Ford Global Technolgoies, LLC

Devesh Upadhyay

Michiel Jacques Van Nieuwstadt

Michael Hopka

William Charles Ruona

David John Kubinski

David Hanna

Dimitar Petrov Filev

Huanyi Shui

Liangjun Hu

In Kwang Yoo

Frank M Korpics

Jason Ronald Smith

Cory Hendrickson

Michael Goebelbecker

Alireza Rahimpour

Joseph Norman Ulrey

Brad Alan Boyer

Eric Warren Curtis

Justin Miller, Jr

Satheesh Makkapati

Christopher John Mazur

Ryan Burke

Tao Zeng

Iman Soltani Bozchalooi

Kang Song

Chris Riffle

David Barbe

Yuji Fujii

Fling Finn Tseng

Daryl Joseph Martin

Christine Kay Lambert

Johannes Geir Kristinsson

Jonathan Diedrich

Jacobus Hendrik Visser

Douglas Allen Dobson

Francois Charette

Garth Michael Meyer

John Paul Bogema

David Robert Nader

Shiqi Qiu

Leon Hu

Patrick James Blanchard

Himanshu Verma

Mark Gehrke

Brandon Michael Dawson

Thomas Alan Brewbaker

Janice Lisa Tardiff

Timothy Brian Chanko

Bhagyashri Satyabodha Katti

Dean Pennala

James Robert Warner

Yijing Zhang

Hiral Jayantilal Haria

Avra Brahma

Jeff Reich

Hao Wu

Hang Yang

Jonathan Niemi

David Wynn Philion

Navid Fallahinia

Michiel J Van Nieustadt

Jim Birley

Harshal Maske

Robert Bennett

Zhe Wang

Alemayehu Admasu

A far-infrared camera mounted in a vehicle generates an image frame. When an image of a large animal is identified in the image frame, a pixel intensity of the large animal image is determined. An estimated distance to the large animal from the far-infrared camera based on the pixel intensity is determined. When the animal is classified as a tracked animal, and future trajectories of the tracked animal and the vehicle intersect, a component in the vehicle is actuated.

Large animal detection and intervention in a vehicle

Methods and systems are provided for monitoring a health of a vehicle component. In one embodiment, a method is provided, comprising dividing a population of vehicles of a connected vehicle population into a plurality of vehicle classes; for each vehicle class of the plurality of vehicle classes, training a class-specific model of the vehicle class to predict a health status variable of a vehicle component included in the vehicle class based on labelled data from historic databases and calibration data; and for each vehicle class of the plurality of vehicle classes, using a first Federated Learning strategy to request local model data from each vehicle of a plurality of vehicles of the vehicle class; receive the local model data from the plurality of vehicles; update the class-specific model based on the received local model data; and send updated parameters of the class-specific model to vehicles included in the vehicle class.

Methods and systems for estimating a remaining useful life of an asset

A server includes an interface configured to communicate with a plurality of vehicles; and a processor, programmed to, send a query to the plurality of vehicles, the query identifying types of vehicle data and indicating an initial sampling rate, responsive to receiving the vehicle data sampled by the vehicles, process the vehicle data to obtain a feature result including an estimated value and a variance extending from the estimated value, and responsive to the variance being greater than a first threshold, send a first updated query indicating an increased sampling rate to the plurality of vehicles.

System for query vehicle data

A method including generating a plurality of synthetic images of a material, where each synthetic image from among the plurality of synthetic images is associated with a feasibility value greater than a threshold synthetic feasibility value. The method includes determining, for each synthetic image from among the plurality of synthetic images, one or more material properties of the material and one or more process parameters of the material based on the synthetic image and generating a plurality of data points and a pareto surface based on the one or more material properties and the one or more process parameters. The method includes selecting a target data point based on the plurality of data points and a distance between a set of data points from among the plurality of data points and the pareto surface.

System and method for identifying and analyzing desired properties of a material

A vehicle includes an engine, a clutch, and a controller. The clutch is configured to crank the engine during an engine start. The controller is programmed to, in response to a command to start the engine, adjust a clutch actuator pressure to drive a disconnect clutch torque toward a desired value. The controller is further programmed to, in response to variances of the disconnect clutch torque relative to the clutch actuator pressure exceeding a threshold, issue a disconnect clutch fault.

Vehicle powertrain control system

A plurality of thermal images forward of a vehicle are collected. Thermal data in the plurality of thermal images is normalized based on an ambient air temperature to generate a plurality of normalized thermal images. The plurality of normalized thermal images are input to a machine learning program trained to output an identification of an object based on the ambient air temperature and a risk of collision between the vehicle and the object. A vehicle component is actuated based on the identification of the object and the risk of collision with the object.

