Crowd SimulationOverviewMotivationApplicationsApproachesState of the Art (Movies)Simulating dynamic features of escape panicContributionCharacteristic features of escape panicThe Problem & SolutionAcceleration of Simulated PeopleForces from Other PeopleTotal Force of Other PeoplePhysical ForcesForces from WallsValues Used for Constants and ParametersSimulation of CloggingSlide 18Widening Can Create CrowdingMass BehaviorEffects of HerdingSlide 22Injured People Block ExitA Column Can Increase OutflowConclusionDemosFuture workHierarchical Model for Real Time Simulation of Virtual Human CrowdsSlide 29ContributionsTermsViCrowdControl of behaviorsCrowd StructureCrowd InformationKnowledgeBeliefsSlide 38Slide 39Slide 40Slide 41IntentionsInter-dependence between the levels of informationOverview of ModelResults & DemosSlide 46SummaryConstrained Animation of FlocksMotivationSlide 50Slide 51Behavior modelSlide 53Behavior rulesConstraintsFinding initial trajectoriesSlide 57Slide 58Finding Initial TrajectoriesSlide 60Slide 61Evaluating plausibility of an animationEvaluating the wander impulsesEvaluating constraint enforcementGenerating a better animationSlide 66ExamplesDemosSlide 69Scalable Behaviors for Crowd SimulationThe Goal: Scalable Crowd SimulationConflicting GoalsAn EnvironmentScalability: Complex EnvironmentsObservation: Behavior Depends on SituationManaging Environmental Complexity: Situation-Based ApproachObservation: Crowds are CrowdsKey IdeasSituation-Based Approach: Agent ArchitectureSituation-Based Approach: Simple Default AgentsSituation-Based Approach: Extensible AgentExampleComposing Behaviors: Action SelectionComposing Behaviors: Probability SchemeSlide 85Composing Behaviors: Extending AgentsSlide 87Situations ComposeAuthoring: Painting interfaceAdvantagesSlide 91Limitations/Future workSummary: Scalable Crowd SimulationPerformance evaluationSlide 95Slide 96Slide 97Slide 98Slide 99Slide 100The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Crowd Simulation Ilknur Kaynar – KabulCOMP 259 – Spring 2006The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Overview•Motivation•Simulating dynamic features of escape panicD. Helbing, I. Farkas, and T. Vicsek•Hierarchical Model for Real Time Simulation of Virtual Human CrowdsSoraia Raupp Musse, Daniel Thalmann•Constrained Animation of FlocksMatt Anderson, Eric McDaniel and Stephen Chenney•Scalable Behaviors for Crowd SimulationMankyu Sung, Michael Gleicher and Stephen Chenney•SummaryThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Motivation•Real worlds: crowds are ubiquitous•Non-real time applications: (films, cut-scenes of games) crowds used more and more, usually to increase epic dimensions•Real-time applications: (games, training simulations) crowds are still rare, most interactive worlds are “ghost towns”The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Applications •Entertainment industry (animation production, computer games)•Training of police & military (demonstrations, riots handling)•Architecture (planning of buildings, towns, visualization)•Safety science (evacuation of buildings, ships, airplanes)•Sociology (crowd behavior)•Physics (crowd dynamics)The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Approaches•Common approaches♦Particle systems♦Agent based models♦Cellular automata♦Probability networks♦Social-force networks•Exotic approaches♦Fractals♦Chaos model♦Flow and network models♦Perceptual control theoryThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL State of the Art (Movies)The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Simulating dynamic features of escape panicDirk Helbing, Illes Farkas, and Tamas VicsekNature, 2000The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Contribution•Proposes a model of pedestrian behaviour to investigate the mechanisms of panic and jamming by uncoordinated motion in crowdsThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Characteristic features of escape panic•People move or try to move considerable faster than normal•Individuals start to pushing, and interactions become physical•Moving becomes uncoordinated•At exist, arching and clogging are observed•Jams build up•Pressure on walls and steel barriers increase•Escape is further slowed by fallen or injured people acting as ‘obstacles’The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL The Problem & SolutionCrowd stampedes can be deadlyPeople act in uncoordinated and dangerous ways when panickingIt is difficult to obtain real data on crowd panicsModel people as self-driven particlesModel physical and socio-psychological influences on people’s movement as forcesSimulate crowd panics and see what happensThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Acceleration of Simulated People•vi0(t) = desired speed•ei0(t) = desired direction•vi(t) = actual velocity•τi = characteristic time•mi = massThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Forces from Other People•Force from other people’s bodies being in the way•Force of friction preventing people from sliding•Psychological “force” of tendency to avoid each other•Sum of forces of person j on person i is fijThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Total Force of Other People•Aiexp[(rij – dij)/Bi]nij is psychological “force”•Ai and Bi are constantspsychological forcesum of the people’s radii distance between people`s centers of massnormalized vector from j to iThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Physical Forces•g(x) is 0 if the people don’t touch and x if they do touch•k and κ are constantsforce from other bodies force of sliding frictiontangential directiontangential velocity differenceThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Forces from Walls•Forces from walls are calculated in basically the same way as forces from other peopleThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Values Used for Constants and Parameters•Insufficient data on actual panic situations to analyze the algorithm quantitatively•Values chosen to match flows of people through an opening under non-panic conditionsThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Simulation of CloggingThe UNIVERSITY of NORTH CAROLINA at CHAPEL HILL Simulation of Clogging•As desired speed increases beyond 1.5m s-1, it takes more time for people to leave•As desired speed increases, the outflow of people becomes irregular•Arch shaped clogging occurs around the doorwayThe UNIVERSITY of NORTH CAROLINA at