Abstract: The present disclosure relates to a method for the detection and determination of the height of objects by means of an environment detection system, including a first environment detection sensor and a second environment detection sensor of a vehicle, wherein at least one of the environment detection sensors is a mono camera. The method includes the following steps: capturing a mono image using the camera; capturing an environment representation using the second environment detection sensor; carrying out object detection in the mono image; carrying out object detection in the environment representation of the second environment detection sensor; measuring the distance from the object in the environment representation of the second environment detection sensor; and carrying out height determination of the detected object.

Abstract: A method for determining depth information relating to image information by an artificial neural network in a vehicle, comprising providing at least one emitter and first and second receiving sensors being spaced apart from one another; emitting electromagnetic radiation by the emitter; receiving reflected proportions of the electromagnetic radiation emitted by the emitter by the receiving sensors and generating first image information by the first receiving sensor and second image information by the second receiving sensor on the basis of the received reflected proportions; comparing the first and second image information for determining an image area unequally illuminated in the first and second image information which occurs by parallax due to the spaced-apart arrangement of the receiving sensors; evaluating geometric information of the unequally illuminated image area and estimating depth information by the artificial neural network on the basis of the evaluation of the geometric information.

Abstract: A method for determining information about the ego-motion of a vehicle, wherein the vehicle comprises a stereo camera system with at least two cameras for capturing stereo images of the area surrounding the vehicle and an artificial neural network for processing the image information provided by the stereo camera system, wherein the stereo camera system captures image sequences which contain a plurality of image information at different points in time by means of the at least two cameras during the movement of the vehicle, wherein the artificial neural network receives the image information and, based thereon, generates stereo images with distance information, and the artificial neural network provides information regarding the ego-motion of the vehicle at an output interface on the basis of the image information of the stereo camera system.

Abstract: The present disclosure relates to a method for the detection and determination of the height of objects by means of an environment detection system, including a first environment detection sensor and a second environment detection sensor of a vehicle, wherein at least one of the environment detection sensors is a mono camera. The method includes the following steps: capturing a mono image using the camera; capturing an environment representation using the second environment detection sensor; carrying out object detection in the mono image; carrying out object detection in the environment representation of the second environment detection sensor; measuring the distance from the object in the environment representation of the second environment detection sensor; and carrying out height determination of the detected object.

Abstract: Example embodiments relate to an ADAS sensor data processing unit, to an ADAS sensor system and to an ADAS sensor data evaluation method for use in driver assistance systems or systems for the automated driving of a vehicle. The ADAS sensor data processing unit includes an input interface, a decompression module, a processing unit and an output unit. The input interface is designed to receive data of an ADAS sensor that have been subjected to lossy compression by a compression module. The decompression module is designed to decompress the compressed data of the ADAS sensor. The processing unit is designed to process the decompressed data (IdSD) of the ADAS sensor, information relevant to an ADAS/AD function being ascertained from the decompressed sensor data. The output unit is designed to output the ascertained information relevant to the ADAS function.

Abstract: The disclosure relates to a method and system for extracting disparity information out of a pair of stereo camera images for processing images of camera sensors for Automated Driving or Advanced Driver Assistance Systems in a vehicle. The method includes: a) receiving a pair of unrectified stereo camera images, b) performing a 2D-matching of the received pair of images using a trained convolutional neural network and providing the 2D-displacement on a pixel-by-pixel level as disparity information, and c) outputting the 2D-displacement on pixel level. The method is robust which does not require a high precision rectification. Applying rectification on the disparity values after the matching process leads to reduced algorithmic complexity with simultaneous preservation of all information.

Abstract: A method for classification of ground conditions in the vicinity of a vehicle using a radar sensor, comprising: receiving reflected portions of a radar signal at a receiver unit of a radar system; calculating information derived from the received portions of the radar signal for discrete spatial regions by the radar system or a control unit connected thereto; assigning the information to data structure units associated with a geographical location and the assignment of the information taking into account movement of the vehicle; collecting pieces of information in the respective data structure units, the pieces of information being obtained from reflected portions of radar signals transmitted at different times; evaluating the information contained in the data structure using a classifier to obtain information regarding the ground condition; assigning ground condition types to the data structure units based on evaluation results obtained by the classifier.

Abstract: A method for determining the roadway plane in the surrounding area of a vehicle, the vehicle comprising a stereo camera system for capturing stereo images of the surrounding area of the vehicle and an artificial neural network for processing the image information provided by the stereo camera system, wherein the neural network determines disparity information of the surrounding area of the vehicle, wherein, on the basis of the disparity information, distance information is calculated which contains information regarding the distance of the objects displayed on the image information from the stereo camera system or the vehicle, wherein roadway distance information is extracted from the distance information, wherein the roadway plane is determined on the basis of the roadway distance information.

Abstract: Example embodiments relate to an ADAS sensor data processing unit, to an ADAS sensor system and to an ADAS sensor data evaluation method for use in driver assistance systems or systems for the automated driving of a vehicle. The ADAS sensor data processing unit includes an input interface, a decompression module, a processing unit and an output unit. The input interface is designed to receive data of an ADAS sensor that have been subjected to lossy compression by a compression module. The decompression module is designed to decompress the compressed data of the ADAS sensor. The processing unit is designed to process the decompressed data (IdSD) of the ADAS sensor, information relevant to an ADAS/AD function being ascertained from the decompressed sensor data. The output unit is designed to output the ascertained information relevant to the ADAS function.

