Systems and methods for detecting mobile device movement within a vehicle using accelerometer data

• US 9,867,015 B1
• Filed: 03/27/2017
• Issued: 01/09/2018
• Est. Priority Date: 09/13/2016
• Status: Active Grant

• Current Assignee: Arity International Limited (Allstate Corporation)
• Original Assignee: Allstate Insurance Company (Allstate Corporation)
• Inventors: Mukhtar, Yasir, Nagpal, Varun, Snyder, Jared S., Walsh, Connor
• Primary Examiner(s): Siddiqui, Kashif
• Application Number:
  US15/470,263
• Time in Patent Office: 288 Days
• CPC Class Codes: G01C 21/18 Stabilised platforms, e.g. by gyroscope
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: H04M 1/724098 Interfacing with an on-board device of a vehicle for hands-free speaking in vehicles H04M1/6075
• CPC Class Codes: H04M 1/724631 by limiting the access to the user interface, e.g. locking a touch-screen or a keypad
• CPC Class Codes: H04M 2250/10 including a GPS signal receiver
• CPC Class Codes: H04W 4/026 using orientation information, e.g. compass
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information

Abstract

One or more mobile device movement detection computing devices and methods are disclosed herein based on acceleration data collected from an accelerometer of a mobile device found within an interior of a vehicle. The mobile device movement detection computing devices may identify a likely mobile device movement event based on a change of angle between two three-dimensional acceleration vectors. Where the mobile device movement detection computing devices detect a likely mobile device movement event, sensor data from various sensors of a mobile device are collected and aggregated for a window of time encompassing the mobile device movement event. Data from vehicle sensors and other external systems may also be used. The mobile device movement detection computing devices calculate a risk score based on the aggregates sensor data, and provide feedback to a mobile device or vehicle based on the calculated risk score.

Claims

1. A mobile device movement detection system comprising:

at least one processor; and

memory storing computer-readable instructions, that when executed by the at least one processor, cause the system to;

obtain acceleration data from an accelerometer associated with a mobile device within a vehicle at a first time and at a second time;

obtain sensor data from sensors associated with the mobile device for a specified window of time, wherein the sensors comprise the accelerometer, a GPS receiver, and a gyroscope;

process the acceleration data to remove a gravity component of the acceleration data, and generate a processed acceleration data at the first time and at the second time;

determine that a mobile device movement event has occurred at the second time based, at least in part, on three-dimensional vectors representing the processed acceleration data at the first time and at the second time; and

determine a risk score based, at least in part, on the sensor data for the specified window of time.

2. The system of claim 1 wherein determining that a mobile device movement event has occurred at the second time includes:

calculating a difference in angle between the three-dimensional vectors representing the processed accelerating data at the first time and the second time; and

determining that the difference in angle is greater than a predetermined threshold angle.

3. The system of claim 1 wherein processing the acceleration data to remove the gravity component of the acceleration data includes:

applying a low pass filter to the acceleration data at the first time to isolate an acceleration due to gravity at the first time;

removing the acceleration due to gravity at the first time from the acceleration data at the first time;

applying the low pass filter to the acceleration data at the second time to isolate an acceleration due to gravity at the second time; and

removing the acceleration due to gravity at the second time from the acceleration data at the second time.

4. The system of claim 1, the memory further including instructions that, when executed by the at least one processor, cause the system to:

obtain supplemental sensor data from sensors associated with the vehicle for the specified window of time; and

determine a risk score based, at least in part, on the sensor data and the supplemental sensor data.

5. The system of claim 1, wherein the risk score is determined based on a plurality of scores assigned to a plurality of factors, wherein the plurality of factors comprise an average speed of the vehicle during the window of time, a weather condition during the window of time, a time of day during the window of time, a phone type of the mobile device, and a magnitude of the processed acceleration data at the second time.

6. The system of claim 1, the memory further including instructions that, when executed by the at least one processor, cause the system to:

prevent interaction with a user interface of the mobile device responsive to the risk score satisfying at least one condition.

