Waymo LLC

Chung Eun Kim

Jonathan Lee Pedersen

Kevin Joseph Malta

Yu Zheng

Eamonn Michael Doherty

Brian Clair Williammee

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a pull-over location using machine learning. One of the methods includes obtaining data specifying a target pull-over location for an autonomous vehicle travelling on a roadway. A plurality of candidate pull-over locations in a vicinity of the target pull-over location are identified. For each candidate pull-over location, an input that includes features of the candidate pull-over location is processed using a machine learning model to generate a respective likelihood score representing a predicted likelihood that the candidate pull-over location is an optimal location. The features of the candidate pull-over location include one or more features that compare the candidate pull-over location to the target pull-over location. Using the respective likelihood scores, one of the candidate pull-over locations is selected as an actual pull-over location for the autonomous vehicle.

Pull-over location selection using machine learning

A flotation system, including a plurality of flotation shoes to float on a body of water, the plurality of flotation shoes including a first shoe to receive a first foot of a user therein, a second shoe to receive a second foot of a user therein, and a plurality of connecting members removably connected to at least one of the first shoe and the second shoe to bind the first shoe to the second shoe, and a support device to facilitate at least one of walking on a ground surface and movement on the body of water.

Growing community of inventors

San Mateo, CA, United States of America

Chung Eun Kim