Predictive Lane Detection by Interaction with Digital Road Map

• Item type: Journal(1)
• 公開日: 2012-01-15
• タイトル: Predictive Lane Detection by Interaction with Digital Road Map
• タイトル / 言語: en
• タイトル: Predictive Lane Detection by Interaction with Digital Road Map
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 特集：新たな展開を迎えるITS、モバイル通信とユビキタスコンピューティング
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Graduate School of Science and Technology, Kumamoto University
• 著者所属: Graduate School of Science and Technology, Kumamoto University
• 著者所属: LASMEA Laboratory, Blaise Pascal University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Technology, Kumamoto University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Technology, Kumamoto University
• 著者所属(英): en
• 著者所属(英): LASMEA Laboratory, Blaise Pascal University
• 著者名: Chenhao, Wang; Zhencheng, Hu; Roland, Chapuis
• 著者名(英): Chenhao, Wang; Zhencheng, Hu; Roland, Chapuis
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This paper presents a robust hybrid approach to Predictive Lane Detection - PLD, which utilizes information from digital map to improve efficiency and accuracy to vision-based lane detector. Traditional approaches are mostly designed for well maintained and simple road conditions like motorway or interstate road with clear lane markers, to solve out the estimation problems of coming road shape as well as vehicle's position and ego-state, which however becomes ambiguous or unavailable in the complicated road environment and under difficult weather or illumination conditions. In this paper, the proposed approach refers to vehicle localization on digital map for road geometry estimation, which gives strong cues for vision-based detector to limit the search region of road candidates and suppress noise. In addition, other information from digital map like lane marker painting color and categories is utilized in the high level of data fusion on road geometry estimation. Real and synthesized road experiment results verified the effectiveness and efficiency of our approach.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.20(2012) No.1 (online); DOI http://dx.doi.org/10.2197/ipsjjip.20.287; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This paper presents a robust hybrid approach to Predictive Lane Detection - PLD, which utilizes information from digital map to improve efficiency and accuracy to vision-based lane detector. Traditional approaches are mostly designed for well maintained and simple road conditions like motorway or interstate road with clear lane markers, to solve out the estimation problems of coming road shape as well as vehicle's position and ego-state, which however becomes ambiguous or unavailable in the complicated road environment and under difficult weather or illumination conditions. In this paper, the proposed approach refers to vehicle localization on digital map for road geometry estimation, which gives strong cues for vision-based detector to limit the search region of road candidates and suppress noise. In addition, other information from digital map like lane marker painting color and categories is utilized in the high level of data fusion on road geometry estimation. Real and synthesized road experiment results verified the effectiveness and efficiency of our approach.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.20(2012) No.1 (online); DOI http://dx.doi.org/10.2197/ipsjjip.20.287; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 53, 号 1, 発行日 2012-01-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764