Ford Global Technolgoies, LLC

Ford Motor Company Limited

Alexandra Taylor

Ali Hassani

John Robert Van Wiemeersch

Justin Miller, Jr

Jonathan Diedrich

Nitendra Nath

Hafiz Malik

Brian Fath

Muhammad Azhar Aleem

Darren Lee

Matthew Miller

Mohammad Hassani

A method to prevent intoxicated operation is described. The method includes providing instructions to a vehicle user to position a vehicle user body portion posture in a predefined alignment. The method further includes obtaining the vehicle user body portion posture from a first vehicle detector, and determining whether the vehicle user body portion posture is in the predefined alignment. The method includes activating a plurality of vehicle visual indicators to illuminate in a predefined manner when the vehicle user body portion posture is in the predefined alignment. The method further includes providing instructions to the vehicle user to move vehicle user eyes to track the plurality of vehicle visual indicators, and obtaining a vehicle user eye movement from a second vehicle detector. The method further includes determining whether the vehicle user eye movement meets a predetermined condition, and actuating a control action accordingly.

Inebriation test system

Based on a measured intensities of first and second light sources while both the first and second light sources are actuated, and a default secondary illuminator output intensity, a computer may determine an adjusted secondary illuminator output intensity and actuate the secondary light source to output light at the adjusted secondary light source output intensity.

Synchronizing image frames by super sampling

A biometric evaluation system for a vehicle includes a vision sensor configured to detect a biometric quality of a user. The biometric evaluation system also includes an operational system for the vehicle. At least one processor is in communication with the vision sensor. The processor is configured to execute a first classification algorithm that performs a first biometric validation based on the biometric quality to estimate a state of the user. The first classification algorithm requires a first service latency. In response to an outcome of the first biometric validation, the at least one processor is further configured to execute a second classification algorithm that performs a second biometric validation to confirm the state of the user. The second classification algorithm requires a second service latency greater than the first service latency. The processor is further configured to communicate a signal to modify operation of the vehicle.

Biometric service evaluation architecture for a vehicle

A first frame of image data is captured at a first illumination intensity during a first time segment. A second frame of image data is captured at a second illumination intensity during a second time segment. The first frame and the second frame are combined and outputted as a compensated frame.

Image capture with varied illuminations

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to divide each of one or more images acquired by a camera into a plurality of zones, determine respective camera noise values for respective zones based on the one or more images, determine one or more zone expected values for the one or more images by summing camera noise values multiplied by scalar coefficients for each zone and normalizing the sum by dividing by a number of zones in the plurality of zones, and determine a source of the camera as being one of the same camera or an unknown camera based on comparing the one or more zone expected values to previously acquired expected zone values.

Camera identification

A vehicle includes an automated driving assistance system that controls maneuvering of the vehicle under certain conditions. When the vehicle comes to a stop, the driving assistance system dynamically selects a threshold stop time corresponding to a duration of time that the vehicle can remain stopped before the driving assistance system will either detect a physical action from the user to resume automated driving assistance or time out and cease the driving assistance.

Dynamic stop time threshold selection for hands-free driving

Systems, methods, and computer-readable media are disclosed for decentralized authentication for autonomous vehicles and associated transactions. Example system includes a secure distributed network of servers including a biometrics server configured to authenticate a user using biometric data and generate a biometrics server authentication token when the user is authenticated, a transactional server configured to perform the transaction for the user upon receiving the biometrics server authentication token, the transactional server being further configured to generate a transactional server authentication token when the transaction is approved, and a mobility service server configured to receive both the biometrics server authentication token and the transactional server authentication token and provide access to the mobility service.

Decentralized cloud-based authentication for vehicles and associated transactions

The present disclosure is directed toward a method and system for checking a vehicle height and radar aim of a vehicle. The method includes estimating, by a forward imaging system disposed in a vehicle, a vehicle height, and determining whether the estimated vehicle height is within a predefined height tolerance. The method further includes performing, by a radar system disposed in the vehicle, a radar alignment test to determine whether a radar device of the radar system is aligned within a predefined angular range, and adjusting the alignment of the radar device in response to the vehicle height being within the predefined height tolerance and the radar device being misaligned.

Method and system for performing a vehicle height-radar alignment check to align a radar device provided in a vehicle

A method is disclosed for providing drone oversight at a location having high potential for a collision event. The method may include recruiting one or more drones to provide oversight at a location having high potential for a collision event, and dispatching the drones to the location. One or more servers may request from the drones buffers of sensory data corresponding to the location. In response, the servers may receive from the drones the buffers of sensory data. A corresponding system and computer program product are also disclosed and claimed herein.

Drone-based event reconstruction

Methods and systems are disclosed for vehicle cruise control smoothness adaptation. An example vehicle includes a GPS receiver for receiving expected road incline data, a camera for determining a half lane width position, and a radar for determining two respective leading vehicle angles of arrival. The vehicle also includes a processor for determining an actual road incline by filtering the expected road incline, half lane width position, and leading vehicle angles of arrival. And the processor is further for modifying a cruise control system based on the actual road incline.

Growing community of inventors

Harbor Springs, MI, United States of America

Alexandra Taylor