検索に戻る
案件記録

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

発明審査中
20請求項 · 3 独立
§ Ⅰ

案件概要

発明者

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

IPC分類

G6N 20/B60W 60/

CPC分類

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.

原文(中国語)

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.

外部リソース