Dynamic Travel Demand for Emergency Evacuation: The Case of Bushfires

There are two types of emergencies; those which can be anticipated and those that cannot. Among those that can be anticipated are such events as cyclones, floods, bush fires, and tsunamis. When such events are anticipated, one course of action that may be taken is the evacuation of residents from a threatened area. When evacuation takes place, there often remains a need to provide access for emergency vehicles and personnel to the threatened area creating a conflict between the needs to maximise capacity for evacuation, while continuing to provide access to the threatened area. Relatively little is known about when residents will decide to evacuate. A model of evacuation behaviour is needed that would predict the proportions of the population that would leave within certain time periods, thus leading to the development of an evacuation travel demand model. Under a contract from Emergency Management Australia, the authors developed a method to predict evacuation decisions by residents from bush fires. This paper describes the methods used to determine when a household would evacuate, and describes the resulting model that predicts how many partial and full evacuations will take place by time period from when the emergency is first perceived

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Development of a time-dependent, audio-visual, stated choice method of data collection for hurricane evacuation behavior

Revealed preference is the traditional method to collect hurricane evacuation behavior data. However, revealed preference surveys, as they are currently administered, have the disadvantage that they are unable to collect time-sensitive and policy-sensitive data needed to test evacuation policies. In contrast, data collected from a time-dependent, stated-choice survey will allow researchers to collect not only time-sensitive and policy-sensitive data but also information that will allow testing potential new evacuation policies. However, no research has been conducted to establish the methodology of such a survey. To fill the gap, this study was conducted to develop a new time-dependent, audio-visual, stated-choice method to collect evacuation behavior data. To achieve the objective, nine animations of hypothetical storms were developed based on recent hurricane history. To test the new methodology and its effectiveness, data was collected using both new and traditional methods and their cost and ability to produce good evacuation models were compared. In the new method survey respondents had to watch animations of storm scenarios and answer questions related to their intended behavior while in the traditional method they reported on their behavior in hurricane Gustav that made landfall near New Orleans in 2008. Results indicate that the new stated-choice method is easy to use and effective in collecting time-dependent and policy-sensitive data but costs 25 percent more than the traditional method. The new method appears to have the potential of evolving into a survey instrument that can be used by researchers and practitioners working in hurricane evacuation modeling

An Online Decision-Theoretic Pipeline for Responder Dispatch

The problem of dispatching emergency responders to service traffic accidents, fire, distress calls and crimes plagues urban areas across the globe. While such problems have been extensively looked at, most approaches are offline. Such methodologies fail to capture the dynamically changing environments under which critical emergency response occurs, and therefore, fail to be implemented in practice. Any holistic approach towards creating a pipeline for effective emergency response must also look at other challenges that it subsumes - predicting when and where incidents happen and understanding the changing environmental dynamics. We describe a system that collectively deals with all these problems in an online manner, meaning that the models get updated with streaming data sources. We highlight why such an approach is crucial to the effectiveness of emergency response, and present an algorithmic framework that can compute promising actions for a given decision-theoretic model for responder dispatch. We argue that carefully crafted heuristic measures can balance the trade-off between computational time and the quality of solutions achieved and highlight why such an approach is more scalable and tractable than traditional approaches. We also present an online mechanism for incident prediction, as well as an approach based on recurrent neural networks for learning and predicting environmental features that affect responder dispatch. We compare our methodology with prior state-of-the-art and existing dispatch strategies in the field, which show that our approach results in a reduction in response time with a drastic reduction in computational time.Comment: Appeared in ICCPS 201

Innovative Modelling Approaches for the Design, Operation and Control of Complex Energy Systems with Application to Underground Infrastructures

The ventilations systems play a key role in underground infrastructures for health and safety of occupants during normal operation as well as during accidents. Their performances are affected by selection of the optimal design, operation and control that is investigated by predicting air flow. The calculation of ventilation flows and their interaction with fires can be done with different modelling approaches that differ in the accuracy and in the required resources. The 3D computational fluid dynamics (CFD) tools approximate the flow behaviour with a great accuracy but they require high computational resources. The one dimensional (1D) models allow a compact description of the system with a low computational time but they are unsuitable to simulate thermal fluid-dynamic scenarios characterized by turbulence and gradients. Innovative tools are necessary in order to make the analysis and optimization of these systems possible and accurate in a reasonable time. This can be achieved both with appropriate numerical approaches to the full domain as the model order reduction techniques and with the domain decompositions methods as the multiscale physical decomposition technique. The reduced order mode techniques as the proper orthogonal decomposition (POD) is based on the snapshots method provides an optimal linear basis for the reconstruction of multidimensional data. This technique has been applied to non-dimensional equations in order to produce a reduced model not depending on the geometry, source terms, boundary conditions and initial conditions. This type of modelling is adapted to the optimization strategies of the design and operation allowing to explore several configuration in reduced times, and for the real time simulation in the control algorithms. The physical decomposition achieved through multiscale approaches uses the accuracy of the CFD code in the near field e.g. the region close to the fire source, and takes advantage of the low computational cost of the 1-D model in the region where gradients in the transversal direction are negligible. In last years, the multiscale approach has been proposed for the analysis of tunnel ventilation. Among the several CFD codes used in this field, the Fire Dynamic Simulator (FDS) is suitable for the multiscale modelling. This is an open source CFD package developed by NIST and VTT and presents the HVAC routine in which the conservation equations of mass, energy and momentum are implemented. Currently, the HVAC module does not allow one to consider heat and mass transfer, which significanltly limits the applications. For these reasons a multiscale simulator has been created through the fully integration of a 1D continuity, momentum, energy and mass transport equation in FDS modifying its source codes. The multiscale simulator thus obtained, is based on a direct coupling by means of a Dirichlet-Neumann strategy. At each 1-D-CFD interface, the exchange flow information occurs prescribing thermo-fluid dynamic boundary conditions. The 1-D mass transport equation computes the diffusion of the exhaust gas from the CFD domain and the relative concentration that is particularly interesting in the case of back layering of smoke. The global convergence of the boundary conditions at each 1-D-CFD interface has been analyzed by monitoring the evolution of thermo-fluid dynamic variables (temperature, velocity, pressure and concentration. The multiscale simulator is suitable for parametric and sensitivity studies of the design and the operation ventilation and fire safety systems. This new tool will be available for all the scientific community. In this thesis, Chapter 1 provides a general introduction to the role of the system ventilation in underground infrastructures and to the innovative modelling strategies proposed for these systems. Chapter 2 offers a description of the 1D network modelling, its fluid-dynamic application to the Frejus tunnel and its thermal application to ground heat exchangers. In Chapter 3, the proper orthogonal decomposition method is presented and its application to the optimal control of the sanitary ventilation for the Padornelo Tunnel is discussed. To demonstrate the applicability of POD method in other fields, boreholes thermal energy storage systems have been considered in same chapter. In particular, a multi-objective optimization strategy is applied to investigate the optimal design of these system and an optimization algorithm for the operation is proposed. Chapter 4 describes the multiscale approach and the relative simulator. The new open tool is used for modeling the ventilation system of the Monte Cuneo road tunnel in case of fire. Results show that in the case of the current configuration of the ventilation system, depending on the atmospheric conditions at portals, smoke might not be fully confined. Significant improvements in terms of safety conditions can be achieved through increase of in smoke extraction, which requires the installation of large dumpers and of deflectors on the jet fans. The developed tool shows to be particularly effective in such analysis, also concerning the evaluation of local conditions for people evacuation and fire-brigades operation