Ford Global Technolgoies, LLC

Anjali Krishnamachar

Venkatapathi Raju Nallapa

Gautham Sholingar

Umair Ibrahim

Matthew A Warner

Systems and methods are provided for predicting drawbridge operation based on incoming vessel information and historical drawbridge operation data, and transmitting the drawbridge operation prediction to a GPS system such as an autonomous vehicle or a mobile device application for rerouting a planned navigation route. A transceiver may receive vessel information, e.g., incoming vessel size, type, speed, position, or quantity, or estimated incoming vessel arrival time, from one or more cameras and/or a marine radio, and may receive historical drawbridge operation data based on the incoming vessel information from an online database such that the drawbridge operation prediction is based on the historical data.

Systems and methods for predictive drawbridge operation for vehicle navigation

The present invention extends to methods, systems, and computer program products for validating gesture recognition capabilities of automated systems. Aspects include a gesture recognition training system that is scalable, efficient, repeatable, and accounts for permutations of physical characteristics, clothing, types of gestures, environment, culture, weather, road conditions, etc. The gesture recognition training system includes sensors and algorithms used to generate training data sets that facilitate more accurate recognition of and reaction to human gestures. A training data set can be scaled from both monitoring and recording gestures performed by a humanoid robot and performed by animated humans in a simulation environment. From a scaled training data set, autonomous devices can be trained to recognize and react to a diverse set of human gestures in varying conditions with substantially improved capabilities. Recognition capabilities of an autonomous device can be validated and (re)trained until recognition capabilities are determined to be sufficient.

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Mountain View, CA, United States of America

Anjali Krishnamachar