US 11,754,408 B2
Methods and systems for topological planning in autonomous driving
Neal Seegmiller, Pittsburgh, PA (US); Christopher Cunningham, Pittsburgh, PA (US); Ramadev Burigsay Hukkeri, Pittsburgh, PA (US); Thomas Petroff, Gibsonia, PA (US); and Albert Costa, Pittsburgh, PA (US)
Assigned to Argo AI, LLC, Pittsburgh, PA (US)
Filed by Argo AI, LLC, Pittsburgh, PA (US)
Filed on Oct. 9, 2019, as Appl. No. 16/597,283.
Prior Publication US 2021/0108936 A1, Apr. 15, 2021
Int. Cl. G01C 21/26 (2006.01); B60W 30/18 (2012.01); G01C 21/34 (2006.01); G05D 1/00 (2006.01); G05D 1/02 (2020.01)
CPC G01C 21/3461 (2013.01) [B60W 30/18163 (2013.01); G05D 1/0088 (2013.01); G05D 1/0212 (2013.01); B60W 2554/00 (2020.02); B60W 2555/60 (2020.02); G05D 2201/0213 (2013.01)] 20 Claims
OG exemplary drawing
 
3. A system comprising:
an autonomous vehicle comprising one or more sensors;
a processor; and
a non-transitory computer readable medium comprising one or more programming instructions that when executed by the processor, will cause the processor to:
determine, for the autonomous vehicle while traversing a route to a destination location, a local region that surrounds the autonomous vehicle;
receive real-time information corresponding to the local region;
perform topological planning to identify one or more topologically distinct classes of trajectories, wherein each of the one or more topologically distinct classes is associated with a plurality of trajectories that take the same combination of discrete actions with respect to objects in the local region;
compute a constraint set for each of the one or more topologically distinct classes of trajectories, the constraint set for a topologically distinct class defining a bounded area in curvilinear space that confines the plurality of trajectories associated with that topologically distinct class;
for each constraint set, generate a candidate trajectory; and
select, from amongst one or more candidate trajectories, a trajectory for the autonomous vehicle to traverse the local region
assigning a score to each of the one or more candidate trajectories, and
selecting a candidate trajectory that has a best score as the trajectory for the autonomous vehicle to traverse the local region.