IP Library Granted Patent US 10,173,776
Granted Patent B2
US 10,173,776 · App. 15/246,777 · Granted Jan 8, 2019

Aerial drone for deploying a warning sign

Inventors: Itzhack Goldberg (Hadera, IL); Sharathchandra U. Pankanti (Darien, CT); Erik Rueger (Ockenheim, DE); Neil Sondhi (Pilisborosjeno, HU)
Assignee: International Business Machines Corporation
B64D1/22B64C39/024B64D1/02B64D47/06B64D47/08G05D1/0011G05D1/101G08G1/0955G08G5/0069B64C2201/12
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Quick Facts
Patent No.
US 10,173,776
App. No.
15/246,777
Granted
Jan 8, 2019
Kind
B2
Abstract

An aerial drone is coupled to a warning sign for warning other vehicles of a presence of a faulty vehicle. The aerial drone is positioned at a location of the faulty vehicle, in response to detecting the faulty vehicle. The aerial drone assesses environmental conditions at the location of the faulty vehicle. An optimal position for positioning the warning sign is determined, based on the environmental conditions at the location of the faulty vehicle, and the aerial drone is positioned at the optimal position.

Claims (73)

1. A computer-implemented method comprising:

pre-positioning an aerial drone on an immovable docking station;

detecting, by one or more processors, a faulty vehicle;

deploying, by one or more processors, the aerial drone from the immovable docking station to a location of the faulty vehicle, wherein the aerial drone is coupled to a warning sign that warns other vehicles of a presence of the faulty vehicle in response to detecting the faulty vehicle, and wherein the aerial drone is deployed to the location of the faulty vehicle by flying the aerial drone from the immovable docking station to the location of the faulty vehicle;

assessing, by the aerial drone, environmental conditions at the location of the faulty vehicle in response to said deploying the aerial drone to the location of the faulty vehicle;

determining, by one or more processors, an optimal position for positioning the warning sign based on the environmental conditions at the location of the faulty vehicle; and

positioning, by one or more processors, the aerial drone to the optimal position;

detecting, by the aerial drone, that the faulty vehicle has damaged a traffic sign;

in response to detecting that the faulty vehicle has damaged the traffic sign, determining, by one or more processors, that the optimal position is a location of the damaged traffic sign; and

positioning, by one or more processors, the aerial drone at the location of the damaged traffic sign until the damaged traffic sign is repaired.

2. The computer-implemented method of claim 1 , wherein the faulty vehicle is moving at a diminished velocity that has been predetermined to cause a hazard to the other vehicles, wherein the optimal position is a moving position that moves along with the faulty vehicle traveling at the diminished velocity, and wherein the aerial drone flies the warning sign at the moving position while the faulty vehicle is moving at the diminished velocity.

3. The computer-implemented method of claim 1 , wherein the environmental conditions are current traffic conditions at the location of the faulty vehicle.

4. The computer-implemented method of claim 1 , wherein the environmental conditions are current weather conditions at the location of the faulty vehicle.

5. The computer-implemented method of claim 1 , wherein the environmental conditions are current ambient lighting conditions at the location of the faulty vehicle.

6. The computer-implemented method of claim 1 , wherein the warning sign remains affixed to the aerial drone while the aerial drone flies above the faulty vehicle at the optimal position, and wherein the computer-implemented method further comprises:

determining, by one or more processors, a secondary position for positioning the warning sign based on the environmental conditions at the location of the faulty vehicle;

detecting, by the aerial drone, an oncoming vehicle;

determining, by one or more processors, that the oncoming vehicle is on a collision course with the aerial drone; and

in response to determining that the oncoming vehicle is on the collision course with the aerial drone, repositioning, by one or more processors, the aerial drone to the secondary position.

7. The computer-implemented method of claim 1 , further comprising:

receiving, by one or more processors, a fuel gauge reading from a fuel state sensor on the aerial drone; and

in response to determining that the fuel gauge reading is below a predefined level, landing, by one or more processors, the aerial drone at the optimal position.

8. The computer-implemented method of claim 1 , further comprising:

receiving, by one or more processors, a fuel gauge reading from a fuel state sensor on the aerial drone; and

in response to determining that the fuel gauge reading is above a predefined level, hovering the aerial drone at the optimal position.

9. The computer-implemented method of claim 1 , wherein the faulty vehicle is on a roadway, and wherein the computer-implemented method further comprises:

retrieving, by one or more processors, a record of faulty vehicle incidents on the roadway, wherein the record describes a most frequent occurrence of faulty vehicle incidents at a specific location on the roadway at a particular time and day of a week; and

pre-positioning, by one or more processors, the aerial drone at the specific location on the roadway at a particular time and day of the week.

