METHOD AND SYSTEM FOR VEHICLE-RELATED DRIVER CHARACTERISTIC DETERMINATION
A method for characterizing a user associated with a vehicle including collecting a movement dataset sampled at least at one of a location sensor and a motion sensor associated with the vehicle, during a time period associated with movement of the vehicle; extracting a set of movement features associated with movement of at least one of the user and the vehicle during the time period; and determining one or more user characteristics describing the user based on the set of movement features, wherein the one or more user characteristics include a classification of the user as at least one of a passenger and a driver for the time period associated with movement of the vehicle.
1 . A method for characterizing a user associated with a vehicle, the method comprising:
during a post-trip time period occurring after a trip, wherein a mobile device associated with the user is arranged within the vehicle during the trip:
collecting a post-trip motion dataset with a motion sensor of the mobile device, wherein the post-trip motion dataset comprises turning data associated with the mobile device;
determining a set of post-trip movement features from the post-trip motion dataset, wherein the set of post-trip movement features comprises a turning radius of the mobile device;
classifying the user as one of a passenger and a driver during the trip based on the post-trip movement features; and
in an event that the user is classified as the driver, updating a driving parameter associated with the user.
2 . The method of claim 1 , wherein the driving parameter comprises a driving risk score associated with the user.
3 . The method of claim 1 , wherein the motion sensor is an accelerometer.
4 . The method of claim 1 , further comprising determining an egress direction of the user exiting the vehicle based on the set of post-trip movement features, wherein the user is classified as one of the passenger and the driver based on the egress direction.
5 . The method of claim 1 , further comprising collecting an in-trip dataset sampled at a set of sensors of the mobile device, wherein the in-trip dataset is collected during the trip.
6 . The method of claim 5 , wherein the set of sensors comprises the motion sensor and a location sensor.
7 . The method of claim 6 , wherein classifying the user as one of a passenger and a driver is further performed based on the in-trip dataset.
8 . The method of claim 1 , wherein the vehicle is parked during the post-trip time period.
9 . The method of claim 8 , wherein the user egresses the vehicle during the post-trip time period, and wherein an egress direction of the user is determined based on the set of post-trip movement features.
10 . The method of claim 9 , wherein determining the egress direction based on the set of post-trip movement features comprises extracting the egress direction relative to a heading of the vehicle, wherein the heading of the vehicle is determined based on a set of vehicle motion features collected at the mobile device during the trip.
1 . method of claim 1 , wherein classifying the user as one of a passenger and a driver is performed with a machine learning model trained based on a corpus of post-trip motion datasets collected from a population of users.
12 . The method of claim 11 , further comprising updating the model based on classifying the user as one of a passenger and a driver.
13 . A system for characterizing a user associated with a vehicle, the system comprising:
a client application executable on a mobile device associated with the user, wherein the mobile device is arranged within the vehicle during a trip, wherein the client application:
during a post-trip time period occurring after a trip, collects a post-trip motion dataset with a motion sensor of the mobile device, wherein the post-trip motion dataset comprises turning data associated with the mobile device;
a computing system in communication with the client application, wherein the computing system:
determines a set of post-trip movement features from the post-trip motion dataset, wherein the set of post-trip movement features comprises a set of turning parameters associated with the mobile device; and
classifies the user as one of a passenger and a driver during the trip based on the set of turning parameters.
14 . The system of claim 13 , wherein the computing system comprises a remote computing system arranged remote from the mobile device.
15 . The system of claim 13 , wherein the motion sensor is an accelerometer.
16 . The system of claim 13 , wherein the set of turning parameters comprises a turning radius of the mobile device.
17 . The system of claim 13 , further comprising, in response to classifying the user as the driver, updating a driving parameter associated with the user.
13 . system of claim 13 , wherein at least a portion of the computing system is arranged remote from the mobile device.
19 . The system of claim 18 , wherein a portion of the computing system is arranged onboard the mobile device.
20 . The system of claim 13 , further comprising a trained model, wherein the computing system classifies the user as one of a passenger and a driver based on the trained model, and wherein the trained model is updated based on the classification and the post-trip motion dataset.