Systems and methods of determining effectiveness of vehicle safety features
Systems and methods for determining the effectiveness of vehicle safety features are provided. Vehicle build information (VBI) for vehicles manufactured by a plurality of OEMs may be obtained. The VBI may contain OEM-specific terminology for smart safety features associated with each vehicle. The obtained VBI may be analyzed to generate an ontology model mapping each feature to any OEM-specific terminology associated with the feature. The ontology model may be applied to the VBI to generate translated VBI for each vehicle, such that the OEM-specific terminology associated with each feature is replaced with OEM-agnostic terminology for the feature. Vehicle accident record information may be obtained for each vehicle, including, e.g., the number, frequency, severity, etc. of accidents associated with each vehicle. Using the OEM-agnostic terminology for each feature associated with each vehicle and the vehicle accident information for each vehicle, an effectiveness score associated with each feature may be calculated.
1. A computer-implemented method for determining the effectiveness of vehicle safety features, the method comprising:
obtaining, by a processor, vehicle build information for a plurality of vehicles manufactured by a plurality of original equipment manufacturers (OEMs), the vehicle build information containing OEM-specific terminology associated with one or more smart safety features associated with each vehicle;
analyzing, by a processor, obtained vehicle build information to generate an ontology model mapping each smart safety feature to any OEM-specific terminology associated with the smart safety feature for each OEM;
applying, by a processor, the ontology model to the vehicle build information to generate translated vehicle build information for each of the plurality of vehicles, such that the OEM-specific terminology associated with each smart safety feature is replaced with OEM-agnostic terminology for the smart safety feature;
obtaining, by a processor, vehicle accident record information for each of the plurality of vehicles, 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 each of the plurality of vehicles; and
calculating, by a processor, using the OEM-agnostic terminology for each smart safety feature associated with each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, an effectiveness score associated with each smart safety feature.
2. The computer-implemented method of claim 1 , wherein analyzing the obtained vehicle build information to generate an ontology model mapping each smart safety feature to OEM-specific terminology associated with the smart safety feature for each OEM comprises:
training, by a processor, a machine learning model using OEM-specific terminology associated with each of a plurality of known smart safety features for a plurality of OEMs; and
applying, by a processor, the trained machine learning model to the obtained vehicle build information in order to identify OEM-specific terminology associated with each smart safety feature for each OEM.
3. The computer-implemented method of claim 1 , further comprising:
determining, by a processor, an insurance rating for a particular vehicle based upon an effectiveness score associated with each smart safety feature associated with the particular vehicle.
4. The computer-implemented method of claim 1 , further comprising:
obtaining, by a processor, vehicle telematics data for each of the plurality of vehicles; and
determining, by a processor, based upon the vehicle telematics data for each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, that a smart safety feature associated with a vehicle was deactivated at a date and/or time of an accident associated with the vehicle; and
wherein calculating the effectiveness score associated with the smart safety feature is further based upon the determination that the smart safety feature associated with the vehicle was deactivated at a date and/or time of an accident associated with the vehicle.
5. The computer-implemented method of claim 1 , further comprising:
obtaining, by a processor, vehicle telematics data for each of the plurality of vehicles; and
determining, by a processor, based upon the vehicle telematics data for each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, that a smart safety feature associated with a vehicle was activated at a date and/or time of an accident associated with the vehicle; and
wherein calculating the effectiveness score associated with the smart safety feature is further based upon the determination that the smart safety feature associated with the vehicle was activated at a date and/or time of an accident associated with the vehicle.
6. The computer-implemented method of claim 1 , further comprising:
obtaining, by a processor, vehicle telematics data for each of the plurality of vehicles, the vehicle telematics data including data associated with one or more a road upon which the vehicle is operating or an environment in which the vehicle is operating; and
determining, by a processor, based upon the vehicle telematics data for each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, that a smart safety feature associated with a vehicle was activated at a date and/or time of an accident associated with the vehicle; and
wherein calculating the effectiveness score associated with the smart safety feature is further based upon the determination that the smart safety feature associated with the vehicle was activated at a date and/or time of an accident associated with the vehicle, an operational design domain of the safety feature, and the road upon which the vehicle was operating and/or the environment in which the vehicle was operating at the date and/or time of the accident.
7. The computer-implemented method of claim 1 , further comprising:
receiving, by a processor, an indication that a smart safety feature associated with a vehicle had been updated prior to a date and/or time of an accident associated with the vehicle; and
wherein calculating the effectiveness score associated with the smart safety feature is further based upon the indication that the smart safety feature associated with the vehicle had been updated prior to the date and/or time of the accident associated with the vehicle.
8. The computer-implemented method of claim 1 , further comprising:
calculating, using the OEM-agnostic terminology for each smart safety feature associated with each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, an effectiveness score associated with a particular combination of smart safety features.
9. A computer system for determining the effectiveness of vehicle safety features, comprising:
one or more processors; and
a non-transitory program memory communicatively coupled to the one or more processors and storing executable instructions that, when executed by the one or more processors, cause the computer system to:
obtain vehicle build information for a plurality of vehicles manufactured by a plurality of original equipment manufacturers (OEMs), the vehicle build information containing OEM-specific terminology associated with one or more smart safety features associated with each vehicle;
analyze obtained vehicle build information to generate an ontology model mapping each smart safety feature to any OEM-specific terminology associated with the smart safety feature for each OEM;
apply the ontology model to the vehicle build information to generate translated vehicle build information for each of the plurality of vehicles, such that the OEM-specific terminology associated with each smart safety feature is replaced with OEM-agnostic terminology for the smart safety feature;
obtain vehicle accident record information for each of the plurality of vehicles, 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 each of the plurality of vehicles; and
calculate, using the OEM-agnostic terminology for each smart safety feature associated with each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, an effectiveness score associated with each smart safety feature.