10. The computer-implemented method of claim 1 , wherein the faulty vehicle is on a roadway, and wherein the computer-implemented method further comprises:

retrieving, by one or more processors, a record of faulty vehicle incidents on the roadway, wherein the record describes a most frequent occurrence of faulty vehicle incidents at a specific location on the roadway at a particular recurring annual date; and

pre-positioning, by one or more processors, the aerial drone at the specific location on the roadway at the particular recurring annual date.

11. The computer-implemented method of claim 1 , wherein the faulty vehicle is on a roadway, and wherein the computer-implemented method further comprises:

retrieving, by one or more processors, an indication of current environmental conditions at a specific location on the roadway; and

pre-positioning, by one or more processors, the aerial drone at the specific location on the roadway based on the current environmental conditions at the specific location on the roadway.

12. The computer-implemented method of claim 1 , further comprising:

flying the aerial drone in a patrol pattern;

searching for, by the aerial drone, the faulty vehicle while flying in the patrol pattern;

in response to detecting the faulty vehicle while flying in the patrol pattern, identifying, by the aerial drone, the location of the faulty vehicle; and

flying the aerial drone to the location of the faulty vehicle.

13. A computer program product for positioning a warning sign with an aerial drone, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions readable and executable by a processor to cause the processor to perform a method comprising:

pre-positioning an aerial drone on an immovable docking station;

detecting a faulty vehicle;

in response to detecting the faulty vehicle, deploying the aerial drone from the immovable docking station to a location of the faulty vehicle, wherein the aerial drone is coupled to a warning sign that warns other vehicles of a presence of the faulty vehicle, and wherein the aerial drone is deployed to the location of the faulty vehicle by flying the aerial drone from the immovable docking station to the location of the faulty vehicle;

in response to the aerial drone arriving at the location of the faulty vehicle, assessing environmental conditions at the location of the faulty vehicle;

determining an optimal position for positioning the warning sign based on the environmental conditions at the location of the faulty vehicle;

positioning the aerial drone to the optimal position;

detecting, by the aerial drone, that the faulty vehicle has damaged a traffic sign;

in response to detecting that the faulty vehicle has damaged the traffic sign, determining, by one or more processors, that the optimal position is a location of the damaged traffic sign; and

positioning, by one or more processors, the aerial drone at the location of the damaged traffic sign until the damaged traffic sign is repaired.

14. The computer program product of claim 13 , wherein the warning sign remains affixed to the aerial drone while positioned at the optimal position, and wherein the method further comprises:

determining a secondary position for positioning the warning sign based on the environmental conditions at the location of the faulty vehicle;

detecting an oncoming vehicle;

determining that the oncoming vehicle is on a collision course with the aerial drone; and

in response to determining that the oncoming vehicle is on the collision course with the aerial drone, repositioning the aerial drone to the secondary position.

15. The computer program product of claim 13 , wherein the method further comprises:

receiving a fuel gauge reading from a fuel state sensor on the aerial drone; and

in response to determining that the fuel gauge reading is above a predefined level, hovering the aerial drone at the optimal position.

16. The computer program product of claim 13 , wherein the program instructions are provided as a service in a cloud environment.

17. A computer system comprising:

one or more processors,

one or more computer readable memories communicably coupled to the one or more processors, and

program instructions stored on at least one of the one or more computer readable memories for execution by at least one of the one or more processors via at least one of the one or more computer readable memories, the stored program instructions comprising:

program instructions to pre-position an aerial drone on an immovable docking station;

program instructions to detect a faulty vehicle;

program instructions to, in response to detecting the faulty vehicle, deploy the aerial drone to a location of the faulty vehicle, wherein the aerial drone is coupled to a warning sign that warns other vehicles of a presence of the faulty vehicle, and wherein the aerial drone is deployed to the location of the faulty vehicle by flying the aerial drone from the immovable docking station to the location of the faulty vehicle;

program instructions to, in response to the aerial drone arriving at the location of the faulty vehicle, assess, by the aerial drone, environmental conditions at the location of the faulty vehicle;

program instructions to determine an optimal position for positioning the warning sign based on the environmental conditions at the location of the faulty vehicle;

program instructions to position the aerial drone to the optimal position;

program instructions to detect that the faulty vehicle has damaged a traffic sign;

program instructions to, in response to detecting that the faulty vehicle has damaged the traffic sign, determine that the optimal position is a location of the damaged traffic sign; and

program instructions to position the aerial drone at the location of the damaged traffic sign until the damaged traffic sign is repaired.

18. The computer system of claim 17 , wherein the environmental conditions are current traffic conditions at the location of the faulty vehicle.

19. The computer system of claim 17 , wherein the environmental conditions are current weather conditions at the location of the faulty vehicle.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 25, 2016
From: GOLDBERG, ITZHACK; PANKANTI, SHARATHCHANDRA U.; RUEGER, ERIK; SONDHI, NEIL
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 039539/0038 →
Continuity (1)
Related Publication 20180061235A1 · Mar 1, 2018
Cited By (2)
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