Abstract
Air traffic networks are essential to today’s global society. They are the fastest means of transporting physical goods and people and are a major contributor to the globalisation of the world’s economy. This increasing reliance requires these networks to have high resilience; however, previous events show that they can be susceptible to natural hazards. We assess two strategies to improve the resilience of air traffic networks and show an adaptive reconfiguration strategy is superior to a permanent re-routing solution. We find that, if traffic networks have fixed air routes, the geographical location of airports leaves them vulnerable to spatial hazard.
Highlights
Air travel is critical to the functioning of countries and the world economy as a whole
We applied both of these resilience strategies to the European air traffic network (EATN) and subjected the networks to a growing spatial hazard located over the geographic centre of the network, choosing this hazard location to cause the most disruption to the network
We quantified the resilience of the networks by initially plotting the proportion of cancelled air routes and the proportion of closed airports and area, and by applying a network graph theory measure of connectivity (MCS) and performance (APL)
Summary
Air travel is critical to the functioning of countries and the world economy as a whole. The US is not the only country to experience air traffic disruption due to snowstorms; in December 2010 Heathrow airport was closed for arrivals and departures on 18 December, with only a limited number of flights operating the day, due to 70 mm of snow falling in one hour This event caused the cancellation of over 4000 flights, disrupting the travel plans of many passengers during what was predicted to be Heathrow’s busiest weekend of the year (Heathrow Winter Resilience Enquiry, 2011). In the UK, Heathrow airport has already taken steps to minimise disruption caused by extreme weather events, snow/ice hazard, by reducing the capacity of scheduled flights per day in the winter season to 1279, in comparison to 1341 flights in the summer season (Transport Committee, 2013a). We assess the change in connectivity and performance of the network by applying two network graph theory metrics, maximum cluster size (MCS) and shortest average path length (APL)
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