基于线圈大数据的道路交通运行分析与挖掘

Road Traffic Operation Analysis and Data Mining Based on Loop Detector Big Data

摘要: 以检测线圈大数据为研究对象，对其数据特征进行了分析，归纳了检测线圈大数据丢失和异常的原因，提出了数据修复的处理方法。以天津市围堤道检测线圈大数据为例，分析了交通量、交通时空分布和交通拥堵特征。以检测线圈的流量数据为基础，提出了基于交通仿真的车速挖掘方法，并进行了案例分析，案例结果表明该方法可获取交通拥堵时段和拥堵范围等信息。

Abstract: Loop detector big data was focused and its characteristics were analyzed. Then, the reasons of big data lost and abnormality were illustrated, and the data repairment method was given. Next, taking loop detector big data of Weidi Road in Tianjin City as an example, the traffic volume situation, the traffic spatial-temporal distribution and traffic congestion were analyzed. Finally, based on traffic volume data, a data mining method using traffic simulation was proposed to obtain traffic speed, and the case result showed that both the traffic congestion period and region can be acquired.