Abstract: A computer-implemented method for validating a behavior planner for an automated vehicle. The behavior planner has a database having previously defined partial situations and an evaluation model for each partial situation to break down a given situation into partial situations of the database and, based on the associated evaluation models, to determine boundary conditions for permissible behavior options of the vehicle in the given situation, as a combination of boundary conditions of the individual partial situations. The evaluation models of the partial situations are made available in a declarative program representation which enables the determination of formally explorable boundary conditions for permissible behavior options of the vehicle in the particular partial situation. A test situation is predefined as a composition of selected partial situations.

Abstract: A method for controlling a vehicle. In the method, data of a digital road map are read in, zones are determined for the digital road map, and possible sequences of trips along a road of the digital road map are ascertained as a function of the determined zones. Furthermore, it is ascertained, as a function of sensor data and/or current driving data of the vehicle, whether a current or predicted traffic situation is outside the possible sequences or corresponds to a possible sequence that is determined as being outside an intended operating range. If the current or predicted traffic situation is outside the possible sequences or corresponds to the possible sequence outside the intended operating range, a measure is determined and the vehicle is controlled as a function of the measure that is taken.

Abstract: A computer-implemented method and a corresponding system for planning the behavior of a vehicle using a predefined set of rules with prioritized rules for assessing possible behaviors of the vehicle in a given situation. For this purpose, situation-specific information is aggregated, and an environmental model of the given situation is generated based on the aggregated situation-specific information. The set of rules includes a decision-making process structure, which represents the prioritization of the individual rules of the set of rules. On the basis of the environmental mode, boundary conditions for the possible behaviors of the vehicle are determined. The latter are then prioritized by applying the decision-making process structure to the respective boundary conditions.

Abstract: A computer-implemented method for the behavior planning of an at least partially automated EGO vehicle. The method uses a database of pre-defined partial situations and an evaluation model for each partial situation, as well as a pre-defined rule set for evaluating possible behaviors of the EGO vehicle in a given situation. The EGO vehicle performs: aggregating situation-specific information; generating an environment model of the given situation based on the situation-specific information; analyzing the environment model to identify at least one partial situation in the database; generating at least one instance for each identified partial situation; analyzing all generated instances by using the evaluation model of the respectively underlying partial situation to determine boundary conditions for the possible behaviors of the EGO vehicle in the given situation; prioritizing the possible behaviors of the EGO vehicle based on the boundary conditions determined in this way in conjunction with the rule set.

Abstract: A computer-implemented method for providing a digital road map for testing an at least partially automated vehicle system. the method includes: accessing a database in which are stored permissible characteristics of the road properties for a multitude of road properties; creating at least one road map section by one of the possible characteristics being selected for the road map section for the first of the multitude of road properties, in each particular case in automated fashion from the database; providing the digital road map, the digital road map including the at least one road map section.

Abstract: A computer-implemented method for evaluating an image classifier, in which a classifier output of the image classifier is provided for the actuation of an at least semi-autonomous robot. The evaluation method includes: ascertaining a first dataset including image data and annotations being assigned to the image data, the annotations including information about the scene imaged in the respective image and/or about image regions to be classified and/or about movement information of the robot; ascertaining regions of the scenes that are reachable by the robot based on the annotations; ascertaining relevance values for image regions to be classified by the image classifier; classifying the image data of the first image dataset with the aid of the image classifier; evaluating the image classifier based on image regions correctly classified by the image classifier and incorrectly classified image regions, as well as the calculated relevance values of the corresponding image regions.

Abstract: A computer-implemented method for detecting an obstacle on a route ahead of a first vehicle. In the method, information on a second vehicle driving ahead on the route is recorded in the first vehicle by at least one sensor of the first vehicle. In the first vehicle, depending on the recorded information, a computer detects an avoidance maneuver of the second vehicle due to an obstacle or detects that the second vehicle has driven over an obstacle. An obstacle is detected on the route depending on the detected avoidance maneuver or the detection that the vehicle has driven over an obstacle. A measure for protecting the vehicle and/or the obstacle is initiated depending on the detected obstacle.

Abstract: A method for controlling a vehicle. In the method, data of a digital road map are read in, zones are determined for the digital road map, and possible sequences of trips along a road of the digital road map are ascertained as a function of the determined zones. Furthermore, it is ascertained, as a function of sensor data and/or current driving data of the vehicle, whether a current or predicted traffic situation is outside the possible sequences or corresponds to a possible sequence that is determined as being outside an intended operating range. If the current or predicted traffic situation is outside the possible sequences or corresponds to the possible sequence outside the intended operating range, a measure is determined and the vehicle is controlled as a function of the measure that is taken.

Abstract: A computer-implemented method for testing a vehicle system. In the method, data of a digital road map are read in, zones are determined for the digital road map, possible sequences of drives along a road of the digital road map are ascertained as a function of the determined zones, a behavior of the vehicle or of a vehicle system of the vehicle is ascertained in a simulation for at least one of the possible sequences, and it is determined as a function of a comparison of the ascertained behavior with at least one predetermined requirement whether the vehicle system exhibits an error or a weakness.

Abstract: A computer-implemented method for providing a digital road map for testing an at least partially automated vehicle system. the method includes: accessing a database in which are stored permissible characteristics of the road properties for a multitude of road properties; creating at least one road map section by one of the possible characteristics being selected for the road map section for the first of the multitude of road properties, in each particular case in automated fashion from the database; providing the digital road map, the digital road map including the at least one road map section.

Abstract: A computer-implemented method for controlling a vehicle. The method includes: data of a digital road map are read in, zones are determined for the digital road map, possible sequences of drives along a road of the digital road map are ascertained as a function of the determined zones, a behavior of the vehicle or of a vehicle system of the vehicle is ascertained in a simulation for at least one of the possible sequences, and the vehicle is controlled in accordance with one of the possible sequences as a function of a comparison of the ascertained behavior with at least one predetermined requirement.