Volkswagen Ag

Audi Ag

Scania Cv Ab

Simon Steinmeyer

Marc-Michael Meinecke

Carsten Deeg

Thorsten Graf

Marek Musial

Michael Schlichte

Pär Degerman

Alexander Schwithal

Thorsten Bagdonat

Tim Kubertschak

Daniel Mossau

Jon Andersson

Oliver Birbach

Pär German

Joseph Ah-King

Patrick Glässer

A method, a device and a computer-readable storage medium with instructions for processing sensor data. In a first step, camera images are taken by a camera. Additionally, 3D-checkpoints are detected by at least one 3D-sensor. Optionally, at least one of the camera images can be segmented. The camera images are then merged with the 3D-checkpoints by a data fusion circuit to form data of a virtual sensor. The resulting data are finally output for further processing.

Method, device and computer-readable storage medium with instructions for processing sensor data

A method for detecting a parallax problem in sensor data from two sensors, wherein the sensors are spaced apart at different positions and at least partly capture the same environment, and one of the sensors provides distance information items. The method includes receiving the acquired sensor data from the sensors; receiving or estimating sensor visual range information items from the other of the sensors; assigning measured values in the acquired sensor data of the one sensor to measured values corresponding to each of them from the other sensor, the assignment taking into account respective imaging conditions; comparing the distance information items and the received or estimated sensor visual range information items on each of the measured values of the sensor data, wherein a parallax problem is detected in response to a distance exceeding a threshold criterion; and outputting a comparison result.

Method and device for determining a parallax problem in sensor data of two sensors

A method for detecting a parallax problem in sensor data from two sensors spaced apart from each other and at least partly capturing the same environment, wherein at least one of the sensors provides distance information. The method includes obtaining the acquired sensor data from the sensors; assigning measured values in the acquired sensor data of one sensor to corresponding measured values in the acquired sensor data of the other sensor, wherein the assignment takes the respective imaging conditions of the two sensors into account; consecutively numbering the measured values in the sensor data; checking whether a sorting order of the numbering of the measured values that correspond to each other matches, a parallax problem being determined in response to a sorting order not matching; and outputting a test result. Also disclosed is an apparatus for detecting a parallax problem in sensor data from two sensors and a transportation vehicle.

A device, transportation vehicle, and method for checking a calibration of surroundings sensors, wherein the surroundings sensors at least partially detect similar surroundings and provide mutually time-synchronized sensor data, periodic features at least for at least one distinguished area are detected in the sensor data of the surroundings sensors belonging to the same surroundings, a transformation of the sensor data corresponding to the at least one distinguished area to a frequency domain is carried out at least for the at least one distinguished area, a frequency and/or a phase angle of the periodic features is determined in the sensor data transformed to the frequency domain, a decalibration of the surroundings sensors is detected based on a comparison of the determined frequencies and/or of the determined phase angles, and a result of the check is provided.

Method and device for checking a calibration of environment sensors

A method for checking a calibration of N environmental sensors, wherein the N environmental sensors acquire an environment and each provide sensor data, N subfusions are formed from the acquired sensor data, each of the N subfusions leaves sensor data of one singular one of the N environmental sensors unconsidered upon the fusing, fusion results of the N subfusions are compared to one another, an incorrect calibration of the N environmental sensors is established based on a comparison result, and a check result is provided. Also disclosed are an associated device and a transportation vehicle.

The invention relates to a method for improved data fusion during environment detection in a motor vehicle (), comprising the following steps: detecting () an environment () of the motor vehicle () using at least one sensor (); recognising () objects () in measurement data () detected by the at least one sensor (); fusioning () of the recognised objects () and the object positions thereof in an environment map (), wherein a probability of existence is/will be assigned to objects () recorded in the environment map (), and wherein the probability of existence of a recorded object () is reduced, when a free region () is measured during the detection of the position of the recorded object, wherein a respective orientation attribute () is assigned to the objects () recorded in the environment map () and recorded in the environment map (), and for a region in the sensor region () of the at least one sensor (), in which a free region () is measured, the probability of existence of an object () recorded in the region of the environment map () corresponding to the region is reduced in accordance with the assigned orientation attribute (). The invention also relates to the associated device ().

Method and device in a motor vehicle for improved data fusion in an environment detection

A pressure ratio between a setpoint tire pressure and an actual tire pressure for a tire of a vehicle is ascertained by the following steps:

Method and system for ascertaining a pressure ratio between a setpoint tire pressure and an actual tire pressure for tire of a vehicle

A pressure deviation between a setpoint tire pressure and an actual tire pressure for a tire of a vehicle is determined by the following steps:

Method and system for determining a pressure deviation between a setpoint tire pressure and an actual tire pressure for a tire of a vehicle as well as for determining a wheel load

Regulation of a longitudinal acceleration of a main vehicle (), particularly a truck, includes: detecting a driving behavior of vehicles traveling in front of a preceding vehicle that is traveling immediately in front of the main vehicle (), regulating the longitudinal acceleration of the main vehicle () based on an evaluation of the driving behavior of the vehicles in such a way as to minimize energy consumption of the main vehicle ().

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Braunschweig, Germany

Simon Steinmeyer