Statistical Modeling of Traffic Flow in Commercial Clusters Based on a Street Network

Traffic flow characterizes vitality in commercial clusters, and the accurate prediction of traffic based on street network has significant implications for planning regulation clusters. However, existing studies are limited by certain problems, such as difficulty obtaining data carrying out technical methods. The purpose this study is to use urban physical so quickly effectively estimate This takes networks 100 clusters China research objects classifies them into three forms according theory “A city not a tree”. Taking typical these unit, space syntax was used five metrics connectivity, integration (Dn) selected proxy variable connectivity. results show that can be predicted using multiple regression models established integration, level, operation cycle. establishes connection between form flow, which enables possibility effectively. For areas with poorly structured data, help administrators predict potential economic attributes easily accessible