{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00212971","sets":["6164:6165:6640:10712"]},"path":["10712"],"owner":"44499","recid":"212971","title":["LSTMを用いた高精度歩行者測位方法に関する検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-06-23"},"_buckets":{"deposit":"59dda7d3-bc0c-49ca-aafe-f2067b89a29f"},"_deposit":{"id":"212971","pid":{"type":"depid","value":"212971","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"LSTMを用いた高精度歩行者測位方法に関する検討","author_link":["544157","544156","544158"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"LSTMを用いた高精度歩行者測位方法に関する検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ITS","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2021-06-23","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"電気通信大学大学院情報理工学研究科情報・ネットワーク工学専攻"},{"subitem_text_value":"電気通信大学大学院情報理工学研究科情報・ネットワーク工学専攻"},{"subitem_text_value":"電気通信大学"},{"subitem_text_value":"電気通信大学大学院情報理工学研究科情報・ネットワーク工学専攻"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/212971/files/IPSJ-DICOMO2021073.pdf","label":"IPSJ-DICOMO2021073.pdf"},"date":[{"dateType":"Available","dateValue":"2023-06-23"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2021073.pdf","filesize":[{"value":"1.9 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"4bf0c3f8-2773-4416-bdd2-e217f55306c9","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"井上, 真樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"湯, 素華"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小花, 貞夫"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"自動運転の実現に向けて交通事故防止が大きな課題となっている.見通し外の歩行者との事故を回避するために,歩行者が自身の所有する端末から位置情報を含むパケットを送信し周囲の車両に知らせる歩車間通信が提案されている.歩行者位置の測位には一般的に GPS が用いられるが,都市部では建物の遮蔽などにより測位精度が大幅に劣化しうる.この問題を解決するために,GPS に加えて車両を測位の基準点とし,チャネル状態情報(CSI)から歩車間距離を推測して歩行者位置を算出する測位方式が検討されている.本稿では,歩行者と車両の位置関係が連続的に変化していくことに着目し,従来の SVR(Support Vector Regression)を利用して瞬間CSIから歩車間距離を算出する代わりに,LSTM(Long short-term memory)ネットワークを用いた深層学習を介して CSI の時系列変化から歩車間距離を高精度に推測する手法を検討し,測距・測位精度を評価した.3D レイトレーシングを用いたシミュレーションにより,LSTM を用いた検討方式は SVR を利用した先行方式に比べ,平均歩車間距離誤差を 44.9%,平均水平測位誤差を 46.9% 削減可能であることを確認した.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"554","bibliographic_titles":[{"bibliographic_title":"マルチメディア,分散協調とモバイルシンポジウム2021論文集"}],"bibliographicPageStart":"547","bibliographicIssueDates":{"bibliographicIssueDate":"2021-06-23","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":212971,"updated":"2025-01-19T17:18:59.664477+00:00","links":{},"created":"2025-01-19T01:13:53.458690+00:00"}