System and method of adaptive controlling of traffic using camera data

• US 10,373,489 B2
• Filed: 07/09/2018
• Issued: 08/06/2019
• Est. Priority Date: 08/11/2017
• Status: Active Grant

• Current Assignee: Cubic Corporation
• Original Assignee: Cubic Corporation
• Inventors: Malkes, William A., Overstreet, William S., Price, Jeffery R., Tourville, Michael J.
• Primary Examiner(s): Akki, Munear T
• Application Number:
  US16/030,396
• Publication Number:
  US 20190051160A1
• Time in Patent Office: 393 Days
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/08 according to detected number or speed of vehicles
• CPC Class Codes: G08G 1/081 Plural intersections under common control

Abstract

A system and a method for adaptively controlling of traffic are disclosed. The method includes receiving traffic data from one or more sensors at the intersection; detecting at least one pattern in the traffic data for a given period of time; identifying at least one variable in the pattern; determining if the at least one variable is associated with one or more available traffic patterns at the intersection; based on the determining, retrieving a current traffic control program implemented at the intersection; adaptively controlling the traffic at the intersection during the given period of time by adjusting one or more parameters of the current traffic control program to yield a modified traffic control program; and storing the modified traffic control program in a database for future use.

Claims

1. A method of controlling traffic at an intersection comprising:

receiving traffic data from one or more sensors at the intersection, wherein the traffic data comprises data regarding objects at the intersection detected by the one or more sensors;

detecting, using the traffic data for a period of time, a pattern of movement of the objects on at least two roads of the intersection during the period of time, wherein detecting the pattern comprises;

analyzing the traffic data to determine a number of the objects at the intersection during the period of time; and

detecting the pattern by determining a rate of change in the number of the objects relative to at least one variable;

determining if the pattern is associated with one or more predetermined traffic patterns at the intersection;

based on the determining, retrieving a current traffic control program implemented at the intersection;

controlling the traffic at the intersection by adjusting one or more parameters of the current traffic control program to yield a modified traffic control program, wherein the adjusting is based on the one or more predetermined traffic patterns; and

storing the modified traffic control program in a database for future use.

2. The method of claim 1, wherein the number of the objects is determined using identified zones at the intersection.

3. The method of claim 2, further comprising:

receiving identifications of the zones at the intersection via a graphical user interface.

4. The method of claim 1, further comprising identifying at least one statistically independent variable in the pattern.

5. The method of claim 4, wherein the at least one statistically independent variable is one or more of a time of day, a day of a week, weather conditions at or near the intersection or at least one scheduled event at or near the intersection.

6. The method of claim 1, wherein adjusting the one or more parameters is proportional to a rate of change in objects detected in the pattern.

7. The method of claim 1, further comprising:

monitoring live conditions at the intersection;

determining if at least one live condition matches at least one variable of the detected pattern; and

applying the modified traffic control program to the intersection when the at least one live condition matches the at least one variable.

9. The traffic controller of claim 7, wherein the one or more processors are further configured to execute the computer-readable instructions to identify at least one statistically independent variable in the pattern.

10. The traffic controller of claim 9, wherein the at least one statistically independent variable is one or more of a time of day, a day of a week, weather conditions at or near the intersection or at least one scheduled event at or near the intersection.

11. The traffic controller of claim 7, wherein the database is communicatively coupled to the traffic controller.

12. The traffic controller of claim 7, wherein the one or more sensors are one or more of a fish-eye camera, an infrared camera, a motion sensor, or an audio sensor.

13. The traffic controller of claim 7, wherein the one or more processors are configured to execute the computer-readable instructions to:

send the modified traffic control program to at least one smart traffic light installed at the intersection for implementation.

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 from one or more sensors at an intersection, wherein the traffic data comprises data regarding objects at the intersection detected by the one or more sensors;

detect, using the traffic data for a period of time, a pattern of movement of the objects on at least two roads of the intersection during the period of time, wherein the one or more processors are configured to execute the computer-readable instructions to detect the pattern by;

analyzing the traffic data to determine a number of the objects at the intersection during the period of time; and

detecting the pattern by determining a rate of change in the number of the objects relative to at least one variable;

determine if the pattern is associated with one or more predetermined traffic patterns at the intersection;

based on the determining, retrieve a current traffic control program implemented at the intersection;

control traffic at the intersection by adjusting one or more parameters of the current traffic control program to yield a modified traffic control program, wherein the adjusting is based on the one or more predetermined traffic patterns; and

store the modified traffic control program in a database for future use.

14. One or more non-transitory computer-readable medium having computer-readable instructions stored thereon, which when executed by one or more processors, cause the one or more processors to:

receive traffic data from one or more sensors at an intersection, wherein the traffic data comprises data regarding objects at the intersection detected by the one or more sensors;

detect, using the traffic data for a period of time, a pattern of movement of the objects on at least two roads of the intersection during the period of time, wherein the execution of the computer-readable instructions by the one or more processors, further cause the one or more processors to detect the pattern by;

analyzing the traffic data to determine a number of the objects at the intersection during the period of time; and

detecting the pattern by determining a rate of change in the number of the objects relative to at least one variable;

determine if the pattern is associated with one or more predetermined traffic patterns at the intersection;

based on the determining, retrieve a current traffic control program implemented at the intersection;

control traffic at the intersection by adjusting one or more parameters of the current traffic control program to yield a modified traffic control program, wherein the adjusting is based on the one or more predetermined traffic patterns; and

store the modified traffic control program in a database for future use.

15. The one or more non-transitory computer-readable medium of claim 14, wherein the execution of the computer-readable instructions by the one or more processors, cause the one or more processors to identify at least one statistically independent variable in the pattern.

16. The one or more non-transitory computer-readable medium of claim 15, wherein the at least one statistically independent variable is one or more of a time of day, a day of a week, weather conditions at or near the intersection or at least one scheduled event at or near the intersection.

17. The one or more non-transitory computer-readable medium of claim 14, wherein the execution of the computer-readable instructions by the one or more processors, cause the one or more processors to further detect the pattern by:

monitoring live conditions at the intersection;

determining if at least one live condition matches at least one variable of the detected pattern; and

applying the modified traffic control program to the intersection when the at least one live condition matches the at least one variable.