Ford Global Technolgoies, LLC

Ford Motor Company Limited

Aaron Lewis Mills

Nitendra Nath

Shane Elwart

Gerald H Engelman

Liwen Xu

Samir Mohamad Beydoun

John Robert Van Wiemeersch

Thomas Lee Miller

Kevin Thomas Hille

Anthony Dwayne Cooprider

Karl Wojcik

Shimul Bhuva

Gopichandra Surnilla

Jianbo Lu

Brendan F Diamond

Keith Weston

Thomas Edward Pilutti

Jordan Barrett

John Shutko

Alex Maurice Miller

Ronald Patrick Brombach

Michael Hafner

Keith Glenn Mattson

Anthony Gerald King

John Vincent Bond, Iii

Dorian Jack Spero

Harish Dutt

Paul Schmitt

John Stephen Wuerth

Kurt Peterson

John Wilds, Sr

Zhao Wang

Bahgat Aboushaban

Jeffrey Alan Hartley

Michael Czarnecki

Joseph Ciaravino

John Juronoc

Paul L Stanko

Nicolas Salciccioli

Mahmoud Yousef Ghannam

Brian Bennie

Dale Scott Crombez

David Michael Herman

John Ottavio Michelini

Daniel A Makled

Steven Yellin Schondorf

Hafiz Shafeek Khafagy

Michael Mcquillen

Eric L Reed

Andrew Denis Lewandowski

Christoph Arndt

Kirk Pebley

Daniel A Gabor

Scott Howard Gaboury

Bo Wu

Patrick Lawrence Jackson Van Hoecke

Lawrence Daniel Cepuran

Scott Alan Watkins

Danielle Rosenblatt

Hao Zhang

Xingping Chen

Chad Michael Korte

Andrew Arthur Brown

Helmuth Bosch

Matthew Y Rupp

John Curtis Hickey

Terry Thomas Cwik

Peter W A Zegelaar

Yashanshu Jain

Peter Gyumyeong Joh

Jake S Schwartz

Robert Schroeter

Brian Wolski

Andrew D Sarkisian

Matthew J Dalebout

Shadi Jammoul

Benjamin Carl Mukkala, Ii

Brian Tamm

Michael Lopez

Andreas Ediger

Andreas Giersiefer

Sabine Notelaers

Rebecca Lynne Seiler

Robert Lietz

Stephanie Rosenberg

Kevin Wegienka

Benjamin Baecker

Joel Matthew Bickmann

Kurt Mitts

Alekhya Ratnala

Ronald Patrick Bromnach

Manuel Strauch

Ryan Danko

Chet Hearn

Jonathan Mcneely

Thomas Edward Pilluti

Benjamin Bäcker

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 system has memory that stores instructions executable by the processor to instruct operation of at least one vehicle system (e.g., braking system, propulsion system, steering system, suspension system) in a minimum time mode for travel of the vehicle from a starting point to a destination point of a roadway. The system collects roadway data for the roadway from the starting point to the destination point. Based on the roadway data, the system determines a minimum time path from the starting point to the destination point and speed along the minimum time path. In response to a maximum acceleration input from a human driver of the vehicle when the vehicle is at the starting point, the system initiates the minimum time mode and instructs operation of at least one vehicle system to pursue the minimum time path and speed along the minimum time path from starting point to destination point.

Driver assistance for high accelleration and speed on a minimum time path

A computer is programmed to receive a plurality of first values for a respective plurality of variables transmitted over a communications network of a vehicle; determine a similarity measure between the first values and a plurality of second values of the variables; determine whether to transmit a collection of data transmitted over the communications network based on the similarity measure; and, upon so determining, transmit the collection of data to a server remote from the vehicle. The second values are a most similar set of values from an activation surface for a feature of the vehicle. The activation surface is a surface in a space defined by the variables dividing the space into regions in which activation of the feature is more or less likely than not, respectively, to have occurred when the variables have values in that region.

Vehicle data storage activation

Systems and methods for road disturbance detection and torque vectoring control. A vehicle may comprise: a torque vectoring system for independently varying torque to a plurality of wheels, an external sensor suite, and an electronic control unit. The control unit may comprise one or more processors and memory storing executable instructions that, as a result of execution by the one or more processors, cause the one or more processors to implement an appropriate torque vectoring strategy. The torque vectoring strategy may comprise biasing torque towards or away from a wheel/motor/axle.

