Ford Global Technologies, LLC

Ford Motor Company Limited

Other

Michigan State University

Mahmoud Yousef Ghannam

Aed M Dudar

Swadad A Carremm

Brian Bennie

David James Tippy

John W Jensen

Saied Nusier

John Robert Van Wiemeersch

Todd Nelson Clark

David James Bauch

Abraham G Philip

Clara Bennie

Muhannad Anwar Hamdan

Venkatesh Krishnan

Mohamed Ridha Baccouche

Steven Yellin Schondorf

Adil Nizam Siddiqui

Jayagopal Appukutty

Howard E Churchwell, Ii

Somak Datta Gupta

Howard Churchwell

Rajarshi Roychowdhury

Roy Joseph Scott

Dana Conner

Jonathan Diedrich

Eric Layton Stratten

Robert Schroeter

Doug Thornburg

Joel Allen Pittenger

Segundo Baldovino

Cynthia M Neubecker

Dilip B Patel

Joshua R Wheeler

Scott Andrew Amman

David Jeffeory Berels

Cheri Lyn Hansen

Scott Mayberry

John Vincent Fazio

Haron Abdel-raziq

Christian Wegner

Sai Prasanth Velusamy

Jonathan Engels

Kam Hage

Pramita Mitra

Justin Miller, Jr

Prashant Dubey

Jake S Schwartz

Yeruva Satya Reddy

Paul Kevin Kula

Stuart C Salter

Brendan F Diamond

Mark Anthony Cuddihy

Dennis Seung-Man Yang

Russell Randall Pearce

Mark Eifert

David J Schmidt

Robert Parenti

Deepa Ramaswamy

Ryan Joseph Gorski

Erich Kemnitz

Brian Michael Siler

Michael Dupuis

Paul Kenneth Dellock

Pietro Buttolo

Erick Michael Lavoie

Saeed David Barbat

Keith Weston

Zhibing Deng

Fling Finn Tseng

James Chih Cheng

Oliver Lei

Vivekanandh Elangovan

Jialiang Le

Srinivasan Sundararajan

Joseph Edward Abramczyk

Allen R Murray

Aaron Lewis Mills

Harry Lobo

Edward Joseph Abramoski

Krishnakanth E Aekbote

Bhimaraddi Venkaraddi Alavandi

Matt Alan Niesluchowski

Nicholas Colella

James Martin Lawlis

Mark Gehrke

John Frederick Locke

Arun Dutta

Kelly Michael Kohlstrand

Galen Keith Thomas

James Joseph Loschiavo

Haysam M Kadry

Venky Krishnan

Marcus Edward Merideth

Kirk David Arthurs

Ira Jason Goldberg

Jason Shomsky

Se Kyoon Shin

Robert Ognjanovski, Jr

William Jerome Olsen

Scott Cutler

A vehicle with sound monitoring, having a cabin interior configured to transport one or more occupants, an interior microphone located in the cabin interior for detecting interior sound, a navigation device for detecting a geographic location of the vehicle, and a controller to determine sound ordinance rules with a sound limit based on the detected location, the controller further determining an exterior sound level based on the detected interior sound with the interior microphone, wherein the controller further generates an output indicative of the detected exterior sound level relative to the sound limit.

Vehicle sound ordinance control and method

A vehicle is provided including a plurality of wheel assemblies, a body supported on the plurality of wheel assemblies and having a cargo area for receiving a cargo load, a load sensing system configured to sense a vehicle load and generate vehicle load signals indicative of the sensed vehicle load, and an object recognition system configured to detect one or more objects in the cargo area and recognize the one or more objects. The vehicle also includes a controller processing the recognized one or more objects and determining dimensions of the cargo load and an estimated center of gravity of cargo load based on the dimensions of the one or more objects in the cargo area, and generates an output indicative of the estimated center of gravity of the cargo load.

Vehicle having center of gravity load estimation

A method for managing occupant interaction with components of a vehicle includes generating, via a time-of-flight sensor, a point cloud representing a compartment of the vehicle, the point cloud including three-dimensional positional information about the compartment. The method further includes identifying at least one body segment of a user based on the point cloud. The method further includes determining, via processing circuitry in communication with the time-of-flight sensor, a position of at least one feature of the at least one body segment. The method further includes calculating an orientation of the at least one body segment based on the at least one feature. The method further includes estimating an intended task of the user based on the orientation of the at least one body segment. The method further includes generating, via the processing circuitry, a response signal in response to estimation of the intended task.

Systems and methods for managing occupant interaction using depth information

A detection system for a target vehicle includes a camera capturing images of a region external to the target vehicle, a RADAR module that scans the region to detect a depth of a splash event in the region, an actuator configured to operate in response to a response signal and control circuitry configured to determine a distance between the target vehicle and a front of the splash event based on the images, compare the front of the splash event to the depth to determine an intensity of the splash event, and communicate the response signal based on the intensity of the splash event.

Splash detection using radar

A vehicle is provided including a cabin interior, one or more sensors located on the vehicle and configured to capture images of the cabin interior and generate sensor outputs, one or more powered windows configured to be controlled between open and closed positions, and a controller processing the sensor outputs of the one or more sensors with one or more pet profiles to detect a pet in the cabin interior, the controller controlling the one or more powered windows based on the detected pet.

