Ford Global Technolgoies, LLC

Honeywell International Inc.

Jonathan Thomas Mullen

Shane Elwart

Anthony Mario D'Amato

Brett Stephens

Dimitar Petrov Filev

John Ottavio Michelini

Victoria Leigh Schein

Scott Vincent Myers

Steven Joseph Szwabowski

Jaroslav Pekar

Bibhrajit Halder

Walter Joseph Talamonti

Zachary David Nelson

Ondrej Santin

Tory Smith

Markian Oleh Diakiw

Kyu Jeong Han

A method for routing a vehicle includes determining, based on roadway section information for two or more potential driving routes for a vehicle, a first route along which a driver assistance feature or an automated driving feature will not be available and a second route along which the driver assistance feature or the automated driving feature will be available. The method further includes providing navigation instructions for the second route to a driver or control system.

Route generation using road lane line quality

Example user identification systems and methods are described. In one implementation, a method determines a first step pulse associated with a user carrying a key fob and detects a user device proximate the key fob. The method further identifies a second step pulse measured by the user device and determines whether the first and second step pulses match. If the step pulses match, the user carrying the key fob is identified as the owner of the user device.

User identification systems and methods

Methods, devices and apparatuses pertaining to routing with U-turn inhibition. A method may include receiving, by a computing device, geographic information of a destination and geographic information of a current location of a vehicle and evaluating feasibility of a U-turn along a path between the current location and the destination using the geographic information. The computing device may further calculate a U-turn cost parameter associated with the U-turn representative of the feasibility, and determine a feasible route between the current location and the destination based on the U-turn cost parameter using a routing algorithm.

Routing with U-turn inhibition

Methods, devices and apparatuses pertaining to U-turn assistance. The method may include detecting an intention of an operator of a vehicle of rendering a U-turn at a location. A computing device may obtain geographic information associated with the U-turn, and assess feasibility of the U-turn at the location based on the geographic information. Further, the computing device may provide a notification to the operator based on the feasibility of the U-turn to assist the operator to operate the U-turn of the vehicle at the location.

Assessing U-turn feasibility

Methods, devices and apparatuses pertaining to U-turn assistance. The method may include obtaining, by a computing device, geographic obtaining of a location designated for an operation of a U-turn. The computing device may further obtain vehicle information of a vehicle performing the U-turn, and collect user information of an operator of the vehicle. Based on the geographic information, the vehicle information and the user information, the computing device may determine a level of difficulty of the U-turn and assist the operator with the operation of the U-turn based on the level of difficulty.

U-turn assistance based on difficulty in maneuvering

Systems, methods, and devices for network-based storage of vehicle and infrastructure data for vehicle optimization are disclosed. A method includes receiving sensor data from a vehicle sensor, uploading the sensor data to a network, and storing the sensor data in a vehicle map database. The method includes downloading aggregated drive data from the network and storing the aggregated drive data in the vehicle map database. The method includes optimizing a vehicle route based on route costs for a plurality of potential driving routes based on a reliability of an automated driving feature or driver assistance feature.

Network based storage of vehicle and infrastructure data for optimizing vehicle routing

A method for post-processing to synchronize audio data with vehicle data includes generating an artificial sound data based on time-series vehicle data. The method includes determining an offset that maximizes cross-correlation between the artificial sound data and recorded audio data. The method also includes shifting one or more of the time-series data and the recorded audio data relative to each other in time based on the offset. The shift may be used to generate or render a synchronized set of time-series data and recorded audio data.

Systems, methods, and devices for synchronization of vehicle data with recorded audio

Systems, methods, and devices for estimating a speed limit are disclosed herein. A system for estimating a speed limit includes one or more perception sensors, an arbitrated speed component, an attribute component, an estimator component, and a notification component. The one or more perception sensors are configured to generate perception data about a region near a vehicle. The arbitrated speed component is configured to determine that a high confidence or arbitrated speed limit is not available. The attribute component is configured to detect one or more environmental attributes based on the perception data. The estimator component is configured to determine an estimated speed limit based on the environmental attributes. The notification component is configured to provide the estimated speed limit to an automated driving system or driver assistance system of the vehicle.

Perception-based speed limit estimation and learning

A vehicle implements a method of selecting gear ratios that utilizes two shift schedules, one for flat terrain and one for hilly terrain. Initially, the vehicle switches between the shift schedules based on estimation of the road gradient of a recently traversed route. When the vehicle switched between the shift schedules, the vehicle stores location information associated with the switch. When stored information about previous shift schedule switches is available, the information is utilized, in combination with navigation system data, to switch shift schedules at more appropriate times.

Terrain adaptive shift scheduling

Methods and systems are presented for improving performance of a vehicle operating in a cruise control mode where a controller adjusts torque output from a vehicle to maintain vehicle speed within a desired range while preventing the unnecessary downshifts. The methods and systems include adapting a vehicle dynamics model and a vehicle fuel consumption model that provide input to nonlinear model predictive controller.

Method and system for controlling shifting of a vehicle in cruise control

Systems and methods for communicating data to a control system of a vehicle are described. A system may include a server, which generates a set of coefficients using an approximation function and based on path-preview data indexed to future values of a road attribute with respect to a road traveled by the vehicle. The system may also include a client, which utilizes an evaluation of the approximation function to direct the control system of the vehicle.

Compression algorithms for vehicle-bus-messaging of preview data

Method and system are provided for vehicle route planning based on adaptive model predictive control. In one example, a method may include real-time online identification of the vehicle model base on the vehicle inputs and outputs; compression of the input space to increase the optimization efficiency; and optimization of the route planning based on the model parameter of the vehicle and the known road grade.

Adaptive model predictive control for vehicle route planning

A method for routing a vehicle includes determining, based on aggregated drive data from a plurality of sources, route costs for a plurality of potential driving routes for a vehicle based on reliability of an automated driving feature or driver assistance feature. The method includes selecting a route of the one or more potential driving routes based on the route costs. The method includes providing information about the route to a driver, automated driving system, or driver assistance system.

Growing community of inventors

Palo Alto, CA, United States of America

Jonathan Thomas Mullen