Ford Global Technolgoies, LLC

Ford Motor Company Limited

Yan Fu

Zhen Jiang

Ian Brewster Hall

Paul Simmons

Dominique Meroux

Weigang Chen

Yuzhou Li

Baohua Xiao

Yao Ge

Marwan El-Bkaily

Xianfeng Hu

Jian Fang

A transportation mobility system includes a data storage configured to maintain vehicle data indicating fuel consumption and count of passengers for vehicles of a transportation system, and user data describing movements of the passengers within the transportation system. The system also includes an emissions monitoring portal, programmed to provide, for vehicles of a fleet, estimates of pollutant emissions for the fleet and a percent share of miles completed by zero-emissions transportation for the fleet.

Real-time emissions estimation and monitoring

User generated content, particularly Chinese language content, is retrieved from various sources such as forums, microblogs, social media sites, and the like. A portion of the content is manually labeled with a sentiment associated with the content and may be classified according to subject matter referenced. Sentiment-indicating features of the content is extracted according to a sentiment dictionary, which may include topic-specific jargon. The features are used to train a classifier to determine sentiment of content based on sentiment-indicating features. The sentiment for other content may then be determined using the classifier. The output of the classifier may be combined with an explicit rating of a product or product feature.

Sentiment analysis of product reviews from social media

A computer system receives data sets for a driving maneuver at a location, such as data regarding a state of a vehicle, an external environment indicated by external sensors, and user feedback regarding the driving maneuver. Data sets may be collected from users having various demographic and behavioral attributes. Users may be selected using design of experiment (DOE) algorithms to cover a wide range of possible combinations. A stochastic response surface model (SRSM) is generated that relates sensor data (vehicle state and environmental) to user feedback regarding safety and comfort. The SRSM may be generated using Gaussian process regression (GPR) in order to model uncertainty. The SRSM is then used to generate a control model using an optimization under uncertainty (OUU) algorithm.

Feedback-based control model generation for an autonomous vehicle

A method of inflating an airbag with a fluid includes sending a signal to open a first valve and opening the first valve. The method also includes directing a control pressure through the first valve and toward a second valve. The method further includes throttling the second valve in response to the control pressure. The throttling of the second valve produces a variable inflation mass flow rate of the fluid at a second valve outlet. Opening the first valve and closing the first valve are performed as a step function to achieve a desired predetermined variable inflation mass flow rate of the airbag.

Variable output inflator

An airbag restraint for an automotive vehicle includes generally circular front and rear panels, and an inflator attached to the rear panel and acting through an inflator aperture formed in the rear panel. At least one internally tethered section extends laterally along a chord of the front panel at a position at or near the projected location of the inflator. The internally tethered section is defined and shaped by more than one laterally extending tether extending between the front and rear panels of the airbag.

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Bloomfield Hills, MI, United States of America

Yan Fu