基于大数据分析的交叉口时空协同优化方法

Space-time coordination optimization method for intersection based on big data analysis

针对城市交叉口交通拥堵频发的状况,以电子警察卡口、线圈检测器、视频监控采集的路网交通信息数据为基础,基于交通大数据分析,对交叉口的交通运行进行时空协同优化。协同优化时,首先对采集的交叉口交通大数据进行分析挖掘,精准剖析现有交叉口存在的问题,找出交叉口交通流的运行特征,再从时间、空间两个维度根据实际交通状况进行渠化方案设计和与之协同的定周期多时段精细化信号控制方案设计,并进行仿真试验验证。验证结果表明:优化后的方案能够改善交通现状,提高通行效率。

In view of frequent traffic congestions at urban intersections,based on the road network traffic information data collected by electronic police bayonet,coil detector and video surveillance as the foundation,and in use of the traffic big data analysis,this study optimized the traffic operation of the intersection in space-time.In collaborative optimization,the big traffic data collected at the intersection is firstly analyzed and mined to accurately analyze the problems at intersections and find out the operation characteristics of the traffic flow at intersections.From the two dimensions of time and space,the channelization scheme is designed according to the actual traffic conditions,and the refined signal control scheme with fixed time cycle and multi-period is designed in coordination with it,and the simulation test is carried out.The results show that the optimized scheme can improve the traffic status and traffic efficiency.