Authenticating Drivers

• US 20180270241A1
• Filed: 03/14/2017
• Published: 09/20/2018
• Est. Priority Date: 03/14/2017
• Status: Active Grant

• Current Assignee: Allstate Insurance Company (Allstate Corporation)
• Original Assignee: Allstate Insurance Company (Allstate Corporation)
• Inventors: Herrmann, Alexander, Walsh, Connor, Harish, Pratheek M.
• Granted Patent: US 10,250,611 B2
• Time in Patent Office: Days
• CPC Class Codes: B62D 15/021 Determination of steering angle
• CPC Class Codes: B62D 15/025 Active steering aids, e.g. helping the driver by actively influencing the steering system after environment evaluation B62D1/28 takes precedence
• CPC Class Codes: G01C 21/14 by recording the course traversed by the object G01C21/16 takes precedence
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 21/316 by observing the pattern of computer usage, e.g. typical user behaviour
• CPC Class Codes: G06F 2221/2111 Location-sensitive, e.g. geographical location, GPS
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: H04L 63/102 Entity profiles
• CPC Class Codes: H04W 12/06 Authentication
• CPC Class Codes: H04W 12/63 Location-dependent; Proximity-dependent
• CPC Class Codes: H04W 12/68 Gesture-dependent or behaviour-dependent
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]

Abstract

One or more devices in a data analysis computing system may be configured to receive and analyze movement data and determine driving trips based on the received data. The driving trips may be used along with the movement data to authenticate drivers based on a determined driver profile.

Claims

1. A device, comprising:

a processor; and

memory storing computer-executable instructions that, when executed by the processor, cause the device to;

receive GPS data indicating location data of the device collected during a driving trip;

receive movement data associated with at least one movement sensor of the device, the movement data indicating movement detected during the driving trip;

analyze the received GPS data and the received moment data to determine stopping points and a total number of turns during the driving trip; and

determine a driving pattern for the driving trip, based at least in part on the determined stopping points and number of turns.

2. The device of claim 1, further comprising:

determine a driving profile for the driving trip, based on the determined driving pattern;

compare the determined driving profile to previously determined driver profiles and a background driver profile;

determine an identity of a driver of the driving trip, based on the comparison to the previously determined driver profiles and the background driver profile; and

display data corresponding to the determined identity of the driver.

3. The device of claim 1, wherein the device is one of a smartphone, tablet computer, or vehicle-based computer system.

4. (canceled)

5. A method, comprising:

receiving, at a movement data analysis computing device, GPS and movement data collected by at least one movement sensor of the movement data analysis computing device and during a driving trip;

analyzing by the movement data analysis computing device, the received GPS and movement data to determine stopping points and a total number of turns during the driving trip;

determining, by the movement data analysis computing device, a driving pattern for the driving trip, based at least in part on the determined stopping points and number of turns;

determining, by the movement data analysis computing device, a driving profile for the driving trip based on the determined driving pattern; and

displaying, by the movement data analysis computing device, data corresponding to the determined driving pattern.

6. The method of claim 5, further comprising:

comparing the determined driving profile to previously determined driver profiles and a background driver profile;

determining an identity of a driver of the driving trip, based on the comparison to the previously determined driver profiles and the background driver profile; and

displaying data corresponding to the determined identity of the driver.

7. (canceled)

8. A method, comprising:

receiving, at a movement data analysis computing device, GPS and movement data collected during one or more driving trips, by at least one movement sensor of the movement data analysis computing device;

extracting, by the movement data analysis computing device and from the GPS and movement data, unlabeled driving trips, wherein each of the unlabeled driving trips is a driving trip in which a user of the movement data analysis computing device is not identified as a driver of the driving trip; and

for each driving trip for the unlabeled driving trips;

determining, by the movement data analysis computing device, a driving pattern, based on the GPS and movement data associated with the driving trip;

determining, by the movement data analysis computing device, a driving profile, based on the determined driving pattern for the driving trip;

comparing the determined driving profile for the driving trip with other determined driver profiles; and

authenticating driver identity.

9. The method of claim 8 further comprising, displaying, by the movement data analysis computing device and for each driving trip of the unlabeled driving trips, data corresponding to the determined driving pattern for the driving trip.

10. The method of claim 8, further comprising:

comparing, for each driving trip of the unlabeled driving trips, the determined driving profile for the driving trip to a background driver profile;

wherein authenticating the driver identify comprises determining an identity of the driver for the driving trips, based on the comparison to the other determined driver profiles and the comparison to the background driver profile; and

displaying, for each driving trip of the unlabeled driving trips, data corresponding to the authenticated driver.

11. The method of claim 8, further comprising:

extracting a set of labeled driving trips, wherein the labeled driving trips is a driving trip in which the user is identified as the driver of the driving trip; and

determining a user driver profile based on the extracted set of labeled driving trips.

12. The method of claim 8, further comprising:

extracting a set of labeled driving trip data, wherein the labeled driving trip data is data associated with a driving trip in which the user is identified as the driver of the driving trip; and

generating a background driver profile based at least in part on the extracted set of labeled driving trip data.

13. The method of claim 12, further comprising, for each driving trip of the unlabeled driving trips:

comparing the determined driving profile to the background driver profile;

determining an identity of a driver based on the comparison to previously determined driver profiles and the background driver profile; and

displaying data corresponding to the authenticated driver.

14. The method of claim 8, further comprising, for each driving trip of the unlabeled driving trips;

determining stopping points within the associated GPS and movement data;

determining a total number of turns within the ass., d movement data; and

determining the driving pattern based on at least the determined stopping points and the determined number of turns.

15. The method of claim 8, further comprising, for each driving trips of the unlabeled driving trips, determining a starting point latitude and an end point latitude within the associated GPS and movement data.

16. The method of claim 8, further comprising, for each driving trip of the unlabeled driving trips, determining a start time and an end time of day within the associated GPS and movement data.

17. The method of claim 8, further comprising, for each driving trip of the unlabeled driving trips, determining distance traveled associated within the associated GPS and movement data.

18. The method of claim 8, further comprising, for each driving trip of the unlabeled driving trips:

determining steering wheel angle positions within the associated GPS and movement data; and

determining the driving pattern based on at least the determined steering wheel angle positons.

19. The method of claim 8, further comprising, for each driving trip of the unlabeled driving trips:

determining brake pedal positions within the associated GPS and movement data; and

determining the driving pattern based on at least the determined brake pedal positons.

20. The method of claim 8, further comprising, for each driving trip of the unlabeled driving trips:

determining gas pedal positions within the associated GPS and movement data; and

determining the driving pattern based on at least the determined gas pedal positons.

21. The method of claim 11, wherein the user is identified as the driver based on a likelihood of the user driving during the driving trip exceeding a predetermined threshold or based on receiving a user input identifying the user as the driver of the driving trip.

22. The method of claim 12, wherein the user is identified as the driver based on a likelihood of the user driving during the driving trip exceeding a predetermined threshold or based on receiving a user input identifying the user as the driver of the driving trip.