Continental Teves, Ag and Company Ohg

Conti Temic Microelectronic Gmbh

Stefan Lueke

Stefan Hegemann

Matthias Komar

Dirk Waldbauer

Matthias Strauss

Andree Hohm

Alfred Eckert

Georg Halasy-Wimmer

Thomas Berthold

Christian Scharfenberger

Michelle Karg

Ronald Bayer

Stefan Fritz

Ralph Grewe

Chen Zhang

Xiuxun Yin

Christoph Hassenpflug

Bernd Piller

Ann-Katrin Fattal

Matthias Happ

Wolfgang Guenther

Juergen Pfeiffer

A device for object recognition of an input image includes: a patch selector configured to subdivide the input image into a plurality of zones and to define a plurality of patches for the zones; a voting maps generator configured to generate a set of voting maps for each zone and for each patch, and to binarize the generated set of voting maps; a voting maps combinator configured to combine the binarized set of voting maps; and a supposition generator configured to generate and refine a supposition out of or from the combined, binarized set of voting maps.

Device and method for object recognition of an input image for a vehicle

In order to recognize hazard areas and/or construction areas on a roadway, an environment sensor produces detected environment data regarding objects indicating the hazard areas and/or construction areas. A traffic light system is detected in the environment data, position data of the traffic light system is determined, an environment scenario is determined from the environment data and is compared with a reference model of the environment scenario. If the reference model does not indicate the presence of a traffic light system, or indicates a traffic light system having position data differing from the position data of the detected traffic light system, then it is concluded that the detected traffic light system is a traffic light system identifying a hazard and/or construction area.

Method and device for recognizing marked hazard areas and/or construction areas in the region of lanes

In a method and a driver assistance system for representing vehicle surroundings of a vehicle having a sensor system for detecting the environment, a boundary of a traffic lane or driving path on which the vehicle is currently being driven is represented by position points that each have a predefined set of attributes especially including a width attribute indicating a lateral width of an unobstructed area available as a maneuvering space on an opposite side of the respective position point.

Method for representing vehicle surroundings

A method of operating a driver assistance system of a motor vehicle for performing an automatic steering intervention involves detecting how firmly a driver is holding a steering wheel, and determining an intensity value i.e. control value dependent on how firmly the driver is holding the steering wheel. The control value is higher when the driver is holding the steering wheel more firmly, and lower when the driver is holding the steering wheel less firmly. The method then applies an automatic steering intervention with an applied intensity that is controlled in accordance with the control value, so that the applied intensity of the automatic steering intervention is higher when the driver is holding the steering wheel more firmly, and lower when the driver is holding the steering wheel less firmly. A steering assistance system includes a memory, a processor, sensors and an automatic steering control system, to implement the method.

Method and device for an automatic steering intervention

A sensor system detects objects in an environment ahead of a vehicle. The environment is represented by a predetermined fixed number of position points in an environment model. Initially and when no objects are detected, the position points may be distributed stochastically over the detection area of the sensor system. When objects are detected, the position points are re-distributed based on the detected objects, e.g. with a higher density of position points to represent the detected objects. Because the total number of position points is a predefined fixed number that remains constant, the processing, storage and transmission of the environment model involves a constant data volume and efficient use of memory and transmission bandwidth.

Method for representing a vehicle environment with position points

A method for the automated braking and/or steering of a vehicle uses at least one sensor system for detecting the vehicle's surroundings, a potential collision object in the vehicle's surroundings, and a relative speed of the vehicle relative to the potential collision object. The activation and/or the sequence of an automated steering intervention and/or an automated braking intervention is determined based on the relative speed. The braking intervention is activated at first when the relative speed is below or equal to a predefined threshold, and the steering intervention is activated at first when the relative speed is above the predefined threshold.

Method and device for the automated braking and steering of a vehicle

A method for automatic direction indication for a vehicle includes the following steps:

Method and device for automatic direction indication

A method and a device for an assistance system, e.g. a parking assistance system, perform an autonomous or semi-autonomous driving maneuver of a vehicle. A camera system generates image data from the surroundings of the vehicle. A processor arrangement processes the image data to produce control information that is used by the assistance system to perform the driving maneuver. If the image data show that a restriction or impediment is present, then the assistance system is put in a safe state.

Method and device for an assistance system in a vehicle for performing an autonomous or semi-autonomous driving maneuver

A method and a device determine whether a vehicle can pass through a passage of an object, based on image data from a 3-D camera, which records an image of surroundings of the vehicle. A trajectory of the vehicle is ascertained. From the image data, it is determined whether an object located above the trajectory is recognized and whether the object has at least one connection to the ground. The dimensions and the shape of an entry area or a passage space between the object and the roadway, through which the vehicle is to pass, are determined from the image data. By comparing the dimensions and shape of the entry area or the passage space with the dimensions and shape of the vehicle, it is determined whether and how the vehicle can pass through the entry area or passage space.

Method for determining whether a vehicle can pass through an object by means of a 3-D camera

A method supports a vehicle's traffic-light-sequence assistant system that detects traffic light sequences of a traffic light () with a camera (). According to the method, when the traffic light () is detected in the field of view (a ) of the camera (), a length or an end stopping point (L) of a driving path (W) toward the traffic light () is determined by a control unit (), such that the traffic light will remain within view of the camera when the vehicle drives the determined length along the driving path to the end stopping point, and a control signal (St) concerning the determined length (L) or the end stopping point of the driving path (W) is outputted.

Method for supporting a traffic-light-sequence assistant of a vehicle, said assistant detecting traffic lights

In a method for determining a course of a traffic lane for a vehicle (), structures that demarcate a trafficable space are detected in image data from an image acquisition unit (), and these structures are plotted on a surroundings map () that subdivides the surroundings of the vehicle into a two-dimensional grid () of cells (). The position of the vehicle in the grid of the surroundings map is determined and updated by odometric data. The distance and the direction of the vehicle () relative to those cells () of the grid () having structures that demarcate the pavement and/or the traffic lane are determined. Brightness transitions in the image data are detected and are plotted on the cells () of the grid (). The course of the traffic lane () is determined from the cells with the detected brightness transitions.

Method for determining a course of a traffic lane for a vehicle

A method and a device are provided for calibrating a plurality of environment sensors in a vehicle. Traffic light signals are detected and identified from the data of at least one environment sensor or from data received by a car-2-X communication unit. A calibration of the plurality of environment sensors is activated and performed in response to a determination that a traffic light signal pertaining to the vehicle has turned red.

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Bad Homburg, Germany

Stefan Lueke