Ford Global Technolgoies, LLC

Tory Smith

Vidya Nariyambut Murali

Alexandru Mihai Gurghian

Sarah Houts

Shane Elwart

Scott Vincent Myers

Bibhrajit Halder

Jonathan Thomas Mullen

Walter Joseph Talamonti

Zachary David Nelson

Kyu Jeong Han

According to one embodiment, a system for determining a position of a vehicle includes an image sensor, a top-down view component, a comparison component, and a location component. The image sensor obtains an image of an environment near a vehicle. The top-down view component is configured to generate a top-down view of a ground surface based on the image of the environment. The comparison component is configured to compare the top-down image with a map, the map comprising a top-down light LIDAR intensity map or a vector-based semantic map. The location component is configured to determine a location of the vehicle on the map based on the comparison.

Vehicle localization using cameras

Example user identification systems and methods are described. In one implementation, a method determines a first step pulse associated with a user carrying a key fob and detects a user device proximate the key fob. The method further identifies a second step pulse measured by the user device and determines whether the first and second step pulses match. If the step pulses match, the user carrying the key fob is identified as the owner of the user device.

User identification systems and methods

The present invention extends to methods, systems, and computer program products for identifying a person as a driver of a vehicle. Aspects include using in-vehicle sensors to increase the accuracy of driver identification initially determined using other mechanisms. As such, at least two different types of sensory devices can be utilized to gather data in an effort to identify the driver. The data gathered from the first sensor (e.g., at a key fob) is processed to identify the driver based on learned characteristic patterns, such as the driver's gait, before the driver enters the vehicle. The data gathered from the second sensor (e.g., in an in-vehicle face or voice recognition system) is processed to confirm the driver. The confirmation is based on biometric data and learned characteristic patterns. Data from the second sensor is provided back to the first sensor to confirm the driver identity.

Identifying a driver of a vehicle

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San Francisco, CA, United States of America

Tory Smith