IP Library Granted Patent US 11,100,336
Granted Patent B2
US 11,100,336 · App. 16/058,214 · Granted Aug 24, 2021

System and method of adaptive traffic management at an intersection

Inventors: William A. Malkes (Knoxville, TN); William S. Overstreet (Knoxville, TN); Jeffery R. Price (Knoxville, TN); Michael J. Tourville (Lenoir City, TN)
Assignee: CUBIC CORPORATION
G06K9/00785G06K9/00778G08G1/04G06K9/6254G06K9/6268
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Quick Facts
Patent No.
US 11,100,336
App. No.
16/058,214
Granted
Aug 24, 2021
Kind
B2
Abstract

A traffic control system and a method of automatic zone creation for a smart traffic camera to be used in adaptive traffic management at an intersection are disclosed. In one aspect of the present disclosure, a method includes receiving traffic data at an intersection; creating zones at the intersection to be applied to one or more smart traffic cameras installed at the intersection; determining whether the zones are to be validated; validating the zones upon determining that the zones are to be validated; and applying the validated zones to the one or more smart traffic cameras at the intersection.

Claims (64)

1. A method comprising:

receiving traffic data at an intersection from one or more smart traffic cameras installed at the intersection;

using on the traffic data received from the one or more smart traffic cameras installed at the intersection to create conditional zones at the intersection to be applied to the one or more smart traffic cameras installed at the intersection, wherein:

the conditional zones are a portion of a field of view of the one or more smart traffic cameras, and

the conditional zones filter what is processed by the one or more smart traffic cameras;

automatically determining whether the conditional zones are to be validated;

upon automatically determining that the conditional zones are to be validated, validating the conditional zones manually based on human feedback or automatically to create validated zones; and

applying the validated zones to the one or more smart traffic cameras at the intersection, wherein switching from the conditional zones to the validated zones changes the portion that are processed from the one or more smart traffic cameras.

2. The method of claim 1 , wherein creating the conditional zones at the intersection comprises:

tracking objects detected at the intersection including points at the intersection at which different objects stop; and

creating the conditional zones based on movement of the objects and the points.

3. The method of claim 2 , wherein tracking the objects is based on data collected on the objects by one or more sensors installed at the intersection.

4. The method of claim 1 , the method comprises:

prior to validating the conditional zones, determining whether the conditional zones are to be validated manually based on the human feedback or automatically.

5. The method of claim 4 , wherein upon determining that the conditional zones are to be validated manually, validating the conditional zones comprises:

providing an operator a visual prompt, via graphical user interface, to one of confirm or modify the conditional zones and corresponding parameters; and

updating the conditional zones and the corresponding parameters based on a response to the visual prompt, updated zones and corresponding parameters constituting the validated zones.

6. The method of claim 4 , wherein upon determining that the conditional zones are to be validated automatically, validating the conditional zones comprises:

querying a zone creation database to retrieve identified zones and parameters corresponding to intersections of a same type as the intersection; and

updating the conditional zones and the corresponding parameters based on the identified zones and the parameters retrieved from the zone creation database, updated zones and corresponding parameters constituting the validated zones.

7. The method of claim 6 , wherein the zone creation database stores, for each different type of intersection, corresponding zones and parameters, the corresponding zones and the parameters being constantly updated using a machine-learning algorithm operating on data collected on movement of objects at the intersection.

8. A traffic controller comprising:

memory having computer-readable instructions stored therein; and

one or more processors configured to execute the computer-readable instructions to:

receive traffic data at an intersection from one or more smart traffic cameras installed at the intersection;

use the traffic data received from the one or more smart traffic cameras installed at the intersection to create conditional zones at the intersection to be applied to the one or more smart traffic cameras installed at the intersection, wherein:

the conditional zones are a portion of a field of view of the one or more smart traffic cameras, and

the conditional zones filter what is processed by the one or more smart traffic cameras;

automatically determine whether the conditional zones are to be validated;

upon automatically determining that the conditional zones are to be validated, validate the conditional zones manually based on human feedback or automatically to create validated zones; and

apply the validated zones to the one or more smart traffic cameras at the intersection, wherein switching from the conditional zones to the validated zones changes the portion that is processed from the one or more smart traffic cameras.

