Comparison of Field-based Crowd Simulation Approach Based on Different Parallel Architectures ⋆

Crowd simulation has been very significant and widely applied in many fields of virtual reality. How to greatly increase the efficiency and realism becomes the focus of the research about crowd simulation. In this paper, a real-time crowd simulation system is designed on parallel architectures. The system is applied to simulating the evacuation of massive crowd in an Olympic venue and then experiments are done to compare and analyze their different simulation efficiencies on different architectures. The best simulation performance comes from the hybrid architecture in combination of CPU and GPU with parallel computing on multi-core CPUs and the it can reach 52 fps when the number of crowd is 10000. GPU architecture can be used in the crowd simulation system with few data transmission times between CPU and GPU, branch statements and texture look-ups better.

[1]  Soraia Raupp Musse,et al.  Simulating crowds based on a space colonization algorithm , 2012, Comput. Graph..

[2]  Dinesh Manocha,et al.  Directing Crowd Simulations Using Navigation Fields , 2011, IEEE Transactions on Visualization and Computer Graphics.

[3]  Xiao Xiao-fang.  Voronoi-Based Real-Time Crowd Path Planning , 2009 .

[4]  Erik Millán,et al.  Impostors, Pseudo-instancing and Image Maps for GPU Crowd Rendering , 2007, Int. J. Virtual Real..

[5]  Daniel Thalmann,et al.  Real-time Shader Rendering for Crowds in Virtual Heritage , 2005, VAST.

[6]  Carol O'Sullivan,et al.  Geopostors: a real-time geometry / impostor crowd rendering system , 2005, I3D '05.

[7]  K. Shimoo,et al.  A new parallel processing paradigm using a reconfigurable computing system , 2004, IEEE International Symposium on Communications and Information Technology, 2004. ISCIT 2004..

[8]  Stephen Chenney,et al.  Flow tiles , 2004, SCA '04.

[9]  R. Hughes.  The flow of human crowds , 2003 .

[10]  Soraia Raupp Musse,et al.  Hierarchical model for real time simulation of virtual human crowds , 2001, 5th IEEE EMBS International Summer School on Biomedical Imaging, 2002..

[11]  Dirk Helbing,et al.  Self-Organizing Pedestrian Movement , 2001 .

[12]  Eric Bouvier,et al.  From crowd simulation to airbag deployment: particle systems, a new paradigm of simulation , 1997, J. Electronic Imaging.

[13]  Lydia E. Kavraki,et al.  Probabilistic roadmaps for path planning in high-dimensional configuration spaces , 1996, IEEE Trans. Robotics Autom..

[14]  Craig W. Reynolds.  Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.