Vehicle having pet detection and control

A vehicle includes a plurality of RADAR modules arranged at a common side of a plurality of sides of the vehicle and configured to detect an obstruction in a region exterior to the vehicle. A first RADAR module is on a left portion of the common side and has a first field of view. A second RADAR module is on a right portion of the common side and has a second field of view. A third RADAR module is between the first and second RADAR modules and is spaced from the first RADAR module by a first distance and spaced from the second RADAR module by a second distance. The third RADAR module has a third field of view at least partially overlapping each of the first and second fields of view. Control circuitry triangulates a position of the obstruction between a pair of the plurality of RADAR modules.

Detection system for a vehicle

A method for determining spatial availability for a compartment of a vehicle includes generating, via at least one time-of-flight sensor, a first point cloud representing the compartment of the vehicle, the first point cloud including three-dimensional positional information of the compartment. The method further includes calculating, via processing circuitry in communication with the at least one time-of-flight sensor, spatial information corresponding to a target configuration for the compartment. The method further includes comparing, via the processing circuitry, the spatial information to the first point cloud. The method further includes determining an availability of the target configuration based on the comparison of the spatial information to the first point cloud.

Vehicle space morphing

A vehicle includes a window separating a compartment of the vehicle from a region external to the vehicle. The window includes an outer surface. An imaging device is in the compartment and configured to capture an image of the region external to the vehicle through the window. Control circuitry is in communication with the imaging device and configured to receive the image from the imaging device, detect an obstruction in the image data corresponding to a substance on the window, and generate an output in response to the detection of the obstruction, wherein the imaging device is disposed within 50 millimeters (mm) from the window.

Visibility obstruction detection for a vehicle

A vehicle having a tailgate configured to move between retracted and extended positions is disclosed. The vehicle includes a first detection unit, a second detection unit, a third detection unit and a control unit. The control unit obtains a first input from the first detection unit and determines whether the tailgate is in extended position. The control unit further obtains a second input and a third input from the second and third detection units respectively, when the tailgate is in the extended position. Responsive to obtaining the second and third inputs, the control unit identifies a tailgate extended orientation. In addition, the control unit detects an obstacle presence in a vehicle rear side proximity and calculates a calibrated distance between the obstacle and a tailgate top side, based on the tailgate extended orientation. The control unit notifies a vehicle user when the calibrated distance is less than a threshold.

Method for truck backup with dynamic length

Systems and methods for providing a three-dimensional (3-D) parking assist feature include receiving sensor data from a plurality of different sensors with respect to a 3-D volume surrounding a top side of a vehicle, lateral sides of the vehicle, and at least one longitudinal end side of the vehicle, determining a 3-D envelope around the vehicle defined by a closest object relative to each of the top side, the lateral sides, and the at least one longitudinal end side of the vehicle, and outputting a distance measurement of the 3-D envelope relative to each of the top side, the lateral sides, and the at least one longitudinal end side of the vehicle on one or more vehicle display, wherein a negative distance is indicative of an overshoot or interference condition.

Three-dimensional parking assist

A wheel motor compensation system is for a vehicle. The vehicle has a wheel motor and a tire coupled to the wheel motor. The system includes a hybrid wireless tire sensor (HWTS) coupled to an interior of the tire, a processor electrically connected to the wheel motor, and a memory. The memory has instructions that, when executed by the processor, cause the processor to perform operations including gathering real time data with the HWTS, and utilizing the real time data to compensate the wheel motor so that preferred torque is applied to the tire.

Wheel motor compensation systems and methods using wheel sensor data

A vehicle includes a compartment having a first space having a first environmental condition and a second space having a second environmental condition. At least one camera captures a first image of a first part of a region external to the vehicle and a second image of a second part of the region. The first part of the region aligns with the first space, and the second part of the region aligns with the second space. An environmental control system of the vehicle has at least one of lighting control and climate control. Control circuitry is configured to determine brightness conditions of the region based on the first image and the second image and control the environmental control system to adjust the environmental conditions based on the brightness conditions.

Localized brightness detection for a vehicle

A system for determining lane information. A memory storing instructions executable by a processor includes instructions to receive forward image data of a roadway from a forward-facing camera of a vehicle, determine visible lane boundaries of the driving lane based on lane marking features in the forward image data, determine a predicted lane boundary of the driving lane based, at least in part, on forward features in the forward image data, and determine a driving path of the vehicle through the visible lane boundaries and the predicted lane boundary.

Vehicle lane boundary detection

A vehicle includes at least one camera that captures at least one image of a region external to the vehicle. The vehicle includes an environmental control system of the vehicle having at least one of lighting control and climate control for the vehicle. The vehicle includes control circuitry configured to process a first set of images of the plurality of images at a first sampling rate, determine a brightness condition of the region external to the vehicle based on processing the first set of images, process a second set of images of the plurality of images at a second sampling rate different than the first sampling rate, detect a shift in the brightness condition based on the second set of images, and control the environmental control system in response to the shift in the brightness condition.

Vehicle environment control using brightness detection

A drive mode adaptation system is for a vehicle. The vehicle has a drive mode selector. The system includes a hybrid wireless tire sensor (HWTS) coupled to an interior of a tire of the vehicle, a processor electrically connected to the drive mode selector, and a memory. The memory has instructions that, when executed by the processor, cause the processor to perform operations including gathering real time data with the HWTS, and utilizing the real time data with the drive mode selector to determine a preferred drive mode.

Drive mode adaptation systems and methods using wheel sensor data

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Canton, MI, United States of America

Mahmoud Yousef Ghannam