Conti Temic Microelectronic Gmbh

Martin Pfitzer

Stefan Heinrich

Elias Strigel

Dieter Kroekel

Robert Thiel

Karsten Breuer

Thomas Fechner

Dieter Krökel

Jan Giebel

Felix Hachfeld

Manuel Du Bois

The invention relates to a method for detecting beacons () in the surroundings of an ego vehicle (), comprising the steps of:

Method for detecting beacons

Example embodiments relate to an ADAS sensor data processing unit, to an ADAS sensor system and to an ADAS sensor data evaluation method for use in driver assistance systems or systems for the automated driving of a vehicle. The ADAS sensor data processing unit includes an input interface, a decompression module, a processing unit and an output unit. The input interface is designed to receive data of an ADAS sensor that have been subjected to lossy compression by a compression module. The decompression module is designed to decompress the compressed data of the ADAS sensor. The processing unit is designed to process the decompressed data (IdSD) of the ADAS sensor, information relevant to an ADAS/AD function being ascertained from the decompressed sensor data. The output unit is designed to output the ascertained information relevant to the ADAS function.

Processing of lossy-compressed ADAS sensor data for driver assistance systems

A method and a driver assistance system recognize the intention of a pedestrian to move on the basis of a sequence of images of a camera. The method includes detecting a pedestrian in at least one camera image. The method also includes selecting a camera image that is current at the time t and selecting a predefined selection pattern of previous camera images of the image sequence. The method further includes extracting the image region in which the pedestrian was detected in the selected camera images of the image sequence. The method also includes classifying the movement profile of the detected pedestrian on the basis of the plurality of extracted image regions. The method outputs the class that describes the movement intention determined from the camera images of the image sequence.

Recognizing the movement intention of a pedestrian from camera images

A method of ascertaining disparities in sensor data uses at least one neural network implemented in a controller of a vehicle. The method involves capturing () a learning data record from temporally successive raw sensor data, evaluating () the learning data record to train the neural network exclusively based on the learning data record of the captured raw sensor data, ascertaining () expected sensor data, comparing () the ascertained expected sensor data with sensor data currently captured by the sensor arrangement, and ascertaining () a disparity between the currently captured sensor data and the ascertained expected sensor data.

Method and system for predicting sensor signals from a vehicle

A camera device includes an optronics system and an image capture control unit, for acquiring a sequence of images of a surrounding region of a vehicle. The optronics system includes a wide-angle optical system and a high-resolution image acquisition sensor. The optronics system and the image capture control unit are configured to generate a reduced-resolution binned image of the entire capture region of the optronics system, or to capture an unbinned high-resolution image of a subregion of the capture region, respectively for each individual image of the sequence of images, depending on a current traffic and/or surrounding situation. A height and a width of the subregion are set depending on the current situation. A size of the subregion is set such that the pixel count of the high-resolution image of the subregion is no greater than the pixel count of the reduced-resolution image of the entire capture region.

Growing community of inventors

Bodolz, Germany

Martin Pfitzer