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Network Reconfiguration for Increasing Transportation System Resilience Under Extreme Events

机译：在极端事件下重新配置网络以提高运输系统的弹性

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Evacuating residents out of affected areas is an important strategy for mitigating the impact of natural disasters. However, the resulting abrupt increase in the travel demand during evacuation causes severe congestions across the transportation system, which thereby interrupts other commuters' regular activities. In this article, a bilevel mathematical optimization model is formulated to address this issue, and our research objective is to maximize the transportation system resilience and restore its performance through two network reconfiguration schemes: contraflow (also referred to as lane reversal) and crossing elimination at intersections. Mathematical models are developed to represent the two reconfiguration schemes and characterize the interactions between traffic operators and passengers. Specifically, traffic operators act as leaders to determine the optimal system reconfiguration to minimize the total travel time for all the users (both evacuees and regular commuters), while passengers act as followers by freely choosing the path with the minimum travel time, which eventually converges to a user equilibrium state. For each given network reconfiguration, the lower-level problem is formulated as a traffic assignment problem (TAP) where each user tries to minimize his/her own travel time. To tackle the lower-level optimization problem, a gradient projection method is leveraged to shift the flow from other nonshortest paths to the shortest path between each origin-destination pair, eventually converging to the user equilibrium traffic assignment. The upper-level problem is formulated as a constrained discrete optimization problem, and a probabilistic solution discovery algorithm is used to obtain the near-optimal solution. Two numerical examples are used to demonstrate the effectiveness of the proposed method in restoring the traffic system performance.
机译：将居民撤离灾区是减轻自然灾害影响的重要策略。然而，在疏散过程中旅行需求的突然增加导致整个运输系统的严重拥堵，从而打断了其他通勤者的正常活动。在本文中，我们建立了一个双层数学优化模型来解决此问题，我们的研究目标是通过两种网络重构方案来最大化运输系统的弹性并恢复其性能：逆流（也称为车道逆转）和交叉口消除交叉路口。建立了数学模型来表示这两种重新配置方案，并描述了交通运营商和乘客之间的相互作用。具体来说，交通运营商充当领导者，以确定最佳的系统重新配置，以最大程度地减少所有用户（撤离人员和常规通勤者）的总旅行时间，而乘客则通过自由选择旅行时间最短的路径充当追随者，从而最终收敛达到用户平衡状态。对于每个给定的网络重新配置，较低级的问题被表述为流量分配问题（TAP），其中每个用户都试图将自己的旅行时间减至最少。为了解决较低级别的优化问题，利用梯度投影方法将流量从其他非最短路径转移到每个起点-目的地对之间的最短路径，最终收敛到用户均衡流量分配。上层问题被公式化为约束离散优化问题，并使用概率解发现算法来获得近似最优解。两个数值例子被用来证明所提出的方法在恢复交通系统性能方面的有效性。

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