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Conference Paper: Behavior Prediction Based on Obstacle Motion Patterns in Dynamically Changing Environments

TitleBehavior Prediction Based on Obstacle Motion Patterns in Dynamically Changing Environments
Authors
Issue Date2008
PublisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4740404
Citation
IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Sydney, NSW, Australia, 9-12 December 2008. In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008, p. 132-135 How to Cite?
AbstractThis paper proposes a behavior prediction method for navigation application in dynamically changing environments, which predicts obstacle behaviors based on learned obstacle motion patterns (OMP) from observed obstacle motion trajectories. A multi-level prediction model is then proposed that predicts long-term or short-term obstacle behaviors. Simulation results show that it works well in a complex environment and the prediction is consistent with actual behaviors. © 2008 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/62021
ISBN

 

DC FieldValueLanguage
dc.contributor.authorChen, Zen_HK
dc.contributor.authorNgai, CKen_HK
dc.contributor.authorYung, NHCen_HK
dc.date.accessioned2010-07-13T03:52:16Z-
dc.date.available2010-07-13T03:52:16Z-
dc.date.issued2008en_HK
dc.identifier.citationIEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Sydney, NSW, Australia, 9-12 December 2008. In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008, p. 132-135en_HK
dc.identifier.isbn9780769534961-
dc.identifier.urihttp://hdl.handle.net/10722/62021-
dc.description.abstractThis paper proposes a behavior prediction method for navigation application in dynamically changing environments, which predicts obstacle behaviors based on learned obstacle motion patterns (OMP) from observed obstacle motion trajectories. A multi-level prediction model is then proposed that predicts long-term or short-term obstacle behaviors. Simulation results show that it works well in a complex environment and the prediction is consistent with actual behaviors. © 2008 IEEE.en_HK
dc.languageengen_HK
dc.publisherI E E E. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4740404-
dc.relation.ispartofProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technologyen_HK
dc.rightsProceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. Copyright © I E E E.-
dc.rights©2008 IEEE. 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 to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleBehavior Prediction Based on Obstacle Motion Patterns in Dynamically Changing Environmentsen_HK
dc.typeConference_Paperen_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/WIIAT.2008.214en_HK
dc.identifier.scopuseid_2-s2.0-62949181360-
dc.identifier.hkuros164709en_HK
dc.identifier.spage132en_HK
dc.identifier.epage135en_HK
dc.publisher.placeUnited States-

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