Continuum crowds

Treuille, Adrien; Cooper, S. I.; Popović, Zoran V.

doi:10.1145/1179352.1142008

Cited by 278 publications

(230 citation statements)

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“…Reynolds's seminal Boids model [Rey87] is representative of microscopic approaches: local interactions, which match an individual's speed and orientation to its neighbors', determine the individual's motion and result in large scale emergent behaviors that are visible at the crowd level. Reynolds [Rey99] This is only a representative sample, for there are many more algorithms than those listed here, for instance algorithms that operate at the macroscopic level such as [TCP06]. One major problem is developing metrics to compare these dissimilar models; they are based on very different principles, and are qualitatively different as a result.…”

Section: Related Workmentioning

confidence: 99%

Parameter estimation and comparative evaluation of crowd simulations

Wolinski

Guy

Olivier

et al. 2014

Computer Graphics Forum

139

113

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Figure 1: Parameter Optimization Applied to Crowd Data (a) motion capture session for recording reference trajectories for six human agents (b) reference data plot (circles are initial positions) (c) paths taken by simulated agents with default parameters (d) paths taken by simulated agents with optimized parameters. The stock parameters of a simulation model often do not match closely with actual paths humans take in the same situation. Using our parameter optimization technique, the resulting simulation can be made to better match the human trajectories. AbstractWe present a novel framework to evaluate multi-agent crowd simulation algorithms based on real-world observations of crowd movements. A key aspect of our approach is to enable fair comparisons by automatically estimating the parameters that enable the simulation algorithms to best fit the given data. We formulate parameter estimation as an optimization problem, and propose a general framework to solve the combinatorial optimization problem for all parameterized crowd simulation algorithms. Our framework supports a variety of metrics to compare reference data and simulation outputs. The reference data may correspond to recorded trajectories, macroscopic parameters, or artist-driven sketches. We demonstrate the benefits of our framework for example-based simulation, modeling of cultural variations, artist-driven crowd animation, and relative comparison of some widely-used multi-agent simulation algorithms.

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Section: Related Workmentioning

confidence: 99%

Parameter estimation and comparative evaluation of crowd simulations

Wolinski

Guy

Olivier

et al. 2014

Computer Graphics Forum

139

113

View full text Add to dashboard Cite

show abstract

“…A popular approach based on continuum dynamics, continuum crowds, is proposed by Treuille et al 17 Their method evaluates a potential field over the simulation grid at each frame to direct the agents. Maïm et al 18 further extend continuum crowds by integrating a navigation graph composed of circular search nodes for global path planning.…”

Section: Background and Related Workmentioning

confidence: 99%

Adaptive grids: an image-based approach to generate navigation meshes

Akaydın

Güdükbay

2013

Opt. Eng.

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Abstract. We propose adaptive grids, an image-based approach for constructing navigation meshes, which are used for path planning. A cellular navigation mesh, called an adaptive grid, is constructed from a top-view range image of a three-dimensional urban model. A navigation graph can then be extracted from this adaptive grid for path planning. We compare our approach with two popular navigation mesh-generation approaches and obtain promising results in terms of path accuracy and memory cost.

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“…One common method to the simulation of mass flow is to model pedestrian in a particlelike manner [6], [7]. To the degree that humans are physical entities, and behave like particles, e.g., forming vortices as they move through an aperture [8], these flow-based models have been able to account for certain crowd characteristics. However, humans are more than particles, and physicsonly flow models are incapable for accounting for human volitional behavior such as individual interest, social activity maintenance, and individual and group preferences.…”

Section: A Crowd Dynamics Simulation Modelsmentioning

confidence: 99%

Modeling Agent Social Joint Actions via Micro and Macro Coordination Strategies

Park

Quek

Cao

2012

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology

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Abstract-This paper presents a multi-agent model for large crowd simulations that addresses the need for socially plausible coordination behavior. A computational model for multi-agent coordination informed by well-established common ground theory is proposed. We introduce the idea of macro-and microcoordination strategies that allow agent-based simulations to adapt to different domains. Our agent model allows the selection of appropriate behaviors based on the spatiotemporal conditions of the agent-group's environment. By showing that different micro-coordination strategies of individual groups has an influence on the overall distribution of a crowd, we demonstrate the importance of incorporating such models into multi-agent simulations of large crowd behaviors.

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Continuum crowds

Cited by 278 publications

References 0 publications

Parameter estimation and comparative evaluation of crowd simulations

Parameter estimation and comparative evaluation of crowd simulations

Adaptive grids: an image-based approach to generate navigation meshes

Modeling Agent Social Joint Actions via Micro and Macro Coordination Strategies

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