{"_buckets": {"deposit": "bae5840a-1fbe-461b-8ced-61af84e979c1"}, "_deposit": {"id": "7875", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "7875"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00007875"}, "item_10_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2007", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "827", "bibliographicPageStart": "823", "bibliographic_titles": [{"bibliographic_title": "IEEE Intelligent Vehicles Symposium"}]}]}, "item_10_description_4": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "This paper presents a method to generate car-following patterns for individual drivers. We assume that driving is a recursive process. A driver recognizes a road environment such as velocity and following distance and adjusts gas and brake pedal positions. A vehicle status changes according to the driver\u0027s operation and the road environment changes according to the vehicle status. Driving patterns of each driver are modeled with a Gaussian mixture model (GMM), which is trained as a joint probability distribution of following distance, velocity, pedal position signals and their dynamics. Gas and brake pedal operation patterns are generated from the GMMs in a maximum likelihood criterion so that the conditional probability is maximized for a given environment i.e., following distance and velocity. Experimental results for a driving simulator show that car-following patterns generated from GMMs for three different drivers maintain their individual driving characteristics.", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/9597"}]}, "item_10_publisher_32": {"attribute_name": "\u51fa\u7248\u8005", "attribute_value_mlt": [{"subitem_publisher": "IEEE"}]}, "item_10_relation_11": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "http://dx.doi.org/10.1109/IVS.2007.4290218", "subitem_relation_type_select": "DOI"}}]}, "item_10_relation_8": {"attribute_name": "ISBN", "attribute_value_mlt": [{"subitem_relation_type_id": {"subitem_relation_type_id_text": "1-4244-1068-1", "subitem_relation_type_select": "ISBN"}}]}, "item_10_rights_12": {"attribute_name": "\u6a29\u5229", "attribute_value_mlt": [{"subitem_rights": "Copyright \u00a9 2007 IEEE. Reprinted from (relevant publication info). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University\u2019s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org."}]}, "item_10_select_15": {"attribute_name": "\u8457\u8005\u7248\u30d5\u30e9\u30b0", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_10_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "1931-0587", "subitem_source_identifier_type": "ISSN"}]}, "item_10_text_14": {"attribute_name": "\u30d5\u30a9\u30fc\u30de\u30c3\u30c8", "attribute_value_mlt": [{"subitem_text_value": "application/pdf"}]}, "item_creator": {"attribute_name": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Nishiwaki, Yoshihiro"}], "nameIdentifiers": [{"nameIdentifier": "22512", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Miyajima, Chiyomi"}], "nameIdentifiers": [{"nameIdentifier": "22513", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Kitaoka, Norihide"}], "nameIdentifiers": [{"nameIdentifier": "22514", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Itou, Katsunobu"}], "nameIdentifiers": [{"nameIdentifier": "22515", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Takeda, Kazuya"}], "nameIdentifiers": [{"nameIdentifier": "22516", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "\u30d5\u30a1\u30a4\u30eb\u60c5\u5831", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-02-19"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "Miyajima_2.pdf", "filesize": [{"value": "562.5 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 562500.0, "url": {"label": "Miyajima_2.pdf", "url": "https://nagoya.repo.nii.ac.jp/record/7875/files/Miyajima_2.pdf"}, "version_id": "9fd60f29-1541-4652-9490-1f9caf5745f6"}]}, "item_language": {"attribute_name": "\u8a00\u8a9e", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Generation of Pedal Operation Patterns of Individual Drivers in Car-Following for Personalized Cruise Control", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "Generation of Pedal Operation Patterns of Individual Drivers in Car-Following for Personalized Cruise Control"}]}, "item_type_id": "10", "owner": "1", "path": ["312/313/314"], "permalink_uri": "http://hdl.handle.net/2237/9597", "pubdate": {"attribute_name": "\u516c\u958b\u65e5", "attribute_value": "2008-03-18"}, "publish_date": "2008-03-18", "publish_status": "0", "recid": "7875", "relation": {}, "relation_version_is_last": true, "title": ["Generation of Pedal Operation Patterns of Individual Drivers in Car-Following for Personalized Cruise Control"], "weko_shared_id": 3}