Systems and methods for authenticating drivers based on GPS data

• US 10,339,287 B2
• Filed: 03/06/2018
• Issued: 07/02/2019
• Est. Priority Date: 06/27/2017
• Status: Active Grant

• Current Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Original Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Inventors: Chowdhury, Arijit, Ghose, Avik, Chakravarty, Tapas
• Primary Examiner(s): Nguyen, Nam V
• Application Number:
  US15/913,515
• Publication Number:
  US 20180373855A1
• Time in Patent Office: 483 Days
• Field of Search: 340 581, 340 58, 340 52, 340 572, 701 1, 701 25, 477159, 477183
• CPC Class Codes: B60W 2040/0809 Driver authorisation; Driver identity check
• CPC Class Codes: B60W 2540/30 Driving style
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: B60W 40/10 related to vehicle motion
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 21/316 by observing the pattern of computer usage, e.g. typical user behaviour
• 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

Abstract

Currently automobiles use embedded sensors and computational powers for performance optimization. For better performance and maintenance knowing driver and driving style is important. It is known that driver identification can be achieved using dedicated sensors. Since these are external sensors they add to cost and also deployment of many sensors increases operational and maintenance overhead. Embodiments of the present disclosure obtain GPS data including trip information pertaining to a vehicle being driven by a driver and features are extracted from trip information which are ranked by comparing these features with features associated with trip information of other drivers to selectively identify and obtain ranked features. Value of each ranked feature is compared with value of corresponding feature pertaining to driving patterns and an abnormality score for each relevant feature is generated and the driver is authenticated based on the abnormality score.

Claims

1. A processor implemented method, comprising:

obtaining, from a Global Positioning System (GPS), GPS data comprising trip information pertaining to a vehicle being driven by a driver;

extracting one or more features from the trip information;

ranking the one or more features from the trip information by performing a first comparison of the one or more features with a plurality of features associated with a plurality of trip information pertaining to other drivers to selectively identify and obtain one or more ranked features, wherein the one or more ranked features are selectively identified based on the trip information and historical data pertaining to one or more driving patterns of the driver stored in a database, and wherein the one or more ranked features are associated with a corresponding importance value;

performing a second comparison of (i) the importance value of each ranked feature from the one or more ranked features and (ii) a value of corresponding feature pertaining to the one or more driving patterns stored in the database;

generating an abnormality score for each of the ranked feature based on the second comparison; and

authenticating the driver based on the abnormality score.

2. The processor implemented method of claim 1, wherein the step of authenticating the driver based on the abnormality score comprises:

performing a third comparison of the abnormality score with a first pre-defined threshold; and

authenticating the driver based on the third comparison.

3. The processor implemented method of claim 2, wherein when the abnormality score does not match the first pre-defined threshold, the method comprises:

generating an average abnormality score based on the abnormality score for each of the relevant feature; and

authenticating the driver based on the average abnormality score.

4. The processor implemented method of claim 3, wherein the step of authenticating the driver based on the average abnormality score comprises:

performing a fourth comparison of the average abnormality score and a second pre-defined threshold; and

authenticating the driver based on the fourth comparison.

5. The processor implemented method of claim 3, further comprising upon the driver being authenticated based on the abnormality score or the average abnormality score, updating a driver profile for the driver in the database.

6. The processor implemented method of claim 1, wherein the step of extracting the one or more features from the trip information comprises:

obtaining a primary data from the trip information, and deriving a secondary data from the primary data; and

extracting the one or more features from the primary data and the secondary data.

7. A system, comprising:

a memory storing instructions, and a database comprising one or more driving patterns and one or more driver profiles;

one or more communication interfaces; and

one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to;

obtain, from a Global Positioning System (GPS), GPS data comprising trip information pertaining to a vehicle being driven by a driver;

extract one or more features from the trip information;

rank the one or more features from the trip information by performing a first comparison of the one or more features with a plurality of features associated with a plurality of trip information pertaining to other drivers to selectively identify and obtain one or more ranked features, wherein the one or more ranked features are selectively identified based on the trip information and historical data pertaining to one or more driving patterns of the driver stored in the database, and wherein the one or more ranked features are associated with a corresponding importance value;

perform a second comparison of the importance value of each of the ranked feature from the one or more ranked features and a value of corresponding feature pertaining to the one or more driving patterns stored in the database;

generate an abnormality score for each of the ranked feature based on the second comparison; and

authenticate the driver based on the abnormality score.

8. The system of claim 7, wherein the driver is authenticated based on the abnormality score by:

performing a third comparison of the abnormality score with a first pre-defined threshold; and

authenticating the driver based on the third comparison.

9. The system of claim 8, wherein when the abnormality score does not match the first pre-defined threshold, the one or more hardware processors are further configured by the instructions to:

generate an average abnormality score based on the abnormality score for each of the relevant feature; and

authenticate the driver based on the average abnormality score.

10. The system of claim 9, wherein the driver is authenticated based on the average abnormality score by:

performing a fourth comparison of the average abnormality score and a second pre-defined threshold; and

authenticating the driver based on the fourth comparison.

11. The system of claim 9, upon the driver being authenticated based on the abnormality score or the average abnormality score, the one or more hardware processors are further configured by the instructions to update a driver profile of the driver in the database.

12. The system of claim 7, wherein the one or more features are extracted from the trip information by:

obtaining a primary data from the trip information, and deriving a secondary data from the primary data; and

extracting the one or more features from the primary data and the second data.

13. One or more non-transitory machine readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors causes:

obtaining, from a Global Positioning System (GPS), GPS data comprising trip information pertaining to a vehicle being driven by a driver;

extracting one or more features from the trip information;

ranking the one or more features from the trip information by performing a first comparison of the one or more features with a plurality of features associated with a plurality of trip information pertaining to other drivers to selectively identify and obtain one or more ranked features, wherein the one or more ranked features are selectively identified based on the trip information and historical data pertaining to one or more driving patterns of the driver stored in a database, and wherein the one or more ranked features are associated with a corresponding importance value;

performing a second comparison of (i) the importance value of each ranked feature from the one or more ranked features and (ii) a value of corresponding feature pertaining to the one or more driving patterns stored in the database;

generating an abnormality score for each of the ranked feature based on the second comparison; and

authenticating the driver based on the abnormality score.

14. The one or more non-transitory machine readable information storage mediums of claim 13, wherein the step of authenticating the driver based on the abnormality score comprises:

performing a third comparison of the abnormality score with a first pre-defined threshold; and

authenticating the driver based on the third comparison.

15. The one or more non-transitory machine readable information storage mediums of claim 14, wherein when the abnormality score does not match the first pre-defined threshold, the method comprises:

generating an average abnormality score based on the abnormality score for each of the relevant feature; and

authenticating the driver based on the average abnormality score.

16. The one or more non-transitory machine readable information storage mediums of claim 15, wherein the step of authenticating the driver based on the average abnormality score comprises:

performing a fourth comparison of the average abnormality score and a second pre-defined threshold; and

authenticating the driver based on the fourth comparison.

17. The one or more non-transitory machine readable information storage mediums of claim 15, wherein the one or more instructions which when executed by the one or more hardware processors further causes:

upon the driver being authenticated based on the abnormality score or the average abnormality score, updating a driver profile for the driver in the database.

18. The one or more non-transitory machine readable information storage mediums of claim 13, wherein the step of extracting the one or more features from the trip information comprises:

obtaining a primary data from the trip information, and deriving a secondary data from the primary data; and

extracting the one or more features from the primary data and the secondary data.