Determining the number of people in a vehicle

Patent metadata

Field	Value
Publication number	US-9840166-B2
Application number	US-201514684807-A
Country	US
Kind code	B2
Filing date	Apr 13, 2015
Priority date	Apr 13, 2015
Publication date	Dec 12, 2017
Grant date	Dec 12, 2017

Abstract

A computer device may include logic configured to detect a wake up event that wakes the computer device from an idle mode, wherein the wake up event indicates that a user is getting ready to use a vehicle; obtain accelerometer data from an accelerometer, associated with the vehicle, during a time period that includes the wake up event; determine a number of door slam events during the time period based on the obtained accelerometer data; and determine a number of people in the vehicle based on the determined number of door slam events.

First claim

What is claimed is:

1. A method, performed by a computer device, the method comprising:
detecting, by the computer device, a wake up event that wakes the computer device from an idle mode, wherein the wake up event indicates that a user is getting ready to use a vehicle;
obtaining, by the computer device, accelerometer data from an accelerometer, associated with the vehicle, during a time period that includes the wake up event;
determining, by the computer device, a number of door slam events during the time period based on the obtained accelerometer data using a classifier trained using training data that includes accelerometer data for door slam events and accelerometer data for response events that do not correspond to door slam events to filter out accelerometer response events that do not correspond to door slam events; and
determining, by the computer device, a number of people in the vehicle based on the determined number of door slam events.

2. The method of claim 1 , wherein detecting the wake up event that wakes the computer device from an idle mode includes:
detecting an unlocking of the vehicle;
detecting an opening of a door of the vehicle; or
detecting a short range wireless signal associated with a mobile communication device associated with the user.

3. The method of claim 1 , further comprising:
obtaining audio data from a microphone during the time period that includes the wake up event; and
wherein determining the number of people in the vehicle is further based on the obtained audio data.

4. The method of claim 1 , further comprising:
obtaining data relating to mobile communication devices in the vehicle during the time period that includes the wake up event; and
wherein determining the number of people in the vehicle is further based on the obtained data relating to the mobile communication devices.

5. The method of claim 4 , wherein the data relating to the mobile communication devices in the vehicle includes data relating to at least one of:
detected short range wireless signals associated with the mobile communication devices, or
location data associated with the mobile communication devices received from a base station.

6. The method of claim 1 , further comprising: obtaining data from one or more additional sensors in the vehicle during the time period that includes the wake up event; and wherein determining the number of people in the vehicle is further based on the obtained data from the one or more sensors in the vehicle.

7. The method of claim 6 , wherein the one or more additional sensors in the vehicle include at least one of: a door sensor, a proximity sensor, a dashboard camera, or a weight sensor.

8. The method of claim 1 , further comprising:
providing information identifying the number of people in the vehicle to a device configured to collect usage-based insurance information.

9. The method of claim 1 , further comprising:
determining that the number of people in the vehicle exceeds a passenger threshold; and
sending an alert to a mobile communication device, in response to determining that the number of people in the vehicle exceeds the passenger threshold.

10. The method of claim 1 , further comprising:
adjusting one or more vehicle settings, based on the determined number of people in the vehicle.

11. A computer device comprising:
logic configured to:
detect a wake up event that wakes the computer device from an idle mode, wherein the wake up event indicates that a user is getting ready to use a vehicle;
obtain accelerometer data from an accelerometer, associated with the vehicle, during a time period that includes the wake up event;
determine a number of door slam events during the time period based on the obtained accelerometer data using a classifier trained using training data that includes accelerometer data for door slam events and accelerometer data for response events that do not correspond to door slam events to filter out accelerometer response events that do not correspond to door slam events; and
determine a number of people in the vehicle based on the determined number of door slam events.

12. The computer device of claim 11 , wherein the computer device includes an on-board diagnostics device.

13. The computer device of claim 11 , wherein the computer device includes:
a server device communicating with an on-board diagnostics device;
an embedded vehicle computer device; or
a mobile communication device located within the vehicle.

14. The computer device of claim 11 , wherein, when detecting the wake up event that wakes the computer device from an idle mode, the logic is further configured to at least one of:
detect an unlocking of the vehicle;
detect an opening of a door of the vehicle; or
detect a short range wireless signal associated with a mobile communication device associated with the user.

15. The computer device of claim 11 , wherein the logic is further configured to at least one of:
obtain audio data from a microphone during the time period that includes the wake up event;
obtain data relating to mobile communication devices in the vehicle during the time period that includes the wake up event; or
obtain data from one or more additional sensors in the vehicle during the time period that includes the wake up event; and
wherein the logic is further configured to: determine the number of people in the vehicle based on at least one of the obtained audio data, the obtained data relating to the mobile communication devices in the vehicle, or the obtained data from the one or more sensors in the vehicle.

16. The computer device of claim 11 , wherein the logic is further configured to at least one of:
provide information identifying the number of people in the vehicle to a device configured to collect usage-based insurance information;
sending an alert to a mobile communication device when the number of people in the vehicle exceeds a passenger threshold; or
adjust one or more vehicle settings, based on the determined number of people in the vehicle.

17. An on-board diagnostics device comprising:
logic configured to:
detect a wake up event that wakes the on-board diagnostics device from an idle mode, wherein the wake up event indicates that a user is getting ready to use a vehicle;
obtain accelerometer data from an accelerometer, associated with the vehicle, during a time period that includes the wake up event;
obtain data that includes one or more of:
audio data from a microphone during the time period that includes the wake up event;
data relating to mobile communication devices in the vehicle during the time period that includes the wake up event; or
data from one or more additional sensors in the vehicle during the time period that includes the wake up event;

determine a number of door slam events during the time period based on the obtained accelerometer data using a classifier trained using training data that includes accelerometer data for door slam events and accelerometer data for response events that do not correspond to door slam events to filter out accelerometer response events that do not correspond to door slam events; and
determine a number of people in the vehicle using the classifier based on the determined number of door slam events and the obtained data.

18. The on-board diagnostics device of claim 17 , wherein the classifier includes at least one of:
a neural network classifier;
a support vector machine classifier; or
a logistic regression classifier.

19. The on-board diagnostics d

Assignees

• Verizon Patent & Licensing Inc

Inventors

• Taylor Thomas Steven
• Barfield Jr James Ronald

Classifications

• B60H1/00742

  by detection of the vehicle occupants' presence; by detection of conditions relating to the body of occupants, e.g. using radiant heat detectors · CPC title

• G06N20/00

  Machine learning · CPC title

• B60H1/00757

  by the input of sound, e.g. by using a voice synthesizer · CPC title

• G06N3/0499

  Feedforward networks · CPC title

• G06N3/09

  Supervised learning · CPC title