US 12,304,494 B2
Control of autonomous vehicle based on determined yaw parameter(s) of additional vehicle
Warren Smith, McKees Rocks, PA (US); Ethan Eade, Pittsburgh, PA (US); Sterling J. Anderson, Sunnyvale, CA (US); James Andrew Bagnell, Pittsburgh, PA (US); Bartholomeus C. Nabbe, Palo Alto, CA (US); and Christopher Paul Urmson, Los Altos, CA (US)
Assigned to Aurora Operations, Inc., Pittsburgh, PA (US)
Filed by Aurora Operations, Inc., Pittsburgh, PA (US)
Filed on Mar. 11, 2024, as Appl. No. 18/601,710.
Application 18/601,710 is a continuation of application No. 18/133,509, filed on Apr. 11, 2023, granted, now 11,964,663.
Application 18/133,509 is a continuation of application No. 17/135,171, filed on Dec. 28, 2020, granted, now 11,654,917, issued on May 23, 2023.
Application 17/135,171 is a continuation of application No. 16/173,660, filed on Oct. 29, 2018, granted, now 10,906,536, issued on Feb. 2, 2021.
Claims priority of provisional application 62/655,965, filed on Apr. 11, 2018.
Prior Publication US 2024/0217520 A1, Jul. 4, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. B60W 40/04 (2006.01); B60W 30/095 (2012.01); G01S 17/89 (2020.01); G01S 17/931 (2020.01); G05D 1/00 (2024.01); G05D 1/247 (2024.01); G05D 1/81 (2024.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01)
CPC B60W 40/04 (2013.01) [B60W 30/0956 (2013.01); G01S 17/89 (2013.01); G01S 17/931 (2020.01); G05D 1/0088 (2013.01); G05D 1/024 (2013.01); G05D 1/247 (2024.01); G05D 1/81 (2024.01); G06F 18/214 (2023.01); G06F 18/2178 (2023.01); G06N 20/00 (2019.01); B60W 2554/4041 (2020.02); B60W 2554/803 (2020.02)] 19 Claims
OG exemplary drawing
 
1. A computer implemented method, comprising:
receiving, from a phase coherent Light Detection and Ranging (LIDAR) component of a vehicle, a group of LIDAR data points of a sensing cycle of the phase coherent LIDAR component;
each of the LIDAR data points of the group indicating a corresponding instantaneous range and a corresponding instantaneous velocity for a corresponding point in an environment of the vehicle;
each of the LIDAR data points of the group being generated based on a corresponding sensing event of the phase coherent LIDAR component during the sensing cycle; and
processing the group of LIDAR data points with a machine learning model to generate an output that indicates that a subset of the group of LIDAR data points correspond to a dynamic object in the environment; and
controlling an autonomous vehicle based on a determined at least one instantaneous characteristic of the dynamic object.