基于模糊C均值聚类的交通状态判别研究

Study on identification of traffic state based on fuzzy C-means clustering

本文根据实测京津塘高速公路感应线圈数据,利用模糊聚类的方法对交通流状况的分类进行了研究,将交通状态分为畅通、拥挤、堵塞3类。同时对比了车速、车流量和占有率3种参数对交通状态判别的影响。分析结果表明:用模糊聚类进行交通流状况分类是一种可行的方法;车速对交通流分类的影响最大,其次是占有率和流量。

The fuzzy clustering method was used to classify the traffic flow data of Jing-Jin-Tang Highway in this paper. The traffic state was classified into 3 categories as free flow, crowded flow and clogged flow. Meanwhile the significance of three parameters to judge on the situation of traffic flow was analyzed. The analysis results showed that using fuzzy clustering to classify the traffic flow was feasible. The speed influenced on the traffic flow classification greatly, occupancy the second, flow the last.