US 12,189,387 B2
Object uncertainty models to assist with drivable area determinations
Rasmus Fonseca, Boulder Creek, CA (US); Marin Kobilarov, Mountain View, CA (US); Mark Jonathon McClelland, San Francisco, CA (US); and Jack Riley, San Francisco, CA (US)
Assigned to Zoox, Inc., Foster City, CA (US)
Filed by Zoox, Inc., Foster City, CA (US)
Filed on Nov. 25, 2020, as Appl. No. 17/247,047.
Prior Publication US 2022/0163966 A1, May 26, 2022
Int. Cl. G05D 1/00 (2024.01); B60W 60/00 (2020.01)
CPC G05D 1/0088 (2013.01) [G05D 1/0214 (2013.01); B60W 60/0027 (2020.02); G05D 1/0221 (2013.01)] 20 Claims
OG exemplary drawing
 
1. One or more non-transitory computer readable media storing instructions executable by one or more processors, wherein the instructions, when executed, cause the one or more processors to perform operations comprising:
generating a discretized probability distribution representative of a physical environment at a future time, the discretized probability distribution comprising a plurality of cells representative of an area in the physical environment, a first cell of the plurality of cells representing a first prediction probability that an object in the physical environment is at a first location at the future time and a second cell of the plurality of cells representing a second prediction probability that the object in the physical environment is at a second location at the future time;
receiving a reference trajectory associated with an autonomous vehicle; and
determining, based at least in part on the discretized probability distribution, a drivable area comprising a bounded area in the physical environment through which the reference trajectory passes and having an associated width and length,
wherein determining the drivable area comprises performing a ray trace to determine a nearest occupied region in the physical environment.