Driver identification based on driving maneuver signature

• US 9,390,568 B2
• Filed: 01/23/2015
• Issued: 07/12/2016
• Est. Priority Date: 12/19/2011
• Status: Active Grant

• Current Assignee: Lytx, Inc.
• Original Assignee: Lytx, Inc.
• Inventors: Nemat-Nasser, Syrus C., Smith, Andrew Tombras, Boer, Erwin R.
• Primary Examiner(s): Shaawat, Mussa A
• Assistant Examiner(s): INGRAM, THOMAS P
• Application Number:
  US14/604,588
• Publication Number:
  US 20150235485A1
• Time in Patent Office: 536 Days
• US Class Current: 1/1
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06F 7/00 Methods or arrangements for processing data by operating upon the order or content of the data handled logic circuits H03K19/00
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06V 20/597 Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/08 Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
• CPC Class Codes: G07C 5/0808 Diagnosing performance data testing of vehicles G01M17/00; testing of electrical installation on vehicles G01R31/005
• CPC Class Codes: G07C 5/0816 Indicating performance data, e.g. occurrence of a malfunction
• CPC Class Codes: G07C 5/085 using electronic data carriers
• CPC Class Codes: G07C 5/12 in graphical form
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: G08G 1/16 Anti-collision systems road vehicle drive control systems for predicting or avoiding probable or impending collision otherwise than by control of a particular sub-unit B60W30/08

Abstract

A system for driver identification comprises a processor and a memory. The processor is configured to receive a driving maneuver signature and to determine a driver identification based at least in part on the driving maneuver signature. The memory is coupled to the processor and is configured to provide the processor with instructions.

Claims

1. A system for driver identification, comprising:

a processor configured to;

receive driving data captured during vehicle operation comprising at least a GPS location data;

determine a driving maneuver signature at a specific location from the driving data and the GPS location data, wherein the specific location is common to a plurality of trips in a database of previously stored set of driving maneuver signatures associated with known drivers; and

determine a driver identification based at least in part on the driving maneuver signature at the specific location by comparing the driving maneuver signature with the previously stored set of driving maneuver signatures associated with known drivers at the specific location and determining a known driver with a highest similarity; and

a memory coupled to the processor configured to provide the processor with instructions.

2. The system of claim 1, wherein the driving maneuver signature comprises a set of vehicle sensor data.

3. The system of claim 2, wherein the set of sensor data comprises one or more of the following:

a longitudinal velocity time profile, a lateral velocity time profile, an angular velocity profile, a steering wheel angle time profile, a steering wheel angle, a gas pedal position, a brake pedal position, a yaw rate, a pitch rate, or a roll rate.

4. The system of claim 1, wherein the driving maneuver signature is associated with a specific trip.

5. The system of claim 1, wherein a similarity metric is used to measure similarity between the driving maneuver signature and the previously stored set of driving maneuver signatures.

6. The system of claim 1, wherein the driving data is segmented into driving maneuvers based on defined periods of time during which vehicle sensor data is active.

7. The system of claim 1, wherein the driving maneuver signature comprises one or more of the following driving maneuvers:

a right/left turn maneuver, a highway on/off ramp maneuver, a U-turn maneuver, a lane change maneuver, a vehicle launching from stop maneuver, a vehicle braking maneuver, a curve-handling maneuver, and a car following maneuver.

8. A method for driver identification, comprising:

receiving driving data captured during vehicle operation comprising at least a GPS location data and a vehicle sensor data;

determining a driving maneuver signature at a specific location from the driving data and the GPS location data, wherein the specific location is common to a plurality of trips in a database of previously stored set of driving maneuver signatures associated with known drivers; and

determining, using a processor, a driver identification based at least in part on the driving maneuver signature at the specific location by comparing the driving maneuver signature with the previously stored set of driving maneuver signatures associated with known drivers at the specific location and determining a known driver with a highest similarity.

9. The method of claim 8, wherein the driving maneuver signature comprises a set of vehicle sensor data.

10. The method of claim 9, wherein the set of sensor data comprises one or more of the following:

a longitudinal velocity time profile, a lateral velocity time profile, an angular velocity profile, a steering wheel angle time profile, a steering wheel angle, a gas pedal position, a brake pedal position, a yaw rate, a pitch rate, or a roll rate.

11. The method of claim 8, wherein the driving maneuver signature is associated with a specific trip.

12. The method of claim 8, wherein a similarity metric is used to measure the similarity between the driving maneuver signature and the previously stored set of driving maneuver signatures.

13. The method of claim 8, wherein the driving data is segmented into driving maneuvers based on defined periods of time during which vehicle sensor data is active.

14. The method of claim 8, wherein the driving maneuver signature comprises one or more of the following driving maneuvers:

a right/left turn maneuver, a highway on/off ramp maneuver, a U-turn maneuver, a lane change maneuver, a vehicle launching from stop maneuver, a vehicle braking maneuver, a curve-handling maneuver, and a car following maneuver.

15. A computer program product for driver identification, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:

receiving driving data captured during vehicle operation comprising at least a GPS location data and a vehicle sensor data;

determining a driving maneuver signature at a specific location from the driving data and the GPS location data, wherein the specific location is common to a plurality of trips in a database of previously stored set of driving maneuver signatures associated with known drivers; and

determining a driver identification based at least in part on the driving maneuver signature at the specific location by comparing the driving maneuver signature with the previously stored set of driving maneuver signatures associated with known drivers at the specific location and determining a known driver with a highest similarity.

16. The computer program product of claim 15, wherein the driving maneuver signature comprises a set of vehicle sensor data.

17. The computer program product of claim 16, wherein the set of sensor data comprises one or more of the following:

a longitudinal velocity time profile, a lateral a velocity time profile, an angular velocity profile, a steering wheel angle time profile, a steering wheel angle, a gas pedal position, a brake pedal position, a yaw rate, a pitch rate, or a roll rate.

18. The computer program product of claim 15, wherein the driving maneuver signature is associated with a specific trip.

19. The computer program product of claim 15, wherein a similarity metric is used to measure the similarity between the driving maneuver signature and the previously stored set of driving maneuver signatures.

20. The computer program product of claim 15, wherein the driving data is segmented into driving maneuvers based on defined periods of time during which vehicle sensor data is active.

21. The computer program product of claim 15, wherein the driving maneuver signature comprises one or more of the following driving maneuvers:

a right/left turn maneuver, a highway on/off ramp maneuver, a U-turn maneuver, a lane change maneuver, a vehicle launching from stop maneuver, a vehicle braking maneuver, a curve-handling maneuver, and a car following maneuver.