Intelligent Systems for Crisis Management

Part of the series Lecture Notes in Geoinformation and Cartography pp 3-16


Multi-agent Evacuation Simulation Data Model with Social Considerations for Disaster Management Context

  • Mohamed BakillahAffiliated withRupprecht-Karls-Universität Institute for GI-Science Email author 
  • , J. Andrés DomínguezAffiliated withDepartment of Sociology and Social Work, University of Huelva
  • , Alexander ZipfAffiliated withRupprecht-Karls-Universität Institute for GI-Science
  • , Steve H. L. LiangAffiliated withDepartment of Geomatics Engineering, University of Calgary
  • , M. A. MostafaviAffiliated with Geomatics Research Center, Laval University

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Large scale disasters often create the need for evacuating affected regions to save lives. Disaster management authorities need evacuation simulation tools to assess the efficiency of various evacuation scenarios and the impact of a variety of environmental and social factors on the evacuation process. Therefore, sound simulation models should include the relevant factors influencing the evacuation process and allow for the representation of different levels of detail, in order to support large scale evacuation simulation while also offering the option of considering factors operating at a finer level of detail, such as at the single individual level. In particular, the impact of social factors, such as interaction between agents, should be integrated into the simulation model to reflect the reality of evacuation processes. In this paper, we present a generic data model for agent-based evacuation simulation that includes the relevant social parameters identified in the emergency literature. The model is composed of three sub-models that describe the agents, their context and behaviour, the dynamic environment in which the agents evolve and the parameters of the evacuation scenario. The objective of this model is to improve the simulation so that it can be better represent reality.


Data model Disaster management Evacuation simulation Multi-agent systems Social behaviour