Aptiv Technologies Limited

Delphi Technologies, Inc.

Jens Westerhoff

Alexander Ioffe

Mirko Meuter

Stephanie Lessmann

Uri Iurgel

Jan Siegemund

Wolfgang Doerr

Stephanie Leßmann

Wolfgang Dörr

The present disclosure describes systems and techniques for estimating a height of an object by processing wave signals transmitted from a detection device to the object and reflected by the object. In aspects, a detection device transmits wave signals, which propagate via a direct path and an indirect path via reflection over a reflecting surface, to be reflected by the object. Operations include measuring wave signals reflected by the object and generating measurement vectors and producing a spectrum of an estimated elevation angle of the object over the range. Further, the operations include estimating the height of the object from the spectrum. The length of the window can be determined by estimating the range interval covered by a full phase cycle of a phase difference between the direct path and the indirect path from a current value of the range and a current estimate of the height of the object.

Method for estimating height of object

An illustrative example embodiment of a computer implemented method for estimating a vertical profile of a road in front of or behind a host vehicle includes monitoring a detection point at a surrounding or preceding vehicle by a sensor on the host vehicle, determining at least one value for a height of the detection point with respect to a reference level at the host vehicle based on the elevation angle of the detection point, and estimating the vertical profile of the road based on the at least one value for the height of the detection point. An estimation of a height of the object with respect to a road surface may be corrected by the estimated vertical profile.

Vertical road profile estimation

A method of generating a confidence measure for an estimation derived from images captured by a camera mounted on a vehicle includes: capturing consecutive training images by the camera while the vehicle is moving; determining ground-truth data for the training images; computing optical flow vectors from the training images and estimating a first output signal based on the optical flow vectors for each of the training images, the first output signal indicating an orientation of the camera; classifying the first output signal for each of the training images as a correct signal or a false signal depending on how good the first output signal fits to the ground-truth data; determining optical flow field properties for each of the training images derived from the training images; and generating a separation function that separates the optical flow field properties into two classes based on the classification of the first output signal.

Method and a device for generating a confidence measure for an estimation derived from images captured by a camera mounted on a vehicle

A method of generating an occupancy map representing free and occupied space around a vehicle, wherein the occupancy map is divided into a plurality of cells Mx,y, the method includes: capturing two consecutive images by a camera mounted on the vehicle; generating optical flow vectors from the two consecutive images; estimating 3D points in the space around the vehicle from the optical flow vectors; generating rays from the camera to each of the estimated 3D points, wherein intersection points of the rays with the cells Mx,y defining further 3D points; determining for each of the cells Mx,y a function L_(x,y)^t for a time step t; and determining an occupancy probability from the function L_(x,y)^t for each of the cells Mx,y.

Method and a device for generating an occupancy map of an environment of a vehicle

A method of estimating an orientation of a camera relative to a surface includes providing a first image and a subsequent second image captured by the camera; selecting a first point from the first image and a second point from the second image, where the first and second points represent the same object; defining a first optical flow vector connecting the first point and the second point; carrying out a first estimation step comprising estimating two components of the normal vector in the camera coordinate system by using the first optical flow vector and restricting parameter space to only the two components of the normal vector, wherein a linear equation system derived from a homography matrix that represents a projective transformation between the first image and the second image is provided and the two components of the normal vector in the camera coordinate system are estimated by solving the linear equation system; and determining the orientation of the camera relative to the surface using the results of the first estimation step.

Growing community of inventors

Dortmund, Germany

Jens Westerhoff