Abstract: The present disclosure is directed at systems and methods for determining objects around a vehicle. In aspects, a system includes a sensor unit having at least one radar sensor arranged and configured to obtain radar image data of external surroundings to determine objects around a vehicle. The system further includes a processing unit adapted to process the radar image data to generate a top view image of the external surroundings of the vehicle. The top view image is configured to be displayed on a display unit and useful to indicate a relative position of the vehicle with respect to determined objects.

Abstract: A computer-implemented method for generating ground truth data may include the following steps carried out by computer hardware components: for a plurality of points in time, acquiring sensor data for a respective point in time; and for at least a subset of the plurality of points in time, determining ground truth data of the respective point in time based on the sensor data of at least one present and/or past point of time and at least one future point of time.

Abstract: A computer-implemented method for training a machine-learning method comprises the following steps carried out by computer hardware components: determining measurement data from a first sensor; determining approximations of ground truths based on a second sensor; and training the machine-learning method based on the measurement data and the approximations of ground truths; wherein approximations of ground truths of lower-approximation quality have a lower effect on the training than approximations of ground truths of higher-approximation quality.

Abstract: A computer implemented method for detection of objects in a vicinity of a vehicle comprises the following steps carried out by computer hardware components: acquiring radar data from a radar sensor; determining a plurality of features based on the radar data; providing the plurality of features to a single detection head; and determining a plurality of properties of an object based on an output of the single detection head.

Abstract: A method for lane marker recognition includes: providing a filter bank with a plurality of different pairs of filters adapted to detect the left edge and the right edge of a specific type of a lane marker, respectively; receiving an image of a road; dividing the image of a road into a plurality of image segments, wherein each image segment includes at least one row of pixels of the image of a road; and for each of the image segments: applying a plurality of the pairs of filters of the filter bank to the image segment to generate a plurality of filter outputs; and determining which of the filter outputs correspond to a lane marker by using geo-metric information and appearance based information, wherein the geometric in-formation describes allowable dimensions of a determined lane marker, and the appearance based information describes allowable pixel values of a determined lane marker.

Abstract: A method for lane marker recognition includes: providing a filter bank with a plurality of different pairs of filters adapted to detect the left edge and the right edge of a specific type of a lane marker, respectively; receiving an image of a road; dividing the image of a road into a plurality of image segments, wherein each image segment includes at least one row of pixels of the image of a road; and for each of the image segments: applying a plurality of the pairs of filters of the filter bank to the image segment to generate a plurality of filter outputs; and determining which of the filter outputs correspond to a lane marker by using geo-metric information and appearance based information, wherein the geometric in-formation describes allowable dimensions of a determined lane marker, and the appearance based information describes allowable pixel values of a determined lane marker.