Methods and systems for driver identification

• US 10,231,093 B2
• Filed: 09/04/2014
• Issued: 03/12/2019
• Est. Priority Date: 12/26/2012
• Status: Active Grant

• Current Assignee: Cambridge Mobile Telematics, Inc.
• Original Assignee: Truemotion, Inc.
• Inventors: Cordova, Brad, Adelmann, Joe
• Primary Examiner(s): Ebersman, Bruce I
• Application Number:
  US14/477,519
• Publication Number:
  US 20140370919A1
• Time in Patent Office: 1,650 Days
• CPC Class Codes: B60W 2420/905 the sensor being an xyz axis sensor
• CPC Class Codes: B60W 2520/14 Yaw
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: G06Q 40/08 Insurance
• 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: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/38 for collecting sensor information
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]

Abstract

A method of determining a position of a mobile device in a vehicle includes obtaining accelerometer data collected using a accelerometer in the mobile device, obtaining angular orientation data collected using a gyroscope in the mobile device, and determining a start time of a driving event. The method also includes determining an entry side for the mobile device prior to the driving event, detecting an acceleration event, aligning the mobile device to a reference frame of the vehicle, and determining a front/back location of the mobile device. The method further includes detecting a braking event, determining an end time of the driving event, determining an exit side for the mobile device after the driving event, and determining the position of the mobile device during at least a portion of the driving event.

Claims

1. A method of determining a position of a mobile device in a vehicle, the method comprising:

obtaining accelerometer data collected using an accelerometer in the mobile device;

obtaining angular orientation data collected using a gyroscope in the mobile device;

determining a first time span associated with a user of the mobile device entering the vehicle;

determining an entry side for the mobile device based on angular orientation data collected during the first time span, wherein determining the entry side of the mobile device comprises;

providing acceleration data and yaw data, wherein a y-axis of the mobile device is aligned to a longitudinal axis of the vehicle and an x-axis of the mobile device is aligned to a transverse axis that is perpendicular to both the longitudinal axis of the vehicle and acceleration due to gravity;

selecting a subset of the provided acceleration data and yaw data, wherein the subset is associated with the first time span;

predicting the entry side for the mobile device using the subset and an integral method, wherein the integrated method comprises;

determining a sign of an integral of the subset projected onto the x-axis of the mobile device and calculated over the first time span;

predicting that the mobile device enters on the right side of the vehicle if the sign of the integral of the subset is positive;

predicting that the mobile device enters on the left side of the vehicle if the sign of the integral of the subset is negative;

selecting a second subset of the provided acceleration data and yaw data, wherein the second subset is associated with the second time span;

determining a sign of an integral of the second subset projected onto the x-axis of the mobile device and calculated over the second time span;

predicting that the mobile device exits on the left side of the vehicle if the sign of the integral of the second subset is positive; and

predicting that the mobile device exits on the right side of the vehicle if the sign of the integral of the second subset is negative;

selecting a second subset of the provided acceleration data and yaw data, wherein the second subset is associated with a driving time of the driving event; and

predicting a transverse position of the mobile device in the vehicle during the driving tine using a centripetal acceleration method;

detecting an acceleration event;

aligning the mobile device to a reference frame of the vehicle;

determining a front/back location of the mobile device;

detecting a braking event;

determining a second time span associated with the user of the mobile device exiting the vehicle;

determining an exit side for the mobile device based on angular orientation data collected during the

second time span; and

determining the position of the mobile device during at least a portion of a driving event occurring between the first time span and the second time span.

2. The method of claim 1 wherein determining at least one of the entry side for the mobile device or the exit side for the mobile device comprises measuring a yaw value for the mobile device associated with the first time span or the second time span.

3. The method of claim 2 wherein measuring the yaw value comprises:

obtaining rotation data collected using the gyroscope in the mobile device, wherein the rotation data is with respect to a vector aligned with acceleration due to gravity; and

detecting a rotation in an x-y plane orthogonal to the vector aligned with acceleration due to gravity, wherein the rotation is greater than a predetermined threshold.

4. The method of claim 2 wherein measuring the yaw value comprises:

obtaining rotation data collected using the gyroscope in the mobile device, wherein the rotation data is with respect to a vector aligned with acceleration due to gravity; and

detecting a rotation in an x-y plane orthogonal to the vector aligned with acceleration due to gravity, wherein the rotation is characterized by a pattern associated with user entry.

5. The method of claim 1 wherein predicting at least one of the entry side or the exit side comprises computing a weighted combination of predictions resulting from a plurality of a vector-product-based method, an integral method, or a seatbelt-based method.

6. The method of claim 1 wherein predicting the transverse position of the mobile device comprises computing a weighted combination of at least a plurality of a yaw method, a centripetal acceleration method, a vector product method, or an integral method.

7. The method of claim 1 wherein determining the front/back location of the vehicle comprises:

obtaining acceleration data associated with a driving time of the driving event, the driving event being characterized by an initial entry signal and a terminal exit signal; and

determining a longitudinal position of the mobile device in the vehicle based on at least one of a bump detection method and a paired Y,Z acceleration method.

8. The method of claim 7 wherein determining the longitudinal position of the mobile device in the vehicle comprises computing a weighted combination of the bump detection method and the paired Y,Z acceleration method.