IP Library Granted Patent US 11,700,356
Granted Patent B2
US 11,700,356 · App. 16/544,942 · Granted Jul 11, 2023

Control transfer of a vehicle

Inventors: Igal Raichelgauz (Tel Aviv, IL); Karina Odinaev (Tel Aviv, IL)
Assignee: AUTOBRAINS TECHNOLOGIES LTD.
H04N7/183G05D1/0061G05D1/0088G05D1/0094G05D1/0238G05D1/0253G05D1/0276G05D1/0287G06F18/211G06F18/214G06F18/23G06F18/25G06F18/28G06N3/04G06N3/08G06T7/246G06T7/74G06V10/255G06V10/762G06V10/764G06V10/82G06V20/56G06V20/58G06V40/103G08G1/166H04N7/185H04W4/46H04W4/48G06T2207/20076G06T2207/20081G06T2207/30261G06V2201/08G08G1/162G08G1/165H04L67/12
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Quick Facts
Patent No.
US 11,700,356
App. No.
16/544,942
Granted
Jul 11, 2023
Kind
B2
Abstract

A method for finding at least one trigger for human intervention in a control of a vehicle, the method may include receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired during situations that are suspected as situations that require human intervention in the control of at least one of the plurality of vehicles; determining, based at least on the visual information, the at least one trigger for human intervention; and transmitting to one or more of the plurality of vehicles, the at least one trigger.

Claims (37)

1. A method for finding at least one trigger for human intervention in a control of a vehicle, the method comprises:

receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired by the plurality of vehicles and during situations that are suspected as situations that require human intervention in the control of at least one vehicle of the plurality of vehicles; wherein a human intervention in a control of a certain vehicle of the at least one vehicle comprises handling over a control of the certain vehicle from an autonomous driving manager of the certain vehicle to a human driver of the certain vehicle;

determining, based at least on the visual information, the at least one trigger for human intervention; wherein the determining comprises detecting situations that are the situations that are suspected as the situations that require human intervention; wherein the detecting is based on behavioral information that represents behaviors of the plurality of vehicles during the situation that are suspected as the situations that require human intervention; wherein the behavioral information comprises a damping of a shock by a shock absorber of a vehicle of the plurality of vehicles; and

transmitting to one or more of the plurality of vehicles, the at least one trigger.

2. The method according to claim 1 wherein the determining is executed in an unsupervised manner.

3. The method according to claim 1 wherein the determining is responsive to at least one human intervention policy of the at least one vehicle.

4. The method according to claim 1 wherein the determining of the at least one trigger for human intervention comprises determining a complexity of the situation.

5. The method according to claim 1 wherein the determining of the at least one trigger for human intervention comprises determining a danger level associated with the situation, a location associated with the situation, and a time of occurrence of the situation.

6. The method according to claim 1 wherein the determining is responsive to statistics of maneuvers executed by different vehicles during a same situation that is suspected as a situation that requires human intervention in the control of at least one of the plurality of vehicles.

7. The method according to claim 1 comprising generating or receiving movement information of entities included in the visual information; and wherein the determining of the at least one trigger is also responsive to the movement information.

8. The method according to claim 7 wherein the movement information represents entity movement functions of the entities; and wherein the method comprises estimating, based on the entity movement functions, a future movement of the entities.

9. The method according to claim 1 , wherein the determining of the at least one trigger for human intervention comprises determining whether the situation is too dangerous for being managed by an autonomous driving manager of a vehicle.

10. The method according to claim 1 comprising detecting situations that are the situations that are suspected as the situations that require human intervention by applying an unsupervised machine learning process.

11. The method according to claim 1 wherein a detecting of a situation that is suspected as a situation that requires human intervention is executed by a vehicle of the plurality of vehicles that faces the situation.

12. The method according to claim 1 wherein the determining of the at least one trigger for human intervention comprises determining whether the situation is too complex for being managed by an autonomous driving manager of a vehicle.

13. The method according to claim 1 wherein the determining of the at least one trigger for human intervention comprises determining a complexity of the situation based on a complexity of maneuvers required to overcome the situation.

14. The method according to claim 1 wherein the determining is responsive to at least one human intervention policy of the at least one vehicle; wherein the at least one human intervention policy defines certain situations that require human intervention, wherein at least one of the certain situations is defined by a combination of a specific location and time.

