Aptiv Technologies Limited

Aptiv Technologies Ag

Delphi Technologies, Inc.

Uri Iurgel

Alexander Ioffe

Stephanie Lessmann

Ahmad Pishehvari

Wolfgang Doerr

Michael H Laur

Kai Zhang

Mirko Meuter

Kun Zhao

Krzysztof Kogut

Jakub Porebski

Konstantin Statnikov

Amith Somanath

Nanhu Chen

Aron Sommer

Mohamed A Moawad

Aniello Sorrentino

Stephanie Leßmann

Ceyhan Karabulut

Damjan Karanovic

Dariusz Cieslar

Honghui Yan

Jens Westerhoff

Markus Stefer

Lutz Roese-Koerner

Maryam Foroughi

Wolfgang Dörr

Dennis Müller

Mirko Nicolas Meuter

Christian Markus Nunn

A method is provided for estimating an angle of an object with respect to a vehicle. A transformation of reflected radar signals is calculated, wherein the result of the transformation depends on a range with respect to the vehicle. A long beam vector is generated for respective range bins provided by the transformation by rearranging the result of the transformation such that the respective long beam vector comprises elements of the transformation from radar all receiver elements for each range bin. A reference vector is calculated for each range bin based on a signal model which depends on the motion of the target object relative to the vehicle and which is parameterized regarding the angle of the target object. The long beam vector and the reference vector are correlated, and the angle of the target object is determined based on the correlation result.

Method and device for determining an angle of a target object

This document describes methods and systems for vehicle localization based on radar detections. Radar localization starts with building a radar reference map. The radar reference map may be generated and updated using different techniques as described herein. Once a radar reference map is available, real-time localization may be achieved with inexpensive radar sensors and navigation systems. Using the techniques described in this document, the data from the radar sensors and the navigation systems may be processed to identify stationary localization objects, or landmarks, in the vicinity of the vehicle. Comparing the landmark data originating from the onboard sensors and systems of the vehicle with landmark data detailed in the radar reference map may generate an accurate pose of the vehicle in its environment. By using inexpensive radar systems and lower quality navigation systems, a highly accurate vehicle pose may be obtained in a cost-effective manner.

Vehicle localization based on radar detections

Provided is method for determining free space surrounding a device, the method comprising: acquiring radar data regarding each of one or more radar antennas, the acquired radar data comprising range data and range rate data; extracting, from the acquired radar data, a specific set of radar data having values equal to or below a noise-based threshold; and determining a free space around the device based on the extracted specific set of radar data.

Directly determining free spaces around devices

A method of determining ego-motion information of a vehicle comprising a radar sensor having a plurality of antenna elements, comprising: acquiring motion spectrum comprising a plurality of data elements, each calculated for a respective one of a plurality of Doppler bin indices and for a respective one of a plurality of spatial bin indices, each spatial bin index indicating a respective angle-of-arrival of a radar return signal at the radar sensor; and determining the ego-motion information by solving a motion equation system comprising equations of motion generated using the motion spectrum data and each relating a respective value indicating a radial velocity, a respective value indicating an angular displacement, and a variable indicating a velocity of the vehicle.

Radar data processing for vehicle ego-motion estimation

Methods and systems are described that enable radar reference map generation. A high-definition (HD) map is received and one or more HD map objects within the HD map are determined. Attributes of the respective HD map objects are determined, and, for each HD map object, one or more occupancy cells of a radar occupancy grid are indicated as occupied space based on the attributes of the respective HD map object. By doing so, a radar reference map may be generated without a vehicle traversing through an area corresponding to the radar reference map.

Radar reference map generation

A computer-implemented method for determining a position of a vehicle is disclosed, wherein the vehicle is equipped with a sensor for capturing scans of a vicinity of the vehicle, wherein the method comprises at least the following steps carried out by computer-hardware components: capturing at least one scan by means of the sensor with a plurality of sensor data samples given in a sensor data representation; determining, from a database, a predefined map with at least one element is given in a map data representation; determining a transformed map by transforming the at least one element of the predefined map from the map data representation into the sensor data representation; matching at least a subset of the sensor data samples of the at least one scan and the at least one element of the transformed map; and determining the position of the vehicle based on the matching.

Method for determining position data and/or motion data of a vehicle

Method for determining a position of a vehicle

A method is provided for determining a mobility status of a target object located in an environment of a sensor configured to monitor a surrounding environment of a vehicle. According to the method, a detection angle of the target object is determined with respect to the sensor based on data acquired by the sensor, and an ideal beam vector for a stationary object is predicted based on the detection angle. The ideal beam vector and a measured beam vector obtained from the data acquired by the sensor are normalized, and a correlation of the normalized ideal beam vector and the normalized measured beam vector is determined. A score is determined based on the correlation of the normalized ideal and measured beam vectors and indicates whether the target object is stationary or moving.

