Abstract: The disclosure relates to a method for checking plausibility of a trajectory generated based on swarm data for a first motor vehicle, which is operated in an at least partially assisted manner. The method includes: receiving the swarm data, detecting a second motor vehicle in a surrounding area of the first motor vehicle by a detection device, determining a driving trajectory of the second motor vehicle, comparing the trajectory generated based on the swarm data with the driving trajectory of the second motor vehicle, and checking the plausibility of the swarm data based on the comparing. The disclosure further relates to a computer-readable medium and to an assistance system.

Abstract: The disclosure relates to a motor vehicle and a method for summarizing a conversation in a motor vehicle. The method involves determining by a vehicle sensor device whether a challenging driving task is present; if the challenging driving task is present, masking a conversation in the motor vehicle for a driver by generating counter noise; recording the conversation in the motor vehicle by at least one vehicle microphone; summarizing the conversation by artificial intelligence; outputting a summary of the conversation to the driver after determining that the challenging driving task is no longer present; and deactivating the counter noise after the outputting the summary of the conversation.

Abstract: A method is provided for the spatial characterization of at least one vehicle image of image information, wherein the image information encompasses the vehicle image of an external vehicle and an environment image of an environment of the external vehicle. The method comprises: determining a bounding box for the vehicle image, in order to use the bounding box for a delimiting of the vehicle image from the environment image, determining a splitting line for the bounding box, in order to use the splitting line for a partitioning of the vehicle image into at least two vehicle sides, determining the spatial characterization with the aid of the bounding box and the splitting line, wherein at least one evaluation means based on machine learning, especially a neural network, is used for the determining of the bounding box and the splitting line.

Abstract: The invention relates to a method for checking the fitness of a driver to drive a motor vehicle (10) and to a motor vehicle (10) for carrying out a method of this kind.

Abstract: The disclosure relates to a method for deleting user data in a motor vehicle. The method includes storing user data in an eUICC chip of a communication controller that enables user access to a mobile radio network, the user profile data including setting data of a device setting performed during use of the motor vehicle by at least one user in at least one other controller different from the communication controller, and receiving a delete command for removal of the user profile data in the communication controller by a profile assistant module of the communication controller from a server computer, the profile assistant module being coupled to a data management module of the motor vehicle, executing the delete command, wherein the user access to the mobile radio network is prevented by executing the delete command, and sending a clearing command by the profile assistant module to the data management module.

Abstract: The disclosure relates to a method for outputting a navigation instruction in a motor vehicle to head toward a possible stopping point, wherein a navigation system of the motor vehicle determines a current speed of the motor vehicle and at least one topology parameter in a predetermined vicinity of a previously determined possible stopping point and determines a time at which the outputting of the navigation instruction to the user to head toward the possible stopping point should occur, at least in dependence on the determined current speed and the at least one determined topology parameter. At the determined time, the navigation system outputs the navigation instruction to the user to head toward the possible stopping point. The disclosure furthermore relates to a server device that provides electronic map data to a navigation system of a motor vehicle in order to carry out such a method.

Abstract: The disclosure relates to a method for operating a vehicle interior monitoring system including at least one camera unit. A control device sets an adjustable camera parameter of the camera unit by a camera-specific control command in the camera unit and receives and evaluates at least one image recorded by the camera unit, and a result of the evaluation is output as a camera-specific result datum. The control device generates a general control command that sets the adjustable camera parameter of the camera unit, the general control command is converted based on a camera configuration of the camera unit saved in the control device into the camera-specific control command, the camera-specific result datum is converted based on the camera configuration of the camera unit saved in the control device into a general result datum, and the general result datum of the camera unit is provided to a data fusion device.

Abstract: A method for localizing a motor vehicle in an environment during a driving operation comprises, by a processor circuit in repeated estimation cycles, receiving sensor data of landmarks of the environment from an environment sensor, and ascertaining a respective estimated position of the motor vehicle from feature data, which are formed of map data of a map region of the environment and of the sensor data, using an estimation module. A movement path is estimated from the positions of multiple of the estimation cycles using a statistical observer model, and the observer model, during the formation of the movement path, models measurement noise contained in the position data as a covariance matrix of position coordinates of the position data, with matrix values of the covariance matrix being ascertained by the estimation module as a function of the sensor data and the map data.

Abstract: A method for performing a checking of a person, such as a vehicle passenger, by way of infrared radiation involves determining the distance between a source of infrared radiation and the person by way of light according to a distance definition and setting the intensity of the infrared radiation in dependence on the distance as determined.

Abstract: Automatically moving a vehicle based on defined sequences on private grounds, which are passed by the automatically moved vehicle one after the other. Thereby it is may be easier to perform automated driving.

Abstract: The invention relates to a method (100) for generating a data set (60) for training and/or testing a machine learning system (50), comprising: providing (101) image data that are specific for depictions in which different environment scenarios are represented, providing (102) metadata (65) that are specific for a description of the different environment scenarios, creating (103) text prompts (70) based on the provided metadata (65), using information contained in the metadata (65) for the text prompts (70), generating (104) the data set (60) based on the created text prompts (70) and preferably the provided image data.

