Ford Global Technolgoies, LLC

Saeid Nooshabadi

Jinhyoung Oh

Vidya Nariyambut Murali

Bruno Sielly Jales Costa

Vijay K Nagasamy

Mohsen Lakehal-ayat

Daniel R Fuhrmann

Mojtaba Bahramgiri

Kunle T Olutomilayo

The disclosure is generally directed to systems and methods for trailer hitch ball position location including receiving a plurality of image frames from a camera directed at a front of a trailer coupled to a vehicle at a coupling point, modeling the image frames in a convolutional neural network to form an initial estimate of a pivot point position as a location, optimizing the model using a nonlinear equation to identify the pivot point position, and locating the coupling point as the optimized pivot point position. The convolutional neural network includes a plurality of bounding boxes centered as locations of predetermined markers on the front of the trailer, the modeling via a reverse pinhole projection of a pixel onto a three-dimensional coordinate frame projected on a trailer plane to enable computed marker positions to determine relative dimensions of the trailer and locate the coupling point. The optimizing includes solving a nonlinear least-squares (NLLSQ) optimization formulation for multiple markers on the trailer. The method include the use of geometrical means to determine the angle of articulation between the trailer and tow-vehicle (hitch angle) by tracking the plurality of bounding boxes centered as locations of predetermined markers on the front of the trailer, as the vehicle and trailer move in a circular arc with respect to each other.

Systems and methods for trailer hitch ball position and hitch angle

A vehicle trailer detection system includes a radar system and a controller receiving object point location data from the radar system at an increased sensitivity level, storing sequential first and second object point location data sets, and applying a rotational point set registration to the first and second object point location data sets to achieve a match between a subset of persistent point locations within the first and second object point location data sets to output an estimated rotation angle. The persistent point locations in the first and second data sets are determined to correspond with detected points on a trailer coupled with the vehicle. The controller refines the estimated rotation angle by minimizing an error in matching between the persistent point locations in the first and second object point location data sets to output a determined hitch angle between the trailer and the vehicle about a coupling point.

Hitch angle detection using automotive radar

A trailer detection system for a vehicle includes a radar system outputting object point location data to a rear of the vehicle and a controller. The controller receives the object point location data and determines a position of an edge of the trailer relative to the vehicle by processing the object point location data from the radar system at a reduced threshold relative to use of the data in detecting a vehicle and filters out object point location data not correlated with the edge of the trailer based on object point location data persistence during driving of the vehicle. The controller further correlates the determined position of the edge of the trailer relative to the vehicle to determine an angle of the trailer relative to the vehicle about a coupling point.

A trailer angle identification system comprises an imaging device configured to capture an image. An angle sensor is configured to measure a first angle of the trailer relative to a vehicle. A controller is configured to process the image in a neural network and estimate a second angle of the trailer relative to the vehicle based on the image. The controller is further configured to train the neural network based on a difference between the first angle and the second angle.

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Houghton, MI, United States of America

Saeid Nooshabadi