Ford Global Technologies, LLC

Toyota Motor Engineering & Manufacturing North America, Inc.

University of Michigan

Michael Hafner

Thomas Edward Pilutti

Erick Michael Lavoie

Mrdjan J Jankovic

Abhishek Sharma

Roger Arnold Trombley

Darrel Alan Recker

Aakar Mehra

Alexander Jaeckel

Mohit Srinivasan

Nathaniel Abram Rolfes

Erol Dogan Sumer

Donald Jacob Mattern

John Bales

Eric Hongtei Tseng

Aaron Lewis Mills

Mario Anthony Santillo

John Shutko

Nitendra Nath

Bradley George Hochrein

Xingping Chen

Yousaf Rahman

Zhao Wang

Bahgat Aboushaban

Shane Elwart

John Patrick Joyce

Hongtei Eric Tseng

Li Xu

Douglas Scott Rhode

Kevin Smith

Levasseur Tellis

Kyle Simmons

Matt Y Rupp

Andrew Arthur Brown

Zheng Hu

Timothy D Zwicky

Matthew Y Rupp

Mohsen Lakehal-Ayat

Brian George Buss

Lorenzo Caminiti

Quazi Farooqi

Shadi Jammoul

Drew Cunningham

Andy Chuan Hsia

Greg Blaisdell Stevens

Paul James Novak

Jiyi Liu

Domitilla Del Vecchio

Andreas Giersiefer

Jonathan Mcneely

Dogan Sumer

A computer includes a processor and a memory, and the memory stores instructions executable by the processor to receive sensor data indicating an obstacle, formulate a control barrier function for a vehicle and the obstacle based on the sensor data, determine a control input based on the control barrier function and a combination function, and actuate a component of the vehicle according to the control input. The combination function is a sum of a first function weighted by a first weight and a second function weighted by a second weight, and the first weight and the second weight are based on a kinematic state of the obstacle.

Obstacle avoidance for vehicle

A system includes a processor and a memory. The memory stores instructions executable by the processor to determine a virtual barrier around a vehicle based on receiving a first user input and data indicating a vehicle sprung mass, upon receiving a second user input selecting the virtual barrier, to determine an updated virtual barrier based on the received second user input, upon determining the virtual barrier, to verify that the virtual barrier satisfies one or more vehicle parameters; and to provide output based on the virtual barrier.

Vehicle path adjustment

A system for detecting a road surface includes a computer programmed to determine a virtual boundary for a vehicle body based on a shape of the vehicle body, upon identifying an object, to identify a plurality of points on the object based on received sensor data, to determine a barrier function based on each of the identified plurality of points, wherein the barrier function includes a barrier distance from a reference point of the virtual boundary of the vehicle to a respective one of the points on the object, based on (i) the determined barrier functions, (ii) the determined virtual boundary of the vehicle, and (iii) an input to at least one of propulsion, steering, or braking, to determine at least one of a braking override or a steering override, and based on the determination, to adjust at least one of a vehicle steering or a vehicle speed.

Vehicle path adjustment with control barrier function

A computer includes a processor and a memory, the memory storing instructions executable by the processor to receive sensor data indicating an obstacle, formulate a control barrier function for a vehicle based on the sensor data, determine a control input based on the control barrier function, and actuate a component of the vehicle according to the control input. The control barrier function is defined with respect to a reference point that is spaced from a centroid of the vehicle.

A system for detecting a road surface includes a processor and a memory. The memory stores instructions executable by the processor to determine a virtual boundary for a vehicle body based on a shape of the vehicle body, to identify one or more objects based on vehicle sensor data, based on the identified one or more objects, the determined virtual boundary, and an input to at least one of propulsion, steering, or braking, to determine at least one of a braking override or a steering override, and based on the determination, to perform at least one of adjusting a vehicle steering and a vehicle speed.

Vehicle path adjustment using a virtual boundary that is based on a shape of a vehicle body

A computer is programmed to identify first and second virtual boundaries of a roadway lane based on a predicted boundary between the roadway lane and an adjacent roadway lane, determine a first constraint value based on a first virtual boundary approach acceleration, determine a second constraint value based on a second virtual boundary approach acceleration, output a prescribed steering angle, brake input, and propulsion input when one of the constraint values violates a respective threshold, and actuate components to attain the prescribed steering angle, brake input, and propulsion input. The first virtual boundary approach acceleration is based on a steering wheel angle of a vehicle and input to one of a brake or a propulsion of the vehicle. The second virtual boundary approach acceleration is based on a steering wheel angle of the vehicle and input to one of a brake or a propulsion of the vehicle.

Vehicle detection and response

A computer includes a processor and a memory storing instructions executable by the processor to identify a virtual boundary between a host roadway lane of a host vehicle and a target roadway lane of a target vehicle, the virtual boundary based on a predicted path of the target vehicle, determine a first constraint value based on a boundary approach velocity of the target vehicle, determine a second constraint value based on (1) a boundary approach velocity of the host vehicle and (2) a boundary approach acceleration of the host vehicle and perform a threat assessment of a collision between the host vehicle and the target vehicle upon determining that the first constraint value violates a first threshold or the second constraint value violates a second threshold.

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 road friction is determined for a road location based on a traffic speed determined from respective speeds of each of a plurality of vehicles. A vehicle can be operated based on the determined road friction.

Vehicle road friction control

A trailer backup assist system for motor vehicles includes an auxiliary user input feature that can be used by a vehicle operator to provide a steering curvature command corresponding to a desired vehicle path curvature without requiring a user to move a steering wheel of the motor vehicle. The trailer backup assist system is configured to control a vehicle speed while the vehicle is backing up with a trailer attached thereto utilizing an input comprising at least one of a steering curvature command and an angle of a trailer relative to the vehicle. The trailer backup assist system controls at least one of a brake system, an engine torque, and a transmission gear selection to thereby control vehicle speed in a reverse direction.

Speed optimized trajectory control for motor vehicles

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 and a method are described. The method includes: receiving sensed input from a vehicle sensor suite; using the input, providing a first output; determining that a vehicle-lane confidence level is less than a threshold; and then instead, providing a second output, wherein the first and second outputs comprise lane-correction data, wherein the second output is determined using an estimation filter.

Autonomous steering control

A trailer backup assist system is provided herein. The system includes a calibration feature for calibrating an imaging device used for hitch angle detection. The system also employs multiple hitch angle detection methods, a number of which may run in parallel to increase the intervals at which a hitch angle can be measured. The system additionally includes a predictive feature in which a hitch angle can be predicted in instances where a trailer sensing device fails. The system is further configured to estimate a trailer length and generate steering commands that are invariant to the estimated trailer length under certain conditions.

Trailer backup assist system with predictive hitch angle functionality

A method for assisting in parking a vehicle, comprises the steps of: initiating a parking sequence having a reference velocity; altering a velocity of the vehicle to about the reference velocity by generating a brake torque during a first mode of operation of a controller; outputting the brake torque to a disturbance estimator; storing the brake torque within the disturbance estimator; and utilizing the brake torque from the disturbance estimator in a second mode of operation of the controller to stop the vehicle at a target location.

Vehicle parking assist system

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Ann Arbor, MI, United States of America

Michael Hafner