基于固定检测器的区域交通状态判别方法

Method for traffic state identification based on fixed detector

以固定检测器获得的交通数据为基础,分别建立路段和交叉口交通状态判别模型;考虑不同路段和交叉口对区域路网整体交通状态影响程度的差异性,建立路段和交叉口交通状态的权重计算模型;在此基础上建立区域交通状态的综合判别模型;并分析状态指标P与路网中车辆平均行程速度的相互关系,确定路网P所表示的交通状态级别;最后利用Vissim软件设计包含9个交叉口的典型路网,根据采集的数据对模型进行验证。仿真结果表明:所建立的方法可以有效地对区域交通状态进行判别。

Models of state identification for road sections and intersections were established based on the basic traffic parameters which were captured by the fixed detector. Considering the different influences of road sections and intersections on the overall traffic status of the regional road network, models of weight calculation for road sections and intersections were established. On this basis, integrated models of traffic state identification for regional area were established. In order to classify the traffic states by the value of P, the relation between P and v was determined, and the traffic state was classified by P. A typical road network environment with nine intersections was designed in Vissim software, and the models were verified by the collected data. The results show that the methods constructed can effectively identify the traffic state of the urban area.