Robert Boschgmbh

Michael Rittel

Christian Heinzemann

Jens Oehlerking

Martin Herrmann

Nadja Schalm

Martin Butz

Andreas Heyl

Christoph Gladisch

Konrad Groh

Oliver Willers

Matthias Woehrle

Dirk Ziegenbein

Tino Brade

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.

Method and device for evaluating an image classifier

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.

Method for detecting an obstacle on a route

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.

Method for controlling a vehicle

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.

Method for providing a digital road map

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Markgroeningen, Germany

Michael Rittel