{"id":230207,"updated":"2025-01-19T11:14:43.580385+00:00","links":{},"created":"2025-01-19T01:29:49.580050+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230207","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"230207","title":["人流シミュレーションにおける格子分割を用いた進行方向ベクトル計算の削減手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"d00282c1-bc67-41ff-992b-29b571074920"},"_deposit":{"id":"230207","pid":{"type":"depid","value":"230207","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"人流シミュレーションにおける格子分割を用いた進行方向ベクトル計算の削減手法","author_link":["619365","619366","619363","619364"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"人流シミュレーションにおける格子分割を用いた進行方向ベクトル計算の削減手法"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"千葉工大"},{"subitem_text_value":"千葉工大"},{"subitem_text_value":"千葉工大"},{"subitem_text_value":"千葉工大"}]},"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/230207/files/IPSJ-Z85-5W-08.pdf","label":"IPSJ-Z85-5W-08.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-5W-08.pdf","filesize":[{"value":"207.1 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"2ce33d43-acae-4dcb-8165-3afc9603fea4","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"片寄, 颯人"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, あすか"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"富永, 浩文"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"前川, 仁孝"}],"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_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本研究では,Social Force Model(SFM)を用いた人流シミュレーションを高速化するために,前処理を行うことで,エージェントが経由地点に向かうための方向ベクトルを再計算せずにSFMの運動方程式を算出する手法を提案する.SFMは,時間ステップごとに各エージェントの運動方程式を解くことで,人の流れを解析する手法である.SFMの運動方程式は,目的地に向かう進行方向ベクトルや周囲のエージェントから受ける力,障害物から受ける力の合力を用いて,エージェントの移動方向や速度を算出する.目的地に向かう進行方向ベクトルは,人が目的地に向かう動きを再現するため,エージェント座標が変わるたびに再計算する必要がある.そこで,提案手法では,解析領域を格子状に分割し,格子領域ごとに方向ベクトルをあらかじめ計算し,それを目的地までの進行方向ベクトルとして用いる.","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"844","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"843","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}