Systems and methods for determining an actual driver of a vehicle based at least in part upon telematics data

A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising:

• receiving, by a computing device and from a first user device of a first user in a vehicle, first telematics data;
• receiving, by the computing device and from a second user device of a second user in the vehicle, second telematics data;
• determining, using a trained machine learning model, patterns in the first and second telematics data;
• determining, using the patterns in the first and second telematics data, relative positions of the first user device and the second user device, comprising analyzing the first and second telematics data associated with a turn of the vehicle to identify that a first one of the first user device or the second user device experiences greater angular acceleration than a second one of the first user device or the second user device, indicating that the second one of the first user device or the second user device is positioned closer to a center of the turn, wherein respective acceleration data of the first and second telematics data is measured by respective accelerometers and gyroscopes onboard the first and second user devices, and wherein the respective acceleration data is used to determine a left-to-right positioning of the first user device relative to the second user device with respect to a direction of forward movement of the vehicle;
• determining, based on the relative positions of the first user device and the second user device, a predicted position of the first user device relative to the second user device;
• and
• identifying, by the computing device, that the first user or the second user is a driver of the vehicle based at least in part upon the predicted position of the first user device relative to the second user device.

One or more non-transitory computer-readable media storing computing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving, by a computing device and from a first user device of a first user in a vehicle, first telematics data;
• receiving, by the computing device and from a second user device of a second user in the vehicle, second telematics data;
• determining, using a trained machine learning model, patterns in the first and second telematics data;
• determining, using the patterns in the first and second telematics data, relative positions of the first user device and the second user device, comprising analyzing the first and second telematics data associated with a turn of the vehicle to identify that a first one of the first user device or the second user device experiences greater angular acceleration than a second one of the first user device or the second user device, indicating that the second one of the first user device or the second user device is positioned closer to a center of the turn, wherein respective acceleration data of the first and second telematics data is measured by respective accelerometers and gyroscopes onboard the first and second user devices, and wherein the respective acceleration data is used to determine a left-to-right positioning of the first user device relative to the second user device with respect to a direction of forward movement of the vehicle;
• determining, based on the relative positions of the first user device and the second user device, a predicted position of the first user device relative to the second user device;
• and
• identifying, by the computing device, that the first user or the second user is a driver of the vehicle based at least in part upon the predicted position of the first user device relative to the second user device.