Continental Autonomous Mobility US, LLC

Continental Automotive Systems Corporation

Eduardo Jose Ramirez Llanos

Xin Yu

Julien Ip

Matthew Donald Berkemeier

Kyle P Carpenter

Dhiren Verma

Andrew Phillip Bolduc

Dominik Froehlich

Victor Manuel Camacho Ruiz

Ibro Muharemovic

Brandon Herzog

James Hockridge Critchley

William Benson Nichols

Joseph Zagroba

Francisco Alejandro Fuentes Perez

Erick Daniel Rivera Gutierrez

Isemany Angelica Leal Martinez

A method for determining a trailer angle between a tow vehicle and a trailer attached to the tow vehicle includes receiving images from a camera positioned on a rear portion of the tow vehicle with a data processing hardware device, determining visual features from the images, tracking the visual features while the tow vehicle and trailer are moving and calculating, at the data processing hardware, the trailer angle based on the visual features. The trailer angle is then transmitted from the data processing hardware to one or more vehicle systems.

Vehicle trailer angle estimation via projective geometry

A method for visual trailer tracking of vehicle-trailer angle estimation, including: (a) camera receiving images, each most recently received image being identified as a current image, replacing a previously identified current image; (b) during a driving maneuver, extracting visual features from the current image, calculating a trailer angle from the current image, and storing the current image as a reference image, the trailer angle as a trailer angle reference and the extracted visual features as visual reference features; and (c) matching the visual features from the current image with the visual reference features. When a number of matches is below a threshold, repeating operation (c) to update the reference image, the trailer angle reference and the visual reference features. The method includes calculating a trailer angle between a trailer representation in the current image and a trailer representation in the reference image based in part upon the trailer angle reference.

Long-term visual trailer tracker for vehicle-trailer angle estimation

A method for calibrating extrinsic parameters () of a trailer camera () supported by a trailer () attached to a tow vehicle (). The method includes determining a three-dimensional feature map () from one or more vehicle images () received from a camera () supported by the tow vehicle and identifying reference points () within the three-dimensional feature map. The method includes detecting the reference points within one or more trailer images received from the trailer camera after the vehicle and the trailer moved a predefined distance in the forward direction. The method also includes determining a trailer camera location () of the trailer camera () relative to the three-dimensional feature map () and determining a trailer reference point () based on the trailer camera location. The method also includes determining extrinsic parameters () of the trailer camera relative to the trailer reference point.

Automatic trailer camera calibration

A method and system for locating and tracking a trailer coupler for autonomous vehicle operation is disclosed. The system converts an image from a vehicle camera to a depth map that includes a plurality of points indicative of a distance between an object within the image and a reference point. The system used the depth map to identify and track a coupler of a trailer.

Autonomous vehicle trailer hitch coupling system

A method of determining a tow hitch position. The method includes obtaining a two-dimensional image of a tow hitch in a three-dimensional scene. A model tow hitch is obtained in three dimensions. A three-dimensional rendering of a scene is generated that includes the model tow hitch. The model tow hitch in the three-dimensional rendering is positioned in an orientation corresponding with an orientation of the tow hitch in the three-dimensional scene.

Method for determining a tow hitch position

A vehicle driver assist system provides for the location of a target feature in an initial image and updates the location of that target feature based on information indicative of vehicle dynamic operation. The system predicts a relative position of the target feature within subsequent images such that only a portion of subsequent images need by analyzed and searched.

Visual tracking of target features

A method for autonomously parking a vehicle-trailer system is provided. The method includes receiving sensor system data from a sensor system supported by the vehicle. The sensor system data includes images of surroundings along a driving path of the vehicle-trailer system. The method includes determining a local map based on the sensor system data. The local map includes surroundings along the driving path. The method includes receiving a user selection of an image location within the images. The image location representing a position in the local map associated with a selected location within the surroundings. The method includes determining a parking path from a current location of the vehicle-trailer system to the position based on the local map and instructing a drive system to execute an autonomous parking behavior causing the vehicle-trailer system to autonomously drive along the parking path and autonomously park in the selected location.