Systems and methods for road disturbance detection and torque vectoring control

A computer includes a processor and a memory, the memory storing instructions executable by the processor to, in a host vehicle, determine a threat number for a first target vehicle based on data received from the first target vehicle indicating at least one of a position, speed, or route history of the first target vehicle, identify a second target vehicle based on data collected with one or more host vehicle sensors when the threat number of the first target vehicle exceeds a threshold, determine that the first target vehicle and the second target vehicle are not a same vehicle, and, then, upon determining that the first target vehicle and the second target vehicle are not the same vehicle and that at least one of (a) a barrier is detected between the host vehicle and the first target vehicle or (b) that a threat number of the second target vehicle exceeds a second threshold, suppress a collision avoidance action.

Enhanced threat assessment

A computer in a vehicle includes first and second electronic control units (ECUs). The first and second ECUs are programmed to monitor, respectively, a first operating condition and a second operating condition. Each operating condition includes one of path deviation, lane width, user awareness, or steering torque. The second ECU is programmed to monitor the second operating condition according to a protocol with a security measure. The first or second ECU is further programmed to control vehicle operation based on the first or second operating condition.

Enhanced vehicle operation

A computer includes a processor and a memory, the memory storing instructions executable by the processor to identify an error between a predicted steerable path of a vehicle based on data collected according to a first protocol and a predicted lane path based on data collected according to a second protocol and to identify a path fault when the error exceeds an error threshold for an elapsed time exceeding a time threshold.

Vehicle path processing

A system, comprising a processor and a memory, the memory including instructions to be executed by the processor to pilot a vehicle based on determining first and second lane markers, where lane markers are mathematical descriptions of roadway lane markers applied to a roadway to mark traffic lanes, determine a missing first or second lane marker, and pilot the vehicle for a determined period of time based on a remaining first or second lane marker.

In-vehicle traffic assist

A computer for a vehicle is described. The computer includes a processor and memory storing instructions executable by the processor. The instructions include, to: determine a trigger to initiate a highway assist mode; based on the determined trigger, determine vehicle-location data; and based on the data, inhibit initiation of the mode.

Inhibiting highway assist mode

A vehicle computer includes a memory and a processor programmed to execute instructions stored in the memory. The instructions include determining a first lane center, autonomously operating a host vehicle relative to the first lane center, detecting a change in the first lane center to a second lane center, selecting a filter, and applying the filter while transitioning autonomous operation of the host vehicle from the first lane center to the second lane center.

Lane centering disturbance mitigation

Method and apparatus are disclosed for monitoring and adjustment of gaps between vehicles. An example vehicle includes a rear sensing device and a controller. The controller is to determine a target lead gap for following a lead vehicle during adaptive cruise control and measure, via the rear sensing device, a trailing distance to a trailing vehicle. The controller also is to determine a target trailing gap for the trailing vehicle. The example vehicle also includes a cruise control unit to increase, responsive to the trailing distance being less than the target trailing gap, the target lead gap based on the trailing distance.

Monitoring and adjustment of gaps between vehicles

A method for controlling a vehicle includes automatically adapting vehicle acceleration responsive to a cruise control setpoint acceleration associated with a detected speed limit, and a drive setpoint acceleration based on the cruise control setpoint acceleration, wherein a cruise controller determines a distance control setpoint acceleration based on a detected vehicle distance from a vehicle traveling ahead, and wherein the drive setpoint acceleration is limited by the distance control setpoint acceleration.

Method for automatically adapting acceleration in a motor vehicle

A computing system can determine a probability of precipitation based on Bayesian inference conditioned on probabilities associated with vehicle wiper status, vehicle jerk, vehicle sway, and vehicle lateral offset. The computing system can disable a vehicle lane assist system based on the probability of precipitation and operate a vehicle with the disabled vehicle lane assist system.

Driver assist

A communication from a second vehicle is received. Upon failing to detect the second vehicle based on first vehicle sensor data, a message indicating a forward collision warning is sent. Upon detecting the second vehicle based on the first vehicle sensor data, the forward collision warning is suppressed and a first vehicle brake is actuated.

Vehicle detection and avoidance

A camera is configured to be mounted facing a front of a vehicle. A computer is programmed to receive first and second images from the camera, determine a height of an obstacle located to the front of the vehicle using at least the first and second images, and, based at least in part on the height of the obstacle, send an instruction via a communications bus to a component controller to control a speed of the vehicle.

Vehicle underside impact avoidance

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Ann Arbor, MI, United States of America

Aaron Lewis Mills