A New Opportunity to Urban Evacuation Analysis: Very Large Scale Simulations of Social Agent Systems in Repast HPC

Due to catastrophic disasters induced by forces of nature like flooding or tsunamis, terrorism or nuclear power plant accidents, understanding the dynamics of urban evacuation systems has elicited massive interest over the past years. While discrete event simulations of evacuation models become prohibitively complex dealing with the time, space and individual behavior, multiagent based models have revealed to be a potentially more effective. This paper introduces models of configurations of social agents at a massive scale, which, together with the most recent supercomputing technology, allows for a simulation analysis of realistic evacuation models at the level of large cities (106 -108 agents). Agent based models of demographics and the morphology of cities together with population densities, mobility patterns, individual decision making, and agent interactions are implemented into a tool chain which ultimately generates Repast HPC code, which is then executed on a 2,048 node shared memory multiprocessor server (SGI Altix UV-1000). We demonstrate how different evacuation strategies can be assessed based on costly, yet feasible simulation runs - thus evidencing, that a whole class of demanding, very complex simulation problems has found a convincing solution.

[1]  Kalyan S. Perumalla,et al.  Data parallel execution challenges and runtime performance of agent simulations on GPUs , 2008, SpringSim '08.

[2]  Harry J. P. Timmermans,et al.  A Multi-Agent Cellular Automata System for Visualising Simulated Pedestrian Activity , 2000, ACRI.

[3]  Joseph M. Whitmeyer,et al.  Social Emergence: Societies as Complex Systems , 2006 .

[4]  R. Sawyer Social Emergence: Societies As Complex Systems , 2005 .

[5]  Alois Ferscha,et al.  Comparing Parallel Simulation of Social Agents Using Cilk and OpenCL , 2011, 2011 IEEE/ACM 15th International Symposium on Distributed Simulation and Real Time Applications.

[6]  Alois Ferscha,et al.  LifeBelt: Crowd Evacuation Based on Vibro-Tactile Guidance , 2010, IEEE Pervasive Computing.

[7]  Xiaohu Zhang,et al.  Parallel cellular automata for large-scale urban simulation using load-balancing techniques , 2010, Int. J. Geogr. Inf. Sci..

[8]  G. An,et al.  The Basic Immune Simulator: An agent-based model to study the interactions between innate and adaptive immunity , 2007, Theoretical Biology and Medical Modelling.

[9]  Scott E. Page,et al.  Agent-Based Models , 2014, Encyclopedia of GIS.

[10]  Michael J. North,et al.  Experiences creating three implementations of the repast agent modeling toolkit , 2006, TOMC.

[11]  Werner Dubitzky,et al.  Large-Scale Computing Techniques for Complex System Simulations , 2011 .

[12]  Joshua M. Epstein,et al.  Growing Artificial Societies: Social Science from the Bottom Up , 1996 .

[13]  Sean Luke,et al.  MASON: A Multiagent Simulation Environment , 2005, Simul..

[14]  Alois Ferscha,et al.  LifeBelt: Silent Directional Guidance for Crowd Evacuation , 2009, 2009 International Symposium on Wearable Computers.

[15]  Emiliano Ferreira Castejon,et al.  Using neural networks and cellular automata for modelling intra‐urban land‐use dynamics , 2008, Int. J. Geogr. Inf. Sci..

[16]  Charles M. Macal,et al.  Introduction: The Simulation of Social Agents , 2001 .

[17]  M. Batty,et al.  Stochastic cellular automata modeling of urban land use dynamics: empirical development and estimation , 2003, Comput. Environ. Urban Syst..

[18]  A. Troisi,et al.  An agent-based approach for modeling molecular self-organization. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Alois Ferscha,et al.  On the Efficiency of LifeBelt Based Crowd Evacuation , 2009, 2009 13th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications.

[20]  Tengda Sun,et al.  A traffic cellular automata model based on road network grids and its spatial and temporal resolution's influences on simulation , 2007, Simul. Model. Pract. Theory.

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

[22]  Dirk Helbing,et al.  Self-Organization and Emergence in Social Systems: Modeling the Coevolution of Social Environments and Cooperative Behavior , 2011 .

[23]  Suzana Dragicevic,et al.  Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour , 2008 .

[24]  R. White,et al.  High-resolution integrated modelling of the spatial dynamics of urban and regional systems , 2000 .