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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.accessioned2018-08-21T05:56:57Z-
dc.date.available2018-08-21T05:56:57Z-
dc.date.issued2017-01-01en_US
dc.identifier.urihttp://hdl.handle.net/11536/146859-
dc.description.abstractThanks for the common use of Automatic Identification System (AIS) network has made a large number of the maritime traffic data to be available. Ships equipped with AIS automatically exchange navigational information with nearby ships and terrestrial AIS receivers to facilitate the tracking and monitoring of ships' location and movement for collision avoidance and control. Obviously, with increasing amount of maritime shipping traffic, the navigational collisions are one of the growing safety concerns in maritime traffic situation awareness. To understand the collision situations can help the maritime traffic managers to improve the safety control of maritime traffic. However, it is difficult to statistically analyze such collision due to the number of collected real cases of collisions are relatively low within a short period of time. To overcome the problem of low sample size, we discover traffic conflict from data collected by AIS network to substitute the real collision. Given a set of maritime traffic data collected from AIS network, we try to discover ships' movements that have conflict behaviors and these behaviors may bring a possible collision if they do not take any evasive action. We propose a framework of Clustering-and-Detection to automatically discover the clusters of conflict trajectory from AIS trajectory data in an unsupervised way. Based on real AIS data, the experimental results show that the proposed framework is able to effectively discover sets of trajectory with conflict situation from maritime AIS traffic data. The statistical analysis on the discovered sets of conflict trajectory is able to provide useful knowledge for maritime traffic monitoring.en_US
dc.language.isoen_USen_US
dc.subjectMaritime traffic dataen_US
dc.subjectAIS dataen_US
dc.subjectTrajectory data miningen_US
dc.subjectNavigation collisionen_US
dc.subjectConflict detectionen_US
dc.titleA Framework for Discovering Maritime Traffic Conflict from AIS Networken_US
dc.typeProceedings Paperen_US
dc.identifier.journal2017 19TH ASIA-PACIFIC NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM (APNOMS 2017): MANAGING A WORLD OF THINGSen_US
dc.citation.spage1en_US
dc.citation.epage6en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.identifier.wosnumberWOS:000417431200001en_US
Appears in Collections:Conferences Paper