Robert Boschgmbh

Samsung Sdi Co., Inc.

Andreas Heyl

Holger Niemann

Thomas Benjamin Gussner

Oliver F Schwindt

Stephan Reuter

Theresa Veronika Kienle

Joachim Carsten Mueller

Markus Schweizer

Roland Schleser

Paulius Duplys

Jochen Weber

Wilfried Feuchter

Daniel Kanth

Astrid Rall

Daniel Damm

Christian Zimmermann

Berengar Krieg

Christian Heinzemann

Martin Herrmann

Michael Rittel

Nadja Schalm

Bernd Doerr

Jens Oehlerking

Martin Butz

Sandeep Bisht

Stefan Butzmann

Chrysanthos Tzivanopoulos

Oliver Kaefer

Christoph Gladisch

Dragan Mikulec

Gerit Edler Von Schwertfuehrer

Frank Schindler

Per Hagman

Frank Stimm

Markus Kretschmer

Dirk Hasenkopf

Stefan Blind

Peter Munk

Dirk Gollub

Dieter Hanauer

Alexey Yushin

Alexander Dubs

Siegfried Greskamp

Michael Gloeckler

Tino Brade

Philipp Mundhenk

Thomas Kirschbaum

A method for monitoring a distributed system, in which a change in a composition of components of the system is provided in an ongoing operation of the system. The method includes: carrying out a component check in which an incompatibility of the components with one another is identified; carrying out an interface check in which an incompatibility of at least one interface between the components is identified. The component check and the interface check in the case of the change in the composition of the components are carried out repeatedly in ongoing operation of the system.

Method for monitoring in a distributed system

A method for operating a management program that is provided to manage at least one intervention from at least one application program in a motor vehicle into at least one component of the motor vehicle. When establishing the extent of the at least one intervention, information being made available from outside of the vehicle is taken into account.

Method for operating a management program

A method for location-dependent verification of a teleoperator for remote control of a vehicle. At its current location, the vehicle repeatedly and automatedly performs the following: receiving, from the teleoperator, during remote control by the teleoperator, a response message requested via a network, ascertaining a current value of at least one network-dependent property of the received response message, determining a target value of the at least one network-dependent property, verifying the teleoperator by means of a verification of the current value of the at least one network-dependent property and of the determined target value based on a test condition, wherein in the case of a positive test result of the check, the teleoperator is authorized to perform the remote control of the vehicle, and in the case of a negative test result of the check, the vehicle terminates the remote control and/or sends a safety warning.

Method for location-dependent verification of a teleoperator for remote control of a vehicle

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 providing a function by a group of computing units in which computation instances are executed, each computation instance implementing the function using at least one algorithm and being set up to determine at least one result in response to a call of the function. The method includes: determining an integrity level for each of the computation instances; receiving a function request from a subscriber, the function request including a quality requirement that includes an integrity requirement; selecting a plurality of the computation instances corresponding to the quality requirement, so that the integrity level of the selected computation instances corresponds to the integrity requirement; calling the function in the selected computation instances corresponding to the function request in order to determine a plurality of results; determining a response based on the results, taking into account the quality requirement; and sending the response to the subscriber.

Method for the provision of a function by a group of computing units

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 method for controlling a robotic device. In the method, for a version of a control software which is not the initial version of the control software for which the test values delivered by the tests at least partially do not fall within predefined ranges, it is checked whether that version of the control software fulfills safety criteria that have been created for a previous version (and are fulfilled by that version) for which the test values delivered by the tests at least partially do not fall within the predefined ranges, but was safe. If this is the case, the robotic device is controlled with that version of the control software.

Method for controlling a robotic device

A method for providing a function via a network of processing units using multiple computing instances. Each computing instance implements the function and is configured, when it is executed, to determine at least one result in response to a call-up of the function. The method includes validating the computing instances, each being checked as to whether the computing instance corresponds to a respective predetermined state; determining a respective level of reliability for each of the processing units; starting execution of successfully validated computing instances in the processing units, which have a level of reliability that is equal/greater than a predetermined minimum level of reliability; receiving a function request from a user; calling up the function in at least a portion of the executed computing instances corresponding to the function request, in order to determine multiple results; determining a response based on the results; and sending the response to the user.

