Method and system for operating an autonomous agent with incomplete environmental information

1. A method for operating an autonomous vehicle with an incomplete environmental understanding, the method comprising:

collecting sensor data from a set of sensors onboard the autonomous vehicle;

characterizing an environment of the autonomous vehicle based on the sensor data, wherein the characterized environment comprises a set of known objects;

identifying a set of unknown regions in the characterized environment;

locating the set of unknown regions within a labeled map, wherein the labeled map comprises a set of labeled conflict zones;

identifying a subset of unknown regions from the set of unknown regions based on an overlap between the subset of unknown regions and the set of labeled conflict zones;

placing a virtual object from a set of virtual objects into each of the subset of unknown regions in the characterized environment;

performing a simulation based on the set known objects and the set of virtual objects; and

operating the autonomous vehicle based on the simulation.

2. The method of claim 1 , wherein the set of labeled conflict zones is determined at least in part based on a behavior associated with the autonomous vehicle.

3. The method of claim 2 , wherein the behavior is a simulated behavior assigned to the autonomous vehicle in the simulation.

4. The method of claim 1 , wherein the simulation is a forward simulation, and wherein the simulation is performed in accordance with a predetermined cycle frequency.

5. The method of claim 1 , wherein operating the autonomous vehicle comprises selecting a behavior for the autonomous vehicle based on the simulation and maneuvering the autonomous vehicle according to the behavior.

6. The method of claim 1 , further comprising selecting each of the set of virtual objects, wherein selecting each of the set of virtual objects comprises referencing a predetermined lookup table.

7. The method of claim 6 , wherein the predetermined lookup table is referenced at least in part based on a size associated with each of the subset of unknown regions.

8. The method of claim 1 , further comprising assigning a set of parameters to each of the set of virtual objects, wherein the set of parameters comprises a speed.

9. The method of claim 8 , wherein the speed is determined based on information associated with the set of known objects.

10. The method of claim 9 , wherein the information comprises a set of historical speeds associated with the set of known objects.

11. The method of claim 1 , wherein determining the subset of unknown regions further comprises determining a probability associated with each of the subset of unknown regions and determining that each of the probabilities has exceeded a predetermined threshold.

12. The method of claim 11 , wherein the probability is determined at least in part based on historical information.

13. The method of claim 12 , wherein the historical information comprises at least one of: historical sensor data associated with a location corresponding to the unknown region of the subset and historical sensor data associated with a set of known objects in the characterized environment.

14. The method of claim 12 , wherein the historical information is used to determine a change in a number of known objects in the characterized environment, wherein the probability is determined based on the change.

15. The method of claim 1 , wherein the set of unknown regions is identified based at least in part on a set of height metrics associated with the characterized environment.

16. The method of claim 15 , wherein each of the set of unknown regions has a height exceeding a predetermined height threshold relative to a ground level of the characterized environment.

17. The method of claim 1 , wherein the sensor data comprises LiDAR data.

18. A method for operating an autonomous vehicle with an incomplete environmental understanding, the method comprising:

collecting sensor data from a set of sensors onboard the autonomous vehicle;

characterizing an environment of the autonomous vehicle based on the sensor data, wherein the characterized environment comprises a set of known objects;

identifying a set of unknown regions in the characterized environment;

determining a set of size parameters associated with each of the set of unknown regions;

locating the set of unknown regions within a labeled map, wherein the labeled map comprises a set of labeled conflict zones;

identifying a subset of unknown regions from the set of unknown regions based on an overlap between the subset of unknown regions and the set of labeled conflict zones;

selecting a virtual object from a set of virtual objects for each of the subset of unknown regions based on the set of size parameters;

placing the set of virtual objects into the subset of unknown regions in the characterized environment to form an updated characterized environment comprising the set of known objects and the set of virtual objects; and

operating the autonomous vehicle based on the updated characterized environment.

19. The method of claim 18 , further comprising assigning a first set of parameters to each of the set of virtual objects, wherein the first set of parameters is determined at least in part based on a second set of parameters associated with the set of known objects.

20. The method of claim 19 , wherein each of the first and second sets of parameters comprises a speed.