Uatc, LLC

Uber Technologies, Inc.

Charles R Hogg, Iii

Galen Clark Haynes

Neil Traft

Skanda Shirdhar

David McAllister Bradley

Chenggang Liu

Moslem Kazemi

Jacob Panikulam

Andy Lee

Systems and methods for detecting a surprise or unexpected movement of an actor with respect to an autonomous vehicle are provided. An example computer-implemented method can include, for a first compute cycle, obtaining motion forecast data based on first sensor data collected with respect to an actor relative to an autonomous vehicle; and determining, based on the motion forecast data, failsafe region data representing an unexpected path or area where a likelihood of the actor following the unexpected path or entering the unexpected area is below a threshold. For a second compute cycle after the first compute cycle, the method can include obtaining second sensor data; determining, based on the second sensor data and the failsafe region data, that the actor has followed the unexpected path or entered the unexpected area; and in response to such determination, determining a deviation for controlling a movement of the autonomous vehicle.

Systems and methods for detecting surprise movements of an actor with respect to an autonomous vehicle

The present disclosure provides systems and methods that enable an autonomous vehicle motion planning system to learn to generate motion plans that mimic human driving behavior. In particular, the present disclosure provides a framework that enables automatic tuning of cost function gains included in one or more cost functions employed by the autonomous vehicle motion planning system.

Automatic tuning of autonomous vehicle cost functions based on human driving data

Growing community of inventors

Bellevue, PA, United States of America

Charles R Hogg, Iii