How does travel demand follow the change in infrastructure? Multiple-year eigenvector centrality analysis

Abstract

The road network is one of the most permanent elements of the physical structure of cities, and the long-term impacts should be considered for effective and efficient road network improvement. It is therefore important to catch up on how the road will be used after construction. However, we do not have much knowledge on the pattern and time lag in the change process of travel demand and supply in the real situation. To explore such changes, this study proposes to evaluate a network with eigenvector centrality (EC) measures that can evaluate the importance of nodes in a network. We believe the analysis based on topological properties by the graph theory is suitable to verify the evolution of road networks. This study analysed long-term changes over 20 years in an actual city to understand the impact of road network improvements. The EC analysis with the weights of traffic indices obtained from survey data evaluates the connectivity of road services on the supply side, and traffic concentration on the demand side.