Ford Global Technologies, LLC

Ford Motor Company Limited

Michigan State University

Kwaku O Prakah-Asante

Manoharprasad K Rao

Gary Steven Strumolo

Hsin-Hsiang Yang

Jianbo Lu

Fling Finn Tseng

Dimitar Petrov Filev

Yifan Chen

Basavaraj Tonshal

Finn Finn Tseng

Mark Anthony Cuddihy

Steven Joseph Szwabowski

Jian Wan

Padma Aiswarya Kolisetty

Jialiang Le

Perry Robinson Macneille

Jeffrey Allen Greenberg

Nikolay V Smirnov

Reates Curry

Saeed David Barbat

Krishnaswamy Venkatesh Prasad

Samuel Edward Ebenstein

Harald C Martinez

Xiaoming Wang

Prayat Anil Hegde

Fazal Urrahman Syed

Imad Hassan Makki

Shane Elwart

Roger Arnold Trombley

James Stewart Rankin, Ii

Doron M Elliott

Kenneth Michael Mayer

Gregory Hugh Smith

Himanshu Verma

Michael Alan Blommer

Radhakrishnan Swaminathan

Bhagyashri Satyabodha Katti

Md Abul Masrur

Tai Luu

Robert Kwiecinski

Kenneth Nero Morman, Jr

Yelena Mordechai Rodin

Swati Johar Rawat

Mike Blommer

Ali Hassani

Ryan Abraham McGee

Ilya V Kolmanovsky

Stefano Di Cairano

John Ottavio Michelini

Oleg Yurievitch Gusikhin

Thomas Edward Pilutti

William David Treharne

Mathew Alan Boesch

Tobias John Pallett

David Anthony Hatton

Johannes Geir Kristinsson

Jayanthi Rao

Mark Douglas Malone

Joseph F Stanek

John Anthony Lockwood

Lee Albert Feldkamp

Devinder Singh Kochhar

Hussein F Nasrallah

David Melcher

Ayush Shah

Mark Davison

Anil K Jain

Louis Tijerina

Sarra Awad Yako

Jeffrey Yeung

Peter John Schuster

Xiaoming Liu

Joseph Wisniewski

Nithya Somanath

Tom Nelson

Xi Yin

David M Bevly

Debayan Deb

Arun Ross

Kalyani Purushottam Sonawane

Brett Stottlemyer

Priyaranjan Prasad

Aiswarya Kolisetty

Greg Blaisdell Stevens

Curtis Sai-Hay To

Nicholas Zorka

Ziyuan Zhang

Yousef Atoum

Donnell Matthew Washington

David Starr

Jonathan Ryan

Thomas E Plutti

Charles Eagen

Sam Ebenstein

Greg Smith

Jeanette J Epps

Gary Steven Strumoto

Prayat Anil Hedge

Mike Bloomer

Luan Tran

A vehicle including a vehicle door, a detection unit and a vehicle processor is disclosed. The detection unit may be configured to detect an object presence in proximity to the vehicle and object information associated with an object. The vehicle processor may be configured to obtain the object information from the detection unit when the detection unit detects the object presence, and determine that the object may be approaching towards the vehicle door based on the object information. The vehicle processor may further output the object information to a user device responsive to determining that the object may be approaching towards the vehicle door.

Systems and methods for facilitating users to exit from a vehicle

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

A vehicle charging management method is disclosed. The method may include obtaining a first input associated with a vehicle. The first input may include a state of charge (SOC) level of a vehicle battery, a distance travelled by the vehicle since last charge, and time since the last charge. The method may further include obtaining a second input associated with historical vehicle battery charging information. Responsive to obtaining the first input and the second input, the method may include determining a vehicle user intent to charge the vehicle battery. The method may further include comparing the vehicle user intent with a threshold value, and transmitting a notification to a communication device when the vehicle user intent is greater than the threshold value.

Vehicle charge intent prediction and recommendation systems and methods

Systems and methods for virtual vehicle parking assistance are disclosed herein. An example method includes determining a current vehicle position and vehicle dimensions of a vehicle, determining parking space dimensions of a parking space, receiving a desired parking position for the vehicle through an augmented reality interface, the augmented reality interface including a three-dimensional vehicle model based on the vehicle dimensions, the augmented reality interface being configured to allow a user to virtually place the three-dimensional vehicle model in the parking space to determine the desired parking position, determining a virtual parking procedure for the vehicle based on the desired parking position selected by the user and the parking space dimensions of a parking space and causing the vehicle to autonomously park based on the virtual parking procedure.

Systems and methods for virtual vehicle parking assistance background

A roadway complexity awareness system for a vehicle, comprising a processor, an augmented reality interface disposed in communication with the processor, and a memory for storing executable instructions. The processor is programmed to execute the instructions to receive roadway status information from an infrastructure processor associated with a roadway, obtain, from a vehicle sensory system, sensory information indicative of roadway route complexity, and determine a likelihood of roadway route complexity based on the roadway status information and the sensory information. The system may select an augmented reality message indicative of the roadway route complexity, and generate the augmented reality message using an augmented reality interface device, wherein the augmented reality message is visible to a vehicle operator.

