Electronic Toll Management and Vehicle Identification

• US 20060278705A1
• Filed: 06/12/2006
• Published: 12/14/2006
• Est. Priority Date: 02/21/2003
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services GmbH (Accenture PLC)
• Inventors: Hedley, Jay E., Thornburg, Neal Patrick
• Granted Patent: US 7,970,644 B2
• Time in Patent Office: Days
• US Class Current: 235/384
• CPC Class Codes: G07B 15/063 using wireless information transmission between the vehicle and a fixed station identification of vehicles G08G

Abstract

Identifying a vehicle in a toll system includes accessing image data for a first vehicle and obtaining license plate data from the accessed image data for the first vehicle. A set of records is accessed. Each record includes license plate data for a vehicle. The license plate data for the first vehicle is compared with the license plate data for vehicles in the set of records. Based on the results of the comparison of the license plate data, a set of vehicles is identified from the vehicles having records in the set of records. Vehicle fingerprint data is accessed for the first vehicle. The vehicle fingerprint data for the first vehicle is based on the image data for the first vehicle. Vehicle fingerprint data for a vehicle in the set of vehicles is accessed. Using a processing device, the vehicle fingerprint data for the first vehicle is compared with the vehicle fingerprint data for the vehicle in the set of vehicles. The vehicle in the set of vehicles is identified as the first vehicle based on results of the comparison of vehicle fingerprint data.

Claims

1. A method of identifying a vehicle in a toll system, the method comprising:

accessing image data for a first vehicle;

obtaining license plate data from the accessed image data for the first vehicle;

accessing a set of records, each record including license plate data for a vehicle;

comparing the license plate data for the first vehicle with the license plate data for vehicles in the set of records;

identifying a set of vehicles from the vehicles having records in the set of records, the set of vehicles being identified based on results of the comparison of the license plate data;

accessing vehicle fingerprint data for the first vehicle, the vehicle fingerprint data for the first vehicle being based on the accessed image data for the first vehicle;

accessing vehicle fingerprint data for a vehicle in the set of vehicles;

comparing, using a processing device, the vehicle fingerprint data for the first vehicle with the vehicle fingerprint data for the vehicle in the set of vehicles; and

identifying the vehicle in the set of vehicles as the first vehicle based on results of the comparison of vehicle fingerprint data.

2. The method of claim 1, wherein comparing license plate data for the first vehicle with the license plate data for vehicles in the set of records includes searching a vehicle record database for records that include license plate data that exactly match the license plate data obtained for the first vehicle.

3. The method of claim 2, wherein comparing license plate data for the first vehicle with the license plate data for vehicles in the set of records includes performing an extended search of the vehicle record database for records that include license plate data that nearly match the license plate data obtained for the first vehicle, the extended search being conditioned on no vehicle identification records being found that include license plate data that exactly match the license plate data obtained for the first vehicle.

4. The method of claim 2, wherein comparing the license plate data for the first vehicle with the license plate data for vehicles in the set of records includes comparing the license plate data using predetermined matching criteria.

5. The method of claim 4, 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 first vehicle based on results of the comparison of vehicle fingerprint data.

7. The method of claim 1, further comprising accessing laser signature data or inductive signature data for the first vehicle.

8. The method of claim 7, wherein the laser signature data comprises data obtained by using a laser to scan the first vehicle.

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

10. The method of claim 7, wherein the inductive signature data comprises data obtained through use of a loop array over which the first vehicle passes.

11. The method of claim 7, wherein the inductive signature data includes one or more of an axle count of the first vehicle, a type of engine of the first vehicle, and a vehicle type or class for the first vehicle.

12. The method of claim 7, wherein each record in the set of records includes laser signature data or inductive signature data for a vehicle.

13. The method of claim 12, further comprising comparing laser signature data or inductive signature data for the first vehicle with laser signature data or inductive signature data for vehicles in the set of records.

14. The method of claim 13, 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 license plate data and the results of the comparison of the laser signature data or the inductive signature data.

15. The method of claim 14, wherein identifying the set of vehicles based on the results of the comparison of the license plate data and the results of the comparison of the laser signature data or inductive signature data includes determining a combined equivalent matching score for each vehicle having a record in the set of records and identifying the set of vehicles as a set of vehicles having combined equivalent matching scores above a predetermined threshold.

16. The method of claim 15, wherein each combined equivalent matching score comprises a weighted combination of a laser or inductive signature matching score and a license plate matching score.

17. The method of claim 13, wherein identifying the vehicle in the set of vehicles as the first vehicle includes identifying the vehicle as the first vehicle based on the results of the comparison of the vehicle fingerprint data and the results of the comparison of the laser signature data or inductive signature data.

