Electronic Toll Management and Vehicle Identification

• US 20130346165A1
• Filed: 05/31/2013
• Published: 12/26/2013
• Est. Priority Date: 02/21/2003
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Hedley, Jay E., Thornburg, Neal Patrick
• Granted Patent: US 8,775,236 B2
• Time in Patent Office: Days
• US Class Current: 705/13
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G06V 20/62 Text, e.g. of license plates, overlay texts or captions on TV images
• CPC Class Codes: G07B 15/06 Arrangements for road pricing or congestion charging of vehicles or vehicle users, e.g. automatic toll systems
• CPC Class Codes: G08G 1/017 identifying vehicles G08G1/015, G08G1/054 take precedence

Abstract

Identifying a vehicle in a toll system includes accessing image data for a first vehicle and obtaining first vehicle identifier data from the accessed image data for the first vehicle. A set of records is accessed. Each record includes first vehicle identifier data for a vehicle. The first vehicle identifier data for the first vehicle is compared with the first vehicle identifier data for vehicles in the set of records. Based on the results of the comparison of the first vehicle identifier data, a set of vehicles is identified from the vehicles having records in the set of records. Second vehicle identifier data is accessed for the first vehicle and is compared to second vehicle identifier data for the set of vehicles in order to identify the first vehicle.

Claims

1. (canceled)

2. A computer-implemented method of identifying a vehicle in a toll system, the method comprising:

accessing image data for a vehicle transacting with a toll system;

obtaining first vehicle identifier data from the accessed image data for the transacting vehicle;

accessing a set of records that includes first vehicle identifier data for vehicles;

executing, using at least one processing device, an algorithm to;

compare the first vehicle identifier data for the transacting vehicle with the first vehicle identifier data for vehicles in the set of records, and

identify a set of vehicle candidates from the vehicles having records in the set of records, wherein the identified set of vehicle candidates excludes at least one vehicle having a record in the set of records; and

selecting, from the set of vehicle candidates, a vehicle candidate as corresponding to the transacting vehicle by;

accessing second vehicle identifier data for the transacting vehicle, the second vehicle identifier data being data for identifying a vehicle that is distinct from first vehicle identifier data,

accessing second vehicle identifier data for a vehicle candidate in the set of vehicle candidates,

comparing, using the at least one processing device, the second vehicle identifier data for the transacting vehicle with the second vehicle identifier data for the vehicle candidate in the set of vehicle candidates, and

identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle based on results of the comparison of second vehicle identifier data.

3. The method of claim 2, wherein comparing the first vehicle identifier data for the first vehicle with the first vehicle identifier data for vehicles in the set of records includes searching a vehicle record database for records that include first vehicle identifier data that exactly match the first vehicle identifier data obtained for the transacting vehicle.

4. The method of claim 3, wherein comparing the first vehicle identifier data for the transacting vehicle with the first vehicle identifier data for vehicles in the set of records includes performing an extended search of the vehicle record database for records that include first vehicle identifier data that nearly match the first vehicle identifier data obtained for the transacting vehicle, the extended search being conditioned on no vehicle identification records being found that include first vehicle identifier data that exactly match the first vehicle identifier data obtained for the transacting vehicle.

5. The method of claim 3,

wherein comparing the first vehicle identifier data for the transacting vehicle with the first vehicle identifier data for vehicles in the set of records includes comparing the first vehicle identifier data using predetermined matching criteria, and

further comprising changing the predetermined matching criteria to increase the number of vehicles in the identified set of vehicles.

6. The method of claim 5, wherein changing the predetermined matching criteria to increase the number of vehicles in the identified set of vehicles is conditioned on a failure to identify any vehicles in the set of vehicles as the transacting vehicle based on results of the comparison of second vehicle identifier data.

7. The method of claim 2,

further comprising accessing laser signature data,

wherein the laser signature data comprises data obtained by using a laser to scan the transacting vehicle.

8. The method of claim 7, wherein the laser signature data includes one or more of an overhead electronic profile of the transacting vehicle, an axle count of the transacting vehicle, and a 3D image of the transacting vehicle.

9. The method of claim 7,

further comprising comparing laser signature data for the transacting vehicle with laser signature data for vehicles in the set of records, and

wherein identifying a set of vehicles from the vehicles having records in the set of records includes identifying the set of vehicles based on the results of the comparison of the first vehicle identifier data and the results of the comparison of the laser signature data or the inductive signature data.

10. The method of claim 2,

further comprising accessing inductive signature data,

wherein the inductive signature data comprises data obtained through use of a loop array over which the transacting vehicle passes.

11. The method of claim 10, wherein the inductive signature data includes one or more of an axle count of the transacting vehicle, a type of engine of the transacting vehicle, and a vehicle type or class for the transacting vehicle.

