DRIVING ASSISTANCE DEVICE, DRIVING ASSISTANCE METHOD, AND PROGRAM
To provide a technology capable of presenting a variety of nearly optimal operation quantity sequence.SOLUTION: A driving assistance device according to one aspect of the present disclosure includes: a learning unit configured to learn a prediction model that predicts a feature quantity of a state v...
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| creator | SHIMAZAKI YUICHI KIRYU SATOSHI KAWAGUCHI MAYUKO ISHIBASHI NAOTO KANEDA TATSUYA |
| description | To provide a technology capable of presenting a variety of nearly optimal operation quantity sequence.SOLUTION: A driving assistance device according to one aspect of the present disclosure includes: a learning unit configured to learn a prediction model that predicts a feature quantity of a state variable from a feature quantity of an operation variable and a feature quantity of an environmental variable using a feature quantity of the operation variable in a past time section, a feature quantity of the state variable in the past time section, and a feature quantity of the environmental variable in the past time section; an optimization unit configured to calculate an optimal feature quantity of the operation variable in a future time section by the prediction model using a feature quantity of the environmental variable in a time section of the future time section and a target feature quantity of the state variable in the future time section; and a time-series extraction unit configured to extract a plurality of time-series data of the operation variable in the future time section using a plurality of feature quantities at least similar to the optimal feature quantity of the operation variable.SELECTED DRAWING: Figure 2
【課題】最適に近い多様な操作量系列を提示できる技術を提供すること。【解決手段】本開示の一態様による運転支援装置は、過去の時間区間における操作変数の特徴量と、前記過去の時間区間における状態変数の特徴量と、前記過去の時間区間における環境変数の特徴量とを用いて、前記操作変数の特徴量と前記環境変数の特徴量から前記状態変数の特徴量を予測する予測モデルを学習するように構成されている学習部と、将来の時間区間における前記環境変数の特徴量と、前記将来の時間区間における前記状態変数の目標特徴量とを用いて、前記予測モデルにより前記将来の時間区間における前記操作変数の最適特徴量を算出するように構成されている最適化部と、前記操作変数の最適特徴量に少なくとも類似する複数の特徴量を用いて、前記将来の時間区間における操作変数の複数の時系列データを抽出するように構成されている時系列抽出部と、を有する。【選択図】図２ |
| format | Patent |
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【課題】最適に近い多様な操作量系列を提示できる技術を提供すること。【解決手段】本開示の一態様による運転支援装置は、過去の時間区間における操作変数の特徴量と、前記過去の時間区間における状態変数の特徴量と、前記過去の時間区間における環境変数の特徴量とを用いて、前記操作変数の特徴量と前記環境変数の特徴量から前記状態変数の特徴量を予測する予測モデルを学習するように構成されている学習部と、将来の時間区間における前記環境変数の特徴量と、前記将来の時間区間における前記状態変数の目標特徴量とを用いて、前記予測モデルにより前記将来の時間区間における前記操作変数の最適特徴量を算出するように構成されている最適化部と、前記操作変数の最適特徴量に少なくとも類似する複数の特徴量を用いて、前記将来の時間区間における操作変数の複数の時系列データを抽出するように構成されている時系列抽出部と、を有する。【選択図】図２</description><language>eng ; jpn</language><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL ; CONTROLLING ; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS ; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS ; PHYSICS ; REGULATING</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240613&DB=EPODOC&CC=JP&NR=2024079938A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240613&DB=EPODOC&CC=JP&NR=2024079938A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>SHIMAZAKI YUICHI</creatorcontrib><creatorcontrib>KIRYU SATOSHI</creatorcontrib><creatorcontrib>KAWAGUCHI MAYUKO</creatorcontrib><creatorcontrib>ISHIBASHI NAOTO</creatorcontrib><creatorcontrib>KANEDA TATSUYA</creatorcontrib><title>DRIVING ASSISTANCE DEVICE, DRIVING ASSISTANCE METHOD, AND PROGRAM</title><description>To provide a technology capable of presenting a variety of nearly optimal operation quantity sequence.SOLUTION: A driving assistance device according to one aspect of the present disclosure includes: a learning unit configured to learn a prediction model that predicts a feature quantity of a state variable from a feature quantity of an operation variable and a feature quantity of an environmental variable using a feature quantity of the operation variable in a past time section, a feature quantity of the state variable in the past time section, and a feature quantity of the environmental variable in the past time section; an optimization unit configured to calculate an optimal feature quantity of the operation variable in a future time section by the prediction model using a feature quantity of the environmental variable in a time section of the future time section and a target feature quantity of the state variable in the future time section; and a time-series extraction unit configured to extract a plurality of time-series data of the operation variable in the future time section using a plurality of feature quantities at least similar to the optimal feature quantity of the operation variable.SELECTED DRAWING: Figure 2
