城市韧性交通系统综述：评估方法与优化提升

To systematically review the assessment methods and optimization strategies of urban resilient transportation systems, an analytical framework centered on robustness and recoverability was constructed, and existing studies were synthesized and reviewed based on this. Regarding resilience assessment, four types of mainstream methods were systematically analyzed: graph theory and complex networks, probability statistical models, data-driven approaches, and multi-indicator assessment. Regarding resilience optimization, from single- and multi-dimensional perspectives, preventive strategies represented by network structure reinforcement and responsive strategies represented by emergency resource dispatching were investigated. By analyzing decision variables and objective functions, a theoretical mapping mechanism between assessment indicators and optimization strategies was constructed. The analysis results show that existing assessment methods are transforming from single physical topology measurement to intelligent assessment integrating spatiotemporal causal inference. Meanwhile, optimization strategies are evolving from static equilibrium of local road networks to dynamic games of cross-system coupling. The study clarifies the synergistic mechanism between assessment and optimization, and the identification of robustness boundaries and vulnerable nodes directly defines the solution space constraints for preventive optimization. In addition, the recoverability curve and performance loss quantification provide standardized benchmarks for constructing the objective functions of responsive optimization. Future research needs to focus on the deep integrated design of assessment and optimization, establishing closed-loop decision-making models capable of dynamic feedback and self-adjustment. Simultaneously, the integration of physical models and artificial intelligence methods should be strengthened to develop predictive assessment and proactive optimization technologies for complex scenarios, thus providing key theoretical and technical support for constructing intelligent and highly resilient urban transportation systems.