Automatically identifying drivers

• US 9,842,437 B2
• Filed: 06/29/2015
• Issued: 12/12/2017
• Est. Priority Date: 06/29/2015
• Status: Active Grant

• Current Assignee: Arity International Limited (Allstate Corporation)
• Original Assignee: Allstate Insurance Company (Allstate Corporation)
• Inventors: Biemer, Edward A.
• Primary Examiner(s): Smith, Jelani
• Assistant Examiner(s): Martinez Borrero, Luis A
• Application Number:
  US14/753,782
• Publication Number:
  US 20160375908A1
• Time in Patent Office: 897 Days
• Field of Search: 701 1, 701 2, 701117, 701119, 701118, 701 22, 701532, 701 99, 701123, 701 23, 701102, 701 19, 701 21, 701 36, 705 4, 705 13, 705306, 705 39, 705 40, 705400
• CPC Class Codes: B60K 2360/573 Mobile devices controlling vehicle functions
• CPC Class Codes: B60K 2370/573 Mobile devices controlling vehicle functions
• CPC Class Codes: B60K 35/80 Arrangements for controlling instruments
• CPC Class Codes: B60W 2040/0809 Driver authorisation; Driver identity check
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2520/105 Longitudinal acceleration
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: B60W 40/08 related to drivers or passengers
• 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

Abstract

One or more devices in a data analysis computing system may be configured to receive and analyze movement data and driving data, and determine driving trips and associated drivers based on the received data. Movement data may be collected by one or more mobile devices, such as smartphones, tablet computers, and on-board vehicle systems. Drivers associated with driving trips may be identified based on the movement data collected by the mobile devices, such as speed data, acceleration data, or distance data.

Claims

1. A device, comprising:

a clock configured to record time of day associated with the device;

a processor; and

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

(a) receive movement data collected by at least one movement sensor;

(b) receive time of day data associated with the received movement data;

(c) determine that a user is driving;

(d) determine a driving pattern for the user based on the received movement data and time of day data;

(e) compare the driving pattern of the user to previously stored driving patterns;

(f) determine a driver based on the comparison; and

(g) output data corresponding to the determined driver;

wherein the device comprises a movement data analysis software application that is automatically initiated by the device and automatically operates as a background application to cause the device to automatically carry out steps (a) through (g) without any specific user input to launch the movement data analysis software application;

wherein the device comprises one or more caches to reduce memory latency and access time,

wherein the one or more caches is from the group consisting of a CPU cache and a database cache, wherein the processor is configured to retrieve data from or write data to the CPU cache rather than retrieve data or write data to the memory, wherein the database cache is on an application server of the device separate from a database server and is configured to cache data from a database of the memory, and the processor is configured to retrieve data from the database cache without needing to communicate over a network with a back-end database server.

2. The device of claim 1, wherein the movement data comprises at least one of acceleration data or speed data, and wherein the device further comprises at least one of an accelerometer or speedometer configured to collect the movement data.

3. The device of claim 2, wherein the device is one of a smartphone, tablet computer, or vehicle-based computer system.

4. The device of claim 1, wherein the memory further comprises computer-executable instructions that, when executed by the processor, cause the device to:

determine stopping points within the movement data;

determine a total number of turns within the movement data; and

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

5. The device of claim 4, wherein the memory further comprises computer-executable instructions that, when executed by the processor, cause the device to:

determine a first point within the determined stopping points that corresponds to a first stop sign or stop light encountered during a driving trip.

6. The device of claim 5, wherein the memory further comprises computer-executable instructions that, when executed by the processor, cause the device to:

determine a second point within said determined stopping points that corresponds to a second stop sign or stop light encountered during the driving trip.

7. The device of claim 6, wherein the memory further comprises computer-executable instructions that, when executed by the processor, cause the device to:

determine a number of left turns and a number of right turns from the determined total number of turns.

8. The device of claim 7, wherein the memory further comprises computer-executable instructions that, when executed by the processor, cause the device to:

determine the driving pattern based on the determined first point, determined second point, determined number of left turns, and determined number of right turns.