Object identification with thermal imaging

An identifier for first set of display content on a vehicle display is input to a statistical model that outputs a plurality of probabilities that a user input will select each of a plurality of second set of display contents for display after the first set of display content is displayed. A first probability is identified for a predicted set of display content that is a highest probability in the plurality of probabilities. The plurality of probabilities are provided to at least one of an optimization model and a neural network upon determining an accuracy of the statistical model is below a threshold. Upon receiving, from the at least one of the optimization model and the neural network, a second probability for the predicted set of display content, the display content is selected based on the first and second probabilities. The vehicle display is updated based on the selected set of display content.

Vehicle display

Methods and systems are provided for increasing an accuracy of anomaly detection in assets such as vehicle components. In one example, a method provides for continuous health monitoring of connected physical assets, comprising adapting thresholds for anomaly detection and root cause analysis algorithms for the connected assets based on an aggregation of new connected data using machine learning; updating and ranking advanced statistical and machine learning models based on their performance using connected data until confirming a best performing model; and deploying the best performing model to monitor the connected physical assets.

Methods and systems for anomaly detection of a vehicle

A method includes obtaining state information from one or more sensors of a digital twin. The method includes determining an action at the first routing control location based on the state information, where the action includes one of a pallet merging operation and a pallet splitting operation, and determining a consequence state based on the action. The method includes calculating a transient production value based on the consequence state and a transient objective function, calculating a steady state production value based on the consequence state and a steady state objective function, and selectively adjusting one or more reinforcement parameters of the reinforcement learning system based on the transient production value and the steady state production value.

Systems and methods for training a reinforcement learning system for pallet routing in a manufacturing environment

A computer includes a processor and a memory, the memory storing instructions executable by the processor to input a signal received from a portable device to a machine learning program trained to output a location of the portable device relative to a vehicle, collect operating data of one or more vehicle components, predict an action of a vehicle user based on the predicted location, and, based on the predicted action of the vehicle user, actuate one or more vehicle components. The machine learning program is trained with a training dataset that is updatable to include the signal, the output predicted location, the collected operating data, the predicted action, and an identified action performed by the vehicle user.

Vehicle and portable device operation

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to train a neural network included in a memory augmented neural network based on one or more images and corresponding ground truth in a training dataset by transforming the one or more images to generate a plurality of one-hundred or more variations of the one or more images including variations in the ground truth and process the variations of the one or more images and store feature points corresponding to each variation of the one or more images in memory associated with the memory augmented neural network. The instructions can include further instructions to process an image acquired by a vehicle sensor with the memory augmented neural network, including comparing a feature variance set for the image acquired by the vehicle sensor to the stored processing parameters for each variation of the one or more images, to obtain an output result.

Vehicle neural network enhancement

A method includes detecting, for each of a plurality of images, a plurality of key points, where each of the plurality of images represents an object of an assembly system. The method includes generating, for each of the plurality of images, a correspondence between the plurality of key points, and generating, for each of the plurality of images, a reference region based on the correspondence between the plurality of key points. The method includes identifying, for each of the plurality of images, a reference key point among the plurality of key points based on the reference region, and determining a pose of the object based on the reference key point of each of the plurality of images and a reference pose of the object.

Systems and methods for image-based component detection

Methods and systems are provided for controlling a vehicle engine to adjust exhaust warm-up strategy based on a vehicle network information. In one example, in response to an expected decrease in temperature of a catalyst of a vehicle below a threshold and an estimated duration thereof based on communications external from the vehicle, a method may include delaying catalyst heating actions, when the catalyst heating actions are determined to be unable to heat up the catalyst to threshold temperatures. However, the catalyst heating actions may be enabled when the catalyst heating actions are determined to be able to achieve the threshold temperature within the duration.

Systems and method for exhaust warm-up strategy

Methods and systems are provided for selecting a first travel route for a vehicle from a database based on particulate filter regeneration requirements and an inferred initial driver state of mind. In one example, the initial driver state of mind may be selected based on a past driver history, and during travel along the first travel route, the driver state of mind may be updated based on the driver interactions with traffic. The route selection may also be updated based on the updated driver state of mind.

Systems and methods for particulate filter regeneration

Methods and systems are provided for regenerating an exhaust particulate filter based on a projected vehicle drive cycle and catalyst ammonia storage level. In one example, a method may include scheduling a PF regeneration during a regeneration window to maintain a threshold ammonia level in an exhaust catalyst, at the end of the drive cycle.

Growing community of inventors

Canton, MI, United States of America

Devesh Upadhyay