Skip to main content

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

Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

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.

Keywords

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

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-642-33218-0_1
  • Chapter length: 14 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   129.00
Price excludes VAT (USA)
  • ISBN: 978-3-642-33218-0
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   169.99
Price excludes VAT (USA)
Hardcover Book
USD   179.99
Price excludes VAT (USA)
Fig. 1
Fig. 2
Fig. 3

Notes

  1. 1.

    http://www.geog.uni-heidelberg.de/forschung/gis_grips.html

  2. 2.

    http://www.matsim.org/

References

  1. M. Bakillah, M.A. Mostafavi, J. Brodeur, Mapping between dynamic ontologies in support of geospatial data integration for disaster management, in Proceedings of the Joint CIG/ISPRS Conference on Geomatics for Disaster and Risk Management, Toronto, Ontario, 23–25 May 2007

    Google Scholar 

  2. A.J. Pel, C. Michiel, J. Bliemer, S.P. Hoogendoorn, A review on travel behaviour modelling in dynamic traffic simulation models for evacuations. Transportation 39, 97–123 (2012)

    CrossRef  Google Scholar 

  3. G. Lämmel, D. Grether, K. Nagel, The representation and implementation of time-dependent inundation in large-scale microscopic evacuation simulations. Transp. Res. Part C 18, 84–98 (2010)

    CrossRef  Google Scholar 

  4. H. Fu, Dissertation. Development of dynamic travel demand models for hurricane evacuation, Louisiana State University, 2004

    Google Scholar 

  5. M.-P. Kwan, D.M. Ransberger, LiDAR assisted emergency response: detection of transport network obstructions caused by major disasters. Comput. Environ. Urban Syst. 34(3), 179–188 (2010)

    CrossRef  Google Scholar 

  6. X. Chen, F.B. Zhan, Agent-based modeling and simulation of urban evacuation: relative effectiveness of simultaneous and staged evacuation strategies. Washington, DC (2004)

    Google Scholar 

  7. X. Pan, C. Han, K. Dauber, K. Law, A multi-agent based framework for the simulation of human and social behavior during evacuations. Artif. Intell. Soc. 22(2), 113–132 (2007)

    Google Scholar 

  8. H. Klüpfel, T. Meyer-König, A. Keßel, M. Schreckenberg, Simulating evacuation processes and comparison to empirical results, in Traffic and Granular Flow’01, ed. by M. Fukui, et al. (Springer, Berlin, 2003), pp. 449–454

    Google Scholar 

  9. M. Jafari, I. Bakhadyrov, A. Maher, Technological advances in evacuation planning and emergency management: current state of the art. Final research reports EVAC-RU4474, Center for Advanced Infrastructure and Transportation (CAIT), Rutgers University, March 2003

    Google Scholar 

  10. E. Kuligowski, Review of 28 Egress Models. Technical report (National Institute of Standards and Technology (NIST), Gaithersburg, 2004)

    Google Scholar 

  11. M.K. Lindell, EMBLEM2: an empirically-based large scale evacuation time estimate model. Transp. Res. A 42, 14–154 (2008)

    Google Scholar 

  12. C. Xie, D.Y. Lin, S.T. Waller, A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies. Transp. Res. E 46, 295–316 (2010)

    CrossRef  Google Scholar 

  13. N.R. Johnson, Panic and the breakdown of social order: popular myth, social theory. Empirical Evid. Sociol. Focus. 20(3), 171 (1987)

    CrossRef  Google Scholar 

  14. P. Murray-Tuite, Perspectives for network management in response to unplanned disruptions. J. Urban Plan. Dev. 133(1), 9–17 (2007)

    CrossRef  Google Scholar 

  15. B. Zhang, W. Kin, S.V. Ukkusuri, Agent-based Modeling for household level hurricane evacuation, in Proceedings of the 2009 Winter Simulation Conference, ed. by M.D. Rossetti, R.R. Hill, B. Johansson, A. Dunkin R.G. Ingalls (Institute of Electrical and Electronics Engineers, Inc Piscataway, 2009), pp. 2778–2784

    Google Scholar 

  16. Y. Murakami, K. Minami, T. Kawasoe, T. Ishida, Multi-agent simulation for crisis management, in Proceedings of the IEEE on Knowledge Media Networking Workshop (Washington DC, 2002), pp. 135–139

    Google Scholar 

  17. N. Pelechano, N. Badler, Modeling crowd and trained leader behavior during building evacuation. IEEE Comput. Graph. Appl. 26(6), 80–86 (2006)

