Systems and methods for determining vehicle trip information

Abstract

The present disclosure provides methods and systems for identifying or verifying trip information. A method for identifying or verifying a trip of a vehicle comprises detecting a presence of the vehicle with a mobile computing device of a user. The mobile computing device may be removable from the vehicle. Next, a trip start may be determined when the vehicle is detected by the mobile computing device as being present. Trip data may be recorded for a trip of the vehicle subsequent to the trip start, the trip data being based at least in part on sensor readings. A trip end that corresponds to an end of the trip of the vehicle may be detected and verified.

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.