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dc.contributor.authorLei, Po-Rueyen_US
dc.contributor.authorTsai, Tzu-Haoen_US
dc.contributor.authorWen, Yu-Tingen_US
dc.contributor.authorPeng, Wen-Chihen_US
dc.date.accessioned2018-08-21T05:57:03Z-
dc.date.available2018-08-21T05:57:03Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn1551-6245en_US
dc.identifier.urihttp://dx.doi.org/10.1109/MDM.2017.60en_US
dc.identifier.urihttp://hdl.handle.net/11536/146978-
dc.description.abstractCollision-free is one of the major safety concerns for maritime traffic management. To analyze the collision data and understand the cause of the collision can contribute the improvement of the maritime traffic safety and management. However, the real collisions is not always available to analyze. Based on a massive AIS trajectory data collected, we focus on mining the ships' movement behaviors those may bring a possible collision if they do not take any avoidance, called Maritime Traffic Conflict. Even though the maritime traffic conflict is a non-accident incident, the movement behaviors of maritime traffic conflict may have the similar behaviors of navigational collision for analysis. Thus, we propose ConflictFinder to provide a framework for maritime traffic conflict mining. Different from existing methods those focus on detecting the conflicts between two ships in a restricted water way, we discover the conflicts occurred by multi-ships in open sea. For analysis of maritime traffic conflicts, a prototype of ConflictFinder is implemented which helps with gaining a better understanding of traffic conflicts discovered and can be applied to the improvement of maritime traffic safety evaluation and management.en_US
dc.language.isoen_USen_US
dc.subjectMaritime Trafficen_US
dc.subjectAIS Dataen_US
dc.subjectTrajectory Data Miningen_US
dc.subjectConflict Detectionen_US
dc.titleConflictFinder: Mining Maritime Traffic Conflict from Massive Ship Trajectoriesen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/MDM.2017.60en_US
dc.identifier.journal2017 18TH IEEE INTERNATIONAL CONFERENCE ON MOBILE DATA MANAGEMENT (IEEE MDM 2017)en_US
dc.citation.spage356en_US
dc.citation.epage357en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.identifier.wosnumberWOS:000425916300049en_US
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