Zf Automotive Germany Gmbh

Robert Boschgmbh

Trw Automotive Gmbh

Zf Friedrichshafen Ag

Schwing Gmbh

Torsten Bertram

Christian Wissing

Andreas Homann

Christian Lienke

Manuel Schmidt

Karl-Heinz Glander

Till Nattermann

Carlo Manna

Martin Keller

Niklas Stannartz

Markus Buss

Carsten Hass

Christian Grosse

Peter Dominke

Wolfgang Hermsen

Holger Bellmann

Asmus Volkart

Christian Goette

Jens-Olaf Mueller

Torsten Baumann

Rolf Maier-Landgrebe

Clemens Schmucker

Martin Krüger

Juergen Schirmer

Holger Huelser

Johannes Henikl

Michael Walther

Georg Schoppel

Pio Torre Flores

Christoph Krimpmann

Christoph Rösmann

Frank Hoffmann

Freia Irina Muster

Maximilian Krämer

Anne Stockem Novo

Joerg Petersen

Marc Heckes

Ingo Glowatzky

Systems and methods for sampling based planning of possible trajectories for motor vehicles are provided. For example, a control system is configured to determine information relating to a current driving situation of the subject motor vehicle and at least one other motor vehicle on the basis of the environment data. The control system is also configured to determine a plurality of lateral positions. The control system is further configured to determine a number of longitudinal positions and/or speeds. The control system is yet further configured to sample the plurality of lateral positions and the number of longitudinal positions and/or speed in curvilinear coordinates and transformed based on the reference lane to determine stopping points for a trajectory. The control system is configured to determine the trajectory for the subject motor vehicle utilizing a spline-based interpolation in orthogonal coordinates between the determined stopping points and corresponding to the lateral positions.

Control system and control method for sampling based planning of possible trajectories for motor vehicles

The invention relates to a method for determining a driving corridor for a motor vehicle (). The motor vehicle () comprises at least one camera () and a control unit (), the camera () being designed to generate images of a front region () in front of the motor vehicle () and to forward these images to the control unit (). The control unit () comprises a machine learning module () having an artificial neural network. The method comprises the following steps: an image of the front region () in front of the motor vehicle () is obtained by the at least one camera (); characteristic image features of the image are extracted by means of the artificial neural network; by means of the same artificial neural network, image points () which delimit the driving corridor of the motor vehicle () and/or at least one driving corridor adjacent to the driving corridor are determined on the basis of the extracted characteristic image features. The invention also relates to a system () for determining a vehicle corridor.

Method and system for determining a driving corridor

Methods and systems for controlling driving maneuvers of a motor vehicle driving in a current driving lane on a road are described. Spatio-temporal regions defining free regions and/or occupied regions in the current driving lane and a further driving lane, adjacent to the current driving lane of the motor vehicle, are determined. Changing regions, in which a driving lane change between the current and the further driving lanes is possible, and/or lane-keeping regions, in which a driving lane change between the current and the further driving lanes is not possible, are determined based on the free and/or occupied regions. Possible driving maneuvers of the motor vehicle at least between changing regions and/or lane-keeping regions that adjoin one another in pairs are determined and executed.

Method and system for controlling a motor vehicle

A method for controlling a motor vehicle () traveling on a road () in a current lane () is presented. The road () has at least one further lane () which is adjacent to the current lane () of the motor vehicle (). The method comprises the following steps: A driving maneuver graph is generated and/or received, which contains information about at least two different driving maneuvers for the motor vehicle (). One of the at least two possible driving maneuvers is selected by means of a machine learning module () which applies a machine learning method to the driving maneuver graph. A control device () for a system () for the control of a motor vehicle () is also proposed.

Method and control device for a system for the control of a motor vehicle

A control system for use in a motor vehicle and configured to monitor a current driving situation of the motor vehicle on the basis of surrounding data of the motor vehicle acquired from at least one surrounding sensor arranged on the motor vehicle in a current driving situation is disclosed. The control system is configured to determine information relating to a current driving situation of the motor vehicle on the basis of the provided surrounding data, to determine information relating to a current driving situation of the motor vehicle and to determine a component of a future driving maneuver for the motor vehicle on the basis of the information relating to the current driving situation of the motor vehicle. Furthermore, the control system is configured to determine a multiplicity of model trajectories for the motor vehicle on the basis of the determined component of the future driving maneuver for the motor vehicle and to determine from the multiplicity of model trajectories a trajectory for the motor vehicle which the motor vehicle is to follow in the further course of its travel. The control system is also configured to update the information relating to the current driving situation of the motor vehicle and/or the supplied surrounding data and to adapt the trajectory for the motor vehicle on the basis of a target function and on the basis of the updated supplied surrounding data and/or on the basis of the updated information relating to the current driving situation of the motor vehicle.

Control system and control method for a hybrid approach for determining a possible trajectory for a motor vehicle

A method for determining a driving maneuver includes obtaining vehicle parameters (P) from a driving maneuver planning module () of the vehicle (). At least one possible driving maneuver (M) is determined via the driving maneuver planning module () based on the vehicle parameters (P) received by means of at least one decision-making submodule of the driving maneuver planning module (), At least one possible driving maneuver (M) is transmitted to a motion planning module () of the vehicle (). An evaluation variable (B) is obtained from the motion planning module () via the driving maneuver planning module (). The at least one decision-making submodule is adapted based on the evaluation variable (B) obtained. Furthermore, a system for determining a driving maneuver of a vehicle, a vehicle for executing the driving maneuver, a control device for a vehicle and a computer program for executing the method are shown.

