System and method for monitoring vehicle traffic and controlling traffic signals

• US 9,275,545 B2
• Filed: 03/14/2014
• Issued: 03/01/2016
• Est. Priority Date: 03/14/2013
• Status: Active Grant

• Current Assignee: Christopher Edmond Aiken, John Felix Jr. Hart
• Original Assignee: John Felix Jr. Hart
• Inventors: Hart, John Felix Jr., Aiken, Christopher Edmond
• Primary Examiner(s): Dastouri, Mehrdad
• Assistant Examiner(s): DOBBS, KRISTIN SENSMEIER
• Application Number:
  US14/214,337
• Publication Number:
  US 20140267734A1
• Time in Patent Office: 718 Days
• Field of Search: 348/149
• US Class Current: 1/1
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G08G 1/07 Controlling traffic signals

Abstract

A system and method for monitoring objects, such as vehicle traffic, and controlling a flow of the objects, such as vehicle traffic, through a flow point, such as an intersection having traffic control signals. At least one three-dimensional (3D) vector imaging sensor is operable for detecting an object and capturing node-based object with motion vector data relating to the object. A Sensor Processing Unit (SPU) is associated with the vector imaging sensor(s) and operable for processing the mode-based object with motion vector data, determining a tracked object from a plurality of the objects detected by the vector imaging sensor(s) and extracting the object data of the tracked object to an object database. A Central Tracking Unit (CTU) is associated with the SPU and operable for classifying the tracked object, generating object tracking data from the tracked object, predicting a future object state of the tracked object, and generating an object control output for controlling a control signal to thereby facilitate the flow of the objects through the flow point.

Claims

1. A system for monitoring objects and controlling a flow of the objects through a flow point, the system comprising:

at least one three-dimensional (3D) vector imaging sensor operable for capturing object data relating to an object;

a Sensor Processing Unit (SPU) associated with the at least one three-dimensional (3D) vector imaging sensor, the SPU being operable for processing the object data relating to the object captured by the at least one three-dimensional (3D) vector imaging sensor to represent the object as a node-based object in the form of a vector image comprised of one or more nodes based on a mathematical expression as opposed to a bitmap image or a raster image, the SPU being further operable for determining a tracked object from a plurality of the node-based objects based on a movement of the node-based object over time and for extracting motion vector data of the tracked object over time to represent the tracked object as a node-based object with motion vector data, wherein the motion vector data is an accumulation of motion data relating to the node-based object represented as a graphically numerical value in the form of a vector; and

a Central Tracking Unit (CTU) associated with the SPU, the CTU being operable for classifying the tracked object and for generating object tracking data from the tracked object, the CTU being further operable for predicting a future object state of the tracked object and for generating an object control output for controlling a control signal to thereby facilitate the flow of the tracked object through the flow point.

2. The system of claim 1, wherein the at least one three-dimensional (3D) vector imaging sensor is configured to detect the object and capture the object data relating to the object when the object is located within a Field-Of-View (FOV) defined by the SPU.

3. The system of claim 1, wherein the at least one three-dimensional (3D) vector imaging sensor is selected from the group consisting of a LIDAR, radar, microwave, ultrasonic distance, stereoscopic imaging and a time-of-flight (TOF) camera sensor.

4. The system of claim 1, wherein the SPU is operable to determine at least one of a position, a size, a shape and a current state of the tracked object.

5. The system of claim 1, wherein the SPU is further operable for performing sensor composition of multiple different types of the at least one three-dimensional (3D) vector imaging sensor.

6. The system of claim 1, wherein the SPU is further operable for performing object filtering to identify the tracked object from a plurality of the objects detected by the at least one three-dimensional (3D) vector imaging sensor.

7. The system of claim 1, wherein the SPU is further operable to normalize the node-based object with motion vector data of the tracked object having object data relating to the object captured by a plurality of different types of the at least one three-dimensional (3D) vector imaging sensor.

8. The system of claim 1, wherein the SPU is further operable to interface with at least one of a Distributed Tracking Unit (DTU) and a Network Processing Unit (NPU).