9. The traffic controller of claim 8 , wherein the one or more processors are configured to execute the computer-readable instructions to create the conditional zones at the intersection by:

tracking objects detected at the intersection including points at the intersection at which different objects stop; and

creating the conditional zones based on movement of the objects and the points.

10. The traffic controller of claim 9 , wherein tracking the objects is based on data collected on the objects by one or more sensors installed at the intersection.

11. The traffic controller of claim 8 , wherein the one or more processors are further configured to execute the computer-readable instructions to:

prior to validating the conditional zones, determining whether the conditional zones are to be validated manually based on the human feedback or automatically.

12. The traffic controller of claim 11 , wherein upon determining that the conditional zones are to be validated manually, the one or more processors are configured to execute the computer-readable instructions to validate the conditional zones by:

providing an operator a visual prompt, via graphical user interface, to one of confirm or modify the conditional zones and corresponding parameters; and

updating the conditional zones and the corresponding parameters based on a response to the visual prompt, updated zones and corresponding parameters constituting the validated zones.

13. The traffic controller of claim 11 , wherein upon determining that the conditional zones are to be validated automatically, the one or more processors are configured to execute the computer-readable instructions to validate the conditional zones by:

querying a zone creation database to retrieve identified zones and parameters corresponding to intersections of a same type as the intersection; and

updating the conditional zones and the corresponding parameters based on the identified zones and the parameters retrieved from the zone creation database, updated zones and corresponding parameters constituting the validated zones.

14. The traffic controller of claim 13 , wherein the zone creation database is configured to store, for each different type of intersection, corresponding zones and parameters, the corresponding zones and the parameters being constantly updated using a machine-learning algorithm operating on data collected on movement of objects at the intersection.

15. One or more non-transitory computer-readable medium having computer-readable instructions, which when executed by one or more processors of a traffic controller, cause the traffic controller to:

receive traffic data at an intersection from one or more smart traffic cameras installed at the intersection;

use the traffic data received from the one or more smart traffic cameras installed at the intersection to create conditional zones at the intersection to be applied to the one or more smart traffic cameras installed at the intersection, wherein:

the conditional zones are a portion of a field of view of the one or more smart traffic cameras, and

the conditional zones filter what is processed by the one or more smart traffic cameras;

automatically determine whether the conditional zones are to be validated;

upon automatically determining that the conditional zones are to be validated, validate the conditional zones manually based on human feedback or automatically to create validated zones; and

apply the validated zones to the one or more smart traffic cameras at the intersection, wherein switching from the conditional zones to the validated zones changes the portion that is processed from the one or more smart traffic cameras.

16. The one or more non-transitory computer-readable medium of claim 15 , wherein the execution of the computer-readable instructions by the one or more processors causes the traffic controller to create the conditional zones at the intersection by:

tracking objects detected at the intersection including points at the intersection at which different objects stop; and

creating the conditional zones based on movement of the objects and the points.

17. The one or more non-transitory computer-readable medium of claim 15 , wherein the execution of the computer-readable instructions by the one or more processors further causes the traffic controller to:

prior to validating the conditional zones, determine whether the conditional zones are to be validated manually based on the human feedback or automatically.

18. The one or more non-transitory computer-readable medium of claim 17 , wherein upon determining that the conditional zones are to be validated manually, the execution of the computer-readable instructions by the one or more processors causes the traffic controller to validate the conditional zones by:

providing an operator a visual prompt, via graphical user interface, to one of confirm or modify the conditional zones and corresponding parameters; and

updating the conditional zones and the corresponding parameters based on a response to the visual prompt, updated zones and corresponding parameters constituting the validated zones.