Abstract: A method for training an artificial neural generator network for the generating of synthetic landmark images is provided, in which landmark images are extracted from at least one training map as training data, which form a first training data set, and the generator network as a generator of a generative adversarial network learns with the aid of the first training data set and with the aid of real, non-annotated image data, recorded by a sensor device, to generate synthetic landmark images which are suited to reproducing the probability distribution underlying the first training data set. The invention also relates to a method for training an artificial neural localization network by the trained generator network and a method for determining a position of a mobile unit with at least one sensor device and at least one environment map by the trained localization network.

Abstract: A detection device for determining a topography of a vehicle environment comprises a camera unit which is configured to detect at least one image of the surroundings of the vehicle environment, wherein the respective image of the surroundings comprises pixels arranged at respective image coordinates of the image of the surroundings. It is provided that the detection device comprises an evaluation unit which is configured to process the respective image of the surroundings according to a predetermined height determination method, wherein the image of the surroundings in the predetermined height determination method is fed to a first artificial neural network which is trained to assign respective height values to the respective pixels of the respective image of the surroundings in a world coordinate system of the vehicle environment with respect to a predetermined horizontal plane.

Abstract: A method for operating a driving dynamics system facility of a motor vehicle includes using a control device that provides driving style data while driving, and establishes a driver type for the driver. The control device establishes a road category of a roadway. Based on the driver type and the road category, the control device establishes a current driving context, and performs a preliminary selection of at least one driving mode. Based on driver monitoring data, the control device establishes a current emotion of the driver, and selects with the aid of this one of the preselected driving modes. The control device generates a switching signal for switching to the driving mode being activated and configures accordingly the at least two motor vehicle systems. The driving mode can be adapted based on further driver monitoring data, describing a reaction of the driver to the activated driving mode.

Abstract: An automated driving function in a motor vehicle comprises: a processor circuit of the motor vehicle recognizes respective individual images of an environment of the motor vehicle from sensor data of a least one sensor of the motor vehicle by means of at least one object classifier. At least one relational classifier using the object data for at least some of the individual objects additionally recognizes a respective pairwise object relation with the aid of predetermined relation features of the individual objects in the respective individual image determined from the sensor data, which relation is described by relational data, and an aggregation module is used to aggregate the relational data throughout multiple consecutive individual images to produce aggregation data, which describe aggregated object relations.

Abstract: A method and a system for the at least partially automated parking of a motor vehicle, wherein a trajectory is provided, the motor vehicle is driven in an at least partially automated manner along the trajectory, and the trajectory is displayed on a display device with an overview map of an environment. Furthermore, by at least one camera, environment regions of the environment are captured as respective image data, at least some of which are saved allocated to the related environment regions, wherein at the time of display of the overview map, all of the image data saved up until this point in time are displayed in corresponding display regions on the overview map.

Abstract: In a method for determining and classifying at least one object in a sensing area of a sensor, a two- or three-dimensional image of the sensing area is captured by means of the sensor. Sensor data corresponding to the image is generated. The object in the image is determined by means of the sensor data and by means of first template data of at least one first template object using a neural network. The neural network has been trained using the first template data. The first template data corresponds to an image of the first template object. At least one first object class is associated with the first template object. The object is classified by the neural network determining whether the object belongs to the first object class or not.

Abstract: Approaches, techniques, and mechanisms are disclosed for large scale vehicle data collaborative analysis. According to one embodiment, a large amount of data streams is received from a multitude of vehicles. A distributed event streaming system is applied to parse the data streams based on an attribute, such as time sensitive data, location-specific data, or vehicle maintenance, operational, or fault-prevention data. A data container platform instance hosts applications that receive the parsed data streams. Output of an application is transformed into data streams having a common topic. Other applications may access the data streams by topic. Upon receiving an indication that an application has processed a data stream by topic, a decision point may be reached and executed by an external application, triggering an action on a vehicle from the multitude of vehicles. A vehicle computing system accesses topic data streams and performs an action on the vehicle.

Abstract: The disclosure relates to a method for presenting a shared virtual environment to users residing in different vehicles while driving in a real-world environment. In at least one of the vehicles, an interactive user device of that vehicle receives definition data from the user residing in that vehicle, wherein the definition data describe a new virtual event for the virtual environment, and a position sensor of the vehicle generates position data of the vehicle while the user generates the definition data, wherein the position data describe a current position of the vehicle in the real-world environment. A server device receives the definition data and the corresponding position data and generates corresponding event data of a new virtual event, wherein based on the position data a trigger region is defined that defines where in the real-world environment the virtual event shall be triggered for the users in their respective vehicle.

Abstract: A driver assistance method by a control device is to receive driving environmental data from identically constructed motor vehicle sensor technologies of a first motor vehicle, as well as from at least one further motor vehicle, which drive on a set road section in an at least partially autonomous driving mode. Each motor vehicle may provide a road section model for each of the motor vehicles with an algorithm recorded in each respective motor vehicle. The control device examines the road section models and/or the algorithms for a feasibility of the at least partially autonomous driving mode for the first motor vehicle, evaluates the algorithms of each motor vehicle based on a comparison of the road models, and sets that algorithm, which satisfies the set feasibility criterion with the highest probability, as the target algorithm.