Ford Global Technolgoies, LLC

Ford Motor Company Limited

Nikhil Nagraj Rao

Luke Niewiadomski

Bruno Sielly Jales Costa

Douglas J Rogan

Vidya Nariyambut Murali

Roger Arnold Trombley

Scott Vincent Myers

Harpreetsingh Banvait

Lisa Scaria

Lihui Chen

Shruthi Venkat

Francois Charette

Alexandru Mihai Gurghian

Tarik Safir

Sam Harris

Akhil Perincherry

Erick Michael Lavoie

Hamid M Golgiri

Chen Zhang

Li Xu

Donald Jacob Mattern

Seyed Armin Raeis Hosseiny

Bo Bao

Kyle Simmons

Hemanth Yadav Aradhyula

Arnav Sharma

Katherine Rouen

Mohamed Ahmad

Siyuan Ma

Mark Crawford

Robert Bell

Kunjan Singh

Ramchandra Ganesh Karandikar

Alexandro Walsh

Binduhasini Sairamesh

John Michael Celli

Mohamed El-sawah

Frederic Christen

Mark Bowers

Christoph Kessler

Frank Golub

Sandhya Sridhar

Rick Haubenstricker

Richard Campbell

A location of a first object can be determined in an image. A line can be drawn on the first image based on the location of the first object. A deep neural network can be trained to determine a relative location between the first object in the image and a second object in the image based on the line. The deep neural network can be optimized by determining a fitness score that divides a number of deep neural network parameters by a performance score. The deep neural network can be output.

Efficient neural networks

A system includes a computer programmed to receive first sensor data from a first sensor, wherein the first sensor data is defined in part by a first data space that includes first parameters of the first sensor, and second sensor data from a second sensor, wherein the second sensor data is defined in part by a second data space that includes second parameters of the second sensor, to input the first sensor data and the second sensor data to a machine learning program to train the machine learning program to determine a domain translation of data from the first data space to the second data space, and then to input a set of training data received from the first sensor to the trained machine learning program to generate a training dataset based on the determined domain translation of data from the first data space to the second data space.

Sensor domain adaptation

A monitoring system for a vehicle includes a plurality of surveillance sensors in connection with the vehicle and configured to capture sensor data proximate to the vehicle. A position sensor is configured to detect a location of the vehicle. A controller determines a surveillance mode for the vehicle based on the sensor data and a plurality of security factors associated with the location of the vehicle. The controller activates the surveillance mode in response to the security factors and monitors the sensor data. The controller further filters a plurality of security events from a plurality of benign events and selectively outputs alerts in response to the security events and the benign events.

System and method for vehicle security monitoring

A hitch assist system for a vehicle comprises an imaging system that receives image data of a hitch ball and trailer coupler, and a controller. The controller estimates a distance between a point on each of the hitch ball and trailer coupler. The points are parallel to a plane defined by a surface beneath the hitch ball and trailer coupler. The controller tracks the distance with a pixel-domain comparison between each of the points responsive to the distance being less than a first threshold, and maneuvers, via steering and braking systems, the vehicle along a path such that the distance is indicative of the points being coaxial.

Prevention of trailer coupler tracking jump during hitch assist operation

A system for assisting in aligning a vehicle for hitching with a trailer includes a steering system that adjusts a steering angle of the vehicle, a braking system that adjusts a speed of the vehicle, an imaging system that receives image data of a trailer disposed in an area proximate the vehicle, and a controller. The controller detects, within a threshold distance defined from a stationary point on the vehicle and the trailer, a position of a coupler from the image data, and, responsive to the position being less than the threshold distance, a status of the trailer based on the image data being indicative of a position of a hitch ball relative to the coupler within a second threshold. The controller maneuvers, via the steering and braking systems, the vehicle based on the status.

Differentiating between near trailer and connected trailer

A system for assisting in aligning a vehicle for hitching with a trailer includes a vehicle steering system, a wireless communication module, a detection system outputting a signal including scene data of an area to a rear of the vehicle, and a controller. The controller receives, via the wireless communication module, an automated hitching initiation command from an external wireless device, receives the scene data and identifying the trailer within the area to the rear of the vehicle, derives a backing path to align a hitch ball mounted on the vehicle to a coupler of the trailer, and controls the vehicle steering system to maneuver the vehicle including reversing along the backing path.

