高速公路路网运行指数评估模型应用研究

由于高速公路路网交通流量分布不均衡,往往会造成部分节点或区域拥堵,而量化评估路网运行状态能快速确定交通拥堵位置。提出了一种基于波动率和机器学习的路网运行指数评估模型:首先选取合适的机器学习算法确定路网各节点的基准值;然后运用波动率理论构建各节点的运行指数评估模型;之后利用广东省高速公路若干节点路段的真实数据对模型进行了验证,并与阈值进行对比。研究结果表明:本文提出的路网运行指数评估模型能在各类场景下及时准确地定位交通拥堵节点,为缓解交通拥堵问题提供一定的参考意义。

Research on the Application of Expressway Network Operation Index Evaluation Model

Due to the uneven distribution of traffic flow in highway network,some nodes or regions are often congested,and the quantitative evaluation of network operation can quickly determine the location of traffic congestion.In this paper,a kind of road network operation index evaluation model is proposed based on volatility and machine learning:firstly,the appropriate machine learning algorithm is selected to determine the benchmark value of each node;then the volatility theory is used to build the operation index evaluation model of each node.After that,the model is validated by the real data of several nodes of the expressways in Guangdong Province,and compared with the threshold value.The research results show that:the proposed road network operation index evaluation model can accurately determine the traffic congestion nodes in various scenarios in time,and provide some reference for easing the traffic congestion problems.