Citation

Gao W, Hu X, Wang N. Transp. Res. D Trans. Environ. 2024; 126: e104000.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.trd.2023.104000

PMID

unavailable

Abstract

The road traffic system is frequently disrupted by rainfall events, significantly impacting road system efficiency. It is challenging to capture the resilience of road traffic systems due to variations in road environments. We develop a method for measuring road segment and traffic system resilience using probabilistic modeling techniques. Hierarchical clustering is used to analyze the heterogeneity of resilience patterns from road environment perspectives. A decision support tool is developed to visualize resilience propagation among road segments and communities. Based on a case study in Harbin, China, we identify four typical traffic system resilience patterns considering the influence of land use.

RESULTS reveal that system resilience decreases by 6.7% for every 10mm increase in rainfall intensity when the rainfall intensity is below 50mm. Road segments over 1000 m exhibit an average resilience increase of 13.3% compared to those shorter than 1000 m. Additionally, 66% of low-resilience road segments are concentrated near commercial areas.

Language: en

Keywords

Clustering; Link reliability; Probabilistic model; Rainfall events; Road environment; System resilience