Analysis of vehicle data to predict component failure
First Claim
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1. A method comprising:
- receiving, by one or more computing devices, vehicle data from a plurality of vehicles, the vehicle data including diagnostic trouble codes (DTCs) generated by on-board diagnostic (OBD) computer systems of the plurality of vehicles;
classifying, by the one or more computing devices, a driver associated with a particular one of the plurality of vehicles to obtain a driver archetype, of a plurality of possible driver archetypes, the driver archetypes indicating driving patterns of drivers;
evaluating, by the one or more computing devices, the vehicle data according to a predictive model, to determine predictions of DTCs that are likely to occur for a particular one of the plurality of vehicles, the evaluation including using an indication of the driver archetype for the driver;
generating, by the one or more computing devices and based on the determined predictions of the DTCs, a report describing potential maintenance issues for the particular one of the plurality of vehicles; and
transmitting, by the one or more computing devices, the report to an entity associated with the particular one of the plurality of vehicles.
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Abstract
Vehicle data may be analyzed to predict potential component failures, diagnostic trouble codes (DTCs), or other mechanical failures relating to the vehicle. In one implementation the vehicle data may be received from a number of vehicles, the vehicle data including DTCs generated by on-board diagnostic (OBD) systems of the vehicles. The vehicle data may be evaluated using a predictive model to output predictions of DTCs that are likely to occur for a particular vehicle.
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Citations
24 Claims
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1. A method comprising:
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receiving, by one or more computing devices, vehicle data from a plurality of vehicles, the vehicle data including diagnostic trouble codes (DTCs) generated by on-board diagnostic (OBD) computer systems of the plurality of vehicles; classifying, by the one or more computing devices, a driver associated with a particular one of the plurality of vehicles to obtain a driver archetype, of a plurality of possible driver archetypes, the driver archetypes indicating driving patterns of drivers; evaluating, by the one or more computing devices, the vehicle data according to a predictive model, to determine predictions of DTCs that are likely to occur for a particular one of the plurality of vehicles, the evaluation including using an indication of the driver archetype for the driver; generating, by the one or more computing devices and based on the determined predictions of the DTCs, a report describing potential maintenance issues for the particular one of the plurality of vehicles; and transmitting, by the one or more computing devices, the report to an entity associated with the particular one of the plurality of vehicles. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 23)
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10. A computing system comprising:
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a non-transitory computer-readable medium containing program instructions; and processing circuitry to execute the program instructions to; receive vehicle data from a plurality of vehicles, the vehicle data including diagnostic trouble codes (DTCs) generated by on-board diagnostic (OBD) computer systems of the plurality of vehicles; classify a driver associated with a particular one of the plurality of vehicles to obtain a driver archetype, of a plurality of possible driver archetypes, the driver archetypes indicating driving patterns of drivers; evaluate the vehicle data according to a predictive model to determine predictions of DTCs that are likely to occur for a particular one of the plurality of vehicles, the evaluation including using an indication of the driver archetype for the driver; generate, based on the determined predictions of the DTCs, a report describing potential maintenance issues for the particular one of the plurality of vehicles; and transmit the report to an entity associated with the particular one of the plurality of vehicles. - View Dependent Claims (11, 12, 13, 14, 15, 24)
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16. A computing system comprising:
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a non-transitory computer-readable medium containing program instructions; and processing circuitry to execute the program instructions to; receive vehicle data relating to a vehicle, the vehicle data being received from a telematics device associated with the vehicle and the vehicle data including; diagnostic trouble codes (DTCs) generated by an on-board diagnostic (OBD) computer system, and data from sensors associated with the vehicle; input the vehicle data to a predictive model trained to output maintenance issues that are likely to occur for the vehicle, the predictive model operating to classify a vehicle use pattern associated with the vehicle into one of a plurality of patterns and to generate the output maintenance issues based on the vehicle use pattern, the vehicle use pattern corresponding to a particular driving pattern at which the vehicle has been driven; and transmit an indication of the output of the predictive model, to an entity associated with the vehicle, when the output of the predictive model indicates maintenance issues are likely to occur for the vehicle. - View Dependent Claims (17, 18, 19, 20, 21, 22)
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Specification