【課題】最適に近い多様な操作量系列を提示できる技術を提供すること。【解決手段】本開示の一態様による運転支援装置は、過去の時間区間における操作変数の特徴量と、前記過去の時間区間における状態変数の特徴量と、前記過去の時間区間における環境変数の特徴量とを用いて、前記操作変数の特徴量と前記環境変数の特徴量から前記状態変数の特徴量を予測する予測モデルを学習するように構成されている学習部と、将来の時間区間における前記環境変数の特徴量と、前記将来の時間区間における前記状態変数の目標特徴量とを用いて、前記予測モデルにより前記将来の時間区間における前記操作変数の最適特徴量を算出するように構成されている最適化部と、前記操作変数の最適特徴量に少なくとも類似する複数の特徴量を用いて、前記将来の時間区間における操作変数の複数の時系列データを抽出するように構成されている時系列抽出部と、を有する。【選択図】図２</description><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL</subject><subject>CONTROLLING</subject><subject>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</subject><subject>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</subject><subject>PHYSICS</subject><subject>REGULATING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZHB0CfIM8_RzV3AMDvYMDnH0c3ZVcHEN83R21VHAIuXrGuLh76Kj4OjnohAQ5O8e5OjLw8CalphTnMoLpbkZlNxcQ5w9dFML8uNTiwsSk1PzUkvivQKMDIxMDMwtLY0tHI2JUgQAHKYrSg</recordid><startdate>20240613</startdate><enddate>20240613</enddate><creator>SHIMAZAKI YUICHI</creator><creator>KIRYU SATOSHI</creator><creator>KAWAGUCHI MAYUKO</creator><creator>ISHIBASHI NAOTO</creator><creator>KANEDA TATSUYA</creator><scope>EVB</scope></search><sort><creationdate>20240613</creationdate><title>DRIVING ASSISTANCE DEVICE, DRIVING ASSISTANCE METHOD, AND PROGRAM</title><author>SHIMAZAKI YUICHI ; KIRYU SATOSHI ; KAWAGUCHI MAYUKO ; ISHIBASHI NAOTO ; KANEDA TATSUYA</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_JP2024079938A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; jpn</language><creationdate>2024</creationdate><topic>CONTROL OR REGULATING SYSTEMS IN GENERAL</topic><topic>CONTROLLING</topic><topic>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</topic><topic>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</topic><topic>PHYSICS</topic><topic>REGULATING</topic><toplevel>online_resources</toplevel><creatorcontrib>SHIMAZAKI YUICHI</creatorcontrib><creatorcontrib>KIRYU SATOSHI</creatorcontrib><creatorcontrib>KAWAGUCHI MAYUKO</creatorcontrib><creatorcontrib>ISHIBASHI NAOTO</creatorcontrib><creatorcontrib>KANEDA TATSUYA</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>SHIMAZAKI YUICHI</au><au>KIRYU SATOSHI</au><au>KAWAGUCHI MAYUKO</au><au>ISHIBASHI NAOTO</au><au>KANEDA TATSUYA</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>DRIVING ASSISTANCE DEVICE, DRIVING ASSISTANCE METHOD, AND PROGRAM</title><date>2024-06-13</date><risdate>2024</risdate><abstract>To provide a technology capable of presenting a variety of nearly optimal operation quantity sequence.SOLUTION: A driving assistance device according to one aspect of the present disclosure includes: a learning unit configured to learn a prediction model that predicts a feature quantity of a state variable from a feature quantity of an operation variable and a feature quantity of an environmental variable using a feature quantity of the operation variable in a past time section, a feature quantity of the state variable in the past time section, and a feature quantity of the environmental variable in the past time section; an optimization unit configured to calculate an optimal feature quantity of the operation variable in a future time section by the prediction model using a feature quantity of the environmental variable in a time section of the future time section and a target feature quantity of the state variable in the future time section; and a time-series extraction unit configured to extract a plurality of time-series data of the operation variable in the future time section using a plurality of feature quantities at least similar to the optimal feature quantity of the operation variable.SELECTED DRAWING: Figure 2
【課題】最適に近い多様な操作量系列を提示できる技術を提供すること。【解決手段】本開示の一態様による運転支援装置は、過去の時間区間における操作変数の特徴量と、前記過去の時間区間における状態変数の特徴量と、前記過去の時間区間における環境変数の特徴量とを用いて、前記操作変数の特徴量と前記環境変数の特徴量から前記状態変数の特徴量を予測する予測モデルを学習するように構成されている学習部と、将来の時間区間における前記環境変数の特徴量と、前記将来の時間区間における前記状態変数の目標特徴量とを用いて、前記予測モデルにより前記将来の時間区間における前記操作変数の最適特徴量を算出するように構成されている最適化部と、前記操作変数の最適特徴量に少なくとも類似する複数の特徴量を用いて、前記将来の時間区間における操作変数の複数の時系列データを抽出するように構成されている時系列抽出部と、を有する。【選択図】図２</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING |
| title | DRIVING ASSISTANCE DEVICE, DRIVING ASSISTANCE METHOD, AND PROGRAM |
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