9. The device of claim 8, wherein the memory further comprises computer-executable instructions that, when executed by the processor, cause the device to:

compare the driving pattern to a plurality of previously stored driving patterns; and

determine a driver based on the comparison.

10. A method, comprising:

(a) receiving, at a movement data analysis computing device, movement data collected by at least one movement sensor;

(b) receiving, by the movement data analysis computing device time of day data associated with the received movement data;

(c) determining, by the movement data analysis computing device that a user is driving;

(d) determining, by the movement data analysis computing device, a driving pattern for the user based on the received movement data and time of day data;

(e) comparing, by the movement data analysis computing device, the driving pattern of the user to previously stored driving patterns;

(f) determining, by the movement data analysis computing device, a driver based on the comparison; and

(g) outputting, by the movement data analysis computing device, data corresponding to the determined driver;

wherein the movement data analysis computing device comprises a movement data analysis software application that is automatically initiated by the movement data analysis computing device and automatically operates as a background application to cause the movement data analysis computing device to automatically carry out steps (a) through (g) without any specific user input to launch the movement data analysis software application;

wherein the device comprises one or more caches to reduce memory latency and access time,

wherein the one or more caches is from the group consisting of a CPU cache and a database cache, wherein the processor is configured to retrieve data from or write data to the CPU cache rather than retrieve data or write data to the memory, wherein the database cache is on an application server of the device separate from a database server and is configured to cache data from a database of the memory, and the processor is configured to retrieve data from the database cache without needing to communicate over a network with a back-end database server.

11. The method of claim 10, wherein the movement data comprises at least one of:

acceleration data collected by an accelerometer or speed data collected by a speedometer.

12. The method of claim 10, further comprising:

determining stopping points within the movement data;

determining a total number of turns within the movement data; and

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

13. The method of claim 12, wherein determining stopping points within said movement data comprises:

determining a first point within the determined stopping points that corresponds to a first stop sign or stop light encountered during a driving trip.

14. The method of claim 13, wherein determining stopping points within said movement data comprises:

determining a second point within said determined stopping points that corresponds to a second stop sign or stop light encountered during the driving trip.

15. The method of claim 14, wherein determining a driver comprises analyzing a subset of the movement data proximate to the determined stopping points that comprises:

determining a number of left turns and a number of right turns from the determined total number of turns.

16. The method of claim 15, wherein determining the driver of the driving trip comprises:

determining the driving pattern based on the determined first point, determined second point, determined number of left turns, and determined number of right turns.

17. The method of claim 16, wherein comparing the driving pattern comprises:

comparing the driving pattern to a plurality of previously stored driving patterns; and

determining a driver based on the comparison.

18. A device, comprising:

an accelerometer configured to acceleration associated with the device;

a processor; and

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

(a) receive movement data collected by at least one movement sensor;

(b) receive acceleration data associated with the received movement data;

(c) determine that a user is driving;

(d) determine a driving pattern for the user based on the received movement and acceleration data;

(e) compare the driving pattern of the user to previously stored driving patterns;

(f) determine a driver based on the comparison; and

(g) output data corresponding to the determined driver;

wherein the device comprises a movement data analysis software application that is automatically initiated by the device and automatically operates as a background application to cause the device to automatically carry out steps (a) through (g) without any specific user input to launch the movement data analysis software application;

wherein the device comprises one or more caches to reduce memory latency and access time,

wherein the one or more caches is from the group consisting of a CPU cache and a database cache, wherein the processor is configured to retrieve data from or write data to the CPU cache rather than retrieve data or write data to the memory, wherein the database cache is on an application server of the device separate from a database server and is configured to cache data from a database of the memory, and the processor is configured to retrieve data from the database cache without needing to communicate over a network with a back-end database server.

19. The device of claim 18, wherein the memory further comprises computer-executable instructions that, when executed by the processor, cause the device to:

determine stopping points within the movement data;

determine a total number of turns within the movement data; and

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

20. The device of claim 19, wherein the memory further comprises computer-executable instructions that, when executed by the processor, cause the device to:

determine a first point within the determined stopping points that corresponds to a first stop sign or stop light encountered during a driving trip.