In this paper, the analysis of a transportation system under emergency conditions due to hazardous events is considered. To assess the effects on the analyzed transport network, an extension to a mesoscopic dynamic traffic assignment (DTA) model was developed to determine quantitative indicators for estimating the exposure component of the total risk incurred by the transport networks in an area. In particular, a new version that is able to allow for multimodal networks and to consider network reliability was introduced. To give a practical example of the proposed model, it has been applied to two real networks, studying evacuation in the hypothesis that in the event of a calamity the population in the area follows the instructions proposed by the municipal civil protection plan. The work shows how adequate quantitative methodologies based on a dynamic approach can be a useful tool to support the process of evacuation planning at several scales.

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In this paper we present some results obtained in the research project entitled SURE, carried out by the Laboratory for Transport Systems Analysis (LAST) of the Mediterranea University of Reggio Calabria (Italy).The general objective of the project is risk reduction in urban areas in terms of exposure through the definition and implementation of evacuation procedures. One of the activities concerns the specification and calibration of a system of models able to simulate the transportation system when a population has to evacuate due to a forthcoming disaster. This paper concerns the simulation of pedestrian outflow related to the evacuation of a building, using flow models calibrated on the basis of data collected during experimentation on a test site. This experimentation was conducted in a school in an Italian town but the methodology used can be applied to any building with homogeneous characteristics in terms of activities (i.e. offices, banks, commercials, schools).

One of the actions usually conducted to limit exposure to a hazardous event is the evacuation of the area that is subject to the effects of the event itself. This involves modifications both to demand (a large number of users all want to move together) and to supply (the transport network may experience changes in capacity, unusable roads, etc.). In order to forecast the traffic evolution in a network during an evacuation, a natural choice is to adopt an approach based on Dynamic Traffic Assignment (DTA) models. However, such models typically give a deterministic prediction of future conditions, whereas evacuations are subject to considerable uncertainty. The aim of the present paper is to describe an evacuation approach for decision support during emergencies that directly predicts the time-evolution of the probability of evacuating users from an area, formulated within a discrete-time stochastic process modelling framework. The approach is applied to a small artificial case as well as a real-life network, where we estimate users' probabilities to reach a desired safe destination and analyze time dependent risk factors in an evacuation scenario.

A recently funded research project in Italy concerned reduction in risk exposure in urban areas through the definition and the implementation of evacuation procedures. One of the research aims was to specify and calibrate a system of models that could simulate the transportation system when a population must evacuate because of approaching disaster. Various activities were conducted to calibrate a set of cost functions to be implemented within a dynamic network loading procedure to simulate pedestrian outflow related to the evacuation of a building. How flow models are calibrated on the basis of data collected during experimentation at a test site is shown, and the results of their implementation within a multimodal dynamic loading model used to simulate evacuation procedures are described. A comparison between experimental data and simulation results shows that the use of appropriate simulation models can realistically reproduce user behavior and then shows how such models can be used as a support for creating effective evacuation plans. The experimentation involved evacuation of a primary school in an Italian town, but the method applied can be adapted easily to any public building with homogenous characteristics.