Resilience evaluation model of urban road network based on betweenness centrality

The resilience of urban road networks is a crucial manifestation of a city's ability to respond to various emergencies. Therefore, studying and evaluating the resilience of urban road networks is essential for guiding urban planning and management. In order to quantitatively assess the resilience of urban road networks, a evaluation model based on betweenness centrality was constructed. This model creates a resilience index to quantitatively evaluate the resilience intensity of urban road networks through the betweenness centrality distribution characteristics of road segments in the urban road network. To understand the resilience performance of urban road networks against different types of shocks, two interruption simulation strategies were designed: random attacks and ordered attacks, representing normalized shocks and incidental shocks, respectively. Taking Wuhan, Chongqing, and Nanjing, three typical cities in the Yangtze River Economic Belt, as examples, under normal circumstances, the resilience indices of these three cities are 53.77, 101.45, and 112.82, respectively. This indicates that the road network structure of Nanjing is relatively more reasonable, while that of Wuhan is relatively poor. In the scenario of traffic shocks, we observed that the performance of these three cities facing random attacks was superior to that of facing ordered attacks. Specifically, Nanjing performed relatively strong in response to ordered attacks, Chongqing performed notably well in response to random attacks, while Wuhan's ability to respond was relatively weak under both types of attacks. These findings provide important references for urban planning and management, helping to optimize urban road network structures and enhance the overall resilience level of cities.

Authors

Institutions

Publication Details

Published
2024-12-20
DOI
https://doi.org/10.1117/12.3054644
Citations
1
Primary Topic
Evaluation and Optimization Models
Type
article
Field-Weighted Citation Impact
0.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Resilience evaluation model of urban road network based on betweenness centrality

J. Wu, Shijun Zhu, Q. Jim Chen, Hong Wang et al.
1 citations
Evaluation and Optimization Models
0.36
article

Resilience evaluation model of urban road network based on betweenness centrality

J. Wu, Shijun Zhu, Q. Jim Chen, Hong Wang, Gang Li
article en
1 citations

Abstract

The resilience of urban road networks is a crucial manifestation of a city's ability to respond to various emergencies. Therefore, studying and evaluating the resilience of urban road networks is essential for guiding urban planning and management. In order to quantitatively assess the resilience of urban road networks, a evaluation model based on betweenness centrality was constructed. This model creates a resilience index to quantitatively evaluate the resilience intensity of urban road networks through the betweenness centrality distribution characteristics of road segments in the urban road network. To understand the resilience performance of urban road networks against different types of shocks, two interruption simulation strategies were designed: random attacks and ordered attacks, representing normalized shocks and incidental shocks, respectively. Taking Wuhan, Chongqing, and Nanjing, three typical cities in the Yangtze River Economic Belt, as examples, under normal circumstances, the resilience indices of these three cities are 53.77, 101.45, and 112.82, respectively. This indicates that the road network structure of Nanjing is relatively more reasonable, while that of Wuhan is relatively poor. In the scenario of traffic shocks, we observed that the performance of these three cities facing random attacks was superior to that of facing ordered attacks. Specifically, Nanjing performed relatively strong in response to ordered attacks, Chongqing performed notably well in response to random attacks, while Wuhan's ability to respond was relatively weak under both types of attacks. These findings provide important references for urban planning and management, helping to optimize urban road network structures and enhance the overall resilience level of cities.

Wuhan University of Technology (CN)
Climate action
Openalex Percentile: Top 36%
Evaluation and Optimization Models
0.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.