12. The method of claim 10,

further comprising comparing laser signature data for the transacting vehicle with laser signature data for vehicles in the set of records, and

wherein identifying a set of vehicles from the vehicles having records in the set of records includes identifying the set of vehicles based on the results of the comparison of the first vehicle identifier data and the results of the comparison of the inductive signature data.

13. The method of claim 2, wherein identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle includes identifying the vehicle candidate as the transacting vehicle if the comparison of the second vehicle identifier data for the transacting vehicle with the second vehicle identifier data for the vehicle candidate in the set of vehicle candidates indicates a match having a confidence level that exceeds a confidence threshold.

14. The method of claim 13, wherein identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle includes identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle without human intervention if the confidence level of the match exceeds a first confidence threshold.

15. The method of claim 14, wherein identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle includes identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle if the confidence level of the match is less than the first confidence threshold but greater than a second confidence threshold and a human operator confirms the match.

16. The method of claim 15, further comprising enabling the human operator to confirm or reject the match by:

enabling the human operator to perceive the accessed image data for the transacting vehicle,

enabling the human operator to perceive one or more reference images associated with the vehicle candidate, and

enabling the human operator to interact with a user interface to indicate rejection or confirmation of the match.

17. The method of claim 15, wherein identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle includes identifying the vehicle candidate as the transacting vehicle if the confidence level of the match is less than the first and second confidence thresholds and a human operator manually identifies the vehicle candidate as the transacting vehicle by accessing the image data for the transacting vehicle and the record for the vehicle candidate in the set of records.

18. The method of claim 2, wherein identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle includes identifying the vehicle candidate based on vehicle identification number (VIN), laser signature, inductive signature, and image data.

19. The method of claim 2, wherein identifying a set of vehicle candidates based on the results of the comparison of the license plate data comprises identifying multiple vehicle candidates as corresponding to the transacting vehicle based on the results of the comparison of the first vehicle identifier data.

20. The method of claim 2, wherein the second vehicle identifier comprises vehicle fingerprint data for the transacting vehicle, the vehicle fingerprint data for the transacting vehicle being based on the accessed image data for the transacting vehicle.

21. An apparatus for identifying a vehicle in a toll system, the apparatus comprising:

an image capture device configured to capture image data for a vehicle transacting with a toll system; and

one or more processing devices communicatively coupled to each other and to the image capture device and configured to;

access the image data for the transacting vehicle;

obtain first vehicle identifier data from the accessed image data for the transacting vehicle;

access a set of records that includes first vehicle identifier data for vehicles;

execute, using at least one processing device, an algorithm to;

compare the first vehicle identifier data for the transacting vehicle with the first vehicle identifier data for vehicles in the set of records, and

identify a set of vehicle candidates from the vehicles having records in the set of records, wherein the identified set of vehicle candidates excludes at least one vehicle having a record in the set of records; and

select, from the set of vehicle candidates, a vehicle candidate as corresponding to the transacting vehicle by;

accessing second vehicle identifier data for the transacting vehicle, the second vehicle identifier data being data for identifying a vehicle that is distinct from first vehicle identifier data,

accessing second vehicle identifier data for a vehicle candidate in the set of vehicle candidates,

comparing, using the at least one processing device, the second vehicle identifier data for the transacting vehicle with the second vehicle identifier data for the vehicle candidate in the set of vehicle candidates, and

identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle based on results of the comparison of second vehicle identifier data.

22. A computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:

accessing image data captured by an image capture device, the image data corresponding to a vehicle transacting with a toll system;

obtaining first vehicle identifier data from the accessed image data for the transacting vehicle;

accessing a set of records that includes first vehicle identifier data for vehicles;

executing an algorithm to;

compare the first vehicle identifier data for the transacting vehicle with the first vehicle identifier data for vehicles in the set of records, and

identify a set of vehicle candidates from the vehicles having records in the set of records, wherein the identified set of vehicle candidates excludes at least one vehicle having a record in the set of records; and

selecting, from the set of vehicle candidates, a vehicle candidate as corresponding to the transacting vehicle by;

accessing second vehicle identifier data for the transacting vehicle, the second vehicle identifier data being data for identifying a vehicle that is distinct from first vehicle identifier data,

accessing second vehicle identifier data for a vehicle candidate in the set of vehicle candidates,

comparing, using the at least one processing device, the second vehicle identifier data for the transacting vehicle with the second vehicle identifier data for the vehicle candidate in the set of vehicle candidates, and

identifying the vehicle candidate in the set of vehicle candidates as the transacting vehicle based on results of the comparison of second vehicle identifier data.