User-tailored roadway complexity awareness

A method and system for providing integrated augmented reality (AR) images and content to multiple vehicle occupants having AR devices and methods of generating user-based AR expressions including content control of user generated content.

Integrated augmented reality system for sharing of augmented reality content between vehicle occupants

A passive authentication method includes, in response to receiving a requested action from a first user, obtaining a set of sensor data and categorizing first sensor data of the set of sensor data into a first modality of a set of modalities. The method includes, for the first modality of the set of modalities, determining a distance value by applying a first modality model to the first sensor data and comparing the distance value to a first verified value of the first user for the first modality. The method includes, based on the comparison, determining a first authentication decision of the distance value. The method includes, in response to the first authentication decision indicating the first sensor data corresponds to the first user, performing the requested action.

Integrated systems and methods for passive authentication

A computer includes a processor and a memory storing instructions executable by the processor to, in response to a mobile device synchronizing with a vehicle, identify a first profile from a plurality of profiles stored in the memory as associated with the mobile device by extracting a predetermined set of information from data storing contact information for a plurality of contacts on the mobile device and determining that the predetermined set of information matches data in the first profile; determine that a person associated with the first profile is an operator of the vehicle; and then perform an operation in accordance with at least one setting stored in the first profile.

Identification of vehicle operators

A User-centric Enhanced Pathway (UEP) system may provide vehicle pathway guidance while driving using an augmented reality display system in the event of sun glare. The system uses a route observer module programmed to predict sun glare, by obtaining real-time information about the interior and exterior vehicle environment, heading, speed, and other data. The route observer module may also use an inward-facing camera to determine when the driver is squinting, which may increase the probability function that predicts when the driver is experiencing sun glare. When sun glare is predicted, the route observer sends the weighted prediction function and input signals to a decision module that uses vehicle speed, location, and user activity to determine appropriate guidance output for an enhanced pathway using an Augmented Reality (AR) module. The AR module may adjust brightness, contrast, and color of the AR information based on observed solar glare.

Enhanced augmented reality vehicle pathway

This disclosure is generally directed to systems and methods to locate a parking spot for a vehicle. In an example method, an address of a destination for a trip is provided to a processor. The processor identifies a cluster of parking spots based on determining a statistical probability that at least one parking spot in the cluster of parking spots is available at an expected time of arrival of the vehicle at the cluster of parking spots. An availability of the first parking spot is then checked by the processor at a time of arrival of the vehicle at a perimeter of the cluster of parking spots. The processor may direct the vehicle to travel from the perimeter to either the first parking spot if still available, or to a second parking spot if the first parking spot is unavailable.

Systems and methods to locate a parking spot for a vehicle

A computer includes a processor. The processor is programmed to generate, upon detecting a vehicle entry device, a first data block including a hash of identification data for the entry device. The processor is further programmed, upon detecting a trip event, to generate a second data block including a hash of trip event data and a hash linking the second data block to the first data block.

Storing vehicle data

The disclosure pertains to minimizing delay when a customer seeks a ride in a ride-hail vehicle at a crowded venue where multiple customers are attempting to obtain rides in ride-hail vehicles. In an example procedure, a ride-hail service provider responds to a ride request originated from a personal device of the customer by providing a ride-ID code or some other form of ride-confirmation data. The customer enters any ride-hail vehicle at the crowded venue without interacting with the driver of the vehicle prior to getting into the vehicle. The personal device of the customer then uses communications such as Bluetooth&#xae; to execute a triangulation procedure for determining whether the personal device is inside the vehicle. Upon confirming that the personal device is inside the vehicle, the ride-ID code is automatically transmitted to a personal device of the driver and further communications may then be carried out for authenticating the ride.

Systems and methods for obtaining a ride in a ride-hail vehicle

Gait, the walking pattern of individuals, is one of the most important biometrics modalities. Most of the existing gait recognition methods take silhouettes or articulated body models as the gait features. These methods suffer from degraded recognition performance when handling confounding variables, such as clothing, carrying and view angle. To remedy this issue, a novel AutoEncoder framework is presented to explicitly disentangle pose and appearance features from RGB imagery and a long short-term memory integration of pose features over time produces the gait feature.

Systems and methods for gait recognition via disentangled representation learning

Method and apparatus are disclosed for advanced warnings to drivers of vehicles for upcoming signs. An example vehicle includes a GPS receiver to determine a vehicle location. The example vehicle also includes a condition identifier to determine a familiarity level of a driver for the vehicle location and detect an upcoming sign. The example vehicle also includes a warning determiner to compare the familiarity level to a threshold level and provide, in response to the familiarity level being less than the threshold level, an advanced warning to the driver for the upcoming sign.

Advanced warnings for drivers of vehicles for upcoming signs

Growing community of inventors

Commerce Township, MI, United States of America

Kwaku O Prakah-Asante