Method for determining the mobility status of a target object

A computer implemented method for determining an angle of a detection comprises the following steps carried out by computer hardware components: acquiring a range rate of the detection; determining a pair of candidate angles of the detection based on the range rate; acquiring a beamvector of the detection; determining a correlation between the beamvector and a reference vector; and determining the angle of the detection based on the pair of candidate angles and based on the correlation.

Methods and system for determining an angle of a detection

A method for fusing a first occupancy map and a second occupancy map comprises: determining at least one fusion parameter representing a potential dissimilarity between the first occupancy map and the second occupancy map and determining a fused occupancy map representing free and occupied space around the vehicle. The fused occupancy map is determined based on the first occupancy map, the second occupancy map, and a fusion rule. The fusion rule is configured to control the influence of the first occupancy map and/or the second occupancy map on the fused occupancy map based on the at least one fusion parameter.

Method and system for fusing occupancy maps

A method is described for determining the position of a vehicle equipped with a radar system that includes at least one radar sensor adapted to receive radar signals emitted from at least one radar emitter of the radar system and reflected the radar sensor. The method comprises: acquiring at least one radar scan comprising a plurality of radar detection points, wherein each radar detection point is evaluated from a radar signal received at the radar sensor and representing a location in the vicinity of the vehicle; determining, from a database, a predefined map, wherein the map comprises at least one element representing a static landmark in the vicinity of the vehicle; matching at least a subset of the plurality of radar detection points of the at least one scan and the at least one element of the map; deter-mining the position of the vehicle based on the matching.

Method for determining the position of a vehicle

A method for increasing the reliability of determining the position of a vehicle on the basis of a plurality of detection points is described, the plurality of detection points being acquired using a radio-based and/or an optical sensor system, in particular a radar system, of a vehicle receiving electromagnetic signals from a vicinity of the vehicle, and each of the plurality of detection point representing a location in the vicinity of the vehicle, wherein the method comprises for each detection point of at least a subset of the plurality of detection points: determining at least one geometrical object associated with the detection point; determining at least one group of detection points from the subset sharing the at least one geometrical object; determining a quantity of detection points in the at least one group; evaluating a weight which represents the quantity of detection points in the at least one group on a predefined scale, and processing the detection point with respect to the weight.

Method for increasing the reliability of determining the position of a vehicle on the basis of a plurality of detection points

A vehicle-based method to determine the suitability of an object in the vicinity of a vehicle as a suitable positional landmark, comprising the steps of: a) emitting a plurality of radar signals from a vehicle; b) detecting the radar returns from said emitted radar signals reflected by said object; c) analyzing at least one parameter of at least one radar return to determine the extent to which said object is a stationary object; d) analyzing at least one parameter of at least one radar return to determine the extent to which said object is a single scatterer; e) analyzing at least one parameter of a plurality of radar returns to determine the extent to which said parameter varies with the azimuthal angle between said vehicle and said object, f) determining the suitability of said landmark for the results of steps c), d) and e).

Method to determine the suitability of a radar target as a positional landmark

A device for distinguishing between traversable and non-traversable objects. The device includes: an object-detection sensor unit configured generate data about a space around the sensor, a map generation unit configured to use the data to generate an occupancy grid map and a free space grid map for the space around the object-detection sensor unit. Each of the occupancy grid map and the free space grid map includes an array of cells. Each cell of the occupancy grid map contains an occupied space probability value representing the probability for the respective cell being occupied and each cell of the free grid map contains a free space probability value representing the probability for the respective cell being free. The device includes a classifier unit configured to classify at least one of the cells as containing a traversable or non-traversable object by calculating a difference of two free space probability values derived from the free space probability values of at least two of the cells adjacent to the at least one cell and by using the difference as well as the occupied space probability value of the at least one cell to classify the at least one cell.

Device and a method for distinguishing between traversable and nontraversable objects

The present invention relates to a method for the recognition and tracking of a moving object, in particular of a pedestrian, from a motor vehicle, at which a camera device is arranged. An image of the environment including picture elements is taken in the range of view of the camera device () by means of the camera device at regular time intervals and those picture elements are identified with the help of an image processing system which correspond to moving objects to be tracked. A picture element is extracted for each of these objects which represents a projection in image coordinates of that spatial point at which the object contacts a road plane The movement of the corresponding spatial point in the road plane is tracked by means of a state estimator which uses an at least four-dimensional state vector whose components are a position of the spatial point in the road plane and an associated speed in the road plane, wherein the tracking of the movement by the state estimator includes the steps that a prediction is generated for the state vector, this prediction is converted into image coordinates via suitable projection equations, an error to be expected for this prediction is calculated in image coordinates by means of a covariance matrix, and this prediction is compared with the picture element extracted in a later image and is updated.

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Wuppertal, Germany

Uri Iurgel