How Does Travel Demand Follow the Change in Infrastructure? Multiple-Year Eigenvector Centrality Analysis

Fumitaka Kurauchi,Hiroe Ando

doi:10.3390/su132313366

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.

Highlights

The impact of natural disasters has increased owing to climate and social changes
Based on the idea of coping with disasters and other unpredictable events that should be added to planning and design for sustainability, the effects of actual bridge collapse accidents were evaluated for urban street topology using space syntax theory [2]
The history of actual road values were used to evaluate the impact of road network improvements

Summary

Introduction

The impact of natural disasters has increased owing to climate and social changes. We would like to examine how many lags there are from the supply and demand side for actual road improvement cases based on a simple topological approach of road networks. This study evaluates the road networks based on a topological approach to understand the impact of long-term road improvements. This study verifies the impact of road network improvement by using eigenvector centrality analysis, which is one of the topological-based approaches. This measure identifies sets of nodes in a directed network that are strongly connected to each other and, sets of nodes that are weakly connected to each other. We analysed long-term changes in eigenvector centrality values to understand the impact of road network improvements.

Land Use and Transportation Interaction Model

Network Analysis by Topological Approach

Eigenvector Centrality

Weight Setting

Road Improvement History in Gifu Prefecture

Survey Data of Roads

Impacts of Road Network Improvements

Relationship between Supply and Demand

Conclusions