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
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.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
