Ford Global Technolgoies, LLC

Bhagyashri Satyabodha Katti

Fling Finn Tseng

Shiqi Qiu

Himanshu Verma

Johannes Geir Kristinsson

Nithya Somanath

Kwaku O Prakah-Asante

Joseph Wisniewski

Kalyani Purushottam Sonawane

Swati Johar Rawat

Nikhil Kailas Jamdade

Aed M Dudar

Erick Michael Lavoie

Dimitar Petrov Filev

Devesh Upadhyay

Daryl Joseph Martin

Victoria Leigh Schein

Patrick Maloney

Nicholas Alexander Scheufler

Vishal Vinayak Nageshkar

Finn Finn Tseng

Ayush Shah

Arun Dutta

Alex Perkins

Harald C Martinez

Jonathan Niemi

Samuel Laidlaw

Matthew R Goulet

Electric vehicle battery monitoring systems and methods are disclosed herein. An example method includes displaying a state of charge for a battery of an electric vehicle on a display screen of the electric vehicle, determining a frequency of how often a user views the state of charge, inferring that the user has anxiety over a range for the electric vehicle based on the frequency, and presenting the user with options to extend the state of charge.

Electric vehicle battery monitoring systems and methods

A system for accessing vehicle sensor data. The system includes receiving vehicle sensor data and a vehicle location associated with the vehicle sensor data from a publisher vehicle. A subscriber request for remote data is received from a service subscriber. The subscriber request includes a request location. A match condition is determined. The match condition includes a vehicle location match between the request location and the vehicle location. The vehicle sensor data is transmitted to the service subscriber upon the occurrence of the match condition.

Remote sensor access

Systems and methods for personalized route prediction including receiving, at a first time, first input data associated with a first route; populating a first database with the input data; receiving, at a third time, second input data associated with a second route; comparing the second input data to the first input data included within the first database; determining, based on the comparison, a first cluster including the first data and the second input data or a second cluster including the second input data; populating a second database based on the first cluster or the second cluster; determining, using the first database and at a second time, at least one of: predicted departure data, predicted destination data, and/or predicted route data; and causing, based on the predicted departure data, predicted destination data, and/or predicted route data, to perform an action in association with a vehicle.

Systems and methods for personalized route prediction

An identifier for first set of display content on a vehicle display is input to a statistical model that outputs a plurality of probabilities that a user input will select each of a plurality of second set of display contents for display after the first set of display content is displayed. A first probability is identified for a predicted set of display content that is a highest probability in the plurality of probabilities. The plurality of probabilities are provided to at least one of an optimization model and a neural network upon determining an accuracy of the statistical model is below a threshold. Upon receiving, from the at least one of the optimization model and the neural network, a second probability for the predicted set of display content, the display content is selected based on the first and second probabilities. The vehicle display is updated based on the selected set of display content.

Vehicle display

A method for controlling a vehicle includes identifying a user identity associated with a user riding in the vehicle, determining a destination associated with the user identity, creating a detection zone proximate to the vehicle when the vehicle is localized in a first drop-off location associated with the destination, causing a sensory system to identify a hazard within the detection zone and generate a localization of the hazard, determining that a first probability of realizing a risk associated with the hazard is less than a first probability threshold, and generating a vehicle door actuation that permits the user to exit the vehicle based on the first probability of realizing the risk.

Autonomous vehicle rider drop-off sensory systems and methods

A computer includes a processor and a memory storing instructions executable by the processor to receive a series of pressure maps indicating a respective series of sitting positions of an occupant in a seat, wherein the pressure maps include a current pressure map; update a profile of the occupant based on the pressure maps, wherein the profile includes a plurality of clusters of sitting positions and classifications of the clusters as preferred or nonpreferred, and updating the profile includes sorting one of the sitting positions into one of the clusters that is classified as preferred in response to the occupant remaining in that sitting position for greater than a threshold time; and adjust a physical configuration of the seat in response to the current sitting position being in one of the clusters that is classified as nonpreferred.

Seat adjustment

Parameters of clusters of a context-encoded model are updated, per frequency estimation of an aspect of calls to contacts with respect to unique combinations of contextual data of calls matching the respective clusters. The clusters are weighted according to relevance of the unique combinations of contextual data to current contextual information. First probabilities of calling individual contacts are determined according to the current contextual information and one or more inferences between calls determined from the clusters as weighted. Second probabilities of calling each of the plurality of contacts are determined according to a set of rules defining prioritizations for contacts based on external factors. Third probabilities of calling each of the plurality of contacts are determined according to calling patterns of other of the plurality of contacts. The first, second, and third sets of weights are combined to determine final predictions for predicted probabilities to call each of the contacts.

Enhanced personalized phone number recommender

A vehicle includes one or more vehicle-exterior displays and a processor. The vehicle receives indication of a second proximate vehicle, the indication including viewing preferences for an occupant of the second proximate vehicle. The vehicle selects content for display on at least one of the vehicle-exterior displays and selects at least one display having an exterior orientation determined to be viewable based on a heading of the second proximate vehicle. The vehicle then displays the selected content on the selected display.

Method and apparatus for messaging coordination

Growing community of inventors

Novi, MI, United States of America

Bhagyashri Satyabodha Katti