Evaluation of the resilience of air transportation network with adaptive capacity

Securing network resilience of air transportation system is essential to provide a stable level of service as one of major transport modes carrying international passengers and freights. In 2014, about 851 million passengers and 39 billion pounds of freights were delivered by over 9.5 million flights in the United States. As seen in Iceland volcano eruption in 2010, a deficiency of hub airports can bring a huge impact on the whole transport system and even on the world economy. So how the failure of individual node affects the overall network resilience is an important issue to study. Air transportation is known to be a scale-free network, which has few of hubs having high degree. So it is relatively robust against failure but vulnerable to targeted attack on a hub. There are numerous studies devoted to measure node vulnerability and evaluate network robustness; however, previous studies could not consider the node capacity for evaluating overall network performance. This study focuses on the network resilience, where the nodes are located in a real space and have a capacity to function. Using the data from Federal Aviation Administration, the simulation demonstrates and evaluates the resilience of the US air transportation network. This study proposes the indices of adaptative capacity for quantifying network resilience, which represent the ability of a network to replace an attacked node by other adjacent nodes. The simulation has two parts to measure the adaptive capacity of networks: under a single attack and a sustained attack. The results identify the susceptible nodes degrading the adaptive capacity of the network and evaluate each sub-network’s resilience in case of cascading node failures. Therefore, this study can help us to diagnose the vulnerable node and contribute the plan for improvement of network resilience.

Language

  • English

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Filing Info

  • Accession Number: 01666462
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Apr 4 2018 3:03PM