JP2020004402A - ニューラルネットワークに基づく自動運転車両用の安全監視システム - Google Patents
ニューラルネットワークに基づく自動運転車両用の安全監視システム Download PDFInfo
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Abstract
Description
Claims (21)
- ユーザに自動運転車両の自動運転システムへの介入を促すためのコンピューター実施方法であって、
前記自動運転車両の複数のセンサから、センサデータを受信することと、
機械学習モデルを用いて、前記センサデータから所定量の特徴を抽出することと、
前記機械学習モデルを用いて抽出された特徴に基づいて、前記自動運転システムへの介入をユーザに促すか否かを決定することと、
前記自動運転システムへの介入をユーザに促すか否かの決定に基づいて、安全警報を生成することと、
生成した安全警報に基づいて、自動運転車両の自動運転システムへの介入を前記ユーザに促すことと、を備える方法。 - 前記自動運転車両のための地図データを受信することと、
前記機械学習モデルを用いて、前記センサデータ及び前記地図データの両者に基づいて、前記自動運転システムへの介入をユーザに促すか否かを決定することと、をさらに備える請求項1に記載の方法。 - 前記機械学習モデルは、前記所定量の特徴を抽出するためのニューラルネットワークモデルを含む、請求項2に記載の方法。
- 前記ニューラルネットワークモデルは、前記複数のセンサのそれぞれに対応するセンサデータのための完全接続層を含む請求項3に記載の方法。
- 前記ニューラルネットワークモデルは、前記地図データための部分接続層を含む請求項4に記載の方法。
- 前記部分接続層は、畳込み層である請求項5に記載の方法。
- 前記複数のセンサは、レンジ検出センサと、画像取得センサおよび慣性測定ユニットセンサを含む請求項1に記載の方法。
- 前記レンジ検出センサは、光検出と測距センサ(LIDAR)または電波検知と測距センサ(RADAR)を含む請求項7に記載の方法。
- 前記自動運転システムにより、ユーザの介入に対応するセンサデータを記録することと、
前記記録したレコーディングに基づいて前記機械学習モデルに対しスケジューリングを行ってトレーニングすることを、さらに備える請求項1に記載の方法。 - 命令が記憶される非一時的機械可読媒体であって、前記命令がプロセッサにより実行される場合に、
自動運転車両の複数のセンサから、センサデータを受信することと、
機械学習モデルを用いて、前記センサデータから所定量の特徴を抽出することと、
前記機械学習モデルを用いて抽出された特徴に基づいて、自動運転システムへの介入をユーザに促すか否かを決定することと、
前記自動運転システムへの介入をユーザに促すか否かの決定に基づいて、安全警報を生成することと、
生成した安全警報に基づいて、自動運転車両の自動運転システムへの介入を前記ユーザに促すこと、を前記プロセッサに実行させる非一時的可読媒体。 - 前記自動運転車両ための地図データを受信することと、
前記機械学習モデルを用いて、前記センサデータ及び前記地図データの両者に基づいて、前記自動運転システムへの介入をユーザに促すか否かを決定することと、をさらに備える請求項10に記載の非一時的可読媒体。 - 前記機械学習モデルは、前記所定量の特徴を抽出するためのニューラルネットワークモデルを含む、請求項11に記載の非一時的可読媒体。
- 前記ニューラルネットワークモデルは、前記複数のセンサのそれぞれに対応するセンサデータのための完全接続層を含む請求項12に記載の非一時的可読媒体。
- 前記ニューラルネットワークモデルは、前記地図データための部分接続層を含む請求項13に記載の非一時的可読媒体。
- 前記部分接続層は、畳込み層である請求項14に記載の非一時的可読媒体。
- プロセッサと、前記プロセッサに接続されて命令を記憶するメモリとを備えるデータ処理システムであって、
前記命令がプロセッサにより実行される場合に、
自動運転車両の複数のセンサから、センサデータを受信することと、
機械学習モデルを用いて、前記センサデータから所定量の特徴を抽出することと、
前記機械学習モデルを用いて抽出された特徴に基づいて、自動運転システムへの介入をユーザに促すか否かを決定することと、
前記自動運転システムへの介入をユーザに促すか否かの決定に基づいて、安全警報を生成することと、
生成した安全警報に基づいて、自動運転車両の自動運転システムへの介入を前記ユーザに促すことを、前記プロセッサに実行させるデータ処理システム。 - 前記自動運転車両ための地図データを受信することと、
前記機械学習モデルを用いて、前記センサデータ及び前記地図データの両者に基づいて、前記自動運転システムへの介入をユーザに促すか否かを決定することと、をさらに備える請求項16に記載のデータ処理システム。 - 前記機械学習モデルは、前記所定量の特徴を抽出するためのニューラルネットワークモデルを含む、請求項17に記載のデータ処理システム。
- 前記ニューラルネットワークモデルは、前記複数のセンサのそれぞれに対応するセンサデータのための完全接続層を含む請求項18に記載のデータ処理システム。
- 前記ニューラルネットワークモデルは、前記地図データための部分接続層を含む請求項19に記載のデータ処理システム。
- 前記部分接続層は、畳込み層である請求項20に記載のデータ処理システム。
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US16/021,007 US10457294B1 (en) | 2018-06-27 | 2018-06-27 | Neural network based safety monitoring system for autonomous vehicles |
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