关键词: 城市交通, 交通状态划分, 参数权重, 模糊C均值聚类

Abstract:

Considering the different effect of each traffic parameter (traffic flow, speed, occupancy or density) on traffic state classification，the method is proposed to classify traffic state of urban traffic based on the parameter weighting. According to the similarity measurement method, a parameter evaluation function is put forward to give each parameter a parameter weighting based on weighted Euclidean distance, and minimize the function using the gradient method. After obtaining parameter weighting values, this paper uses the weighted Euclidean distance to replace the common Euclidean distance in Fuzzy C- means Clustering (FCM). Finally, we classify the traffic state using the proposed methodology, the traffic parameter data come from the road network, and comparing to the method of FCM. The results show that the proposed methodology which classifies the traffic state classification is more consistent with actual conditions.

Key words: urban traffic, traffic state classification, parameter weighting, fuzzy c-means clustering