Ford Global Technolgoies, LLC

Ford Motor Company Limited

Zhen Jiang

Dominique Meroux

Yan Fu

Chen Zhang

Yuzhou Li

Yao Ge

Rebecca Kreucher

Jian Fang

Cassandra Telenko

Xianfeng Hu

This disclosure describes an environmentally sustainable peer-to-peer electricity source network. An example method may include receiving, by a processor, a request to perform a charging of a first device. An example method may include determining, by the processor and using a peer-to-peer network including one or more charging sources, a first charging source to provide charge to the first device, wherein determining the first charging source is based on an amount of emissions that would result from charging using the first charging source. An example method may include determining, by the processor, a first time and a first location at which to perform charging of the first device using the first charging source. An example method may include determining, by the processor, that the charging of the first device has been performed.

Environmentally sustainable peer-to-peer electricity source network

Systems, methods, and computer-readable media are disclosed describing ridesharing using blockchain. Example methods may include determining a state associated with a user of a ridesharing vehicle from at least one first device associated with the ridesharing vehicle; identifying a confirmation of the state by one or more second devices; and adding a transaction to a blockchain, the transaction comprising a description of the state, the confirmation, and a link to a trip footage of the state.

Systems and method for ridesharing using blockchain

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

Methods and systems for operating a vehicle that includes an internal combustion engine and a gaseous fuel storage tank are presented. In one example, the gaseous fuel storage tank is cooled so that an amount of gaseous fuel that may be stored in the gaseous fuel tank may be increased to extend a vehicle's driving range.

Method and system for operating a gaseous fuel vehicle

A vehicle includes a controller programmed to activate a fuel savings feature upon satisfaction of transition conditions and inhibit the transition according to satisfaction of inhibit conditions. The controller is further programmed to accumulate data indicative of the inhibit conditions and a time associated with the conditions being satisfied over a drive cycle.

System and method for automated vehicle performance analytics

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.

Growing community of inventors

Mountain View, CA, United States of America

Zhen Jiang