{"links":{},"id":224673,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00224673","sets":["6201:6202:9109:9110:11242"]},"path":["11242"],"owner":"44499","recid":"224673","title":["車両時系列位置情報の逐次適用による車両返却予測手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-03-09"},"_buckets":{"deposit":"1517fe7f-b7df-4d57-b4d2-3ca6ec31613a"},"_deposit":{"id":"224673","pid":{"type":"depid","value":"224673","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"車両時系列位置情報の逐次適用による車両返却予測手法","author_link":["592937","592935","592936","592930","592932","592931","592934","592933"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"車両時系列位置情報の逐次適用による車両返却予測手法"}]},"item_type_id":"19","publish_date":"2023-03-09","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_19_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"奈良先端科学技術大学院大学"},{"subitem_text_value":" 大阪公立大学"},{"subitem_text_value":" 奈良先端科学技術大学院大学"},{"subitem_text_value":" 奈良先端科学技術大学院大学"}]},"item_19_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":" Osaka Metropolitan University","subitem_text_language":"en"},{"subitem_text_value":" Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":" Nara Institute of Science and Technology","subitem_text_language":"en"}]},"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/224673/files/IPSJ-KansaiBCSS09_202305.pdf","label":"IPSJ-KansaiBCSS09_202305.pdf"},"date":[{"dateType":"Available","dateValue":"2025-03-09"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-KansaiBCSS09_202305.pdf","filesize":[{"value":"865.9 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"38155093-3000-4d80-aab6-593a247c060f","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_19_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"佐瀬, 凌太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"藤本 まなと"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"諏訪 博彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"安本 慶一"}],"nameIdentifiers":[{}]}]},"item_19_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ryota, Saze","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Manato Fujimoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hirohiko Suwa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Keiichi Yasumoto","creatorNameLang":"en"}],"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_19_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"都市部における様々な移動需要への対応と，化石燃料の消費削減に貢献できるワンウェイカーシェアが近年注目を集めている．このワンウェイカーシェアでは，特定の時間・場所へ車両需要が偏ってしまうことで“車両偏在問題”が発生してしまい，システムの利用効率の低下を招いてしまうことが知られている．この車両偏在は，“車両再配置”による解決が可能である．本研究では，この車両再配置の実現において必要となる車両返却予測を行う手法を提案する．提案手法では，利用者の情報や開始地点・時間といった静的情報に加えて，時系列的に変化する位置情報等の動的情報を取得し，静的情報・動的情報に基づく機械学習モデルを用いた車両返却予測を行う．さらにこの予測を利用開始時点だけでなく，利用中の一定時間おきに動的情報を更新しながら行うことで返却予測結果を更新し続ける．提案手法を評価するために行った実世界カーシェアデータを用いた評価実験では，返却ステーション予測においては各ステーションのF値のミクロ平均として0.922，返却時間予測においては39.9分の平均絶対誤差（MAE）を達成した．さらに，どちらの予測においても時系列的に予測精度の改善が行われていることを確認した．さらに，提案手法による返却予測結果のフィードバックによってワンウェイカーシェアの利用効率の改善可能性があることが示された．","subitem_description_type":"Other"}]},"item_19_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"行動変容と社会システム vol.09"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2023-03-09","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:24:14.593700+00:00","updated":"2025-01-19T13:03:48.904818+00:00"}