Intersection importance assessment for an operationally resilient urban traffic network: A multi-criteria decision-making-based framework

Assessing the importance of intersections and identifying critical ones whose failure significantly impairs the operational efficiency of the urban traffic network is essential for effective transportation planning. Prior studies often rely on simplified network representations, single-method evaluations, or approaches limited by data availability. To overcome these shortcomings, there is a need for advanced network modeling and holistic evaluation of intersection importance, utilizing adaptable methods capable of functioning in the absence of complex data or expert-dependent input. This study proposes a practical and comprehensive framework to assess intersection importance, primarily leveraging objective Multi-Criteria Decision-Making (MCDM) methods. Particularly, the introduced approach models urban road networks as directed and weighted graphs using accessible foundational traffic characteristics data and their integrations derived through MCDM weighting methods. Intersection importance is then evaluated employing centrality measures and two-stage hybrid methods that combine these measures using MCDM weighting and ranking techniques. The weighting methods utilized include equal, entropy, CRITIC, CILOS, IDOCRIW, angular, Gini coefficient, and variance; the ranking methods applied include TOPSIS, VIKOR, SPOTIS, ARAS, COCOSO, CODAS, EDAS, MABAC, MAIRCA, MARCOS, and ELECTRE III. The performance of constructed objective methods is further compared with that of subjective approaches based on AHP and BWM. A case study of the urban road network of Philadelphia, United States, demonstrates the framework’s effectiveness. Results indicate that intersections with the highest strength and PageRank centrality scores in the constant-weight graph are identified as critical under mild and severe disruptions, respectively. Notably, MCDM-based hybrid methods outperform most centrality measures in assessing intersection importance, with objective hybrid methods performing comparably to subjective ones. Furthermore, spatial analysis reveals that first-tier critical intersections are located around the downtown periphery, highlighting it as a priority area for resilience-focused interventions.