7. The system of claim 6, wherein the at least one condition includes the risk score exceeding a predefined threshold risk score.

8. The system of claim 6, wherein preventing interaction with the user interface includes disabling a user interaction functionality of the user interface.

9. A method comprising:

obtaining, by a risk analysis device, acceleration data from an accelerometer associated with a mobile device within a vehicle at a first time and at a second time;

obtaining, by the risk analysis device, sensor data from sensors associated with the mobile device for a specified window of time, wherein the sensors comprise the accelerometer, a GPS receiver, and a gyroscope;

processing, by the risk analysis device, the acceleration data to remove a gravity component of the acceleration data, and generate a processed acceleration data at the first time and at the second time;

determining, by the risk analysis device, that a mobile device movement event has occurred at the second time based, at least in part, on three-dimensional vectors representing the processed acceleration data at the first time and at the second time; and

determining, by the risk analysis device, a risk score based, at least in part, on the sensor data for the specified window of time.

10. The method of claim 9, further comprising:

preventing interaction with a user interface of the mobile device responsive to the risk score satisfying at least one condition.

11. The method of claim 10, wherein the at least one condition includes the risk score exceeding a predefined threshold risk score.

12. The method of claim 10, wherein preventing interaction with the user interface includes disabling a user interaction functionality of the user interface.

13. The method of claim 9, further comprising:

obtaining supplemental sensor data from sensors associated with the vehicle for the specified window of time; and

determining a risk score based, at least in part, on the sensor data and the supplemental sensor data.

14. The method of claim 9, wherein the risk score is determined based on a plurality of scores assigned to a plurality of factors, wherein the plurality of factors comprise an average speed of the vehicle during the window of time, a weather condition during the window of time, a time of day during the window of time, a phone type of the mobile device, and a magnitude of the processed acceleration data at the second time.

15. A computer-assisted method of detecting mobile device movement events comprising:

obtaining, by a sensor data collection device of a mobile device movement detection system, acceleration data from at least one sensor associated with a mobile device within a vehicle at a first time and at a second time;

determining, by a movement event detection device, that a mobile device movement event has occurred at the second time based, at least in part, on three-dimensional vectors representing the acceleration data at the first time and at the second time;

aggregating, by a sensor data aggregation device, the acceleration data from the at least one sensor for a window of time starting at a first predetermined duration before the second time and ending a second predetermined duration after the second time, and generating aggregated sensor data;

determining, by a risk determination device, a risk score based, at least in part, on the aggregated sensor data for the window of time; and

notifying, by a risk feedback generation device, a user of the determined risk score through the mobile device.

16. The computer-assisted method of claim 15 wherein determining that a mobile device movement event has occurred at the second time includes:

calculating, by the movement event detection device, a difference in angle between the three-dimensional vectors representing the acceleration data at the first time and at the second time; and

determining, by the movement event detection device, that the difference in angle in greater than a predetermined threshold angle.

17. The computer-assisted method of claim 15, further comprising processing the acceleration data to remove a gravity component of the acceleration data, including:

applying, by a sensor data processing device, a low pass filter to the acceleration data at the first time to isolate an acceleration due to gravity at the first time;

removing, by the sensor data processing device, the acceleration due to gravity at the first time from the acceleration data at the first time;

applying, by the sensor data processing device, the low pass filter to the acceleration data at the second time to isolate an acceleration due to gravity at the second time; and

removing, by the sensor data processing device, the acceleration due to gravity at the second time from the acceleration data at the second time.

18. The computer-assisted method of claim 15, further comprising:

preventing interaction with a user interface of the mobile device responsive to the risk score satisfying at least one condition.

19. The computer-assisted method of claim 18, wherein the at least one condition includes the risk score exceeding a predefined threshold risk score.

20. The computer-assisted method of claim 18, wherein preventing interaction with the user interface includes disabling a user interaction functionality of the user interface.