    CrossRef  Google Scholar 

  18. A. Shendarkar, K. Vasudevan, S. Lee, Y. Son, Crowd simulation for emergency response using BDI agent-based on virtual reality, in Proceedings of the 2006 Winter Simulation Conference, Monterey, 3–6 Dec 2006

    Google Scholar 

  19. Y. Liu, M. Hatayama, N. Okada, Development of an adaptive evacuation route algorithm under flood disaster. Ann. Disaster Prev. Res. Inst. 49, 189–195, Kyoto University (2006)

    Google Scholar 

  20. E.L. Quarantelli, Disaster studies: an analysis of the social historical factors affecting the development of research in the area. Int. J. Mass Emerg. Disasters. 5(3), 285–310 (1988)

    Google Scholar 

  21. C. Lalonde, Crisis management and organizational development: towards the conception of a learning model in crisis. Organ. Dev. J. 25(1), 17 (2007)

    Google Scholar 

  22. B.E. Aguirre, E.L. Quarantelli, Methodological, ideological and conceptual-theoretical criticisms of the field of collective behavior: a critical evaluation and implications for future study. Sociol. Focus. 16(3), 195 (1983)

    CrossRef  Google Scholar 

  23. R. Turner, L. Killian, Collective Behaviour, 3rd edn. (Prentice Hall, Englewood Cliffs, 1987)

    Google Scholar 

  24. J. Drury, C. Cocking, S. Reicher, Everyone for themselves? a comparative study of crowd solidarity among emergency survivors. Br. J. Soc. Psychol. 48, 487 (2009)

    CrossRef  Google Scholar 

  25. M.J. Hornsey, Social identity theory and self-categorization theory: historical review. Soc. Pers. Psychol. Compass. 2(1), 204–222 (2008)

    Google Scholar 

  26. T.E. Drabek, D.A. McEntire, Emergent phenomena and the sociology of disaster: lessons, trends and opportunities from the research literature. Disaster Prev. Manag. 12(2), 97–112 (2003)

    CrossRef  Google Scholar 

  27. K.J. Tierney, From the margins to the mainstream? Disaster research at the Crossroad. Annu Rev Sociol. 33 503–525 (2007)

    Google Scholar 

  28. S.K. Schneider, Governmental response to disasters: the conflict between bureaucratic procedures and emergency norms. Public Adm. Rev. 52(2), 135 (1992)

    CrossRef  Google Scholar 

  29. E.L. Quarantelli, Basic themes derived from survey findings on human behavior in the Mexico City earthquake. Int. Sociol. 11(4), 481–499 (1996)

    CrossRef  Google Scholar 

  30. B.E. Aguirre, S. El-Tawil, E. Best, K.B. Gill, V. Fedorov, Contributions of social science to agent-based models of building evacuation. Contemp. Soc. Sci. 6(3), 415–432 (2011)

    CrossRef  Google Scholar 

  31. G. Proulx, Understanding human behaviour in stressful situations (2003) http://www.nrc-cnrc.gc.ca/obj/irc/doc/pubs/nrcc45394/nrcc45394.pdf

  32. H.C.M. Vorst, Evacuation models and disaster psychology, in 1st International Conference on Evacuation Modeling and Management (ICEM ‘09), Delft (2010), pp. 15–21

    Google Scholar 

  33. R. Challenger, C.W. Clegg, M.A. Robinson, Understanding Crowd Behaviours. UK Cabinet office. Crown (2009)

    Google Scholar 

  34. S. Reicher, Blackwell handbook of social psychology: group processes, Chap, in The Psychology of Crowd Dynamics, ed. by M.A. Hogg and R.S. Tindale (Blackwell Publishers, Oxford, 2001), pp. 182–208

    Google Scholar 

  35. E. Bernier, Y. Bédard, F. Hubert, UMapIT: an on-demand web mapping application based on a multiple representation database, in Proceedings of the 8th ICA Workshop on Generalization and Multiple Representation, A Coruna, Spain, 8–9 July 2005

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohamed Bakillah .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Bakillah, M., Andrés Domínguez, J., Zipf, A., Liang, S., Mostafavi, M. (2013). Multi-agent Evacuation Simulation Data Model with Social Considerations for Disaster Management Context. In: Zlatanova, S., Peters, R., Dilo, A., Scholten, H. (eds) Intelligent Systems for Crisis Management. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33218-0_1

Download citation