Centrality Characteristics of Road Network Patterns of Traffic Analysis Zones

Abstract

Road network patterns can affect traffic performance, travel behavior, and traffic safety. Thus, a deep understanding of the properties of different network patterns can provide useful guidance for design and improvement of road systems. The aim of this study is to build a relationship between graphical and topological features of road network patterns of traffic analysis zones (TAZ) and, on the basis of this relationship, to offer a measure that can quantitatively distinguish different graphical pattern types. Toward this goal, a topological analysis measure, centrality, is applied to investigate road network patterns metrically at the TAZ level. First, 662 TAZ road networks are classified according to the graphical features of the networks; then different graphical features are calculated for centrality indices including network degree centrality, network betweenness centrality, and network closeness centrality. It is concluded that the network betweenness centrality is the best measure to distinguish and describe various TAZ road network patterns. Finally, the problem of how to assign a road that happens to be on the border of two adjacent TAZs is studied. A measure that can quantitatively describe and represent different road network patterns is offered. This measure could be useful for further evaluation of the possible effects of TAZ road network patterns on transportation.