弹性(材料科学)
大洪水
中国
计算机科学
流量(计算机网络)
流量网络
心理弹性
服务(商务)
业务
运输工程
地理
计算机安全
工程类
数学
心理学
数学优化
物理
考古
营销
心理治疗师
热力学
作者
Kai Yin,Jianjun Wu,Weiping Wang,Der‐Horng Lee,Yun Wei
标识
DOI:10.1016/j.tra.2023.103687
摘要
The transportation network is essential in providing daily accessibility and essential service to societies. An acceptable level of service needs to be maintained in critical infrastructures, even in the case of disruptions. We develop an integrated model to assess the resilience of urban transportation networks when exposed to different disruptions. Resilience is evaluated from perspectives of both traffic network topology and traffic flow. This model contains three parts: (1) a traffic flow simulation model to get flow distributed throughout the whole network, (2) different real-world disruptions are abstracted as random, localized, and flood disturbances, (3) functional and topological resilience are accessed by analyzing variations in travel time and connected components before and after a disruption occurs. 40 major cities are chosen to conduct resilience assessments. As the intensity of the disruption increases, common trends in the changes of functional and topological resilience values are observed and analyzed across all studied cities. In most cases, flood disruption is the least disruptive one of all three types of disruptions. Regression models are developed to estimate functional and topological resilience after random, localized, and flood disturbances. Possible resilience enhancement strategies are discussed based on analyses of regression models. This study could aid stakeholders in gaining a clear understanding of resilience not only topologically but also from the perspective of traffic flow and offer them practical strategies to enhance resilience in face of disruptions.
科研通智能强力驱动
Strongly Powered by AbleSci AI