Autonomous truck-trailer maneuvering and parking

A method for determining a location of a trailer in an image includes obtaining at least one real-time image from a vehicle. The at least one real-time image is processed with a controller on the vehicle to obtain a feature patch describing at least one real-time image. A convolution is performed of the feature patch and each filter from a set of filters with the filter being based on data representative of known trailers. A location of a trailer is determined in the at least one real-time image based on the convolution between the feature patch and each filter from the set of filters.

Method and device for detecting a trailer

A localization and mapping system and method for a motor vehicle is disclosed and includes at least one camera configured to obtain images of an environment surrounding the motor vehicle, at least one sensor configured to obtain location information for objects surrounding the motor vehicle and a controller configured to receive the images captured by the at least one camera and the location information obtained by the at least one sensor. The controller enhances the captured images utilizing a neural network and combines the enhanced images with the location information to localize the vehicle within the mapped environment.

Automotive localization and mapping in low-light environment

An automated parking system for a vehicle includes a camera configured to obtain images of objects proximate the vehicle, and a controller configured to review the obtained images of objects proximate the vehicle to classify an environment proximate the vehicle, determine a type of parking lot associated with the classified location and initiate an automated parking function of the vehicle corresponding to the determined type of parking lot.

Parking spot detection reinforced by scene classification

An automated vehicle parking system for a motor vehicle is disclosed and includes at least one camera obtaining images proximate a vehicle, at least one sensor array detecting objects proximate the vehicle, and a controller configured to generate a mask of an area proximate the vehicle from the images obtained by the at least one camera including labeled features identified within the obtained images and project the generated mask onto an occupancy grid generated with information from the at least one sensor array, wherein the controller is configured to locate a parking space responsive to open spaces defined within the generated mask.

Image semantic segmentation for parking space detection

A method for determining a position of a tow ball in an image. The method includes obtaining at least one real-time image from a vehicle. The at least one real-time image is processed with a controller on the vehicle to obtain a feature patch (f) describing at least one real-time image. A convolution is performed of the feature patch (f) and each filter (h) from a set of filters (H) with the filter (h) being based on data representative of known tow hitches fixed to the vehicle. A location of a tow ball on the tow hitch is identified in the at least one real-time image is based on the convolution between the feature patch (f) and each filter (h) from the set of filters (H).

Method for real-time tow ball detection

A method for autonomously maneuvering a tow vehicle towards a trailer positioned behind the tow vehicle is provided. The method includes receiving one or more images from one or more cameras positioned on a back portion of the tow vehicle. The method also includes identifying a trailer representation within the one or more images. The trailer representation being indicative of the trailer positioned behind the tow vehicle. The method also includes setting a vertical center of the trailer representation as a target. The method also includes determining a first steering wheel angle to turn the tow vehicle such that the vehicle autonomously maneuvers in a direction towards the target. The method also includes transmitting instructions to a drive system causing the tow vehicle to maneuver based on the first steering wheel angle.

Trailer detection and autonomous hitching

A method of detecting and localizing a coupler of a trailer hitch associated with a trailer positioned behind a tow vehicle is provided. The method includes determining a region of interest within images from a rear camera. The region of interest includes a representation of the trailer hitch. The method includes determining a three-dimensional (3D) point cloud representing objects inside the region of interest. The method includes determining a camera plane based on the images. The method includes projecting the cloud points onto the camera plane and determining a coupler location based on the projected cloud points onto the camera plane. The method includes determining a path based on the coupler location. The path ending when the tow vehicle is attached to the trailer. The method also includes sending instructions to a drive system causing the tow vehicle to autonomously drive in a rearward direction along the path.

Coupler and tow-bar detection for automated trailer hitching via cloud points

A method for autonomously maneuvering a tow vehicle. The method includes receiving images from one or more cameras positioned on a back portion of the tow vehicle and receiving sensor data from an inertial measurement unit supported by the tow vehicle. The method also includes determining a pixel-wise intensity difference between a current received image and a previous received image. The method includes determining a camera pose and a trailer pose with respect to a world coordinate system. The camera pose and the trailer pose are based on the images, the sensor data, and the pixel-wise intensity difference. The method includes determining a tow vehicle path based on the camera pose and the trailer pose. The method also includes instructing a drive system supported by the tow vehicle to autonomously maneuver along the tow vehicle path in a reverse direction causing the tow vehicle to hitch with the trailer.

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Auburn Hills, MI, United States of America

Eduardo Jose Ramirez Llanos