列車前方監視のためのセンサフュージョンによる支障物検知手法

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2024/03/01

タイトル(英語): Sensor Fusion Method for Train Forward Surveillance

著者名: 影山　椋（（公財）鉄道総合技術研究所），長峯　望（（公財）鉄道総合技術研究所）

著者名(英語): Ryo Kageyama (Railway Technical Research Institute), Nozomi Nagamine (Railway Technical Research Institute)

キーワード: 列車前方監視，センサフュージョン，画像処理，3次元点群処理　　train forward surveillance，sensor fusion，image processing，3D point cloud processing

要約(英語): We present the development of a train forward surveillance method using a camera and sensors. In train forward surveillance methods for railroads, it is crucial to establish a sensor technology capable of reliably detecting distant obstacles hundreds of meters away. Therefore, we developed a detection method by sensor fusion between 4K camera and 3D LiDAR. Using a combination of a camera and nine LiDARs, we confirm that the proposed method can detect a person located 400m away with a detection rate of 94% and a car located 600m away with a detection rate of 100%. Moreover, based on the trend that detection performance improves as the number of LiDARs increases, we estimated the conditions required to reliably detect a person 500m away.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.144 No.3 （2024） 特集：J-RAIL 2022

本誌掲載ページ: 70-78 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/144/3/144_70/_article/-char/ja/