US 11,787,422 B2
Systems and methods of determining effectiveness of vehicle safety features
Jaime Skaggs, Chenoa, IL (US); Jody Thoele, Bloomington, IL (US); and Angela Glusick, Bloomington, IL (US)
Assigned to STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY, Bloomington, IL (US)
Filed by STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY, Bloomington, IL (US)
Filed on Sep. 9, 2022, as Appl. No. 17/941,096.
Application 17/941,096 is a continuation of application No. 16/928,793, filed on Jul. 14, 2020, granted, now 11,661,072.
Claims priority of provisional application 63/349,912, filed on Jun. 7, 2022.
Claims priority of provisional application 62/935,890, filed on Nov. 15, 2019.
Claims priority of provisional application 62/905,742, filed on Sep. 25, 2019.
Claims priority of provisional application 62/879,130, filed on Jul. 26, 2019.
Claims priority of provisional application 62/874,749, filed on Jul. 16, 2019.
Prior Publication US 2023/0001936 A1, Jan. 5, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. B60W 50/00 (2006.01); G06Q 40/08 (2012.01); G06N 20/00 (2019.01); G07C 5/02 (2006.01)
CPC B60W 50/0098 (2013.01) [G06N 20/00 (2019.01); G06Q 40/08 (2013.01); G07C 5/02 (2013.01); B60W 2050/0083 (2013.01); B60W 2556/55 (2020.02)] 19 Claims
OG exemplary drawing
 
1. A computer-implemented method for use in determining effectiveness of an update to a vehicle feature, the method comprising:
obtaining, by one or more processors, vehicle data from a vehicle data repository, the vehicle data comprising a vehicle feature, and the vehicle feature being stored in an original equipment manufacturer (OEM)-agnostic terminology;
receiving, by the one or more processors, information indicating an update to the vehicle feature was sent to vehicles having the vehicle feature;
obtaining, by the one or more processors, vehicle accident record information for the vehicles having the vehicle feature, wherein the vehicle accident record information includes one or more of a number of accidents, a frequency of accidents, or a severity of accidents associated with the vehicles having the vehicle feature;
constructing, by the one or more processors, a first dataset with data from before the update was sent to or implemented in the vehicles having the vehicle feature;
constructing, by the one or more processors, a second dataset with data from after the update was sent to or implemented in the vehicles having the vehicle feature; and
calculating, by the one or more processors, an effectiveness score of the update based upon both the first data set and the second dataset, wherein the calculating the effectiveness score comprises inputting the first dataset and the second dataset into a machine learning algorithm trained to calculate effectiveness scores of updates.