10. The computer system of claim 9 , wherein the instructions, when executed by the one or more processors, cause the computer system to analyze the obtained vehicle build information to generate an ontology model mapping each smart safety feature to OEM-specific terminology associated with the smart safety feature for each OEM by:
training a machine learning model using OEM-specific terminology associated with each of a plurality of known smart safety features for a plurality of OEMs; and
applying the trained machine learning model to the obtained vehicle build information in order to identify OEM-specific terminology associated with each smart safety feature for each OEM.
11. The computer system of claim 9 , wherein the instructions, when executed by the one or more processors, cause the computer system to:
determine an insurance rating for a particular vehicle based upon an effectiveness score associated with each smart safety feature associated with the particular vehicle.
12. The computer system of claim 9 , wherein the instructions, when executed by the one or more processors, cause the computer system to:
obtain vehicle telematics data for each of the plurality of vehicles; and
determine, based upon the vehicle telematics data for each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, that a smart safety feature associated with a vehicle was deactivated at a date and/or time of an accident associated with the vehicle, and
wherein the instructions, when executed by the one or more processors, cause the computer system to calculate the effectiveness score associated with the smart safety feature further based upon the determination that the smart safety feature associated with the vehicle was deactivated at a date and/or time of an accident associated with the vehicle.
13. The computer system of claim 9 , wherein the instructions, when executed by the one or more processors, cause the computer system to:
obtain vehicle telematics data for each of the plurality of vehicles; and
determine, based upon the vehicle telematics data for each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, that a smart safety feature associated with a vehicle was activated at a date and/or time of an accident associated with the vehicle; and
wherein the instructions, when executed by the one or more processors, cause the computer system to calculate the effectiveness score associated with the smart safety feature further based upon the determination that the smart safety feature associated with the vehicle was activated at a date and/or time of an accident associated with the vehicle.
14. The computer system of claim 9 , wherein the instructions, when executed by the one or more processors, cause the computer system to:
obtain vehicle telematics data for each of the plurality of vehicles, the vehicle telematics data including data associated with one or more a road upon which the vehicle is operating or an environment in which the vehicle is operating; and
determine, based upon the vehicle telematics data for each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, that a smart safety feature associated with a vehicle was activated at a date and/or time of an accident associated with the vehicle; and
wherein calculating the effectiveness score associated with the smart safety feature is further based upon the determination that the smart safety feature associated with the vehicle was activated at a date and/or time of an accident associated with the vehicle, an operational design domain of the safety feature, and the road upon which the vehicle was operating and/or the environment in which the vehicle was operating at the date and/or time of the accident.
15. The computer system of claim 9 , wherein the instructions, when executed by the one or more processors, cause the computer system to:
receive an indication that a smart safety feature associated with a vehicle had been updated prior to a date and/or time of an accident associated with the vehicle, and
wherein the instructions, when executed by the one or more processors, cause the computer system to calculate the effectiveness score associated with the smart safety feature further based upon the indication that the smart safety feature associated with the vehicle had been updated prior to the date and/or time of the accident associated with the vehicle.
16. The computer system of claim 9 , wherein the instructions, when executed by the one or more processors, cause the computer system to:
calculate, using the OEM-agnostic terminology for each smart safety feature associated with each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, an effectiveness score associated with a particular combination of smart safety features.
17. A tangible, non-transitory computer-readable medium storing executable instructions for determining the effectiveness of vehicle safety features that, when executed by at least one processor of a computer system, cause the computer system to:
obtain vehicle build information for a plurality of vehicles manufactured by a plurality of original equipment manufacturers (OEMs), the vehicle build information containing OEM-specific terminology associated with one or more smart safety features associated with each vehicle;
analyze obtained vehicle build information to generate an ontology model mapping each smart safety feature to any OEM-specific terminology associated with the smart safety feature for each OEM;
apply the ontology model to the vehicle build information to generate translated vehicle build information for each of the plurality of vehicles, such that the OEM-specific terminology associated with each smart safety feature is replaced with OEM-agnostic terminology for the smart safety feature;
obtain vehicle accident record information for each of the plurality of vehicles, 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 each of the plurality of vehicles; and
calculate, using the OEM-agnostic terminology for each smart safety feature associated with each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, an effectiveness score associated with each smart safety feature.
18. The tangible, non-transitory computer-readable medium of claim 17 , wherein the instructions, when executed by the at least one processor, cause the computer system to analyze the obtained vehicle build information to generate an ontology model mapping each smart safety feature to OEM-specific terminology associated with the smart safety feature for each OEM by:
training a machine learning model using OEM-specific terminology associated with each of a plurality of known smart safety features for a plurality of OEMs; and
applying the trained machine learning model to the obtained vehicle build information in order to identify OEM-specific terminology associated with each smart safety feature for each OEM.
19. The tangible, non-transitory computer-readable medium of claim 17 , wherein the instructions, when executed by the at least one processor, cause the computer system to:
determine an insurance rating for a particular vehicle based upon an effectiveness score associated with each smart safety feature associated with the particular vehicle.
20. The tangible, non-transitory computer-readable medium of claim 17 , wherein the instructions, when executed by the at least one processor, cause the computer system to:
obtain vehicle telematics data for each of the plurality of vehicles; and
determine, based upon the vehicle telematics data for each of the plurality of vehicles and the vehicle accident record information for each of the plurality of vehicles, that a smart safety feature associated with a vehicle was deactivated at a date and/or time of an accident associated with the vehicle, and
wherein the instructions, when executed by the at least one processor, cause the computer system to calculate the effectiveness score associated with the smart safety feature further based upon the determination that the smart safety feature associated with the vehicle was deactivated at a date and/or time of an accident associated with the vehicle.