Stephen J. Guy
ABSTRACT
We present a new technique to generate heterogeneous crowd behaviors using personality trait theory. Our formulation is based on adopting results of a user study to derive a mapping from crowd simulation parameters to the perceived behaviors of agents in computer-generated crowd simulations. We also derive a linear mapping between simulation parameters and personality descriptors corresponding to the well-established Eysenck Three-factor personality model. Furthermore, we propose a novel two-dimensional factorization of perceived personality in crowds based on a statistical analysis of the user study results. Finally, we demonstrate that our mappings and factorizations can be used to generate heterogeneous crowd behaviors in different settings.
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Index Terms
- Simulating heterogeneous crowd behaviors using personality trait theory
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Reviews
George Popescu
In crowd settings, the types of behaviors that people exert depend strongly on their personalities. This study models the personalities of different agents in crowd simulations, based on Eysenck's three-factor personality framework. The authors propose an efficient approach to understanding crowd behavior based on agent behavioral traits, including aggressive, shy, tense, assertive, active, and impulsive. They consider trait theory, and, more specifically, the Eysenck model, as the core framework, including three major factors: psychoticism, extraversion, and neuroticism (PEN). The research links crowd simulation parameters to perceived personality within a mapping. The simulation results presented in the images show differences between aggressive and shy agents when exiting a narrow passage, for example. Most notably, the rate at which a user's responses matched the intended personality trait (PEN) success rate is close to 1, indicating high statistical significance. The paper offers a novel solution to the problem of simulating heterogeneous crowd behaviors using perceived personality traits. Online Computing Reviews Service
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