Abstract
Realistic crowd simulation is an important issue for the production of virtual worlds for games, crowd management, public space design, education, entertainment or architectural and urban planning. In this paper, crowd simulation is considered from two aspects: intra-group simulation and inter-group simulation. We propose a unified framework for crowd simulation in real-time virtual environment. Based on this framework, for intra-group simulation, we propose a novel density-based information crowd simulation to collision-free. For inter-group simulation, we propose a novel discrete choice (DC) model to realistic simulation of crowds and path planning. Meanwhile, we also propose a variable bounding box method for intra-group/inter-groups intersection problem. The simulation results show that the developed framework allows different group structures to be easily modeled. And the proposed framework could be used for real-time navigation of many moving crowd in complicated virtual environments.
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Charalambous P, Chrysanthou Y (2014) The PAG crowd: A graph based approach for efficient data-driven crowd simulation. Computer Graphics Forum Early View, online
Chen D, Wang LZ, Wu XM, Chen JY, Khand SU, Kołodziej J, Tian MW, Huang F, Liu WY (2012) Hybrid modeling and simulation of huge crowd over a hierarchical grid architecture. Future Generation Computer Systems:132–145
Chraibi M, Freialdenhoven M, Schadschneider A, Seyfried A (2012) Modeling the desired direction in a force-based model for pedestrian dynamics. Traffic and Granular Flow, Moscow
Daamen W (2002) SimPed: a pedestrian simulation tool for large pedestrian areas. In: Proceedings of the Conference Euro SIW, pp 24–26
Daamen W (2004) Modelling passenger flows in public transport facilities. PhD thesis, Delft University of Technology
Duives DC, Daamen W, Hoogendoorn SP (March 2013) State-of-the-art crowd motion simulation models. Transportation Research Part C: Emerging Technologies
Funge J, Tu X, Terzopoulos D (1999) Cognitive modeling: knowledge, reasoning and planning for intelligent characters. In: Proceedings of ACM SIGGRAPH, pp 29–38
Hart P, Nilsson N, Raphael B (2008) A formal basis for the heuristic determination of minimum cost paths. IEEE Trans Syst Sci Cybernetics 4(2):100–107
Höcker M, Berkhahn V, Kneidl A, Borrmann A, Klein W (2010) Graph-based approaches for simulating pedestrian dynamics in building models. In: Work and Business in Architecture, Engineering and Construction, pp 389–394
Heliövaara S, Korhonen T, Hostikka S, Ehtamo H (2012) Counterflow model for agent-based simulation of crowd dynamics. Building and Environment 48:89–100
Hoogendoorn SP, Bovy P (2004) Pedestrian route-choice and activity scheduling theory and models. Transp Res B Methodol 38:169–190
Huang L, Wong SC, Zhang MP, Shu CW, Lam WH (2009) Revisiting Hughes dynamic continuum model for pedestrian flow and the development of an efficient solution algorithm. IEEE Transp Res Part B 43:127–141
Hughes RL (2003) The flow of human crowds. Annu Rev Fluid Mech 35:169–182
Jund T, Kraemer P, Cazier D (2012) A unified structure for crowd simulation. Computer Animation and Virtual Worlds 23:311–320
Karamouzas I, Geraerts R, Overmars MH (2009) Indicative routes for path planning and crowd simulation. In: Proceedings of the 4th International Conference on Foundations of Digital Games, pp 113–120
Lemercier S, Jelic A, Kulpa R, Hua J, Fehrenbach J, Degond P, Donikian S, Appert-Rolland C, Pettr J (2012) Realistic following behaviors for crowd simulation. Eurographics P. Cignoni, T. Ertl, vol 31, no. 2
Liu WX, Lau R, Manocha D (2012) Crowd simulation using discrete choice model. IEEE Virtual Reality, Orange County, pp 3–6
Pelechano N, Stocker C, Allbeck J, Badler NI (2008) Being a part of the crowd: towards validating VR crowds using presence. In: Proceeding of 7th Autonomous Agents and Multi-agent Systems, pp 136–142
Rao YB, Chen LT, Liu QH, Lin WY, Li YM, Zhou J (2011) Real-time control of individual agents for crowd simulation. Multimed Tools Appl 54 (2):397–414
Reynolds CW (1999) Steering behaviors for autonomous characters. In: Proceedings of Game Developers Conference, pp 763–782
Reynolds CW (1987) Flocks, herds and schools: A distributed behavioral model. In: Processing of 14th Conference on Computer Graphics and Interactive Techniques, New York, pp 25–34
Robin T, Antonini G, Bierlaire M, Cruz J (2010) Specification, estimation and validation of a pedestrian walking behavior model. Trans Res-Part B 43:36–56
Roland G, Overmars MH (2008) Enhancing corridor maps for real-time path planning in virtual environments. Computer Animation and Social Agents: 64–71
Stephen Guy J, Chhugani J, Curtis S, Dubey P, Lin M, Manocha D (2010) PLEdestrians: A least-effort approach to crowd Simulation. Eurographics/ACM SIGGRAPH Symp Comput Animat:13–24
Thalmann D (2007) Crowd simulation. Wiley Encyclopedia of Computer Science and Engineering
Toll WG, Cook IV, Geraerts R (2011) Navigation meshes for realistic multi-layered environments. In: Proceedings of the International Conference on Intelligent Robots and Systems, pp 3526–3532
Train K (2003) Discrete choice methods with simulation. Cambridge University Press
Treuille A, Cooper S, Popovic Z (2006) Continuum crowds. In: ACM SIGGRAPH, pp 1160–1168
Treuille A, Cooper S, Popovic Z (2006) Continuum crowds. ACM Trans Graph 25(3):1160–1168
Wein R, Berg VD, Halperin D (2007) The visibility-voronoi complex and its applications. Comput Geom Theory Appl 36(1):66–78
Wijermans N (2011) Understanding crowd behaviour: simulating situated individuals. PhD thesis, University of Groningen
Wolinski D, Guy SJ, Olivier A-H, Lin M, Manocha D, Pettr J (2014) Parameter estimation and comparative evaluation of crowd simulations. Computer Graphics Forum 33(2):303–312
Wouter G, Toll V, Atlas F, Cook IV, Geraerts R (2012) Real-time density-based crowd simulation. Computer Animation and Virtual Worlds 23:59–69
Acknowledgments
We would like to thank the anonymous reviewers for helpful comments. This work was supported by scientific research fund of Sichuan provincial education department (Grant No: 13ZB0154)
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He, W., Chen, J.X. & Zhang, W. Crowd simulation using DC model and density information. Multimed Tools Appl 75, 5981–5998 (2016). https://doi.org/10.1007/s11042-015-2561-1
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DOI: https://doi.org/10.1007/s11042-015-2561-1