In-vehicle operation of simulation scenarios during autonomous vehicle runs

1. A method for operating an autonomous vehicle, comprising:

performing the following operations by a muxing tool when the autonomous vehicle is deployed within a particular geographic area in a real-world environment:

receiving perception data that is representative of at least one actual object which is perceived while the autonomous vehicle is deployed within the particular geographic area in a real-world environment;

receiving simulation data that represents a simulated object that could be perceived by the autonomous vehicle in the real-world environment and that was generated using a simulation scenario which is selected from a plurality of simulation scenarios based on at least one of the particular geographic area in which the autonomous vehicle is currently located and a current operational state of the autonomous vehicle;

generating augmented perception data by combining the simulation data with the perception data;

detecting whether the combination of the simulation data with the perception data caused the at least one simulated object to have an unnatural physical shape; and

modifying the augmented perception data based on the detecting.

2. The method according to claim 1 , further comprising causing the augmented perception data to be used to control operations of the autonomous vehicle.

3. The method according to claim 1 , further comprising transitioning an operating state of the muxing tool from a disabled state to an enabled state when the autonomous vehicle reaches the particular geographic area during a run.

4. The method according to claim 1 , further comprising:

detecting when the autonomous vehicle is within the particular geographic area in the real-world environment; and

causing initiation of a simulation operation responsive to said detecting.

5. The method according to claim 1 , wherein a state of the simulation operation is reset when the autonomous vehicle travels out of the particular geographic area.

6. The method according to claim 1 , further comprising:

detecting a conflict between the perception data and the simulated data; and

modifying or discarding at least a portion of the simulated data which conflicts with the perception data.

7. The method according to claim 6 , wherein the detecting is based on a location of the simulated object in a simulated environment and a location of the at least one actual object in the real-world environment.

8. The method according to claim 6 , wherein the detecting is based on a similarity between a classification associated with the simulated object and a classification associated with the at least one actual object.

9. A method for operating an autonomous vehicle, comprising:

performing the following operations by a muxing tool when the autonomous vehicle is deployed within a particular geographic area in a real-world environment:

receiving perception data that is representative of at least one actual object which is perceived while the autonomous vehicle is deployed within the particular geographic area in a real-world environment;

receiving simulation data that represents a simulated object that could be perceived by the autonomous vehicle in the real-world environment and that was generated using a simulation scenario which is selected from a plurality of simulation scenarios based on at least one of the particular geographic area in which the autonomous vehicle is currently located and a current operational state of the autonomous vehicle;

generating augmented perception data by combining the simulation data with the perception data;

detecting a conflict between the perception data and the simulated data; and

modifying or discarding at least a portion of the simulated data which conflicts with the perception data;

wherein the detecting is based on a difference between a total number of simulated objects of a particular type and a total number of actual objects of the particular type.

10. The method according to claim 1 , wherein the generating augmented perception data is triggered when the autonomous vehicle reaches a pre-defined location in the particular geographic area or the autonomous vehicle receives a wireless communication from an external transmitter.

11. An autonomous vehicle, comprising:

a muxing tool configured to perform the following operations when the autonomous vehicle is deployed within a particular geographic area in a real-world environment:

receiving perception data that is representative of at least one actual object which is perceived while the autonomous vehicle is deployed within the particular geographic area in a real-world environment;

receiving simulation data that represents a simulated object that could be perceived by the autonomous vehicle in the real-world environment and that was generated using a simulation scenario which is selected from a plurality of simulation scenarios based on at least one of the particular geographic area in which the autonomous vehicle is currently located and a current operational state of the autonomous vehicle;

generating augmented perception data by combining the simulation data with the perception data;

detecting whether the combination of the simulation data with the perception data caused the at least one simulated object to have an unnatural physical shape; and

modifying the augmented perception data based on the detecting.

12. The autonomous vehicle according to claim 11 , wherein the muxing tool is further configured to cause the augmented perception data to be used to control operations of the autonomous vehicle.

13. The autonomous vehicle according to claim 11 , wherein an operating state of the muxing tool is transitioned from a disabled state to an enabled state when the autonomous vehicle reaches the particular geographic area during a run.

14. The autonomous vehicle according to claim 11 , further comprising a processor configured to:

detect when the autonomous vehicle is within the particular geographic area in the real-world environment; and

cause initiation of a simulation operation responsive to said detecting.

15. The autonomous vehicle according to claim 11 , wherein a state of the simulation operation is reset when the autonomous vehicle travels out of the particular geographic area.

16. The autonomous vehicle according to claim 11 , wherein the muxing tool is further configured to:

detect a conflict between the perception data and the simulated data; and

modify or discard at least a portion of the simulated data which conflicts with the perception data.

17. The autonomous vehicle according to claim 16 , wherein the conflict is detected based on a location of the simulated object in a simulated environment and a location of the at least one actual object in the real-world environment, a similarity between a classification associated with the simulated object and a classification associated with the at least one actual object, or a difference between a total number of simulated objects of a particular type and a total number of actual objects of the particular type.

18. A non-transitory computer-readable medium that stores instructions that is configured to, when executed by at least one computing device, cause the at least one computing device to perform the following operations when an autonomous vehicle is deployed within a particular geographic area in a real-world environment:

receiving perception data that is representative of at least one actual object which is perceived while the autonomous vehicle is deployed within the particular geographic area in a real-world environment;

receiving simulation data that represents a simulated object that could be perceived by the autonomous vehicle in the real-world environment and that was generated using a simulation scenario which is selected from a plurality of simulation scenarios based on at least one of the particular geographic area in which the autonomous vehicle is currently located and a current operational state of the autonomous vehicle;

generating augmented perception data by combining the simulation data with the perception data;

detecting whether the combination of the simulation data with the perception data caused the at least one simulated object to have an unnatural physical shape; and

modifying the augmented perception data based on the detecting.