Ford Global Technologies, LLC

Abhishek Sharma

Yifan Chen

Mrdjan J Jankovic

Pramita Mitra

Michael Hafner

Aakar Mehra

Eric H Wingfield

Alexander Jaeckel

Mohit Srinivasan

Erol Dogan Sumer

Prashant Rao

Amanuel Zeryihun

Qianyi Wang

James Fishelson

Mario Anthony Santillo

David Melcher

Yousaf Rahman

Jash Patel

Hongtei Eric Tseng

Theodore Charles Wingrove

Jeroen Lem

Brian Boland

Douglas Blue

John Randolf Vincent

James McBride

Shan Chy Chueh

Steven Lin

Brian Nash

Doug Moore

Gwen Hickey

Dogan Sumer

David Dekime

Kenneth Harkenrider

Laura Elliott

Raina Kumar

Angela Ayers

Adam Brooks

Jenna Love

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 includes a processor and a memory storing instructions executable by the processor to receive sensor data indicating a current position of an object, determine a predicted position of the object at a future time, and instruct a component of a vehicle to actuate based on the current position being in a first zone of a plurality of zones surrounding the vehicle and the predicted position being in a second zone of the plurality of zones different than the first zone. The zones are nonoverlapping and have preset boundaries relative to the vehicle.

Vehicle object tracking

The disclosure generally pertains to systems and methods for trash collection management. In an example embodiment, a dumpster monitoring apparatus may determine that an amount of garbage in a dumpster exceeds a threshold level (such as, for example, above a full-level marked on the dumpster). If the garbage exceeds the threshold level, the dumpster monitoring apparatus automatically transmits a request to a dumpster management apparatus to dispatch a garbage truck. In an example scenario, the dumpster monitoring apparatus may further determine that a current location of the dumpster is stationed is inaccessible to the garbage truck. Consequently, the dumpster monitoring apparatus may automatically transmit a request to a robot vehicle (such as robotic forklift) to move the dumpster from the current location to a new location that is accessible to the garbage truck. The dumpster monitoring apparatus may then inform the dumpster management apparatus of the new location.

Trash collection management systems and methods

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 usage rule specifies a number of tokens to access a vehicle. Authorization of a request to access the vehicle is based on receiving the number of tokens specified by the usage rule. The request is stored to an electronic ledger. Actuation of the vehicle is based on the request being authorized. An allocation rule specifies the number of tokens allocated to each of an entity and the vehicle based on the request. Allocation of tokens to the entity and the vehicle is based on the allocation rule.

Distributed vehicle access

A blockchain block generated by one or more blockchain nodes when the one or more blockchain nodes are only connected to a local area network is received, and the blockchain block is synchronized with a blockchain. After determining that a backhaul network device is not connected to the one or more blockchain nodes and then determining that the backhaul network device is connected to the one or more blockchain nodes, the blockchain is transmitted to the one or more blockchain nodes via the backhaul network device upon determining that the backhaul network device is connected to the one or more blockchain nodes.

TAAS for delay tolerant blockchain networks

A system comprises a computer including a processor and a memory. The memory storing instructions executable by the processor to transmit an authentication request to a vehicle computer, receive, from the vehicle computer, a response including data proving that the vehicle computer includes confidential information, wherein the data does not convey the confidential information, determine whether the response is valid based on the authentication request, and transmit a warning to the vehicle computer when the response is not valid.

Validating vehicles traveling within specific regions

Systems, methods, and computer-readable media are disclosed for simulations of vehicle-based item delivery. In some examples, a method can include generating a simulation of at least a portion of an environment in which items are to be delivered by a delivery vehicle; determining delivery locations associated with at least one delivery route for the delivery vehicle in the environment within the simulation; determining delivery location groups for the delivery location based on a delivery range of drones associated with the delivery vehicles; and determining waypoints for the delivery vehicle on the delivery route based on a minimum travel time associated with at least one drone of the drones.

System and methods for simulations of vehicle-based item delivery

A system includes a computer programmed to identify a plurality of audio amplitudes of an audio input. The computer is programmed to identify a plurality of time intervals of the audio input between respective identified audio amplitudes. The computer is programmed to map a haptic pattern based on identified audio amplitudes and the time intervals. The computer is programmed to actuate a motor to output the haptic pattern.

Haptic device operation

This disclosure is generally directed to systems and methods for operating a monitoring system incorporating a digital twin. In one exemplary method of operating the digital twin, one or more images captured by an imaging apparatus may be used to define a first portion of a surveilled area as a zone of primary interest and a second portion of the surveilled area as a zone of secondary interest. The digital twin may be utilized to primarily focus on the zone of primary interest such as for determining a pattern of movement of one or more objects in the zone of primary interest. One or both of the zone of primary interest and the zone of secondary interest may be dynamically redefined upon receiving additional images that indicate a modification in the pattern of movement of one or more objects in the surveilled area.

Growing community of inventors

Ann Arbor, MI, United States of America

Abhishek Sharma