9. The system of claim 8, wherein at least one of the DTU and the CTU is operable for concatenating the object data of when the tracked object is located within an area of overlap of a Field-Of-View (FOV) of a first SPU and a Field-Of-View (FOV) of a second SPU positioned adjacent the first SPU to combine the object data of the tracked object.

10. The system of claim 8, wherein DTU is operable for classifying the tracked object, generating the object tracking data for the tracked object, and predicting the future object state of the tracked object.

11. The system of claim 10, wherein DTU is further operable for processing the object control output for controlling the control signal.

12. The system of claim 8, wherein DTU is further operable to interface with at least one of another DTU, another CTU and another NPU.

13. The system of claim 8, wherein at least one NPU is operable for sorting a plurality of data transactions, filtering the plurality of data transactions, and transmitting the filtered plurality of data transactions to one or more of at least one connected unit of the system.

14. A system for monitoring vehicle traffic and for controlling a traffic signal at an intersection, the system comprising:

at least one three-dimensional (3D) vector imaging sensor configured for capturing object data relating to an object;

a Sensor Processing Unit (SPU) associated with the at least one three-dimensional (3D) vector imaging sensor, the SPU being operable for processing the object data relating to the object to represent the object as a node-based object in the form of a vector image comprised of one or more nodes based on a mathematical expression as opposed to a bitmap image or a raster image, the SPU being further operable for determining a tracked object from a plurality of the node-based objects based on a movement of the node-based object over time and for extracting motion vector data of the tracked object over time to represent the tracked object as a node-based object with motion vector data, wherein the motion vector data is an accumulation of motion data relating to the node-based object represented as a graphically numerical value in the form of a vector; and

a Central Tracking Unit (CTU) associated with the SPU, the CTU being operable for classifying the tracked object and for generating object tracking data from the tracked object, the CTU being further operable for predicting a future object state of the tracked object and for generating an object control output for controlling the traffic signal to thereby facilitate the flow of vehicle traffic through the intersection.

15. The system of claim 14, wherein the at least one three-dimensional (3D) vector imaging sensor is configured to detect the object and capture the object data relating to the object when the object is located within a Field-Of-View (FOV) defined by the SPU.

16. The system of claim 14, wherein the at least one three-dimensional (3D) vector imaging sensor is selected from the group consisting of a LIDAR, radar, microwave, ultrasonic distance, stereoscopic imaging and a time-of-flight (TOF) camera sensor.

17. A method for monitoring vehicle traffic and controlling a traffic signal at an intersection, the method comprising:

providing at least one three-dimensional (3D) vector imaging sensor;

providing a Sensor Processing Unit (SPU) operably associated with the at least one three-dimensional (3D) vector imaging sensor;

using the at least one three-dimensional (3D) vector imaging sensor to capture object data relating to an object;

providing the object data relating to the object to the SPU;

using the SPU to process the object data relating to the object to represent the object as a node-based object in the form of a vector image comprising at least one node based on a mathematical expression as opposed to a bitmap image or a raster image, and using the SPU to determine a tracked object from a plurality of the node-based objects based on a movement of the node-based object over time and to extract motion vector data of the tracked object over time to represent the tracked object as a node-based object with motion vector data, wherein the motion vector data is an accumulation of motion data relating to the node-based object represented as a graphically numerical value in the form of a vector;

providing the node-based object with motion vector data to an object database;

providing a Central Tracking Unit (CTU) operably associated with the SPU; and

using the CTU to classify the tracked object, to generate object tracking data from the tracked object, to predict a future object state of the tracked object, and to generate an object control output for controlling the traffic signal to thereby facilitate the flow of vehicle traffic through the intersection.

18. The method of claim 17, further comprising selecting the at least one three-dimensional (3D) vector imaging sensor from the group consisting of a LIDAR, radar, microwave, ultrasonic distance, stereoscopic imaging and a time-of-flight (TOF) camera sensor to detect the object and capture the object data relating to the object when the object is located within a Field-Of-View (FOV) defined by the SPU.