Abstract: A computer implemented method for analyzing a reinforcement learning agent based on an artificial neural network, which includes: acquiring data of a plurality of runs of the artificial neural network; processing the acquired data using an attributation method to obtain attributation data; and analyzing the artificial neural network based on the attributation data.

Abstract: A computer implemented method for determining a driving trajectory as training data for machine learning based adaptive cruise control. The method includes the following steps carried out by computer hardware components: determining a cost function; determining at least one side condition; and determining the driving trajectory based on solving an optimization problem, and the optimization problem is based on the cost function and the at least one side condition.

Abstract: A method for planning the motion of a vehicle includes: determining a nominal trajectory for the vehicle based on a desired maneuver to be carried out in a traffic space, on a current state of movement of the vehicle and on a detected state of a surrounding of the vehicle, and determining an abort trajectory branching off from the nominal trajectory and guiding the vehicle to a safe condition regardless of the desired maneuver, wherein the nominal trajectory and the abort trajectory are determined simultaneously using a single optimization process.

Abstract: A computer implemented method for determining a maneuver to be executed by an autonomous vehicle comprises the following steps carried out by computer hardware components: determining a plurality of potential maneuvers; determining a subset of the potential maneuvers based on a pre-determined condition; determining a mask based on the subset; determining an output of a fully connected layer of a neural network; determining a dot product of the output of the fully connected layer and the mask; and determining the maneuver to be executed based on the dot product.

Abstract: The present disclosure enables a collection of training data suitable for training an autonomous driving system of a vehicle. A database is provided that stores predefined road scenarios, and user devices are provided with a simulation game for controlling a vehicle agent in a road scenario. A plurality of user devices, running the simulation game, play a road scenario from the database to control a vehicle agent in the simulation game with steering actions entered by individual users, which generates a human demonstration of each road scenario that is played. Several human demonstrations played on the plurality of user devices can be maintained by a demonstration database and made available as training data suitable for training an autonomous driving system of a vehicle. A large amount of training data can be automatically generated, without requiring expensive or time-consuming real-world tests to generate suitable training data manually.

Abstract: A method for planning the motion of a vehicle includes: determining a nominal trajectory for the vehicle based on a desired maneuver to be carried out in a traffic space, on a current state of movement of the vehicle and on a detected state of a surrounding of the vehicle, and determining an abort trajectory branching off from the nominal trajectory and guiding the vehicle to a safe condition regardless of the desired maneuver, wherein the nominal trajectory and the abort trajectory are determined simultaneously using a single optimization process.

Abstract: A method to determine the heading or orientation of a target vehicle by a host vehicle, said host vehicle equipped with a lidar or radar system, said system including a sensor unit adapted to receive signals emitted from said host vehicle and reflected by said target vehicle, comprising: a) determining at least one reference angle being an initial estimate of target heading or orientation (?); b) emitting a signal from said system and determining a plurality of point radar or lidar detections belonging to said a target vehicle, said point detections having co-ordinates in the horizontal plane; c) formulating an initial rectangular boundary box from said point detections, where the bounding box is formulated such that such that two edges of the boundary box are drawn parallel to the reference angle and two sides are perpendicular to the reference angle and such that all the detections are either on the bounding box sides or lay within the bounding box and each edge has at least one detection point on it; d) fo

Abstract: A method to determine the heading or orientation of a target vehicle by a host vehicle, said host vehicle equipped with a lidar or radar system, said system including a sensor unit adapted to receive signals emitted from said host vehicle and reflected by said target vehicle, comprising: a) determining at least one reference angle being an initial estimate of target heading or orientation (?); b) emitting a signal from said system and determining a plurality of point radar or lidar detections belonging to said a target vehicle, said point detections having co-ordinates in the horizontal plane; c) formulating an initial rectangular boundary box from said point detections, where the bounding box is formulated such that such that two edges of the boundary box are drawn parallel to the reference angle and two sides are perpendicular to the reference angle and such that all the detections are either on the bounding box sides or lay within the bounding box and each edge has at least one detection point on it; d) fo