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为及时判别山地城市快速路交通状态,便于智能化管理,针对山地城市与平原城市快速路交通特征的差异性以及交通流的变化特性,将交通状态划分为4类,提出了一种基于模糊C均值聚类(FCM)判别山地城市快速路交通状态的算法。该算法基于速度、流量、时间占有率不同组合作为判别参数分4种情形进行聚类分析,并以重庆市为例,利用MATLAB模糊逻辑工具箱分析出采集数据的聚类中心,对不同参数组合下的各样本交通状态进行判断,并且结合视频录像验证各参数组合情形判别各状态的准确度,验证了算法判别的可行性。结果分析表明,速度对山地城市快速路状态判断影响最大,其次是流量,以速度、流量为参数的FCM算法能较好地判别山地城市快速路交通状态,精度达到85%以上。
In order to distinguish the expressway traffic status of mountainous cities in time and facilitate intelligent management, aiming at the difference of traffic characteristics between mountainous cities and plain urban expressways and the characteristics of traffic flow, the traffic status is divided into four categories, and a fuzzy C An Algorithm for Determining Traffic State of Expressway in Mountainous Cities Based on Mean Value Clustering (FCM). In this paper, clustering analysis is made based on four different situations of speed, traffic and time share as discriminant parameters. Taking Chongqing as an example, the algorithm uses MATLAB fuzzy logic toolbox to analyze the clustering centers of collected data, Under the traffic conditions of each sample to judge, and combined with video recording to verify the combination of various parameters to determine the accuracy of each state, verify the feasibility of discriminant algorithm. The result shows that speed has the most influence on the state judgment of expressway in mountain city, followed by traffic. The FCM algorithm based on velocity and flow can better distinguish the traffic state of expressway in mountainous city, and the accuracy is over 85%.