IP Library Granted Patent US 11,307,585
Granted Patent B2
US 11,307,585 · App. 16/668,584 · Granted Apr 19, 2022

Introspective competence modeling for AV decision making

Inventors: Connor Basich (Northampton, MA); Kyle Hollins Wray (Fremont, CA); Stefan Witwicki (San Carlos, CA); Shlomo Zilberstein (Amherst, MA)
Assignees: Nissan North America, Inc.; The University of Massachusetts; Renault S.A.S.
G05D1/0088G05D1/0061G05D2201/0213
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Quick Facts
Patent No.
US 11,307,585
App. No.
16/668,584
Granted
Apr 19, 2022
Kind
B2
Abstract

A first method includes detecting, based on sensor data, an environment state; selecting an action based on the environment state; determining an autonomy level associated with the environment state and the action; and performing the action according to the autonomy level. The autonomy level can be selected based at least on an autonomy model and a feedback model. A second method includes calculating, by solving an extended Stochastic Shortest Path (SSP) problem, a policy for solving a task. The policy can map environment states and autonomy levels to actions and autonomy levels. Calculating the policy can include generating plans that operate across multiple levels of autonomy.

Claims (73)

1. A method of autonomous driving by an autonomous vehicle (AV), comprising:

detecting, based on sensor data, an environment state;

selecting an action based on the environment state;

determining an autonomy level associated with the environment state and the action,

wherein the autonomy level indicates an extent to which the action is to be performed autonomously by the AV,

wherein the AV determines respective autonomy levels for actions to be performed,

wherein the autonomy level is selected based at least on an autonomy model and a feedback model, and

wherein the feedback model models feedback types received from a human with respect to the action, how costly each type of feedback is, and how likely is each type of feedback to be received from the human; and

performing the action according to the autonomy level, wherein performing the action according to the autonomy level comprises:

in response to determining that the autonomy level indicates “verified autonomy” and to determining that the AV is being monitored:

performing the action; and

in response to receiving an override signal while the action is being performed, stopping the action and switching to a manual operation mode of the AV.

2. The method of claim 1 , wherein the autonomy level is selected from a set comprising a first autonomy level indicating “no autonomy”, a second autonomy level indicating “verified autonomy”, a third autonomy level indicating “supervised autonomy”, and a fourth autonomy level indicating “unsupervised autonomy”.

3. The method of claim 2 ,

wherein the autonomy level is the second autonomy level indicating “verified autonomy”, and wherein performing the action according to the autonomy level comprises:

receiving, for the action, an approval feedback signal or a disapproval feedback signal.

4. The method of claim 3 , wherein performing the action according to the autonomy level comprises:

querying for the approval feedback signal prior to receiving the approval feedback signal.

5. The method of claim 3 ,

wherein the autonomy level is the third autonomy level indicating “supervised autonomy”, and

wherein performing the action according to the autonomy level comprises:

determining that the AV is being monitored by a human before performing the action.

6. The method of claim 3 , further comprising:

receiving the approval feedback signal.

7. The method of claim 1 , wherein performing the action according to the autonomy level comprises:

determining, based on the autonomy level, whether to request approval from a human for the action before performing the action.

8. The method of claim 1 ,

wherein the autonomy level is an “no autonomy” such that the AV is not allowed to perform autonomous actions, and

wherein performing the action according to the autonomy level comprises:

enabling the AV to be manually controlled by a human.

9. The method of claim 1 ,

wherein the autonomy model comprises a utility model and an autonomy profile,

wherein utility model describes a utility of performing a first action in a first autonomy level with respect to a first environment state given that the AV just operated in second autonomy level, and

wherein the autonomy profile maps respective environment states to respective actions and prescribing constraints on allowed levels of autonomy for particular environment states.

10. The method of claim 1 , further comprising:

updating at least one of an autonomy profile, a feedback profile, or a human transition function in response to the performing the action.

11. An autonomous vehicle (AV), comprising:

a processor configured to execute instructions to:

detect, based on sensor data, an environment state;

select an action based on the environment state;

determine an autonomy level associated with the environment state and the action,

wherein the autonomy level indicates an extent to which the action is to be performed autonomously,

wherein the AV determines respective autonomy levels for actions to be performed,

wherein the autonomy level is selected based at least on an autonomy model and a feedback model, and

wherein the feedback model models feedback types received from a human with respect to the action, how costly each type of feedback is, and how likely is each type of feedback to be received from the human; and

cause the action to be performed according to the autonomy level, wherein to cause the action to be performed according to the autonomy level comprises to:

in response to determining that the autonomy level indicates “verified autonomy” and to determining that the AV is being monitored,

cause the action to be performed; and

in response to receiving an override signal while the action is being performed, cause the action to stop and cause a switch to a manual operation mode of the AV.

12. The AV of claim 11 , wherein the autonomy level is selected from a set comprising a first autonomy level indicating “no autonomy”, a second autonomy level indicating “verified autonomy”, a third autonomy level indicating “supervised autonomy”, and a fourth autonomy level indicating “unsupervised autonomy”.

13. The AV of claim 12 ,

wherein the autonomy level is the second autonomy level indicating “verified autonomy”, and wherein to perform the action according to the autonomy level comprises to:

receive, for the action, an approval feedback signal or a disapproval feedback signal.

14. The AV of claim 13 , wherein to perform the action according to the autonomy level comprises to:

query for the approval feedback signal prior to receiving the approval feedback signal.

15. The AV of claim 13 ,

wherein the autonomy level is the third autonomy level indicating “supervised autonomy”, and

wherein to performing the action according to the autonomy level comprises to:

determine that the AV is being monitored by a human before performing the action.

16. The AV of claim 13 , wherein the processor is further configured to execute instructions to:

receive the approval feedback signal.

17. The AV of claim 11 , wherein to perform the action according to the autonomy level comprises to:

determine, based on the autonomy level, whether to request approval from a human for the action before performing the action.

18. The AV of claim 11 ,

wherein the autonomy level is an “no autonomy” such that the AV is not allowed to perform autonomous actions, and

wherein to perform the action according to the autonomy level comprises to:

enable the AV to be manually controlled by a human.

19. The AV of claim 11 ,

wherein the autonomy model comprises a utility model and an autonomy profile,

wherein utility model describes a utility of performing a first action in a first autonomy level with respect to a first environment state given that the AV just operated in second autonomy level, and

wherein the autonomy profile maps respective environment states to respective actions and prescribing constraints on allowed levels of autonomy for particular environment states.

20. The AV of claim 11 , wherein the processor is further configured to execute instructions to:

update at least one of an autonomy profile, a feedback profile, or a human transition function in response to performing the action.

Assignments (5)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 28, 2022
From: NISSAN NORTH AMERICA, INC.
To: NISSAN MOTOR CO., LTD.
Reel/Frame 060656/0554 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 18, 2020
From: NISSAN NORTH AMERICA, INC.
To: NISSAN NORTH AMERICA, INC.; RENAULT S.A.S.
Reel/Frame 051844/0750 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 11, 2019
From: WRAY, KYLE HOLLINS
To: NISSAN NORTH AMERICA, INC.; THE UNIVERSITY OF MASSACHUSETTS
Reel/Frame 050966/0854 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 11, 2019
From: WITWICKI, STEFAN
To: NISSAN NORTH AMERICA, INC.
Reel/Frame 050966/0911 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 11, 2019
From: BASICH, CONNOR; ZILBERSTEIN, SHLOMO
To: THE UNIVERSITY OF MASSACHUSETTS
Reel/Frame 050966/0975 →
Continuity (1)
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Cited By (1)
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