基于数据挖掘的路网交通拥堵特征分析

交通拥堵的发生通常导致道路通行能力的下降和交通瓶颈的形成，对城市的经济和环境造成影响。对此利用大数据技术挖掘交通数据，通过聚类分析方法，构建交通指数数据集，进而对城市路网交通拥堵进行定量分析。研究表明，路网拥堵在工作日和周末存在差异，周数据具有周期性，在空间上总体呈现由点向线再到面的拥堵扩散过程。依据拥堵的时空特征，分析了路网的拓扑结构和流量的复杂性，为城市的可持续发展和交通优化提供一定的支持。

Analysis of traffic congestion characteristics of road networks based on data mining

The occurrence of traffic congestion usually leads to the reduction of road capacity and the formation of traffic bottlenecks, which affects the economy and environment of cities. In this regard, big data technology is used to mine traffic data and construct a traffic index dataset through cluster analysis method, and then quantitatively analyze the traffic congestion of urban road networks. The study shows that the road network congestion differs between weekdays and weekends, and the weekly data is cyclical, and the overall congestion diffusion process from points to lines to surfaces in space. Based on the spatial and temporal characteristics of congestion, the topology and traffic complexity of the road network are analyzed to provide some support for sustainable development and traffic optimization of the city.