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

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.

[1]  Saundra K. Schneider Governmental Response to Disasters: The Conflict between Bureaucratic Procedures and Emergent Norms , 1992 .

[2]  Carole Lalonde CRISIS MANAGEMENT AND ORGANIZATIONAL DEVELOPMENT: TOWARDS THE CONCEPTION OF A LEARNING MODEL IN CRISIS MANAGEMENT , 2007 .

[3]  Haoqiang Fu,et al.  Development of dynamic travel demand models for hurricane evacuation , 2004 .

[4]  Kincho H. Law,et al.  A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations , 2007, AI & SOCIETY.

[5]  Michael K. Lindell EMBLEM2: An empirically based large scale evacuation time estimate model , 2008 .

[6]  Norris R. Johnson,et al.  Panic and the Breakdown of Social Order: Popular Myth, Social Theory, Empirical Evidence , 1987 .

[7]  Enrico L Quarantelli,et al.  Disaster Studies: An Analysis of the Social Historical Factors Affecting the Development of Research in the Area , 1987, International Journal of Mass Emergencies & Disasters.

[8]  Yvan Bédard,et al.  Mapping between dynamic ontologies in support of geospatial data integration for disaster management , 2007 .

[9]  M. Hornsey Social Identity Theory and Self‐categorization Theory: A Historical Review , 2008 .

[10]  E. Quarantelli,et al.  Methodological, Ideological, and Conceptual-Theoretical Criticisms of the Field of Collective Behavior: A Critical Evaluation and Implications for Future Study , 1983 .

[11]  John Drury,et al.  Everyone for themselves? A comparative study of crowd solidarity among emergency survivors. , 2009, The British journal of social psychology.

[12]  Harrie C. M. Vorst,et al.  Evacuation models and disaster psychology , 2010 .

[13]  Chester G. Wilmot,et al.  Sequential Logit Dynamic Travel Demand Model for Hurricane Evacuation , 2004 .

[14]  K. Tierney From the Margins to the Mainstream? Disaster Research at the Crossroads , 2007 .

[15]  Kai Nagel,et al.  The representation and implementation of time-dependent inundation in large-scale microscopic evacuation simulations , 2010 .

[16]  Pamela Murray-Tuite Perspectives for Network Management in Response to Unplanned Disruptions , 2007 .

[17]  Seungho Lee,et al.  Crowd Simulation for Emergency Response using BDI Agent Based on Virtual Reality , 2006, Proceedings of the 2006 Winter Simulation Conference.

[18]  Wai Kin Chan,et al.  Agent-based modeling for household level hurricane evacuation , 2009, Proceedings of the 2009 Winter Simulation Conference (WSC).

[19]  E. Quarantelli Basic Themes Derived from Survey Findings on Human Behavior in the Mexico City Earthquake , 1996 .

[20]  Michael Schreckenberg,et al.  Traffic and Granular Flow’01 , 2003 .

[21]  Norman I. Badler,et al.  Modeling Crowd and Trained Leader Behavior during Building Evacuation , 2006, IEEE Computer Graphics and Applications.

[22]  Serge P. Hoogendoorn,et al.  A review on travel behaviour modelling in dynamic traffic simulation models for evacuations , 2012 .

[23]  F. Benjamin Zhan,et al.  Agent-based modelling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies , 2008, J. Oper. Res. Soc..

[24]  S. Travis Waller,et al.  A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies , 2010 .

[25]  Mei-Po Kwan,et al.  LiDAR assisted emergency response: Detection of transport network obstructions caused by major disasters , 2010, Comput. Environ. Urban Syst..

[26]  Yohei Murakami,et al.  Multi-agent simulation for crisis management , 2002, Proceedings. IEEE Workshop on Knowledge Media Networking.

[27]  T. Drabek,et al.  Emergent phenomena and the sociology of disaster: lessons, trends and opportunities from the research literature , 2003 .

[28]  Erica D. Kuligowski Review of 28 Egress Models , 2005 .

[29]  B. Aguirre,et al.  Contributions of social science to agent-based models of building evacuation , 2011 .