Runtime Optimisation Approaches for a Real-Time Evacuation Assistant

  • Armel Ulrich Kemloh Wagoum
  • Bernhard Steffen
  • Armin Seyfried
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7203)


This paper presents runtime optimisation approaches for a real-time evacuation assistant. The pedestrian model used for the forecast is a modification of the centrifugal force model which operates in continuous space. It is combined with an event driven route choice algorithm which encompasses the local shortest path, the global shortest path and a combination with the quickest path. A naive implementation of this model has the complexity of O(N2), N being the number of pedestrians. In the first step of the optimisation the complexity is reduced to O(N) using special neighbourhood lists like Verlet-List or Linked-Cell commonly used in molecular dynamics. The next step in this optimisation process is parallelisation on a multicore system. The Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) application programming interfaces are used to this extend. The simulation is performed on the Juropa cluster installed at the Jülich Supercomputing Centre. The speedup factors obtained are ~10 for the linked-cells, ~4 for 8 threads and ~3 for the parallelisation on 5 nodes using a static domain decomposition.


pedestrian dynamics high performance computing evacuation route choice 


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  1. 1.
  2. 2.
    Allen, M.P., Tildesley, D.J.: Computer simulation of liquids, vol. 18. Oxford University Press (1989)Google Scholar
  3. 3.
    Baiardi, F., Bonotti, A., Ferrucci, L., Ricci, L., Mori, P.: Load balancing by domain decomposition: the bounded neighbour approach. In: Proc. of 17th European Simulation Multiconference, pp. 9–11 (2003)Google Scholar
  4. 4.
    Blue, V.J., Adler, J.L.: Cellular automata microsimulation for modeling bidirectional pedestrian walkways. Transportation Research Part B 35, 293–312 (2001)CrossRefGoogle Scholar
  5. 5.
    Chraibi, M., Seyfried, A., Schadschneider, A.: Generalized centrifugal force model for pedestrian dynamics. Physical Review E 82, 046111 (2010)CrossRefGoogle Scholar
  6. 6.
    Galea, E.R., Gwynne, S., Lawrence, P., Filippidis, L., Blackspields, D., Cooney, D.: buildingEXODUS V 4.0 - User Guide and Technical Manual (2004)Google Scholar
  7. 7.
    Geimer, M., Wolf, F., Wylie, B.J.N., Ábrahám, E., Becker, D., Mohr, B.: The scalasca performance toolset architecture. Concurrency and Computation: Practice and Experience 22(6), 702–719 (2010)Google Scholar
  8. 8.
    Griebel, M., Knapek, S., Zumbusch, G.: Numerical Simulation in Molecular Dynamics: Numerics, Algorithms, Parallelization, Applications, 1st edn. Springer Publishing Company, Incorporated (2007)Google Scholar
  9. 9.
    Hanxleden, R.V., Clark, T.W., Clark, T.W., Hanxleden, R., Mccammon, J.A., Scott, L.R.: Parallelizing molecular dynamics using spatial decomposition. In: Scalable High Performance Computing Conference, pp. 95–102. IEEE Computer Society Press (1993)Google Scholar
  10. 10.
    Hegarty, D., Kechadi, M., Dawson, K.: Dynamic Domain Decomposition and Load Balancing for Parallel Simulations of Long-Chained Molecules. In: Waśniewski, J., Madsen, K., Dongarra, J. (eds.) PARA 1995. LNCS, vol. 1041, pp. 303–312. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  11. 11.
    Helbing, D., Molnár, P.: Social force model for pedestrian dynamics. Phys. Rev. E 51, 4282–4286 (1995)CrossRefGoogle Scholar
  12. 12.
    Holl, S., Seyfried, A.: Hermes - an Evacuation Assistant for Mass Events. inSiDe 7(1), 60–61 (2009), Google Scholar
