Spatial and temporal model for urban regional traffic state analysis based on fuzzy C-means clustering
基于FCM城市区域道路交通状态时空分层判别方法*

This paper developed a spatial and temporal hierarchical model based on fuzzy C-means clustering for area traffic state analysis to predict area traffic states.Firstly,it quantitatively analyzed the traffic state of the unit of the road network.Then gained the cluster centers of each traffic state for the unit of the road network based on the method of fuzzy C-means clustering.After this,it recognized and classified the real-time traffic state combining its real-time traffic data.According the units’ space distribution in the network,the model presented the different kinds of spatial distribution under different traffic states.The result of example proves that this analytical method obtain the spatial and temporal traffic state accurately.It also supplies the assistant decision-making information for transportation system managers.