Ford Global Technolgoies, LLC

Arun Dutta

Nunzio Decia

David A Herman

Ali Hassani

Nithya Somanath

Justin Cartwright

Bill Dierker

John William Schmotzer

Donald Paul Bilger

Alexander Groh

Pol Llado

Colleen M Cauvet

Collin P Hurley

Mahmoud Yousef Ghannam

Adil Nizam Siddiqui

Johannes Geir Kristinsson

Nicholas Alexander Scheufler

Timothy Mark Feldkamp

Shiqi Qiu

Jake S Schwartz

Robert Schroeter

Jakob Nikolaus Hoellerbauer

David Alan Hamilton

Bhagyashri Satyabodha Katti

Mahmoud A Abou-Nasr

Ryan Lee Baker

Javier Onate

Matthew R Goulet

Dylan Verster

A brightness management system for a vehicle includes a network providing wireless communication for a vehicle environment, a mobile device in the vehicle environment and including a first light detector for detecting a first light level at a first location of the mobile device, at least one vehicle display coupled with the vehicle and having at least one brightness level, and control circuitry communicatively coupled with the mobile device and the at least one vehicle display via the network. The control circuitry is configured to detect the first location of the mobile device in the vehicle, receive an indication of the first light level from the mobile device, and communicate a signal to adjust the at least one brightness level of the at least one vehicle display based on the first location and the first light level.

Brightness management for a vehicle environment

Upon determining a mobile object is approaching an ice layer above a body of water, a thermal image of the ice layer is obtained. The thermal image and ambient temperature data are input to a neural network that outputs a plurality of regions of the ice layer and respective estimated thicknesses for the regions. A classification for each region is determined based on its estimated thickness and the mobile object. The classification is one of preferred or nonpreferred. The classifications for the regions are output.

Ice thickness estimation for mobile object operation

In order to display driving assistance images to a driver in a vehicle, visible light images are captured using a visible light camera mounted for viewing a roadway on which the vehicle travels and infrared images overlapping with the visible light images are captured using an infrared camera mounted for viewing the roadway. The visible light images are normally displayed on a display screen when a visible light brightness around the vehicle is greater than a brightness threshold. Trigger conditions are monitored which are indicative of limitations of a driver visibility when directly viewing the roadway. The trigger conditions include a driver reaction. The monitored trigger condition is classified according to a plurality of predetermined classifications which indicate an occurrence of an impairment event. The infrared images are selected for display on the display screen upon occurrence of the impairment event.

Multi-camera imaging system selecting between visible and infrared views in a vehicle

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

A vehicle is described that includes a video camera configured to record video, a processor configured to process the recorded video from the video camera into hyperlapse video, and an input/output device to link the hyperlapse video with a social network associated with at least one of a driver of the vehicle and the vehicle. The processor may be configured to receive video data from the video camera and to create the hyperlapse video by reconstructing a video stream from the video data, planning a smooth path through the video stream, and rendering the video data along the smooth path into the hyperlapse video that has a faster speed and less jitter than the video stream. The hyperlapse video may be a non-native, sped-up video of the recorded video from the video camera.

Vehicle with hyperlapse video and social networking

Method and apparatus are disclosed for control module activation of vehicles in a key-off state to determine driving routes. An example system includes a vehicle at a location in a key-off state. The vehicle includes a communication module to receive an activation signal and a telematic control unit. The telematic control unit is to activate upon receipt of the activation signal and determine and present a route from the location. The example system also includes a remote processor to determine the location, identify an event and an end time based upon the location, and send an activation signal based upon the end time.

Control module activation of vehicles in a key-off state to determine driving routes

Method and apparatus are disclosed for control module activation of vehicles in a key-off state. An example system includes a vehicle at a location in a key-off state that includes a battery, a communication module, and an infotainment unit to activate and present media responsive to the communication module receiving an activation signal. The example system also includes a remote processor to determine a charge level of the battery, identify a parking duration for the location, and send the activation signal responsive to the charge level being less than a threshold associated with the parking duration.

Control module activation of vehicles in a key-off state

Method and apparatus are disclosed for control module activation to monitor vehicles in a key-off state. An example system includes a vehicle at a location in a key-off state that includes a sensor for collecting damage detection data, a camera module including a camera for collecting damage identification data, and a communication module. The example system also includes a remote processor to receive the damage detection data from the communication module and detect damage to the vehicle based upon the damage detection data. The remote processor also is to send, responsive to detecting the damage, an activation signal to activate the camera.

Control module activation to monitor vehicles in a key-off state

Method and apparatus are disclosed for monitoring tires of vehicles via personal area networks. An example vehicle includes a body, nodes spaced apart on the body, a tire, a transceiver coupled to the tire, and a tire detector. The tire detector is to determine a tire position based on wireless communication between the transceiver and the nodes, identify a duration that the tire is at the tire position, and present a warning to rotate the tire position when the duration is greater than a predetermined threshold.

Monitoring tires of vehicles via personal area networks

A vehicle includes a steering wheel and a controller. The controller is configured to, in response to receiving location and speed data from other vehicles indicating an expected collision absent a trajectory change, automatically control the steering wheel to direct the vehicle along a collision avoidance path. The collision avoidance path is based on map data identifying a marking type for a traveling lane such that the path crosses the lane when the marking type is broken and does not cross the lane when the marking type is solid.

Dynamic lane positioning for improved biker safety

A vehicle system includes a driver identification fusion module programmed to receive a confidence level from a plurality of identification modules. Each confidence level indicates the likelihood that a driver of a vehicle is a particular person. The driver identification fusion module is programmed to aggregate the confidences levels received from the plurality of identification modules and output an aggregated confidence level signal representing an identity of the driver based at least in part on the confidence levels received from the plurality of identification modules.

Adaptive driver identification fusion

A vehicle system includes a microphone programmed to capture sounds in a passenger compartment of a vehicle and output a sound signal. A speech analyzer analyzes the sound signal for distressed speech and for action words. The speech analyzer outputs an alert signal if distressed speech and action words are detected. A processing device receives the alert signal and initiates contact with an emergency service provider in response to the alert signal.

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Ann Arbor, MI, United States of America

Arun Dutta