SYSTEMS AND METHODS FOR DETERMINING VEHICLE TRIP INFORMATION

1 - 27 . (canceled)

28 . A method for determining an insurance rate for a vehicle on a per-unit distance basis to provide insurance to a user, comprising:

detecting the vehicle with a mobile computing device of the user;

determining a starting point of a trip of the vehicle using a first machine learning algorithm, wherein the first machine learning algorithm uses sensor readings from the mobile computing device when the vehicle is detected by the mobile computing device;

determining an end point of the trip using a second machine learning algorithm to calculate trip data for the vehicle, wherein the trip data includes distance traveled using at least the starting point and end point; and

using the trip data to calculate the insurance for the vehicle on the per-unit distance basis.

29 . The method of claim 28 , wherein an input to the first or second machine learning algorithm is sensor data from the mobile computing device.

30 . The method of claim 28 , wherein an output of the first or second machine learning algorithm is vehicle or driver information.

31 . The method of claim 30 , wherein the vehicle or driver information includes the starting point or the end point.

32 . The method of claim 30 , wherein the vehicle or driver information includes a likelihood that the vehicle is a particular type of vehicle or an indication that the vehicle has implemented a hard brake.

33 . The method of claim 28 , wherein the first or second machine learning algorithm uses user feedback to improve a determination of a starting point and end point of the vehicle during a trip.

34 . The method of claim 33 , wherein the user feedback is received via a graphical user interface of the mobile computing device.

35 . The method of claim 28 , wherein the first machine learning algorithm and the second machine learning algorithm are the same machine learning algorithm.

36 . A system for determining insurance for a vehicle on a per-unit distance basis to provide insurance for a user, comprising:

a mobile computing device comprising one or more sensors for detecting the vehicle;

computer memory that contains the trip data recorded during the trip of the vehicle; and

a computer processor operatively coupled to the computer memory and the one or more sensors, wherein the computer processor is programmed to:

(i) detect the vehicle using the one or more sensors;

(ii) determine a starting point of a trip of the vehicle using a first machine learning algorithm, wherein the first machine learning algorithm uses sensor readings from the mobile computing device when the vehicle is detected by the mobile computing device;

(iii) determine an end point of the trip using a second machine learning algorithm to calculate trip data for the vehicle, wherein the trip data includes distance traveled using at least the starting point and end point; and

(iv) use the trip data to calculate to calculate the insurance for the vehicle on the per-unit distance basis.

37 . The system of claim 36 , wherein the mobile computing device is removable from the vehicle.

38 . The system of claim 36 , wherein an input to the first or second machine learning algorithm is sensor data from the mobile computing device.

39 . The system of claim 36 , wherein an output of the first or second machine learning algorithm is vehicle or driver information.

40 . The system of claim 36 , wherein the first or second machine learning algorithm uses user feedback to improve a determination of a starting point and end point of the vehicle during a trip.

41 . The system of claim 40 , wherein the user feedback is received via a graphical user interface of the mobile computing device.

42 . The system of claim 36 , wherein the first machine learning algorithm and the second machine learning algorithm are the same machine learning algorithm.

43 . A non-transitory computer-readable medium comprising machine executable code that, upon execution by one or more computer processors, implements a method for determining insurance for a vehicle on a per-unit distance basis to provide insurance to a user, the method comprising:

detecting the vehicle with a mobile computing device of the user;

determining a starting point of a trip of the vehicle using a first machine learning algorithm, wherein the first machine learning algorithm uses sensor readings from the mobile computing device when the vehicle is detected by the mobile computing device;

determining an end point of the trip using a second machine learning algorithm to calculate trip data for the vehicle, wherein the trip data includes distance traveled using at least the starting point and end point; and

using the trip data to calculate the insurance for the vehicle on the per-unit distance basis.

44 . The non-transitory computer-readable medium of claim 43 , wherein an input to the first or second machine learning algorithm is sensor data from the mobile computing device.

45 . The non-transitory computer-readable medium of claim 43 , wherein an output of the first or second machine learning algorithm is vehicle or driver information.

46 . The non-transitory computer-readable medium of claim 43 , wherein the first or second machine learning algorithm uses user feedback to improve a determination of a starting point and end point of the vehicle during a trip.

47 . The non-transitory computer-readable medium of claim 46 , wherein the user feedback is received via a graphical user interface of the mobile computing device.