评估极端洪水对城市轨道交通的影响：一个以乘客为导向、具备韧性认知的框架

中文摘要 AI 辅助

城市轨道交通系统（URTS）日益面临强降水后极端洪水的威胁，然而，乘客出行影响往往通过基于延误的指标进行评估，这些指标忽视了大范围中断下不可行的出行。本研究开发了一个以乘客为导向、具备韧性认知的框架，用于评估从中断发生到恢复完成期间洪水对URTS出行的影响。该框架提出了一种新颖的六类别出行影响分类，明确考虑了改道、替代车站使用以及延误阈值。通过伦敦15条URTS线路在30年、100年和1000年洪水风险情景下的每小时动态模拟进行了演示。结果表明，严重的洪水中断导致大量未满足的需求，这主要由不可用路线而非不可接受的延误驱动。与更精细的行为调整相比，改道主导了出行影响。这些发现强调了超越基于延误评估的重要性，并为旨在为URTS洪水韧性干预规划提供信息的战略级压力测试提供了关于关键行为机制的有价值证据。

英文摘要

Urban rail transit systems (URTSs) are increasingly exposed to extreme floods following heavy precipitation, yet passenger travel impacts are often assessed through delay-based indicators that overlook infeasible journeys under large-scale disruptions. This study develops a passenger-oriented, resilience-informed framework for assessing flood impacts on URTS journeys from disruption onset to recovery completion. The framework presents a novel six-category classification of journey impacts, explicitly considering rerouting, alternative station use, and a delay threshold. It is demonstrated through hourly dynamic simulations of 15 London URTS lines under 30-year, 100-year, and 1,000-year flood risk scenarios. Results indicate that severe flood disruptions lead to substantial unsatisfied demand, driven primarily by unavailable routes rather than unacceptable delays. Compared with finer behaviour adjustments, rerouting dominates travel impacts. These findings highlight the significance of moving beyond delay-based assessment and provide valuable evidence on essential behavioural mechanisms for strategic-level stress testing intended to inform URTS flood resilience intervention planning.

发表机构

• University of Cambridge（剑桥大学）
• ETH Zurich（苏黎世联邦理工学院）

机构由 AI 辅助整理，请以论文原文为准。