18. The method of claim 17, wherein identifying the vehicle in the set of vehicles as the first vehicle based on the results of the comparison of the vehicle fingerprint data and the results of the comparison of the laser signature data or inductive signature data includes determining a combined equivalent matching score for the vehicle in the set of vehicles and determining that the combined equivalent matching score is higher than a predetermined threshold.

19. The method of claim 18, wherein the combined equivalent matching score comprises a weighted combination of a laser or inductive signature matching score and a vehicle fingerprint matching score.

20. The method of claim 1, wherein identifying the vehicle in the set of vehicles as the first vehicle includes identifying the vehicle as the first vehicle if the comparison of the vehicle fingerprint data for the first vehicle with the vehicle fingerprint data for the vehicle in the set of vehicles indicates a match having a confidence level that exceeds a confidence threshold.

21. The method of claim 20, wherein identifying the vehicle in the set of vehicles as the first vehicle includes identifying the vehicle in the set of vehicles as the first vehicle without human intervention if the confidence level of the match exceeds a first confidence threshold.

22. The method of claim 21, wherein identifying the vehicle in the set of vehicles as the first vehicle includes identifying the vehicle in the set of vehicles as the first 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.

23. The method of claim 22, 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 first vehicle, and

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

24. The method of claim 22, wherein identifying the vehicle in the set of vehicles as the first vehicle includes identifying the vehicle as the first 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 as the first vehicle by accessing the image data for the first vehicle and the record for the vehicle in the set of records.

25. The method of claim 24, further comprising enabling the human operator to manually identify the vehicle in the set of vehicles as the first vehicle by:

enabling the human operator to access the image data for the first vehicle,

enabling the human operator to access the record for the vehicle in the set of records, and

enabling the human operator to interact with a user interface to indicate positive identification of the first vehicle as the vehicle in the set of vehicles.

26. The method of claim 25, further comprising enabling the human operator to manually identify the vehicle in the set of vehicles as the first vehicle by enabling the human operator to access data stored in databases of external systems.

27. The method of claim 1, wherein identifying the vehicle in the set of vehicles as the first vehicle includes identifying the vehicle by combining vehicle identification number (VIN), laser signature, inductive signature, and image data.

28. An article comprising a machine-readable medium storing machine-executable instructions that, when applied to a machine, cause the machine to perform operations comprising:

accessing image data for a first vehicle;

obtaining license plate data from the accessed image data for the first vehicle;

accessing a set of records, each record including license plate data for a vehicle;

comparing the license plate data for the first vehicle with the license plate data for vehicles in the set of records;

identifying a set of vehicles from the vehicles having records in the set of records, the set of vehicles being identified based on results of the comparison of the license plate data;

accessing vehicle fingerprint data for the first vehicle, the vehicle fingerprint data for the first vehicle being based on the accessed image data for the first vehicle;

accessing vehicle fingerprint data for a vehicle in the set of vehicles;

comparing the vehicle fingerprint data for the first vehicle with the vehicle fingerprint data for the vehicle in the set of vehicles; and

identifying the vehicle in the set of vehicles as the first vehicle based on results of the comparison of vehicle fingerprint data.

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

an image capture device configured to capture image data for a first vehicle; and

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

obtain license plate data from the captured image data for the first vehicle;

access a set of records, each record including license plate data for a vehicle;

compare the license plate data for the first vehicle with the license plate data for vehicles in the set of records;

identify a set of vehicles from the vehicles having records in the set of records, the set of vehicles being identified based on results of the comparison of the license plate data;

access vehicle fingerprint data for the first vehicle, the vehicle fingerprint data for the first vehicle being based on the captured image data for the first vehicle;

access vehicle fingerprint data for a vehicle in the set of vehicles;

compare the vehicle fingerprint data for the first vehicle with the vehicle fingerprint data for the vehicle in the set of vehicles; and

identify the vehicle in the set of vehicles as the first vehicle based on results of the comparison of vehicle fingerprint data.

30. A method of identifying a vehicle in a toll system, the method comprising:

accessing image or sensor data for a target vehicle;

extracting a first identifier and a second identifier from the image or sensor data;

using the extracted first identifier to identify a set of one or more vehicle candidates as potential matches for the target vehicle; and

using the extracted second identifier to identify the target vehicle as a vehicle selected from the set of one or more vehicle candidates.

31. The method of claim 30, wherein using the extracted first identifier to identify a set of one or more vehicle candidates comprises including a vehicle in the set of one or more vehicle candidates if a vehicle identifier for the vehicle matches the extracted first identifier.

32. The method of claim 30, wherein using the extracted first identifier to identify a set of one or more vehicle candidates comprises including a vehicle in the set of one or more vehicle candidates if a vehicle identifier for the vehicle matches within a range around the extracted first identifier.