基于关联路径的城市路网交通模式分析与状态划分

Traffic patterns analysis and traffic states division of urban traffic network based on correlated routes

在城市路网当中,对区域内所有交叉口进行统一控制的方法难以有效利用道路资源,缓解交通拥堵问题。将对整个交叉口的协调控制拆分为对关键路线的控制,可提高协调控制的效率。因此找出交叉口群范围内的关键路线,同时对这些关键路线的交通状态进行划分具有重要的意义。提出了一种针对路网关联路径的交通模式分析与状态划分的方法。引入关联路径、关联路径链、关联路径集的概念,并提出一种考虑路径流量不均匀性的路径关联度计算模型及其判定条件,确定出区域中的关联路径集。然后提出一种结合自组织映射(SOM)算法与Dunn指数(DI)的SOM_DI算法,确定出关联路径链的最佳交通状态划分数目,并分析关联路径链上的交通模式,得到时间状态链和空间状态链。仿真结果表明:所提出的方法可以对区域路网交通的关联路径及其最佳交通状态进行准确的划分。

In the urban road network,the method of unified control of all intersections in the region is difficult to make effective use of road resources and alleviate traffic congestion.The efficiency of coordinated control can be improved by splitting the coordinated control of the whole intersection into the control of key routes.Therefore,it is important to find out the key routes within the intersection group and divide the traffic state of these key routes.In this paper,a method for traffic pattern analysis and state division for correlated routes in the road network is proposed.The concepts of correlated route,correlated route chains,and correlated route sets are defined,and a route correlation degree calculation model that considers route traffic heterogeneity and its judgment criteria are proposed to determine the correlated route sets in the region.We incorporate the self-organizing mapping(SOM)algorithm with Dunn Index(DI),named as SOM_DI,to determine the optimal number of traffic state on the correlated path chain.The traffic pattern on the correlated path chain is analyzed to obtain the temporal state chains and the spatial state chains.Simulation results show that the proposed method can accurately divide the associated path and the best traffic state of regional road network traffic.