System and method for modeling and optimizing the performance of transportation networks

• US 8,666,643 B2
• Filed: 02/01/2011
• Issued: 03/04/2014
• Est. Priority Date: 02/01/2010
• Status: Active Grant

• Current Assignee: Miovision Technologies Incorporated
• Original Assignee: Miovision Technologies Incorporated
• Inventors: McBride, Kurtis, Benda, Tomas, Thompson, David
• Primary Examiner(s): NGUYEN, TAN QUANG
• Application Number:
  US13/019,120
• Publication Number:
  US 20110191011A1
• Time in Patent Office: 1,127 Days
• Field of Search: 701/117, 340/909, 340/907, 340/910, 340/920
• US Class Current: 701/117
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• 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 1/081 Plural intersections under common control
• CPC Class Codes: H04L 41/0823 characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability for optimising operational conditions of wireless networks H04W24/02
• CPC Class Codes: H04W 28/06 Optimizing the usage of the radio link, e.g. header compression, information sizing , discarding information system modifying transmission characteristic according to link quality by modifying frame length H04L1/0007; dynamic adaptation of the packet size for flow control or congestion control H04L47/365

Abstract

A method and system are provided for modeling and optimizing the performance of transportation networks, e.g. for traffic signal retiming. The modeling and optimization may be implemented by obtaining a video signal from a camera at a first intersection; processing data from the video signal to determine at least one value indicative of a corresponding traffic flow through the first intersection; sending the at least one value to a remote processing entity via a wireless network to enable the remote processing entity to update a model of the transportation network, the transportation network comprising the first intersection and at least a second intersection; receiving from the remote processing entity, an instruction for a controller at the first intersection, the instruction having been determined from an update of the model based on data from at least the second intersection; and having the instruction implemented by the controller at the first intersection to optimize at least a portion of the transportation network.

Claims

1. A method of modeling and optimizing a transportation network, the method comprising:

receiving from a first processing module, via a wireless network, at least one value indicative of a corresponding traffic flow through a first intersection, the at least one value having been obtained by processing data from a video signal from a camera at the first intersection;

using the at least one value to update a model of the transportation network, the model being continually updated as data is received from a plurality of sources in the transportation network, the transportation network comprising the first intersection and at least a second intersection;

obtaining a representation of a current state of the model and performing a predictive optimization of the current state of the model to determine an instruction for predictively optimizing a controller at the second intersection; and

sending the instruction to a second processing module at the second intersection via the wireless network, to enable the second processing module to have the instruction implemented by the controller at the second intersection to optimize at least a portion of the transportation network.

2. The method according to claim 1, wherein the obtaining the representation comprises obtaining a snapshot of the model and applying one or more optimization algorithms to the snapshot of the model to determine the instruction.

3. The method according to claim 1, further comprising obtaining third party data from a third party system;

and updating the model using the third party data.

4. The method according to claim 1, further comprising receiving the video signal or data derived therefrom from the first processing module, and applying one or more post-processing algorithms.

5. The method according to claim 1, further comprising receiving from the first processing module, via the wireless network, sensor data having been acquired at or near the first intersection, and using the sensor data in one or more of updating the model and analyzing the model.

6. The method according to claim 5, wherein the received sensor data comprises origin-destination information, the method further comprising including the origin-destination information in one or more of updating the model and analyzing the model.

7. The method according to claim 1, further comprising providing the model or data derived therefrom to a third party.

8. A method of modeling and optimizing a transportation network, the method comprising:

obtaining a video signal from a camera at a first intersection;

processing data from the video signal to determine at least one value indicative of a corresponding traffic flow through the first intersection;

sending the at least one value to a remote processing entity via a wireless network to enable the remote processing entity to update a model of the transportation network, the model being continually updated by the remote processing entity as data is received from a plurality of sources in the transportation network, the transportation network comprising the first intersection and at least a second intersection;

receiving from the remote processing entity, an instruction for a controller at the first intersection, the instruction having been determined from a representation of a current state of the model based on data from at least the second intersection and a predictive optimization performed using the current state of the model; and

having the instruction implemented by the controller at the first intersection to predictively optimize at least a portion of the transportation network.

9. The method according to claim 8, wherein having the instruction implemented comprises sending the instruction to a communications interface coupled to the controller.

10. The method according to claim 9, wherein the instruction is sent to the communications interface via a short-range wireless connection.

11. The method according to claim 8, further comprising sending the video signal or data derived therefrom to the remote processing entity to have one or more post-processing algorithms applied.

12. The method according to claim 8, further comprising sending, via the wireless network, sensor data having been acquired at or near the first intersection to enable the sensor data to be used in one or more of updating the model and analyzing the model.

13. A method of modeling and optimizing a transportation network, the method comprising:

receiving an instruction from a remote processing entity via a wireless network, the instruction for having a controller predictively optimize at least a portion of the transportation network at a first intersection, the instruction having been determined by the remote processing entity obtaining a representation of a current state of a model of the transportation network comprising the first intersection and performing a predictive optimization of the current state of the model, the model having been continually updated as data is received from one or more additional intersections in the transportation network; and

sending the instruction to a communications interface coupled to the traffic signal controller.

14. The method according to claim 13, wherein the instruction is sent to the communication interface via a short-range wireless connection.