  13. 13.
    Janak, J., Pattnaik, P.: Protein calculations on parallel processors. ii. parallel algorithm for the forces and molecular dynamics. Journal of Computational Chemistry 13(9), 1098–1102 (1992)CrossRefGoogle Scholar
  14. 14.
    Kemloh Wagoum, A.U., Seyfried, A., Holl, S.: Modelling dynamic route choice of pedestrians to assess the criticality of building evacuation. Advances in Complex Systems 15(3) (2012)Google Scholar
  15. 15.
    Kirchner, A., Schadschneider, A.: Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics. Physica A 312, 260–276 (2002)MATHCrossRefGoogle Scholar
  16. 16.
    Molnár, P.: Modellierung und Simulation der Dynamik von Fußgängerströmen. Dissertation, Universität Stuttgart (1995)Google Scholar
  17. 17.
    Richmond, P., Romano, D.: A High Performance Framework For Agent Based Pedestrian Dynamics On GPU Hardware. In: Proceedings of EUROSIS ESM 2008 (European Simulation and Modelling) (October 2008)Google Scholar
  18. 18.
    Pettré, J., De Heras Ciechomski, P., Maïm, J., Yersin, B., Laumond, J.P., Thalmann, D.: Real-time navigating crowds: scalable simulation and rendering: Research articles. Comput. Animat. Virtual Worlds 17, 445–455 (2006)CrossRefGoogle Scholar
  19. 19.
    Plimpton, S., Hendrickson, B.: Parallel molecular dynamics algorithms for simulation of molecular systems. In: Mattson, T.G. (ed.) Parallel Computing in Computational Chemistry, pp. 114–136 (1995)Google Scholar
  20. 20.
    Quinn, M.J., Metoyer, R.A., Hunter-zaworski, K.: Parallel implementation of the social forces model. In: Proceedings of the Second International Conference in Pedestrian and Evacuation Dynamics, pp. 63–74 (2003)Google Scholar
  21. 21.
    Reynolds, C.: Big fast crowds on PS3. In: Proceedings of the 2006 ACM SIGGRAPH Symposium on Videogames (2006)Google Scholar
  22. 22.
    Schadschneider, A., Klingsch, W., Klüpfel, H., Kretz, T., Rogsch, C., Seyfried, A.: Evacuation Dynamics: Empirical Results, Modeling and Applications. In: Encyclopedia of Complexity and System Science, vol. 5, pp. 3142–3176. Springer, Heidelberg (2009)Google Scholar
  23. 23.
    Seyfried, A., Chraibi, M., Mehlich, J., Schadschneider, A.: Runtime Optimization of Force Based Models within the Hermes Project. In: Pedestrian and Evacuation Dynamics 2010(2010)Google Scholar
  24. 24.
    Steffen, B., Kemloh Wagoum, A.U., Chraibi, M., Seyfried, A.: Parallel real time computation of large scale pedestrian evacuations. In: Ivanyi, P., Topping, B.H.V. (eds.) The Second International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering, p. 95. Civil-Comp Press, S (2011) 978-1-905088-44-7Google Scholar
  25. 25.
    Sutmann, G., Stegailov, V.: Optimization of neighbor list techniques in liquid matter simulations. Journal of Molecular Liquids 125(2-3), 197–203 (2006)CrossRefGoogle Scholar
  26. 26.
    Thompson, P.A.: Developing new techniques for modelling crowd movement. Phd thesis, University of Edinburgh (1994)Google Scholar
  27. 27.
    Wang, S., Armstrong, M.P.: A quadtree approach to domain decomposition for spatial interpolation in grid computing environments. Parallel Comput. 29, 1481–1504 (2003)CrossRefGoogle Scholar
  28. 28.
    Yu, W.J., Chen, R., Dong, L., Dai, S.: Centrifugal force model for pedestrian dynamics. Phys. Rev. E 72(2), 026112 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Armel Ulrich Kemloh Wagoum
    • 1
  • Bernhard Steffen
    • 1
  • Armin Seyfried
    • 1
  1. 1.Jülich Supercomputing CentreForschungszentrum Jülich GmbHJülichGermany

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