15. A non-transitory computer readable medium that stores instructions for:

receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired by the plurality of vehicles and during situations that are suspected as situations that require human intervention in a control of at least one vehicle of the plurality of vehicles; wherein a human intervention in a control of a certain vehicle of the at least one vehicle comprises handling over a control of the certain vehicle from an autonomous driving manager of the certain vehicle to a human driver of the certain vehicle;

determining, based at least on the visual information, the at least one trigger for human intervention; wherein the determining comprises detecting situations that are the situations that are suspected as the situations that require human intervention; wherein the detecting is based on behavioral information that represents behaviors of the plurality of vehicles during the situation that are suspected as the situations that require human intervention; wherein the behavioral information comprises a damping of a shock by a shock absorber of a vehicle of the plurality of vehicles; and

transmitting to one or more of the plurality of vehicles, the at least one trigger.

16. The non-transitory computer readable medium according to claim 15 wherein the determining is executed in an unsupervised manner.

17. The non-transitory computer readable medium according to claim 15 wherein the determining is responsive to at least one human intervention policy of the at least one vehicle.

18. The non-transitory computer readable medium according to claim 15 wherein the determining of the at least one trigger for human intervention comprises determining a complexity of the situation.

19. The non-transitory computer readable medium according to claim 15 wherein the determining of the at least one trigger for human intervention comprises determining a danger level associated with the situation.

20. The non-transitory computer readable medium according to claim 15 wherein the determining is responsive to statistics of maneuvers executed by different vehicles during a same situation that is suspected as a situation that requires human intervention in the control of at least one of the plurality of vehicles.

21. The non-transitory computer readable medium according to claim 15 that stores instructions for generating or receiving movement information of entities included in the visual information; and wherein the determining of the at least one trigger is also responsive to the movement information.

22. The non-transitory computer readable medium according to claim 21 wherein the movement information represents entity movement functions of the entities; wherein the non-transitory computer readable medium stores instructions for estimating, based on the entity movement functions, a future movement of the entities.

23. The non-transitory computer readable medium according to claim 22 wherein the determining of the at least one trigger for human intervention comprises determining whether the situation is too dangerous for being managed by an autonomous driving manager of a vehicle.

24. A computerized system that comprises a processor and multiple units that are configured to:

receive, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired during situations that are suspected as situations that require human intervention in a control of at least one of the plurality of vehicles;

perform a determining, based at least on the visual information, the at least one trigger for human intervention; wherein the determining comprises detecting situations that are the situations that are suspected as the situations that require human intervention; wherein the detecting is based on behavioral information that represents behaviors of the plurality of vehicles during the situation that are suspected as the situations that require human intervention; wherein the behavioral information comprises a damping of a shock by a shock absorber of a vehicle of the plurality of vehicles; and

transmit to one or more of the plurality of vehicles, the at least one trigger.

25. A method for finding at least one trigger for human intervention in a control of a vehicle, the method comprises:

receiving, from a plurality of vehicles, and by an I/O module of a computerized system, visual information acquired by the plurality of vehicles and during situations that are suspected as situations that require human intervention in a control of at least one vehicle of the plurality of vehicles; wherein a human intervention in a control of a certain vehicle of the at least one vehicle comprises handling over a control of the certain vehicle from an autonomous driving manager of the certain vehicle to a human driver of the certain vehicle;

determining, by the computerized system, and based at least on the visual information, the at least one trigger for human intervention; wherein the determining comprises detecting situations that are the situations that are suspected as the situations that require human intervention; wherein the detecting is based on behavioral information that represents behaviors of the plurality of vehicles during the situation that are suspected as the situations that require human intervention; wherein a detecting of a situation that is suspected as a situation that requires human intervention is (a) executed by a vehicle of the plurality of vehicles that faces the situation, and (b) is followed by sending to the computerized system and by the vehicle, visual information from the situation that is suspected as the situation that requires human intervention; wherein the sending is executed by the vehicle without sending by the vehicle and to the computerized system, visual information from another situation that is not suspected as a situation that requires human intervention; and

transmitting to one or more of the plurality of vehicles, the at least one trigger.

Assignments (2)
CHANGE OF NAME Recorded Jan 3, 2023
From: CARTICA AI LTD
To: AUTOBRAINS TECHNOLOGIES LTD
Reel/Frame 062266/0553 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 10, 2020
From: RAICHELGAUZ, IGAL; ODINAEV, KARINA
To: CARTICA AI LTD
Reel/Frame 052132/0600 →
Continuity (3)
Provisional Application 62827112 · Mar 31, 2019
Provisional Application 62750822 · Oct 26, 2018
Related Publication 20200133290A1 · Apr 30, 2020
Cited By (1)
US 12,260,651