{"created":"2025-01-19T01:18:23.688891+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00217972","sets":["1164:2836:10841:10911"]},"path":["10911"],"owner":"44499","recid":"217972","title":["バス移動時間予測に効果的な特徴量を取得するためのプローブデータ収集地点の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-05-19"},"_buckets":{"deposit":"ca0fda25-ddf0-4e9e-91ff-78b9ca7871f7"},"_deposit":{"id":"217972","pid":{"type":"depid","value":"217972","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"バス移動時間予測に効果的な特徴量を取得するためのプローブデータ収集地点の検討","author_link":["565774","565773","565775","565776"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"バス移動時間予測に効果的な特徴量を取得するためのプローブデータ収集地点の検討"},{"subitem_title":"Investigation of probe data collection points to obtain effective features for bus travel time prediction","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"交通","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-05-19","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"九州大学大学院システム情報科学研究院"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Electrical Engineering, Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Information Science and Electrical Engineering, Kyushu University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/217972/files/IPSJ-DPS22191032.pdf","label":"IPSJ-DPS22191032.pdf"},"date":[{"dateType":"Available","dateValue":"2024-05-19"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DPS22191032.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":"34"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a6977d3e-6408-4939-a75c-dc67f5fdbc92","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"川谷, 卓哉"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"峯, 恒憲"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takuya, Kawatani","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tsunenori, Mine","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10116224","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8906","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"路線バス運行状況の収集解析は，時刻表の改善や遅延の案内，移動時間予測を実現する際に大変有用であり，利用客の満足度を向上させるために重要である．運行状況の収集は，リアルタイムに近い方がその時の状況を案内や予測に即時に反映できる．しかし，リアルタイムに収集できるような設備は設置コストや通信コストが高くなる．本研究では，バス車両に搭載した車載機で走行記録データ（プローブデータ）を蓄積し，運行ルート中の路側機で車載機中の蓄積データを収集するシステムを利用して，路側機の数を増減した場合の設置コストと，当該路側機で取得できる情報を用いてバスの移動時間を予測する場合の，予測精度とデータ収集コストの変化をシミュレーション実験から算出し，適切な設置台数と設置位置を検討した．その結果，「1 時間前の予測対象区間の移動時間」が高精度な予測に有効であること，また，この特徴量を取得するには路側機が路線の起終点に各 1 台あることが望ましいことを確認した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告マルチメディア通信と分散処理（DPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-05-19","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"32","bibliographicVolumeNumber":"2022-DPS-191"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":217972,"updated":"2025-01-19T15:19:12.752505+00:00","links":{}}