Method for providing a function via a network of processing units

Methods and systems for determining an action for a vehicle. The system includes an electronic controller configured to determine a planned route of the vehicle, determine local astronomical data based upon the planned route, compare the local astronomical data to the planned route of the vehicle to determine a probability of completion of the planned route, and if the probability of completion is below a threshold, generate a command indicating an action for the vehicle.

Determining vehicle actions based upon astronomical data

A system for a reliability of objects for a driver assistance or automated driving of a vehicle includes a plurality of sensors that include one or more sensor modalities for providing sensor data for the objects. An electronic tracking unit is configured to receive the sensor data to determine a detection probability (p_D) for each of the plurality of sensors for each of the objects, to determine an existence probability (p_ex) for each of the plurality of sensors for each of the objects, and to provide vectors for each of the objects based on the existence probability (p_ex) for each contributing one of the plurality of sensors for the specific object. The vectors are provided by the electronic tracking unit for display as an object interface on a display device. The vectors are independent from the sensor data from the plurality of sensors.

Redundancy information for object interface for highly and fully automated driving

A method for monitoring a vehicle system configured to detect an environment of a vehicle, wherein the vehicle system has a sensor system with at least two sensor units configured to capture the environment of the vehicle, and an evaluation unit configured to detect objects in the environment of the vehicle by merging sensor data of the at least two sensor units. The method includes, for each of the detected objects, using sensor data to determine separately for each of the at least two sensor units a probability of existence indicating a probability of the detected object representing a real object, and a probability of detection indicating a probability with which the detected object can be captured by the sensors. The method includes determining whether the vehicle system is in a robust state based on the probability of existence and the probability of detection.

Method for monitoring a vehicle system for detecting an environment of a vehicle

A system for controlling an autonomous vehicle when the autonomous vehicle is outside of its operational design domain. The system includes an environment detection system, a vehicle control system, and a first electronic processor. The first electronic processor is configured to detect that an autonomous vehicle is outside of its operational design domain and send a first electronic message. The first electronic message requests that a surrounding vehicle lead the autonomous vehicle until the autonomous vehicle returns to its operational design domain or reaches a predetermined location. The electronic processor is also configured to determine a leading vehicle and control the autonomous vehicle to follow the leading vehicle until the autonomous vehicle returns to its operational design domain or reaches the predetermined location.

Controlling an autonomous vehicle when the autonomous vehicle is outside of its operational design domain

Redundant environment perception tracking for automated driving systems. One example embodiment provides a surveillance system, the system including a plurality of sensors, a memory, and an electronic processor. The electronic processor is configured to receive, from the plurality of sensors, environmental information of a common field of view, generate, based on the environmental information, a plurality of hypotheses regarding an object within the common field of view, the plurality of hypotheses including at least one set of hypotheses excluding the environmental information from at least one sensor of a first sensor type, determine, based on a subset of the plurality of hypotheses, an object state of the object, wherein the subset includes the at least one set of hypotheses excluding the environmental information from the at least one sensor of the first sensor type, and track the object based on the object state that is determined.

Redundant environment perception tracking for automated driving systems

A system and method for assessment of risk involved in transfer of passengers into or out of a vehicle at a particular transfer location. The assessment may utilize environmental data and dynamic data to estimate a risk level for the passengers. If the estimated risk level is not lower than a threshold, a revised transfer location may be found and assessed.

Risk-based assessment of passenger transfer

Methods and systems for controlling an autonomous vehicle. The method includes receiving sensor data from a plurality of sensors, determining, a plurality of probability hypotheses based upon the sensor data, and receiving metadata from at least one sensor of the plurality of sensors. An integrity level of at least one of the plurality of probability hypotheses is determined based upon the received metadata and at least one action is determined based upon the determined integrity level and at least one probability hypothesis of the plurality of probability hypotheses. The at least one action is then initiated by an electronic controller for the vehicle.

Safety architecture for control of autonomous vehicle

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Ludwigsburg, Germany

Andreas Heyl