Method and system for determining a driving maneuver

A method for controlling a motor vehicle () traveling on a roadway () in a current lane () is described, wherein the roadway () has at least one additional lane () that is adjacent to the current lane () of the motor vehicle (). The method has the following steps: Multiple different driving maneuvers are generated and/or received. At least two driving maneuver classes that are defined based on at least one characteristic variable of the driving maneuvers are determined, wherein the driving maneuvers of various driving maneuver classes differ by at least one characteristic variable. The driving maneuvers are classified in one of the at least two driving maneuver classes. In addition, a control unit () for controlling a motor vehicle () is described.

Method and control unit for a system for controlling a motor vehicle

A method for the automated control of a motor vehicle () is presented. The method includes the following steps: A control device () for a system for the control of a motor vehicle () is also proposed.

Method for the automated control of a motor vehicle

The invention relates to a method for determining a lane change for a driver assistance system () of a vehicle (), which method comprises calculating () a probability that other vehicles () are driving at a higher speed in a lane (L) which is adjacent to a current lane (L) of the vehicle (), applying () a hysteresis to the calculated probability based on a driving parameter dependent on a last lane change, and issuing () a command to change lanes depending on the probability. The invention further relates to a driver assistance system and a vehicle which can carry out such a method.

Method for determining a lane change, driver assistance system and vehicle

A large manipulator includes a chassis, a mast pedestal, an articulated mast, and a control unit. The mast pedestal is rotatable around a vertical axis by means of a rotary drive and arranged on the chassis. The articulated mast includes two or more mast arms pivotally-movably connected, via articulated joints, with the respectively adjacent mast pedestal or other mast arm by a pivot drive. The control unit is configured to actuate the pivot drive and/or the rotary drive to move the articulated mast with a control sequence from an initial position of the articulated mast, autonomously, into a pre-specified target position of the articulated mast.

Large manipulator with automated mast set-up

A method for controlling in an automated manner a motor vehicle () traveling on a road () in a current lane () is suggested, wherein the road () has at least one further lane (). The method comprises the following steps: At least two preliminary driving maneuvers are generated and/or received, which include a lane change from the current lane () to the at least one further lane () and a starting time of the lane change. The starting times of the at least two preliminary driving maneuvers are at different times. The at least two driving maneuvers are compared taking into account the respective starting times. One of the starting times is selected based on the comparison. Further, a control device for a system for controlling a motor vehicle is also suggested.

Method and control device for controlling a motor vehicle

A control system for use in a motor vehicle is used for monitoring a current driving situation of the motor vehicle, based on surroundings data of the host motor vehicle in the current driving situation, obtained from at least one surroundings sensor situated on the host motor vehicle. The control system is used to recognize lanes, lane boundary lines, lane markings, and/or other motor vehicles in an area in front of, to the side of, and/or behind the host motor vehicle. In addition, the control system is used to determine at least one driving parameter for each other motor vehicle present in the surroundings of the host motor vehicle, based on the provided surroundings data, and to generate a plurality of possible trajectories for the future travel course for each of the other motor vehicles, based on the driving parameter determined in each case. Lastly, the control system is used to carry out a simulation of the plurality of possible trajectories for the future travel course for each of the other motor vehicles, and to group in each case the plurality of possible trajectories for the future travel course for each of the other motor vehicles, based on the simulation.

Control system and control method for interaction-based long-term determination of trajectories for motor vehicles

A method is proposed for controlling a motor vehicle () traveling on a roadway () in a current lane (), wherein the roadway () has at least one additional lane () that is adjacent to the current lane () of the motor vehicle (). The method has the following steps: At least one possible driving maneuver for the motor vehicle () is generated and/or received. A cost functional is determined, wherein the cost functional associates a cost factor with the at least one possible driving maneuver. At least one time-variant constraint is determined and/or received. The cost functional is extremized under the at least one time-variant constraint, and the possible driving maneuver is adapted based on the extremized cost functional, so that a target driving maneuver is obtained. In addition, a control unit () for a system () for controlling a motor vehicle () is proposed.

A method is presented for controlling a motor vehicle (). Initially, driving maneuver data containing information concerning multiple possible, different driving maneuvers of the motor vehicle () are generated and/or received. Traffic data containing information concerning at least one undisturbed predicted trajectory of at least one further road user () are generated and/or received. An influence of the at least one driving maneuver on the trajectory of the at least one further road user () is determined, based on the driving maneuver data and the traffic data, and a characteristic variable is ascertained that describes the influence of the at least one driving maneuver on the at least one further road user (). In addition, a system () for controlling a motor vehicle () is proposed.

A control system that is suitable for use in a host motor vehicle () is configured and intended for detecting (S) another motor vehicle (), using the road, located in front of the host motor vehicle () by means of the at least one surroundings sensor, determining (S) a lateral movement of the other motor vehicle () relative to a lane () in which the other motor vehicle () or the host motor vehicle () is present, and computing (S) a movement-based likelihood of a lane change by the other motor vehicle (), based on the determined lateral movement of the other motor vehicle (). In addition, the control system is configured and intended for determining (S, S, S) an instantaneous traffic situation in accordance with the surroundings data obtained by means of the surroundings sensor, computing (S) a traffic situation-based likelihood of a lane change by the other motor vehicle (), based on the determined instantaneous traffic situation, and computing (S) an overall likelihood of a lane change by the other motor vehicle (), based on the movement-based likelihood and the traffic situation-based likelihood.

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Duesseldorf, Germany

Torsten Bertram