{"_buckets": {"deposit": "514fec36-e69e-4652-a8d0-45d7adc444fd"}, "_deposit": {"id": "4942", "owners": [1], "pid": {"revision_id": 0, "type": "depid", "value": "4942"}, "status": "published"}, "_oai": {"id": "oai:nied-repo.bosai.go.jp:00004942", "sets": []}, "author_link": [], "item_10001_biblio_info_7": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2020", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "1", "bibliographicPageEnd": "216", "bibliographicPageStart": "210", "bibliographicVolumeNumber": "1", "bibliographic_titles": [{"bibliographic_title": "AI・データサイエンス論文集", "bibliographic_titleLang": "ja"}, {"bibliographic_title": "Intelligence, Informatics and Infrastructure", "bibliographic_titleLang": "en"}]}]}, "item_10001_description_5": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "\u003cp\u003e近年、低頻度降雪地域では、降雪の際に、道路での車両の大規模滞留が見られる。道路管理者による異常事態の監視や路面状態の判別は、主に目視で行われているため、異常検知の効率がやや低い。\u003c/p\u003e\u003cp\u003e本研究は、道路管理者が迅速に異常検知や処理判断をするための支援ツールとして、ドライブレコーダーの画像をもちいて、道路路面を「乾燥」、「湿潤」、「浸水・冠水」、「湿雪」、「圧雪」の 5種類へ目視分類した教師データを作成した。また、自動で路面状態を判別する AIモデルを構築し、昼と夜を合わせた 26199枚の画像で検証した結果、概ね 85％の正答率であった。 \u003c/p\u003e", "subitem_description_language": "ja", "subitem_description_type": "Other"}, {"subitem_description": "\u003cp\u003eIn recent years, even in areas where there is usually little snowfall, large-scale retention on roads is observed when snowfall occurs. The monitoring of abnormal situations by road administrators and the interpretation of road surface conditions are mainly performed visually, and the efficiency of abnormality detection is a little bit low. \u003c/p\u003e\u003cp\u003eIn this study, as a support tool for road administrators to quickly detect anomalies and make processing decisions. We developed an AI model that automatically determines the road surface condition. The training data were made by the image of the dashcam data, which is classified into 5 types, such as dry, wet, flood, wet snow, and consolidation. As a result of automatically discriminating 26199 road surface images of day and night using the AI model, the Training Accuracy rate was around 85%.\u003c/p\u003e", "subitem_description_language": "en", "subitem_description_type": "Other"}]}, "item_10001_publisher_8": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "公益社団法人 土木学会", "subitem_publisher_language": "ja"}, {"subitem_publisher": "Japan Society of Civil Engineers", "subitem_publisher_language": "en"}]}, "item_10001_relation_14": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "10.11532/jsceiii.1.J1_210"}}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "李 瑾", "creatorNameLang": "ja"}, {"creatorName": "LI Jin", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "阿部 雅人", "creatorNameLang": "ja"}, {"creatorName": "ABE Masato", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "杉崎 光一", "creatorNameLang": "ja"}, {"creatorName": "SUGISAKI Kouichi", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "中村 一樹", "creatorNameLang": "ja"}, {"creatorName": "NAKAMURA Kazuki", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "上石 勲", "creatorNameLang": "ja"}, {"creatorName": "KAMIISHI Isao", "creatorNameLang": "en"}]}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "jpn"}]}, "item_title": "AI技術を活用した冬季道路路面判別の効率化", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "AI技術を活用した冬季道路路面判別の効率化", "subitem_title_language": "ja"}, {"subitem_title": "EFFICIENCY IMPROVEMENT OF WINTER ROAD SURFACE INTERPRETATION BY USING ARTIFICIAL INTELLIGENCE MODEL", "subitem_title_language": "en"}]}, "item_type_id": "40001", "owner": "1", "path": ["1670839190650"], "permalink_uri": "https://nied-repo.bosai.go.jp/records/4942", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2023-03-30"}, "publish_date": "2023-03-30", "publish_status": "0", "recid": "4942", "relation": {}, "relation_version_is_last": true, "title": ["AI技術を活用した冬季道路路面判別の効率化"], "weko_shared_id": -1}