This paper proposes a spatial activity-based modeling approach and applies it to pedestrian crowd behavior simulations. Compared to conventional pedestrian crowd models where pedestrians make movement decisions in a time-based manner, the spatial activity-based pedestrian crowd model allows a pedestrian to make decisions only when needed, that is, when there is significant change in the pedestrian’s spatial position, as defined by a threshold called ‘space resolution’. To demonstrate the spatial activity-based modeling, we develop an activity-based model for pedestrian crowd simulation in a two-dimensional environment and compare it with a conventional time-based simulation model. Experiment results show that the spatial activity-based model can lead to more efficient simulations when simulating heterogeneous pedestrian crowds.
ZeiglerBPJammalamadakaRAkerkarSR. Continuity and change (activity) are fundamentally related in DEVS simulation of continuous systems. Artif Intell Simulat2005; 3397: 1–13.
2.
ZeiglerBPSarjoughianHSPraehoferH. Theory of quantized systems: DEVS Simulation of perceiving agents. Int J Cybern Syst2000; 31: 611–648.
3.
ZeiglerBPPraehoferHKimTG. Theory of modeling and simulation. 2nd ed.Academic Press, 2000: New York, USA.
Reynolds CW. Big fast crowds on PS3. In: 2006 ACM SIGGRAPH symposium on Videogames, New York, 2006, pp.113–121.
7.
MusseSRThalmannD. Hierarchical model for real time simulation of virtual human crowds. IEEE Trans Visual Comput Graphics2001; 7: 152–164.
8.
BraunAMusseSRde OliveiraLPL. Modeling Individual behaviors in crowd simulation. In: 16th international conference on computer animation and social agents, 2003, pp.143–148.
9.
LoscosCMarchalDMeyerA. Intuitive crowd behaviour in dense urban environments using local laws. In: theory and practice of computer graphics 2003, Birmingham, UK, 2003, pp.122–129.
10.
IsobeMHelbingDNagataniT. Experiment, theory, and simulation of the evacuation of a room without visibility. Phys Rev E2004; 69: 638–650.
11.
SongWXuXWangBH. Simulation of evacuation processes using a multi-grid model for pedestrian dynamics. Physica A2006; 363: 492–500.
12.
HoogendoornSPBovyPHLDaamenW. Microscopic pedestrian wayfinding and dynamics modelling. In: SchreckenbergMSharmaSD (eds) Pedestrian and evacuation dynamics. Berlin: Springer, 2002, pp.123–154.
13.
HughesRL. A continuum theory for the flow of pedestrians. Transp Res B2002; 36: 507–535.
14.
SavannahSimulationsAG. SimWalk: The simulation software for pedestrian flows, 2009.
15.
Legion. Pedestrian simulation solutions, 1997.
16.
HelbingDFarkasIJMolnarP. Simulation of pedestrian crowds in normal and evacuation situations. In: SchreckenbergMSharmaSD (eds) Pedestrian and evacuation dynamics. Berlin: Springer, 2002, pp.21–58.
17.
HendersonLF. On the fluid mechanics of human crowd motion. Transp Res1974; 8: 509–515.
18.
BlueVJAdlerJL. Cellular automata microsimulation for modeling bi-directional pedestrian walkways. Transp Res B2001; 35: 293–312.
19.
SchadschneiderA. Cellular automaton approach to pedestrian dynamics - Theory. In: SchreckenbergMSharmaSD (eds) Pedestrian and evacuation dynamics. Berlin: Springer, 2002, pp.75–86.
20.
HamacherHTjandraS. Mathematical Modeling of evacuation problems: A state of the art. In: pedestrian and evacuation dynamics, 2002, pp.227–266.
21.
TjandraSA. Dynamic network flow models for evacuation problems. PhD Thesis, Department of Mathematics, Technische Universität Kaiserslautern, Kaiserslautern, Germany, 2001.
22.
MusseSRThalmannD. A Model of human crowd behavior: Group inter-relationship and collision detection analysis. In: computer animation and simulations ‘97, Budapest, Hungary, 1997, pp.39–52.
23.
HanCSPanXDauberK. A multi-agent based framework for simulating human and social behaviors during emergency evacuations. Artif Intell Soc2007; 22: 113–132.
24.
PelechanoNAllbeckJMBadlerNI. Controlling individual agents in high-density crowd simulation. In: ACM SIGGRAPH/eurographics symposium on computer animation, San Diego, CA, 2007, pp.99–108.
25.
QiuFHuX. Modeling social group structures in pedestrian crowds. Simul Modell Pract Theory2010; 18: 190–205.
26.
LakobaTIKaupDJFinkelsteinNM. Modifications of the Helbing-Molnar-Farkas-Vicsek social force model for pedestrian evolution. Simulation2005; 81: 339–352.
27.
HamagamiTHirataH. Method of crowd simulation by using multiagent on cellular automata. In: intelligent agent technology2003, 2003, pp.46–52.
28.
TecchiaFLoscosCConroy DaltonR. Agent Behaviour Simulator (ABS): A platform for urban behaviour development. In: The First International Game Technology Conference and Idea Expo, Hong Kong, China, 2001, pp.17–21.
29.
QuinnMMetoyerR. Parallel implementation of the social forces model. In: the second international conference in pedestrian and evacuation dynamics, Greenwich, London, 2003, pp.63–74.
30.
RichmondPRomanoD. A high performance framework for agent based pedestrian dynamics on GPU hardware. In: EUROSIS ESM 2008 (European Simulation and Modelling), Le Havre, France, 2008, pp.213–221.
JammalamadakaR. Activity characterization of spatial models: Application to the discrete event solution of partial differential equations. MS Degree, Electrical and Computer Engineering, University of Arizona, 2003.
33.
JammalamadakaR. Multilevel methodology for simulation of spatio-temporal systems with heterogeneous activity: Application to spread of Valley Fever Fungus. PhD Degree, Electrical and Computer Engineering, University of Arizona, 2008.
34.
MuzyAJammalamadakaRZeiglerBP. The activity tracking paradigm in discrete-event modeling and simulation: The case of spatially continuous distributed systems. Simulation2010; 10: 449–464.
35.
HuXZeiglerBPMittalS. Variable structure in DEVS component-based modeling and simulation. Simulation2005; 81: 91–102.
36.
QiuFHuX. Modeling dynamic groups for agent-based pedestrian crowd simulations. In: web intelligence and intelligent agent technology, Toronto, Canada, 2010.
37.
QiuFHuX. BehaviorSim: A learning environment for behavior based agent. In: 10th international conference on simulation of adaptive behavior: from animals to animats, Osaka, Japan, 2008, pp.499–508.
38.
DaamenWHoogendoornSP. Experimental research of pedestrian walking behavior. Transp Res Rec2003; 11: 20–30.
