push button 6 detect the position and size of finger contact points and can use the differentiation algorithm 10.1 trained with artificial intelligence to determine whether the corresponding operating hand comes from the driver or the passenger.

As a result, the display device 8 can display different contents 8.1, which can be reduced for a driver whose attention must be focused on the road traffic than for a passenger who can process more information on the display device 8 and also conveys its interest to the driver. As a result, the display device 8 can differentiate, which can be reduced for a driver whose attention must be focused on the road traffic than for a passenger, whose interest is also conveyed to the driver.

2 shows a coordinate system K, which represents the rotary push button 6.

The coordinate system K with its origin O is centered on the center of rotation of the top side 6.1 of the rotary push button 6. Finger contact points 14.1 to 14.4 and the thumb contact point 14.5 of a passenger hand 14 are shown within the coordinate system K. The finger contact points 14.1 to 14.4 and the thumb contact point 14.5 are predominantly located on the peripheral ring 6.2. However, the index finger 14.4 also touches the top side 6.1.

Based on the relative position of the finger contact points 14.1 to 14.4 and the thumb contact point 14.5 to one another as well as the respective surface areas of the contact points 14.1 - 14.5, which the rotary push button 6 can detect, the differentiation algorithm 10.1 can determine that the rotary push button 6 was touched by the passenger's hand 14.

If only one touch point is detected, a different procedure is used. The entire output is marked as right hand if the thumb is on the left side of the rotary push button 6, and as right hand if the thumb is on the left side of the rotary push button 6. The position of the thumb would then be sufficient to obtain a probability that the touching hand is a right or left hand.

If a sufficiently reliable assignment cannot be achieved, it is possible to only display data for the driver as a fallback position.

3 shows a classifier.

Driver hand data vectors 16 and passenger hand data vectors 18 are separated by a dividing line 20, whereby driver hand data vectors 16 and passenger hand data vectors 18 can be grouped together in various ways, for example according to the K-Means method.

The K-means method is an unsupervised machine learning method used for cluster analysis. It is used to divide a set of data points into groups, called clusters, where k is a given number. The goal is to maximize the similarity of the data points within a cluster while minimizing the differences between the clusters. The similarity is typically quantified using a distance metric, such as Euclidean distance.

Although the invention has been illustrated and explained in detail by preferred embodiments, the invention is not limited by the disclosed examples and other variations can be derived therefrom by the person skilled in the art without departing from the scope of the invention. It is therefore clear that a multitude of possible variations exist. It is also clear that embodiments mentioned by way of example really only represent examples that are not to be understood in any way as a limitation of the scope of protection, the possible applications or the configuration of the invention. Rather, the preceding description and the description of the figures enable the person skilled in the art to implement the exemplary embodiments in concrete terms, whereby the person skilled in the art, with knowledge of the disclosed inventive concept, can make various changes, for example with regard to the function or the arrangement of individual elements mentioned in an exemplary embodiment, without departing from the scope of protection defined by the claims and their legal equivalents, such as a further explanation in the description.

list of reference symbols

2

motor vehicle

4

control device

6

rotary push button

6.1

top

6.2

circumferential ring

6.3

center console

8

display device

8.1

Contents

10

steering

10.1

discrimination algorithm

12

driver's hand

14

passenger hand

14.1 - 14.4

finger touch point

14.5

thumb contact point

16

driver hand data vectors

18

passenger hand data vectors

20

dividing line

K

coordinate system

O

origin

QUOTES INCLUDED IN THE DESCRIPTION

This list of documents listed 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 accepts no liability for any errors or omissions.

Cited patent literature

• US 2009/0082951 A1 [0007]

Claims (8)

Operating device (4) of a motor vehicle (2), with a rotary push button (6), wherein the rotary push button (6) has at least one touch-sensitive surface (6.1, 6.2), wherein a controller (10) is provided which is designed to process signals from the rotary push button (6), characterized in that the touch-sensitive surface (6.1, 6.2) is designed to register more than one touch point (14.1 - 14.5) simultaneously, wherein the controller (10) has a differentiation algorithm (10.1) which is designed to register whether the plurality of touch points (14.1 - 14.5) originate from a driver's hand (12) or a passenger's hand (14). Control device (4) according to claim 1 , characterized in that the touch-sensitive surface is a peripheral ring (6.2). Control device (4) according to claim 1 or 2 , characterized in that the touch-sensitive surface (6.1, 6.2) has a projected capacitive touch sensor. Operating device (4) according to one of the preceding claims, characterized in that the differentiation algorithm (10.1) has a neural network which is trained with the aid of at least one data set which contains contact points of driver's hands and contact points of passenger's hands. Operating device (4) according to one of the preceding claims, characterized in that the differentiation algorithm (10.1) is a classification algorithm. Operating device (4) according to one of the preceding claims, characterized in that the differentiation algorithm (10.1) is designed to distinguish a touch of a thumb from a touch of a finger. Operating device according to one of the preceding claims, characterized in that a display device (8) is provided which is designed to display a content (8.1), the content (8.1) depending on whether the rotary push button (6) is operated by a driver's hand (12) or a passenger's hand (14). Motor vehicle with an operating device (4) according to one of the preceding claims.

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