Identifying Critical Links in Degradable Road Networks Using a Traffic Demand-Based Indicator

The primary traffic-based indicators for identifying critical links account for travel time, transportation efficiency, and traffic demand. These indicators are seldom applied to scenarios in which link capacity degradation occurs across the entire network. In addition, the commonly used traffic demand-based indicator, known as unsatisfied demand, can only work when there are disconnected origin–destination (OD) pairs in the network. In this context, this study incorporates the concept of a degradable road network to represent such scenarios and introduces a new network-wide traffic demand-based indicator, defined as late arrival demand (LAD), to identify critical links. Specifically, we built a late arrival rate (LAR)-based user equilibrium (UE) model to capture travel behavior and estimate the LAD in degradable road networks. Then, LAD and four other indicators were introduced to identify critical links in the framework of the LAR-based UE model. Finally, the Nguyen–Dupuis and Sioux Falls networks were employed for numerical experiments. The results, under various levels of traffic demand and degradation, demonstrate that LAD is a flexible and effective network-wide traffic demand-based indicator. This new approach provides insights that can help managers assess link criticality in degradable road networks from the perspective of traffic demand.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2024-09-13
DOI
https://doi.org/10.3390/su16188020
Citations
3
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
2.05

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identifying Critical Links in Degradable Road Networks Using a Traffic Demand-Based Indicator

Chuan Jiang, Zhanji Zheng, Qiang Tu, He Han et al.
3 citations
Sustainability
Transportation Planning and Optimization
2.05
article

Identifying Critical Links in Degradable Road Networks Using a Traffic Demand-Based Indicator

Chuan Jiang, Zhanji Zheng, Qiang Tu, He Han, Xiaomin Lai
article en
3 citations

Abstract

The primary traffic-based indicators for identifying critical links account for travel time, transportation efficiency, and traffic demand. These indicators are seldom applied to scenarios in which link capacity degradation occurs across the entire network. In addition, the commonly used traffic demand-based indicator, known as unsatisfied demand, can only work when there are disconnected origin–destination (OD) pairs in the network. In this context, this study incorporates the concept of a degradable road network to represent such scenarios and introduces a new network-wide traffic demand-based indicator, defined as late arrival demand (LAD), to identify critical links. Specifically, we built a late arrival rate (LAR)-based user equilibrium (UE) model to capture travel behavior and estimate the LAD in degradable road networks. Then, LAD and four other indicators were introduced to identify critical links in the framework of the LAR-based UE model. Finally, the Nguyen–Dupuis and Sioux Falls networks were employed for numerical experiments. The results, under various levels of traffic demand and degradation, demonstrate that LAD is a flexible and effective network-wide traffic demand-based indicator. This new approach provides insights that can help managers assess link criticality in degradable road networks from the perspective of traffic demand.

SustainabilityVol. 16(18)
Chongqing Construction Engineering Investment Holding (China) (CN), Chongqing Jiaotong University (CN)
Chongqing Municipal Education Commission
Sustainable cities and communities
Openalex Percentile: Top 13%
Transportation Planning and Optimization
2.05
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.