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摘要: 基于ECDIS、AIS以及支持向量机, 引入交通冲突研究方法, 提出船舶定线制警戒区水上交通冲突数据自动采集解决方案。方案利用支持向量机学习训练冲突样本数据, 得到判别冲突严重程度SVM分类模型, 并将SVM软件包和SVM分类模型嵌入到ECDIS, 结合实时AIS数据建立水上交通冲突数据自动采集系统, 应用该系统对长江口船舶定线制A警戒区进行72 h水上交通冲突数据采集。实例结果表明: 警戒区72 h船舶流量为681艘次, 水上交通冲突为327个; 严重、中等和一般冲突数量分别占总数的10.7%、21.4%和67.9%。系统运行稳定, 可实现水上交通冲突数据自动采集与处理。Abstract: Traffic conflict research method was introduced, and a solving scheme of automatic acquisition for vessel traffic conflict data in ships' routing precautionary areas was proposed based on ECDIS, AIS and support vector machine (SVM). In the solving scheme, SVM classification model was acquired through training study of sample data, and the conflict degree was identified by using the model. SVM software package and SVM classification model were embedded in ECDIS, and the automatic acquisition system of vessel traffic conflict data was achieved combined with the real-time data of AIS. The vessel traffic conflict data of precautionary area A for Yangtze estuary ships' routing in 72 h were acquired by using the system. Example result shows that the traffic flow and vessel traffic conflict data of precautionary area A in 72 h are 681 and 327 respectively. Severe, moderate and mild conflicts account for 10.7%, 21.4% and 67.9% of the total respectively. The running of the system is steady, and vessel traffic conflict data can be acquired and processed automatically.
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图 1 长江口船舶定线制A、B警戒区
Figure 1. A and B precautionary areas of Yangtze estuary ships' routing
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