基于AGNES聚类算法的城市交通运行状态分析研究

为提高道路运行效率、缓解城市交通拥堵，以宿州市城区为研究对象开展了交通运行状态的分析研究。通过GPS系统获得浮动车数据，运用数理统计方法对数据进行修复和预处理；选用路段行程速度和交通流量作为评价参数，构建了路段行程速度计算模型。利用AGNES聚类算法对道路流量和平均车速进行聚类分析，以此对道路交通状态进行等级划分并确定不同等级的区间值。结果表明：宿州市主干路严重拥堵临界值为20 km/h，低于标准值（21 km/h）；同时次干路的中度和重度拥堵阈值也明显低于规范值，原因可能是车道较窄、机非混行。该研究可以为利用交通数据评估城市交通状况提供新方法，可以提高交通管理者对道路结构的认识，对城市道路的规划和设计有一定的参考价值。

Research on the Analysis of Urban Traffic Operation State Based on Agnes Clustering Algorithm

In order to improve the efficiency of road operation and alleviate urban traffic congestion, the urban area of Suzhou city is taken as the research object to carry out the analysis and research of traffic operation state. The data of floating cars are obtained by GPS system, and the data are repaired and preprocessed by using mathematical statistics method. The travel speed and traffic flow are selected as evaluation parameters to construct the calculation model of road travel speed. Agnes clustering algorithm is used to cluster the road flow and average speed, so as to classify the road traffic status and determine the interval value of different grades. The results show that the critical value of serious congestion on main roads in Suzhou is 20km / h, which is lower than the standard value (21km / h); meanwhile, the threshold of moderate and severe congestion of secondary trunk roads is significantly lower than the standard value, which may be due to narrow lanes and mixed traffic of motor vehicles and non motorized vehicles. This study can provide a new method for evaluating urban traffic conditions by using traffic data, improve the understanding of road structure for traffic managers, and have certain reference value for urban road planning anddesign.