US 12,204,823 B1
Generating perception scenarios for an autonomous vehicle from simulation data
Steven Keith Capell, San Francisco, CA (US); Simon Box, San Francisco, CA (US); and John Michael Wyrwas, Cupertino, CA (US)
Assigned to AURORA OPERATIONS, INC., Pittsburgh, PA (US)
Filed by Aurora Innovation, Inc., Palo Alto, CA (US)
Filed on Dec. 11, 2020, as Appl. No. 17/119,240.
Claims priority of provisional application 62/988,310, filed on Mar. 11, 2020.
Int. Cl. G06F 30/17 (2020.01); G05D 1/00 (2006.01); G06F 30/20 (2020.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01)
CPC G06F 30/20 (2020.01) [G05D 1/0221 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G05D 1/0231 (2013.01); G05D 1/0242 (2013.01); G05D 1/0257 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for an autonomous vehicle, the method comprising:
receiving simulation data including the autonomous vehicle, the simulation data generated based on random sampling of snippets of logged data from a set of snippets of logged data associated with real-world driving, the random sampling of snippets of logged data based on an identifier identifying a specific characteristic in a snippet of logged data;
executing a first simulation of a planning subsystem of the autonomous vehicle based on the simulation data to generate a simulation result;
executing a second simulation of a perception subsystem of the autonomous vehicle using the simulation result as an input to generate an amended simulation result including ground truth data based on dynamic state information of one or more actors in the second simulation;
generating a perception scenario using the amended simulation result; and
validating the perception scenario by verifying whether a constraint is satisfied to produce a validated perception scenario.