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基于模糊C均值聚类的城市道路交通状态判别

DOI: 10.3969/j.issn.1674-0696.2015.02.22, PP. 102-107

Keywords: 交通工程,城市道路,交通流,交通拥挤,交通状态判别,模糊C均值聚类,trafficengineering,urbanroad,trafficflow,trafficcongestion,trafficstateidentification,fuzzyC-meansclustering

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Abstract:

:?根据城市道路交通流特性,针对同一交通状态下交通流参数分散在一个二维区域的现象,将交通流划分为4个状态,讨论了不同状态之间的转变情况;针对城市道路交通状态存在模糊性的特点,以流量、速度、占有率作为样本数据的特征属性,提出了基于模糊C均值聚类(FCM)的交通状态实时判别方法,该方法首先采用模糊聚类技术对历史数据进行分类,得到不同交通状态的聚类中心,然后对新观测到的交通数据所属类别进行实时判别以确定交通状态。以赣州市文明大道为实例进行分析,其结果与实测交通运行状况结果一致,验证了方法的有效性。

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