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提出“路口群落”的概念来分析城市交通网络中拥挤区域的交通信号控制方式,应用二型模糊逻辑对区域交通流量进行预测,得到以防止路口群落堵塞为前提的车辆平均延误最小的多级模糊控制算法(T2F-MACFC).在二型模糊规则提取时,应用了一种改进的c均值模糊聚类算法,该算法可以针对区间型数据进行模糊聚类.计算机仿真表明,T2F-MACFC算法相对于目前实际应用的“绿波”(Green Wave)自适应控制方法,可以减少交通拥挤地区50%的堵塞情况发生,而二型模糊预测方法的引入使得车辆平均速度提高大约15%.
The concept of “intersection community” is proposed to analyze the traffic signal control mode in the crowded area of urban traffic network. The second-type fuzzy logic is used to predict the regional traffic flow, and the average vehicle delay is the minimum Level fuzzy control algorithm (T2F-MACFC) .In the second type of fuzzy rule extraction, an improved c-means fuzzy clustering algorithm is applied, which can carry out fuzzy clustering for interval type data.Computer simulation shows that T2F-MACFC Compared with the current “Green Wave” adaptive control method, the algorithm can reduce 50% congestion in the traffic congestion area. The introduction of the second-type fuzzy prediction method makes the average speed of the vehicle about 15% .