{"created":"2025-01-19T01:19:45.032519+00:00","updated":"2025-01-19T14:48:41.953212+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00219685","sets":["6164:6165:6640:11008"]},"path":["11008"],"owner":"44499","recid":"219685","title":["機械学習を用いた首都高速道路における事象規制情報の評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-07-06"},"_buckets":{"deposit":"6ba5b7a6-0b20-4651-812b-1b9d075e52e8"},"_deposit":{"id":"219685","pid":{"type":"depid","value":"219685","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習を用いた首都高速道路における事象規制情報の評価","author_link":["573220","573219","573218"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習を用いた首都高速道路における事象規制情報の評価"}]},"item_type_id":"18","publish_date":"2022-07-06","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":"現在， 日本貨物鉄道 株式会社"},{"subitem_text_value":"慶應義塾大学大学院政策・メディア研究科"},{"subitem_text_value":"慶應義塾大学環境情報学部"}]},"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/219685/files/IPSJ-DICOMO2022111.pdf","label":"IPSJ-DICOMO2022111.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-06"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2022111.pdf","filesize":[{"value":"1.7 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":"98cc0c5e-453a-47f6-aba7-f38c73804e6f","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"西田, 亘"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐藤, 雅明"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, 修"}],"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":"インターネットやモバイルコンピューティングの普及に伴う道路交通情報提供手法の多様化によって，人の手を介さず，機械的に情報を加工し，運転者への提供までを行う媒体が利用され始めている．こうした媒体において，事象規制情報はその影響度などを考慮せず，一律に表示・提供されている．そのため，特に運転者が情報を得ようとする大規模規制時に，情報の可読性が低下するという課題がある．そこで，本研究では，各個の規制情報について区間積和法による延べ損失時間を算出し，これを道路交通への影響の度合いを示す相対尺度として，過去の実績値に対して交通規制が出された時点での影響に関する回帰モデルを作成した．これを用いることで，現時点で存在する各事象規制情報について，それぞれの影響度を道路間で端的に評価し，比較する手法を提案した．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"791","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2022論文集"}],"bibliographicPageStart":"784","bibliographicIssueDates":{"bibliographicIssueDate":"2022-07-06","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":219685,"links":{}}