A Sensitivity Analysis of a Dynamic Restricted Equilibrium Model to Evaluate the Traffic Network Resilience

Extreme weather events have a devastating impact on traffic networks. Therefore, mathematical tools that are able to measure systematically the impacts of extreme weather events, i.e. to evaluate its resilience, should be developed. With the aim of improving the resilience of a traffic network when affected by a hazard, a profound knowledge of the model to evaluate resilience is necessary. Consequently, the model parameters should be analized, since these parameters represent the characteristics of the network and this analysis will permit to identify those characteristics that should be improved to reach a more resilient system. This paper develops a sensitivity analysis that reduces the number of studied point needed due to its statistical approach using a global technique (Latin Hypercube), without losing efficiency, as a local technique (One-At-a-Time) is applied too. This analysis confirms that the model to evaluate the resilience represents the real behavior of the traffic network. The results show that the intensity of the hazards is the most sensitive parameter. When hazard intensity is low, the impedance of the system becomes the most sensitive parameter