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US 2023/0055012 A1Published application
Dynamic vehicle operation
AssigneeFord Global Technologies, LLC
InventorsLijun Wang, Chen Zhang, Kai Wu, Yan Wang
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Abstract
Data from a vehicle subsystem are input to a machine learning program trained to output a plurality of temporal pattern vectors. The temporal pattern vectors are input to an attention-based encoder trained to output a latent feature matrix. Each of the latent feature vectors is assigned to a respective one of a plurality of clusters. Based on the assigned clusters, an operation value is output to a controller of the vehicle subsystem.
Claims20
A system, comprising a computer including a processor and a memory, the memory storing instructions executable by the processor to:
- input data from a vehicle subsystem to a machine learning program trained to output a plurality of temporal pattern vectors that include data describing operation parameters of the vehicle subsystem;
- input the temporal pattern vectors to an attention-based encoder trained to output a latent feature matrix that includes a plurality of latent feature vectors that each include data describing a respective weight of each temporal pattern vector relative to each other temporal pattern vector;
- assign each of the latent feature vectors to a respective one of a plurality of clusters;
- and
- based on the assigned clusters, output an operation value to a controller of the vehicle subsystem that is programmed to adjust operation of the vehicle subsystem to the output operation value.
2 more elements
A method, comprising:
- inputting data from a vehicle subsystem to a machine learning program trained to output a plurality of temporal pattern vectors that include data describing operation parameters of the vehicle subsystem;
- inputting the temporal pattern vectors to an attention-based encoder trained to output a latent feature matrix that includes a plurality of latent feature vectors that each include data describing a respective weight of each temporal pattern vector relative to each other temporal pattern vector;
- assigning each of the latent feature vectors to a respective one of a plurality of clusters;
- and
- based on the assigned clusters, outputting an operation value to a controller of the vehicle subsystem that is programmed to adjust operation of the vehicle subsystem to the output operation value.
2 more elements
Dependencies are inferred from the claim text.