Abstract: A camera device for a vehicle for 3-D environment sensing includes at least two camera modules having at least partly overlapping sensing ranges, a camera control unit, an evaluation unit and a point light projector. The point light projector is arranged and configured in such a way that the point light projector projects a light pattern of measurement points into the vehicle environment. The at least two camera modules are arranged and configured in such a way that at least part of the projected light pattern is imaged in the overlapping sensing range. The evaluation unit is configured to determine the 3-D position of measurement points in the vehicle environment from image data captured with the at least two camera modules. The point light projector is configured to produce a series of “pseudo-noise patterns” as the light pattern, the “pseudo-noise patterns” being projected into the vehicle environment in temporal succession.

Abstract: A camera system for a vehicle includes a camera and an image evaluating unit. The camera is arranged in an interior of the vehicle behind a windowpane of the vehicle so that the camera can record an image sequence with a plurality of external recordings of external surroundings of the vehicle through the windowpane. The image evaluating unit is adapted to detect static image components that are projected into the external recordings by reflections on the windowpane, and to extract the detected static image components from the external recordings.

Abstract: A method and a device for determining the position of a vehicle, said method comprising the steps: recording sensor data from the ground over which the vehicle travels; extracting ground characteristics of the ground over which the vehicle travels from the recorded sensor data or from occupancy grids which are calculated on the basis of the sensor data; determining the current position of the vehicle on the basis of the extracted ground characteristics using a characteristic map.

Abstract: A driver assistance system of a motor vehicle includes a lighting system of the motor vehicle, having an illumination unit that illuminates a scene in the surroundings of the vehicle by projecting a number of actuatable pixels, whereby the illumination unit projects a predefined pattern onto the scene. An image capture unit captures an image of at least part of the scene. A computation unit computes at least one geometric property of the scene based on the captured image and the predefined pattern.

Abstract: A camera device for a vehicle for 3-D environment sensing includes at least two camera modules having at least partly overlapping sensing ranges, a camera control unit, an evaluation unit and a point light projector. The point light projector is arranged and configured in such a way that the point light projector projects a light pattern of measurement points into the vehicle environment. The at least two camera modules are arranged and configured in such a way that at least part of the projected light pattern is imaged in the overlapping sensing range. The evaluation unit is configured to determine the 3-D position of measurement points in the vehicle environment from image data captured with the at least two camera modules. The point light projector is configured to produce a series of “pseudo-noise patterns” as the light pattern, the “pseudo-noise patterns” being projected into the vehicle environment in temporal succession.

Abstract: A device for determining the detection range of a sensor unit for a motor vehicle includes: a memory unit configured to provide a map having map data regarding a landmark and a target detection range, a reflectivity property and/or a radiant intensity respectively associated with the landmark; a sensor unit configured to detect the landmark in surroundings with an actual detection range and/or to measure a received signal intensity for the landmark; and a computing unit configured to determine a detection range of the sensor unit based on the target detection range and the actual detection range and/or based on a comparison of the received signal intensity with a calculated signal intensity derived from the reflectivity property and/or the radiant intensity associated with the landmark.

Abstract: A method for classification of ground conditions in the vicinity of a vehicle using a radar sensor, comprising: receiving reflected portions of a radar signal at a receiver unit of a radar system; calculating information derived from the received portions of the radar signal for discrete spatial regions by the radar system or a control unit connected thereto; assigning the information to data structure units associated with a geographical location and the assignment of the information taking into account movement of the vehicle; collecting pieces of information in the respective data structure units, the pieces of information being obtained from reflected portions of radar signals transmitted at different times; evaluating the information contained in the data structure using a classifier to obtain information regarding the ground condition; assigning ground condition types to the data structure units based on evaluation results obtained by the classifier.

Abstract: The invention relates to a camera system (2) for a vehicle. The camera system (2) comprises a camera (3) and an image evaluating unit (4), wherein the camera (3) is adapted to be arranged in an interior (6) of the vehicle behind a windowpane (7) of the vehicle so that the camera (3) can record an image sequence with a plurality of external recordings of external surroundings (8) of the vehicle through the windowpane (7). Further, the image evaluating unit (4) is adapted to detect static image components in the external recordings and to extract the detected static image components from the external recordings, wherein the static image components are projected into the external recordings through reflections.

Abstract: The invention relates to a driver assistance system of a motor vehicle comprising a lighting system (1) of the motor vehicle, having an illumination unit (2) configured to illuminate a scene (3) in the surroundings of the vehicle by projecting a total area (5), consisting of a total number of actuatable pixels (4), wherein the illumination unit (2) is configured to project a predefined pattern onto the scene; an image capture unit (7) configured to capture an image of at least part of the scene; and a computation unit (8) configured to compute at least one geometric property (9; 10) of the scene by means of the captured image and the predefined pattern.

Abstract: The present invention relates to a device for determining the range of a sensor for a motor vehicle, wherein the device (1) comprises: a memory unit (10), which is designed to provide, as an attribute, a map having at least one landmark and a target detection range associated with the landmark and/or a reflectivity property associated with the landmark and/or a radiant intensity associated with the landmark; a sensor unit (20), which is designed to detect the at least one landmark with an actual detection range and/or to measure a received signal intensity for the at least one landmark; and a computing unit (30), which is designed to determine a detection range of the sensor unit (20) based on the target detection range and the actual detection range and/or based on a comparison of the signal intensity measured for the respective landmark and the calculated signal intensity, which can be derived from the reflectivity property recorded in the map and/or the radiant intensity of the respective landmark.

Abstract: A method of saving image data of a camera in an accident data recorder of a vehicle involves: a) performing object recognition to determine object data regarding objects detected from the camera image data; b) compressing the camera image data by a lossy compression method to form compressed image data; c) storing the object data and the compressed image data in a storage unit; d) overwriting the data in the storage unit after a predefined volume of data has been stored; and e) statically saving the object data and the compressed image data in response to a trigger signal.