US 2024/0203168 A1 · SYSTEMS AND METHODS FOR AUTOMATICALLY PREDICTING AND SCHEDULING VEHICLE REPAIRS

Abstract

Systems, methods, and computer-readable media are provided for automatically predicting and scheduling vehicle repairs. Particularly, a model (such as a natural language processing model, for example) may be trained using historical data relating to prior vehicle DTCs and actions taken to resolve the DTCs. The trained model may then be used to determine multiple potential resolutions to current DTCs provided by a vehicle. The model may also output probabilities associated with the various resolutions. Finally, the model may be configured to consider historical data associated with different types of vehicles than the current vehicle providing the DTC code. This allows for a larger data set to be considered by the model than if the model only considered data associated with the same type of vehicle.

Claims20

Dependent claims

A system comprising:

memory that stores computer-executable instructions;
and
one or more processors configured to access the memory and execute the computer-executable instructions to:
receive a first diagnostic trouble code (DTC) associated with a first vehicle at a first time, wherein the first DTC indicates a first vehicle fault;
determine a first action that resolves the first vehicle fault;
train a computing model using the first DTC and the first action;
receive a second diagnostic trouble code (DTC) associated with a second vehicle at a second time, wherein the second DTC indicates a second vehicle fault;
and
determine, by a computing model and based on a first correlation between the first DTC and the first action, a second action and a first probability, and a third action and a second probability, wherein the first probability is a probability that the second action will resolve the second vehicle fault, and wherein the second probability is a probability that the third action will resolve the second vehicle fault.

6 more elements

A method comprising:

receiving a first diagnostic trouble code (DTC) associated with a first vehicle at a first time, wherein the first DTC indicates a first vehicle fault;
determining a first action that resolves the first vehicle fault;
training a computing model using the first DTC and the first action;
receiving a second diagnostic trouble code (DTC) associated with a second vehicle at a second time, wherein the second DTC indicates a second vehicle fault;
and
determining, by the computing model and based on a first correlation between the first DTC and the first action, a second action and a first probability, and a third action and a second probability, wherein the first probability is a probability that the second action will resolve the second vehicle fault, and wherein the second probability is a probability that the third action will resolve the second vehicle fault.

3 more elements

A non-transitory computer-readable medium storing computer-executable instructions, that when executed by one or more processors, cause the one or more processors to:

receive a first diagnostic trouble code (DTC) associated with a first vehicle at a first time, wherein the first DTC indicates a first vehicle fault;
determine a first action that resolves the first vehicle fault;
train a computing model using the first DTC and the first action;
receive a second diagnostic trouble code (DTC) associated with a second vehicle at a second time, wherein the second DTC indicates a second vehicle fault;
and
determine, by a computing model and based on a first correlation between the first DTC and the first action, a second action and a first probability, and a third action and a second probability, wherein the first probability is a probability that the second action will resolve the second vehicle fault, and wherein the second probability is a probability that the third action will resolve the second vehicle fault.

3 more elements

Dependencies are inferred from the claim text.

Systems and methods for automatically predicting and scheduling vehicle repairs

Life of this patent

Systems and methods for automatically predicting and scheduling vehicle repairs

Life of this patent

Abstract

Claims20