Resilience-oriented network reconfiguration strategies for community emergency medical services. (March 2023) - Zhao, Taiyi; Tang, Yuchun; Li, Qiming; Wang, Jingquan
Highlights: Develop humancentric bilevel optimization model considering mixed traffic environment. Establish a decision framework to guarantee post-disaster emergency medical services. Validate resilience-based network reconfiguration strategies with a real-world case. Abstract: Emergency medical services (EMSs) play a critical role in community disaster resilience by providing timely and effective medical treatment for the injured. During the post-disaster emergency medical transfer (EMT) phase, the insufficient functionality of a damaged transportation system poses significant challenges to the operational efficiency of EMT. In this study, two network reconfiguration (NR) strategies are integrated to maximize community disaster resilience: the contraflow strategy and the road intersection signal elimination strategy. A bilevel resilience-based optimization model is developed. The upper level of the model adaptively selects the implementation locations of NR strategies, and the lower level quantifies the availability of EMSs through a mixed stochastic user equilibrium traffic assignment model to provide feedback on the effectiveness of the NR strategies. To verify the effectiveness of the proposed optimization model, the configuration of the EMT network is optimized for the case of a destructive earthquake in Tangshan city, China. The numerical results show that the maximum normalized value of the community disaster resilience index can reach 0.76 based on the optimal plan. Moreover, the parameter sensitivity analysis results show that NR strategies are most effective when the penetration of an advanced traveler information system is greater than or equal to 50%.