SYSTEMS AND METHODS FOR INDIVIDUALIZED DRIVER PREDICTION

1 . A system comprising:

a mobile device comprising at least one sensor, wherein the at least one sensor comprises at least one of an accelerometer, a gyroscope, a magnetometer, a GPS, or a compass;

a memory; and

a processor coupled to the memory, wherein the processor is configured to perform operations including:

receiving a driver valuation metric corresponding to an amount of driving events during which a user is a driver of a vehicle as a function of a total number of driving events during which the user is in the vehicle;

determining, using the driver valuation metric, a first probability that the user will be driving the vehicle during a next driving event;

obtaining a first stream of data from a sensor of the at least one sensor of the mobile device;

determining from the first stream of data that the next driving event has initiated;

obtaining a second stream of data from the sensor of the at least one sensor of the mobile device during the next driving event;

determining, using the second stream of data, a second probability that the user is driving the vehicle during the next driving event; and

determining, using the first probability and the second probability, a combined probability that the user is driving the vehicle during the next driving event.

2 . The system of claim 1 , wherein the driver valuation metric is received as input from the user.

3 . The system of claim 1 , further comprising:

a display configured to display a survey to the user and to receive the driver valuation metric as input from the user in response to the survey,

wherein determining the first probability that the user will be driving the vehicle during the next driving event comprises:

determining an amount of time elapsed between displaying the survey and receiving the input; and

adjusting the driver valuation metric based on the amount of time.

4 . The system of claim 1 , wherein determining the first probability that the user will be driving the vehicle during the next driving event comprises:

estimating a historical driver valuation metric corresponding to a percentage of historical driving events during which the user was the driver of the vehicle as a function of a total number of historical driving events during which the user was in the vehicle; and

adjusting the driver valuation metric based on the historical driver valuation metric.

5 . The system of claim 4 , wherein the historical driver valuation metric is estimated using data from the sensor of the at least one sensor of the mobile device.

6 . The system of claim 1 , wherein determining the second probability that the user is driving the vehicle during the next driving event comprises at least one of:

determining, using the first stream of data, whether the user entered the vehicle from a left side or a right side of the vehicle;

determining, using the second stream of data, whether the user exited the vehicle from the left side or the right side of the vehicle;

determining, using the second stream of data, usage of the mobile device by the user;

determining a fraction of the next driving event during which a battery of the mobile device is being charged; and

determining whether the mobile device is connected to hands-free technology in the vehicle during the next driving event.

7 . The system of claim 1 , further comprising, before determining the first probability, but after receiving the driver valuation metric:

facilitating display of a survey question on the mobile device;

receiving input indicative of an answer to the survey question on the mobile device;

adjusting the driver valuation metric in accordance with the answer to the survey question.

8 . A system comprising:

a mobile device comprising at least one sensor, wherein the at least one sensor comprises at least one of an accelerometer, a gyroscope, a magnetometer, a GPS, or a compass;

a memory; and

a processor coupled to the memory, wherein the processor is configured to perform operations including:

facilitating display of a survey question on the mobile device;

receiving input indicative of an answer to the survey question on the mobile device;

correlating the answer to the survey question to a driver valuation metric, wherein the driver valuation metric corresponds to an amount of driving events during which a user if a driver of a vehicle as a function of a total number of driving events during which the user is in the vehicle;

determining, using the driver valuation metric, a first probability that the user will be driving the vehicle during a next driving event;

obtaining a first stream of data from a sensor of the at least one sensor of the mobile device;

determining from the first stream of data that the next driving event has initiated;

obtaining a second stream of data from the sensor of the at least one sensor of the mobile device during the next driving event;

determining, using the second stream of data, a second probability that the user is driving the vehicle during the next driving event; and

determining, using the first probability and the second probability, a combined probability that the user is driving the vehicle during the next driving event.

9 . The system of claim 8 , wherein the survey question is a demographic question.

10 . The system of claim 8 , wherein the answer is different than the driver valuation metric.

11 . A method comprising:

receiving a driver valuation metric corresponding to a percentage of driving events during which a user is a driver of a vehicle as a function of a total number of driving events during which the user is in the vehicle;

determining, using the driver valuation metric, a first probability that the user will be driving the vehicle during a next driving event;

obtaining a first stream of data from a sensor of a mobile device of the user;

determining from the first stream of data that the next driving event has initiated;

obtaining a second stream of data from the sensor of the mobile device of the user during the next driving event;

determining, using the second stream of data, a second probability that the user is driving the vehicle during the next driving event; and

determining, using the first probability and the second probability, a combined probability that the user is driving the vehicle during the next driving event.

12 . The method of claim 11 , wherein the driver valuation metric is received as input from the user.

13 . The method of claim 11 , further comprising:

displaying a survey to the user, wherein the driver valuation metric is received as input from the user in response to the survey,

wherein determining the first probability that the user will be driving the vehicle during the next driving event comprises:

determining an amount of time elapsed between displaying the survey and receiving the input; and

adjusting the driver valuation metric based on the amount of time.

14 . The method of claim 11 , wherein determining the first probability that the user will be driving the vehicle during the next driving event comprises:

estimating a historical driver valuation metric corresponding to a percentage of historical driving events during which the user was the driver of the vehicle as a function of a total number of historical driving events during which the user was in the vehicle; and

adjusting the driver valuation metric based on the historical driver valuation metric.

15 . The method of claim 14 , wherein the historical driver valuation metric is estimated using data from the sensor of the mobile device.

16 . The method of claim 11 , wherein determining the second probability that the user is driving the vehicle during the next driving event comprises at least one of:

determining, using the first stream of data, whether the user entered the vehicle from a left side or a right side of the vehicle;

determining, using the second stream of data, whether the user exited the vehicle from the left side or the right side of the vehicle;

determining, using the second stream of data, usage of the mobile device by the user;

determining a fraction of the next driving event during which a battery of the mobile device is being charged; and

determining whether the mobile device is connected to hands-free technology in the vehicle during the next driving event.

17 . The method of claim 11 , further comprising, before determining the first probability, but after receiving the driver valuation metric:

facilitating display of a survey question on the mobile device;

receiving input indicative of an answer to the survey question on the mobile device; and

adjusting the driver valuation metric in accordance with the answer to the survey question.

18 . A method comprising:

facilitating display of a survey question on a mobile device;

receiving input indicative of an answer to the survey question on the mobile device;

correlating the answer to the survey question to a driver valuation metric, wherein the driver valuation metric corresponds to an amount of driving events during which a user if a driver of a vehicle as a function of a total number of driving events during which the user is in the vehicle;

determining, using the driver valuation metric, a first probability that the user will be driving the vehicle during a next driving event;

obtaining a first stream of data from a sensor of a plurality of sensors of the mobile device;

determining from the first stream of data that the next driving event has initiated;

obtaining a second stream of data from the sensor of the plurality of sensors of the mobile device during the next driving event;

determining, using the second stream of data, a second probability that the user is driving the vehicle during the next driving event; and

determining, using the first probability and the second probability, a combined probability that the user is driving the vehicle during the next driving event.

19 . The method of claim 18 , wherein the survey question is a demographic question.

20 . The method of claim 18 , wherein the answer is different than the driver valuation metric.