15. A non-transitory computer readable medium comprising computer executable instructions for modeling and optimizing a transportation network, the computer executable instructions comprising instructions for:

receiving from a first processing module, via a wireless network, at least one value indicative of a corresponding traffic flow through a first intersection, the at least one value having been obtained by processing data from a video signal from a camera at the first intersection;

using the at least one value to update a model of the transportation network, the model being continually updated as data is received from a plurality of sources in the transportation network, the transportation network comprising the first intersection and at least a second intersection;

obtaining a representation of a current state of the model and performing a predictive optimization of the current state of the model to determine an instruction for predictively optimizing a controller at the second intersection; and

sending the instruction to a second processing module at the second intersection via the wireless network, to enable the second processing module to have the instruction implemented by the controller at the second intersection to optimize at least a portion of the transportation network.

16. A non-transitory computer readable medium comprising computer executable instructions for modeling and optimizing a transportation network, the computer executable instructions comprising instructions for:

obtaining a video signal from a camera at a first intersection;

processing data from the video signal to determine at least one value indicative of a corresponding traffic flow through the first intersection;

sending the at least one value to a remote processing entity via a wireless network to enable the remote processing entity to update a model of the transportation network, the model being continually updated by the remote processing entity as data is received from a plurality of sources in the transportation network, the transportation network comprising the first intersection and at least a second intersection;

receiving from the remote processing entity, an instruction for a controller at the first intersection, the instruction having been determined from a representation of a current state of the model based on data from at least the second intersection and a predictive optimization performed using the current state of the model; and

having the instruction implemented by the controller at the first intersection to predictively optimize at least a portion of the transportation network.

17. A non-transitory computer readable medium comprising computer executable instructions for modeling and optimizing a transportation network, the computer executable instructions comprising instructions for:

receiving an instruction from a remote processing entity via a wireless network, the instruction for having a controller predictively optimize at least a portion of the transportation network at a first intersection, the instruction having been determined by the remote processing entity obtaining a representation of a current state of a model of the transportation network comprising the first intersection and performing a predictive optimization of the current state of the model, the model having been continually updated as data is received from one or more additional intersections in the transportation network; and

sending the instruction to a communications interface coupled to the traffic signal controller.

18. A system comprising a processor and memory, the memory comprising computer executable instructions for:

receiving from a first processing module, via a wireless network, at least one value indicative of a corresponding traffic flow through a first intersection, the at least one value having been obtained by processing data from a video signal from a camera at the first intersection;

using the at least one value to update a model of the transportation network, the model being continually updated as data is received from a plurality of sources in the transportation network, the transportation network comprising the first intersection and at least a second intersection;

obtaining a representation of a current state of the model and performing a predictive optimization of the current state of the model to determine an instruction for predictively optimizing a controller at the second intersection; and

sending the instruction to a second processing module at the second intersection via the wireless network, to enable the second processing module to have the instruction implemented by the controller at the second intersection to optimize at least a portion of the transportation network.

19. The system according to claim 18, wherein the obtaining the representation comprises obtaining a snapshot of the model and applying one or more optimization algorithms to the snapshot of the model to determine the instruction.

20. The system according to claim 18, further comprising instructions for obtaining third party data from a third party system;

and updating the model using the third party data.

21. The system according to claim 18, further comprising instructions for receiving the video signal or data derived therefrom from the first processing module, and applying one or more post-processing algorithms.

22. The system according to claim 18, further comprising instructions for receiving from the first processing module, via the wireless network, sensor data having been acquired at or near the first intersection, and using the sensor data in one or more of updating the model and analyzing the model.

23. The system according to claim 22, wherein the received sensor data comprises origin-destination information, the method further comprising including the origin-destination information in one or more of updating the model and analyzing the model.

24. The system according to claim 18, further comprising instructions for providing the model or data derived therefrom to a third party.

25. A system comprising a processor and memory, the memory comprising computer executable instructions for:

obtaining a video signal from a camera at a first intersection;

processing data from the video signal to determine at least one value indicative of a corresponding traffic flow through the first intersection;

sending the at least one value to a remote processing entity via a wireless network to enable the remote processing entity to update a model of the transportation network, the model being continually updated by the remote processing entity as data is received from a plurality of sources in the transportation network, the transportation network comprising the first intersection and at least a second intersection;

receiving from the remote processing entity, an instruction for a controller at the first intersection, the instruction having been determined from a representation of a current state of the model based on data from at least the second intersection and a predictive optimization performed using the current state of the model; and

having the instruction implemented by the controller at the first intersection to predictively optimize at least a portion of the transportation network.

26. The system according to claim 25, wherein having the instruction implemented comprises sending the instruction to a communications interface coupled to the controller.

27. The system according to claim 26, wherein the instruction is sent to the communications interface via a short-range wireless connection.

28. The system according to claim 25, further comprising instructions for sending the video signal or data derived therefrom to the remote processing entity to have one or more post-processing algorithms applied.

29. The system according to claim 25, further comprising instructions for sending, via the wireless network, sensor data having been acquired at or near the first intersection to enable the sensor data to be used in one or more of updating the model and analyzing the model.

30. A system comprising a processor and memory, the memory comprising computer executable instructions for:

receiving an instruction from a remote processing entity via a wireless network, the instruction for having a controller predictively optimize at least a portion of the transportation network at a first intersection, the instruction having been determined by the remote processing entity obtaining a representation of a current state of a model of the transportation network comprising the first intersection and performing a predictive optimization of the current state of the model, the model having been continually updated as data is received from one or more additional intersections in the transportation network; and

sending the instruction to a communications interface coupled to the traffic signal controller.

31. The system according to claim 30, wherein the instruction is sent to the communication interface via a short-range wireless connection.