A transportation system's resilience refers to its ability to recover and provide timely transportation services in emergency situations, which is extremely important for highly urbanized societies. However, the previous literature has not considered measuring resilience under different emergency levels or maximizing resilience by managing potential traffic demand. This article proposes a novel framework for resilience analysis that is composed of measurement and improvement. An approach based on emergency levels, quantified as the number of damaged lanes, is designed to evaluate the resilience of transportation systems. A genetic algorithm is used to identify the worst combination of damaged lanes under each emergency level. In maximizing the resilience, we use the integrated reconfiguration of both traffic supply and demand as the optimal recovery solution, which reduces traffic demand through a combination of different traffic modes and increases traffic capacity through a contraflow technique. The numerical results show that the proposed model can identify the maximum damage a system can resist and can determine the optimal recovery solution. Finally, some managerial insights on transportation system evaluation and emergency planning are obtained.

中文翻译：

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测量和最大化紧急疏散运输系统的弹性

交通系统的弹性是指其在紧急情况下恢复和提供及时交通服务的能力，这对于高度城市化的社会极为重要。然而，之前的文献并未考虑在不同紧急情况下衡量弹性或通过管理潜在的交通需求来最大化弹性。本文提出了一种由测量和改进组成的弹性分析新框架。一种基于紧急程度的方法，量化为受损车道的数量，旨在评估交通系统的弹性。遗传算法用于识别每个紧急级别下损坏车道的最坏组合。在最大限度地提高弹性的同时，我们采用交通供需一体化重构作为最优恢复方案，通过不同交通方式的组合减少交通需求，通过逆流技术增加交通容量。数值结果表明，所提出的模型可以识别系统可以抵抗的最大损坏，并可以确定最佳恢复解决方案。最后，获得了有关交通系统评估和应急计划的一些管理见解。