Analysis of Evaluation Index System for Safety Resilience in Major Railway Projects Based on AISM

Abstract

Major railway projects are large-scale infrastructure investments facing significant safety challenges due to complex geological conditions, extreme environments, and uncertain risks. This study integrates resilience theory into railway construction safety management, shifting from traditional risk management (Safety-I) to resilience-based management (Safety-II). A resilience evaluation framework was developed using the 4Rs (robustness, redundancy, resourcefulness, rapidity) and ARRA (absorptive, resistant, restorative, adaptive) capabilities. Adversarial Interpretative Structural Modeling (AISM) and systematic clustering analysis were applied to identify key safety resilience factors and construct an evaluation index system. The findings highlight that optimized personnel allocation, adaptive machinery, standardized material use, comprehensive emergency response, and a stable construction environment are crucial for enhancing safety resilience. The proposed framework provides practical insights for improving safety strategies, minimizing risks, and ensuring sustainable railway infrastructure development.