IP Library Granted Patent US 8,775,236
Granted Patent B2
US 8,775,236 · App. 13/907,133 · Granted Jul 8, 2014

Electronic toll management and vehicle identification

Inventors: Jay E. Hedley (Arlington, VA); Neal Patrick Thornburg (Charlotte, NC)
Assignee: Accenture Global Services Limited
G08G1/017
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 8,775,236
App. No.
13/907,133
Granted
Jul 8, 2014
Kind
B2
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 (75)

1. 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,

wherein executing the 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 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, and

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.

2. The method of claim 1 ,

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.

3. The method of claim 2 , 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.

4. The method of claim 1 ,

further comprising accessing laser signature data,

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

5. The method of claim 4 , 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.

6. The method of claim 4 ,

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.

7. The method of claim 1 ,

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.

8. The method of claim 7 , 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.

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 inductive signature data.

10. The method of claim 1 , 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.

11. The method of claim 10 , 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.

12. The method of claim 11 , 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.

13. The method of claim 12 , 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.

14. The method of claim 12 , 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.

15. The method of claim 1 , 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.

16. The method of claim 1 , 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.

17. 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 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 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,

wherein the one or more processing devices being configured to execute 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 comprises the one or more processing devices being configured to:

search 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, and

perform 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.

18. 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 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,

wherein executing the 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 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, and

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.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 21, 2013
From: HEDLEY, JAY E.; THORNBURG, NEAL PATRICK
To: ACCENTURE GLOBAL SERVICES GMBH
Reel/Frame 031050/0832 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 21, 2013
From: ACCENTURE GLOBAL SERVICES GMBH
To: ACCENTURE GLOBAL SERVICES LIMITED
Reel/Frame 031050/0878 →
Continuity (6)
Continuation 13608510 · Sep 10, 2012
Continuation 13113125 · May 23, 2011
Continuation 11423683 · Jun 12, 2006
Continuation In Part 10371549 · Feb 21, 2003
Provisional Application 60689050 · Jun 10, 2005
Related Publication 20130346165A1 · Dec 26, 2013