SYSTEM AND METHOD FOR EVIDENTIAL REASONING FOR TRANSPORTATION SCENARIOS

• US 20090138186A1
• Filed: 11/28/2007
• Published: 05/28/2009
• Est. Priority Date: 11/28/2007
• Status: Active Grant

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Ray, Gary A.
• Granted Patent: US 8,321,122 B2
• Time in Patent Office: Days
• US Class Current: 701/117
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors

Abstract

The system contains a programmable device. At least one camera is in communication with the programmable device. The camera is directed towards at least one road. The camera provides a camera signal to the programmable device. A map of an area, which includes the road, is stored in a memory of the programmable device. A plurality of traffic influences is defined in the map. A first program on the programmable device tracks vehicles on the road utilizing the camera signal. The first program recognizes at least one obstruction and communicates with the map to identify at least one of the traffic influences behind the obstruction.

Claims

1. A traffic monitoring system, comprising:

a programmable device;

at least one camera in communication with the programmable device, the camera directed towards at least one road and configured to provide a camera signal to the programmable device, wherein the programmable device includes a first program for tracking vehicles; and

a map of an area that includes the road, wherein the map is stored in a memory of the programmable device and wherein a plurality of traffic influences are defined in the map;

wherein the first program recognizes at least one obstruction and communicates with the map to identify at least one of the traffic influences behind the obstruction.

2. The system of claim 1, further comprising a second program for calculating an effect of the traffic influence on at least one vehicle that passes behind the obstruction.

3. The system of claim 1, further comprising a plurality of tags, wherein each of the tags is associated with a vehicle on the road and wherein each tag includes identification of at least a color and one dimension of the vehicle to which each tag is associated.

4. The system of claim 1, wherein the map further comprises a plurality of segments, wherein each of the segments represents a portion of the map traversed by vehicles.

5. The system of claim 4, wherein each of the segments further comprises a vector indicative of a direction commonly traveled by vehicles within the segment and an average speed of vehicles within the segment.

6. The system of claim 5, wherein each vector is a representative averaging of at least a portion of collected traffic information.

7. A method for monitoring traffic, the method comprising the steps of:

directing at least one camera towards at least one road;

collecting traffic information from the at least one road through the at least one camera;

communicating the collected traffic information to a programmable device;

comparing collected traffic information with a map of an area that includes the road, wherein the map is stored in a memory of the programmable device and wherein a plurality of traffic influences are defined in the map; and

tracking vehicles on the road, wherein a first program recognizes at least one obstruction of the road and communicates with the map to identify at least one of the traffic influences behind the obstruction.

8. The method of claim 7, further comprising the step of storing map information in the memory, wherein the map information comprises vehicle behavior patterns on the road.

9. The method of claim 8, further comprising the step of predicting behavior of at least one vehicle that passes behind the obstruction based on vehicle behavior patterns on the road.

10. The method of claim 8, further comprising the step of matching vehicles passing out from behind the obstruction with vehicles that previously passed behind the obstruction based on vehicle behavior patterns on the road and at least one matching tracked characteristic of the vehicles that previously passed behind the obstruction.

11. The method of claim 8, further comprising the step of dividing at least a portion of the collected traffic information into a plurality of segments, wherein each of the segments represents a portion of the map traversed by vehicles.

12. The method of claim 11, further comprising the step of assigning a vector to each of the segments, wherein each of the vectors is indicative of a direction commonly traveled by vehicles within the segment and an average speed of vehicles within the segment.

13. The method of claim 12, further comprising the step of calculating the vectors from the collected traffic information.

14. The method of claim 7, further comprising the step of calculating an effect of the traffic influence on at least one vehicle that passes behind the obstruction.

15. The method of claim 7, further comprising the step of maintaining a plurality of tags within the programmable device, wherein each of the tags is associated with one of the vehicles on the road and wherein each tag includes identification of at least a color and one dimension of the vehicle to which each tag is associated.

16. A system for monitoring traffic, the system comprising:

at least one camera directed towards at least one road for collecting traffic information concerning the at least one road and for tracking vehicles on the road,

a computer having a computer readable program for comparing collected traffic information with a stored map of an area that includes the road, wherein a plurality of traffic influences are defined in the map,

for recognizing at least one obstruction of the road, and

for communicating with the map to identify at least one of the traffic influences behind the obstruction.

17. The system of claim 16, further comprising reducing collected traffic information to traffic behavior patterns on the road.

18. The system of claim 17, further comprising predicting behavior of at least one vehicle that passes behind the obstruction based on vehicle behavior patterns on the road.

19. The system of claim 17, further comprising matching vehicles passing out from behind the obstruction with vehicles that previously passed behind the obstruction based on the vehicle behavior patterns on the road and at least one matching tracked characteristic of the vehicles that previously passed behind the obstruction.

20. The system of claim 17, further comprising calculating an effect of the traffic influence on at least one vehicle that passes behind the obstruction.