Driving Scene Retrieval with an Integrated Similarity Measure Using Driving Behavior and Environment Information

電気学会 電子図書館 Verified independent store

→

カテゴリ: 論文誌(論文単位)グループ名: 【C】電子・情報・システム部門発行日: 2014/05/01タイトル(英語): Driving Scene Retrieval with an Integrated Similarity Measure Using Driving Behavior and Environment Information著者名: Y iyang Li (Graduate School of Information Science, Nagoya University), Chiyomi Miyajima (Graduate School of Information Science, Nagoya University), Norihide Kitaoka (Graduate School of Information Science, Nagoya University), Kazuya Takeda (Graduate Scho著者名(英語): Yiyang Li （Graduate School of Information Science, Nagoya University）, Chiyomi Miyajima （Graduate School of Information Science, Nagoya University）, Norihide Kitaoka （Graduate School of Information Science, Nagoya University）, Kazuya Takeda （Graduate School of Information Science, Nagoya University）キーワード: Driving scene retrieval，Integrated similarity measure，Driving behavior，Driving environment要約(英語): This paper proposes a similarity measurement technique for retrieving similar driving scenes, using driving behavior signals and features of the driving environment. A previous work proposed a similarity-based retrieval system for finding driving data, which retrieved driving scenes by measuring similarity between scenes using driving behavior signals, such as steering angle and vehicle velocity. However, driving scenes can also be characterized by the surrounding driving environment. In this study, we assume that driving scenes consist of three major entities: the driver, the driver's vehicle, and the driving environment. We measure the distance between driving scenes using road features as well as the position and motion of surrounding vehicles (i.e., the surrounding driving environment), in addition to driving behavior signals obtained from the driver and the driver's vehicle. We then conduct a driving scene retrieval experiment to evaluate our similarity measurement method, using driving data collected on an expressway. Experimental results show that the additional use of environmental information significantly improves the precision of retrieval of scenes of driving events compared with a conventional method. According to our results, we also find that different people focus on different elements when comparing driving scenes, which may indicate that different drivers focus on different things when driving.本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.134 No.5 （2014） 特集：機械学習手法に基づく設備診断・監視技術本誌掲載ページ: 678-685 p原稿種別: 論文／英語電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/134/5/134_678/_article/-char/ja/ Show more