System and method for remote automated vehicle alignment with a trailer for hitching

A system for assisting in aligning a vehicle for hitching with a trailer includes a steering system that adjusts a vehicle steering angle, a braking system that adjusts a vehicle speed, an imaging system that receives image data of a drawbar assembly being receivable in a hitch receiver, and a controller. The controller is configured to detect an edge of the drawbar assembly from the image data, target an endpoint at a fixed offset from the edge and a stationary point on the vehicle, and maneuver, via the steering and braking systems, the vehicle along a path to align the endpoint with the trailer.

Fixed offset method for hitch detection in hitch assist operation

A monitoring system for a vehicle includes surveillance sensors configured to capture sensor data proximate to the vehicle. A position sensor is configured to detect a location of the vehicle. A controller is in communication with the surveillance sensors and the position sensor. The controller calculates a security score in response to security data based on the location of the vehicle and selects an active mode for the surveillance sensors in response to the security score. The active mode is selected from a plurality of surveillance modes that vary an active operation of the plurality of surveillance sensors. The controller may change or escalate the active mode and a corresponding monitoring operation (e.g., from a first mode to a second mode) in response to a security detection.

A vehicle system configured to control a trailer alignment routine includes a hitch mounted on a vehicle and a controller. The controller is configured to identify a coupler position of a trailer and control motion of the vehicle to toward an aligned position. The controller is further configured to control a braking procedure of the vehicle including a plurality of concurrent deceleration control procedures in response to a portion of the vehicle passing a gradual stopping distance. The concurrent deceleration procedures include monitoring an elapsed time following the portion of the vehicle passing the gradual stopping distance and monitoring a remaining distance to the aligned position based on a velocity of the vehicle and comparing the remaining distance to a rapid stopping distance.

Overshoot protection in hitch assist operation

A system for assisting in aligning a vehicle for hitching with a trailer includes a vehicle steering system, an imager mounted with and directed to a rear of the vehicle and outputting image data, and a controller. The controller receives the image data, applies a location identifier of a vehicle hitch ball to the image data, and identifies a coupler of the trailer within the image data. The controller also outputs a steering control signal to the steering system in reversing of the vehicle to align the location identifier of the vehicle hitch ball in the image data with the coupler of the trailer.

System for aligning a vehicle hitch location identifier with a trailer coupler

A computer includes a processor and a memory, the memory storing instructions executable by the processor to collect a plurality of images of one or more targets at an intersection, input the images to a machine learning program to determine a number of the targets to which a host vehicle is predicted to yield at the intersection based on time differences between the plurality of images, and transmit a message indicating the number of the targets.

Vehicle intersection operation

Techniques pertaining to vehicle occupancy indication and utilization thereof are described. A method may involve determining occupancy information regarding a number of occupants in a vehicle. The method may also involve indicating the occupancy information in either or both of a human-perceivable way and a machine-perceivable way.

Vehicle occupancy indication and utilization thereof

A system for assisting in aligning a vehicle for hitching with a trailer includes a vehicle steering system, a detection system outputting a signal including object position information of an area to a rear of the vehicle, and a controller. The controller receiving the object position data and identifying a targeted trailer and at least one additional object within the area to the rear of the vehicle and controlling the vehicle steering system to maneuver the vehicle during reversing to align a hitch ball mounted on the vehicle to a coupler of the targeted trailer. Upon aligning the hitch ball with the coupler, the controller presents an indication, if it is determined that the at least one additional object is within a threshold distance of a side of the targeted trailer.

Detection and response to confined trailer in system-assisted hitch operation

The present invention extends to methods, systems, and computer program products for using Unmanned Aerial Vehicles (UAVs) to inspect autonomous vehicles. An autonomous vehicle carries a UAV (or 'drone') in a protected area, for example, in a glove compartment, trunk, etc. Between rides, the UAV can be deployed to inspect the autonomous vehicle. Images from the UAV can be sent to other components for image analysis. When an inspection is completed, the UAV can return to the protected area. The UAV can inspect both the interior and exterior of an autonomous vehicle. When an inspection is passed, the autonomous vehicle can begin a new ride. When an inspection is failed, the autonomous vehicle can report for repairs or summon a tow vehicle.

Using unmanned aerial vehicles to inspect autonomous vehicles

Growing community of inventors

Cupertino, CA, United States of America

Nikhil Nagraj Rao