Dynamic restricted equilibrium model to determine statistically the resilience of a traffic network to extreme weather events

Extreme weather events lead transportation systems to critical situations, which imply high social, economical and environmental costs. Developing a tool to quantify the damage suffered by a traffic network and its capacity of response to these phenomena is essential to reduce the damage of this hazard and to improve the system. With this aim, a statistical analysis of the resilience of a traffic network under extreme climatological events is presented. The resilience of a traffic network is determined by means of a dynamic restricted equilibrium model together with a travel cost function that includes the effect of weather on a traffic network. The cost function parameters related to the hazard effect are assumed as random, following Generalized Beta distributions. Then, the fragility curves of the target traffic network are defined using the Monte Carlo method and Latin Hypercube sampling. Fragility curves are a useful tool to analyse of the vulnerability of a traffic network, assisting in the decision-making for the prevention and response to the extreme weather events.