Abstract: A method for generating a self-explaining decision in an artificial intelligence (AI) system includes receiving or defining a graph for a task in the AI system, the graph including a plurality of nodes connected by edges. Message passing is performed among the nodes of the graph, wherein a discrete attention mechanism is implemented during the message passing, whereby features of each node are transformed into a discrete representation, which varies depending on which neighboring node a message is passed to. The self-explaining decision is generated for one of the nodes based on the message passing.

Abstract: A method for determining a location relationship between a camera and a headlight of a vehicle includes positioning the vehicle at a distance in front of a surface exhibiting a calibration pattern, ascertaining the distance between the calibration pattern and the vehicle, projecting a pattern onto the surface using a headlight of the vehicle, and detecting characteristic features in the projected pattern. The method further includes performing the previous steps for at least one additional distance between the vehicle and the surface. In addition, the method includes interpolating positions of detected characteristic features that correspond in each case to one another at the different distances using a linear function, determining an intersection of the ascertained linear functions, and determining the location relationship between the camera and the headlight of the vehicle on the basis of the position of the intersection of the ascertained linear functions relative to the camera.

Abstract: A method for operating a lighting apparatus for a motor vehicle includes producing an overall light distribution based on a desired light distribution and an aiming apparatus of a lamp using an algorithm. The lighting apparatus has at least one lamp configured to provide for illumination of surroundings of the motor vehicle, and the lamp has an overall light distribution that results from a multiplicity of light distributions from light sources of a light source module of the lamp in conjunction with a light shaping element.

Abstract: A method for determining a location relationship between a camera and a headlight of a vehicle includes positioning the vehicle at a distance in front of a surface exhibiting a calibration pattern, ascertaining the distance between the calibration pattern and the vehicle, projecting a pattern onto the surface using a headlight of the vehicle, and detecting characteristic features in the projected pattern. The method further includes performing the previous steps for at least one additional distance between the vehicle and the surface. In addition, the method includes interpolating positions of detected characteristic features that correspond in each case to one another at the different distances using a linear function, determining an intersection of the ascertained linear functions, and determining the location relationship between the camera and the headlight of the vehicle on the basis of the position of the intersection of the ascertained linear functions relative to the camera.

Abstract: A method for checking the plausibility of detected features of a light distribution of a headlamp of a motor vehicle includes irradiating, by the headlamp, a scene in surroundings of the motor vehicle; capturing, by a camera of the motor vehicle, the irradiated scene in an image; dynamically seeking and identifying at least one initial optical feature in the image, adaptively producing and analyzing local surroundings of the at least one initial optical feature; dynamically extracting at least one further optical feature from the local surroundings; and carrying out, using a learned algorithm and on the basis of the at least one initial optical feature and the at least one further optical feature, an adaptive check as to whether the at least one initial optical feature and the at least one further optical feature are plausibly arranged in the local surroundings.

Abstract: A method for checking the plausibility of detected features of a light distribution of a headlamp of a motor vehicle includes irradiating, by the headlamp, a scene in surroundings of the motor vehicle; capturing, by a camera of the motor vehicle, the irradiated scene in an image; dynamically seeking and identifying at least one initial optical feature in the image, adaptively producing and analyzing local surroundings of the at least one initial optical feature; dynamically extracting at least one further optical feature from the local surroundings; and carrying out, using a learned algorithm and on the basis of the at least one initial optical feature and the at least one further optical feature, an adaptive check as to whether the at least one initial optical feature and the at least one further optical feature are plausibly arranged in the local surroundings.