基于ST-ACF与MALST-ACF模型的城市道路时空相关性研究

Research on Spatiotemporal Correlation of Urban Roads Based on ST-ACF and MALST-ACF Models

交通流时空特征的识别对交通拥堵的疏导决策具有重要意义。文章根据城市道路网络的交通流特性,分别从全局和局部研究城市交通拥堵在时间维度和空间维度的变化特征,引入空间延迟算子,提出了基于多元邻接关系的时空相关性度量方法。首先,文章分析了道路网络交通流的时空特性,建立了适用于城市道路网络的空间邻接矩阵;其次,基于ST-ACF函数(Spatio-temporal autocorrelation function)计算全局路段相关程度、基于改进后的MALST-ACF函数(Multivariate adjacent local spatiotemporal correlation function)计算局部路段相关程度;最后,结合唐山市24条路段的交通流量数据验证了路网间存在显著时空相关性,并且这种时空相关性具有时间动态、空间异质等特点。

The recognition of spatiotemporal characteristics of traffic flow is of great significance to the decision-making of easing traffic congestion.According to the traffic flow characteristics of the urban road network,this paper studies the change characteristics of urban traffic congestion in the time and space dimensions from the global and local perspectives,introduces the spatial delay operator,and proposes a spatial-temporal correlation measurement method based on multiple adjacencies.Firstly,the paper analyzes the space-time characteristics of the traffic flow of the road network,and establishes the spatial adjacency matrix applicable to the urban road network.Secondly,the global link correlation degree is calculated based on the ST-ACF function(spatio-temporal autocorrelation function),and the local link correlation degree is calculated based on the improved MALST-ACF function(multivariate adjacent local spatiotemporal correlation function).Finally,combined with the traffic flow data of 24 road sections in Tangshan City,it is verified that there is significant spatiotemporal correlation between the road networks,and this spatiotemporal correlation has the characteristics of temporal dynamics and spatial heterogeneity.