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기록

PRE-TRAINED MACHINE-LEARNED SCENARIO DATA DIFFICULTY METRIC FOR VEHICLE CONTROL

발명심사 중
1조회수
20청구항 · 3 독립항
§ Ⅰ

개요

발명자

Seth Benjamin Aaron; Andrew Scott Crego; Alec Jacob Farid; Peter Scott Schleede; Nathan David Shemonski

IPC 분류

G6N 20/B60W 60/

CPC 분류

G6N20/B60W60/27

A pre-trained machine-learned model, pre-generated clusters determined from embeddings generated by the machine-learned model, and/or difficulty metric(s) determined from simulation and associated with the clusters may be transmitted to and used on a vehicle. The machine-learned model may use sensor data to generate an embedding or a difficulty metric characterizing a current scenario encountered by the vehicle and the vehicle may alter operation of the vehicle based on the difficulty metric or difficulty metric(s) for the cluster associated with the embedding.

원문 (중국어)

A pre-trained machine-learned model, pre-generated clusters determined from embeddings generated by the machine-learned model, and/or difficulty metric(s) determined from simulation and associated with the clusters may be transmitted to and used on a vehicle. The machine-learned model may use sensor data to generate an embedding or a difficulty metric characterizing a current scenario encountered by the vehicle and the vehicle may alter operation of the vehicle based on the difficulty metric or difficulty metric(s) for the cluster associated with the embedding.