Probabilistic Path Finding Method for Post-Disaster Risk Estimation

Abstract

One of the main problems in an immediate post-disaster situation is to find the shortest path between command centres or/and important life care institutions and affected areas, respectively. In this paper, a modified A* search algorithm is proposed, that can find the shortest path between any two points on a map, weighted by the damage probability of the existing infrastructure situated in different locations of an urban area. The proposed approach combines the risk probabilities given by the fragility curves of some relevant constructions located in the disaster area with the deterministic search algorithm. In this case, the real costs provided to the A* algorithm are replaced with expected costs, which are estimated in a stochastic framework. The concept is exemplified on the case study of an urban sample identified in Iaşi, a city of around 300,000 inhabitants, located in the North Eastern region of Romania, exposed to repetitive earthquakes with a recurrence period of around 35–40 years. Thus, probabilistic scenarios can be created for emergency interventions, based on previously recorded local values of Peak Ground Acceleration (PGA). Moreover, the proposed routes for the emergency intervention teams in the post-disaster stage can be visualized on a GIS map, shown actually in our case study. In case of a real extreme event, the information about the proposed routes can be updated in real time, as new data are collected in the field and transmitted to the decision centre.