ABSTRACT
To effectively evaluate the performance level changes of congested road sections under the surge of peak traffic, this paper uses taxi GPS trajectory data and combines the resilience triangle theory to construct three indicators: resilience index, resistance index, and recovery index to build a road section resilience evaluation model; the Ward hierarchical clustering method is used to explore the heterogeneity of resilience of different road sections. A case study based on the “six horizontal and four vertical” road network in Xiangyang city shows that the resilience evaluation model can accurately evaluate the redundancy, resistance, and recovery of road sections when high traffic volumes impact them. The road network in Xiangyang City can be classified into “Relatively Low-Relatively High-Relatively High” (Class I), “Relatively High-Relatively Low-Relatively Low” (Class II), and “high-low-high” (Class III) based on the “resilience value-resistance index-resilience index.” “high-low-high” (Class III) and “high-high-low” (Class IV). Class I is the most concentrated, indicating that the resilience redundancy of the road network in Xiangyang is low when dealing with high traffic impacts. This study can play a positive role in the targeted improvement of the city's operational efficiency of congested road sections.