19. The one or more non-transitory computer-readable medium of claim 17 , wherein upon determining that the conditional zones are to be validated automatically, the execution of the computer-readable instructions by the one or more processors causes the traffic controller to validate the conditional zones by:

querying a zone creation database to retrieve identified zones and parameters corresponding to intersections of a same type as the intersection; and

updating the conditional zones and the corresponding parameters based on the identified zones and the parameters retrieved from the zone creation database, updated zones and corresponding parameters constituting the validated zones.

20. The one or more non-transitory computer-readable medium of claim 19 , wherein the zone creation database is configured to store, for each different type of intersection, corresponding zones and parameters, the corresponding zones and the parameters being constantly updated using a machine-learning algorithm operating on data collected on movement of objects at the intersection.

Assignments (10)
SUPERPRIORITY PATENT SECURITY AGREEMENT Recorded Oct 6, 2025
From: CUBIC CORPORATION; CUBIC DEFENSE APPLICATIONS INC.; CUBIC DIGITAL INTELLIGENCE INC.; CUBIC ITS, INC.; CUBIC SECURE COMMUNICATIONS, LLC; CUBIC TOTAL LEARNING PLATFORM, LLC; CUBIC TRANSPORTATION SYSTEMS, INC.; GATR TECHNOLOGIES INC.; NUVOTRONICS INC.
To: BARCLAYS BANK PLC
Reel/Frame 073008/0761 →
RELEASE OF SECURITY INTEREST Recorded Jul 30, 2025
From: ALTER DOMUS (US) LLC
To: CUBIC CORPORATION; CUBIC DEFENSE APPLICATIONS, INC.; CUBIC DIGITAL INTELLIGENCE, INC.
Reel/Frame 072278/0272 →
RELEASE OF SECURITY INTEREST Recorded Jul 30, 2025
From: ALTER DOMUS (US) LLC
To: CUBIC CORPORATION; CUBIC DIGITAL SOLUTIONS LLC; NUVOTRONICS, INC.
Reel/Frame 072281/0176 →
RELEASE OF SECURITY INTEREST AT REEL/FRAME 056393/0281 Recorded Jul 28, 2025
From: BARCLAYS BANK PLC, AS ADMINISTRATIVE AGENT
To: CUBIC CORPORATION; CUBIC DEFENSE APPLICATIONS, INC.; CUBIC DIGITAL SOLUTIONS LLC (FORMERLY PIXIA CORP.)
Reel/Frame 072282/0124 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 10, 2025
From: CUBIC CORPORATION
To: CUBIC ITS, INC.
Reel/Frame 071370/0881 →
SECURITY INTEREST Recorded May 2, 2025
From: CUBIC DEFENSE APPLICATIONS, INC.; CUBIC DIGITAL INTELLIGENCE, INC.
To: ALTER DOMUS (US) LLC
Reel/Frame 071161/0299 →
SECOND LIEN SECURITY AGREEMENT Recorded May 26, 2021
From: CUBIC CORPORATION; PIXIA CORP.; NUVOTRONICS, INC.
To: ALTER DOMUS (US) LLC
Reel/Frame 056393/0314 →
FIRST LIEN SECURITY AGREEMENT Recorded May 26, 2021
From: CUBIC CORPORATION; PIXIA CORP.; NUVOTRONICS, INC.
To: BARCLAYS BANK PLC
Reel/Frame 056393/0281 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 6, 2019
From: GRIDSMART TECHNOLOGIES, INC.
To: CUBIC CORPORATION
Reel/Frame 048248/0847 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 23, 2018
From: MALKES, WILLIAM A.; OVERSTREET, WILLIAM S.; PRICE, JEFFERY R.; TOURVILLE, MICHAEL J.
To: GRIDSMART TECHNOLOGIES, INC.
Reel/Frame 046686/0814 →
Continuity (2)
Provisional Application 62545268 · Aug 14, 2017
Related Publication 20190050647A1 · Feb 14, 2019
Cited By (1)
US 12,361,823