Analysis of crowd behavior through pattern virtualization

The study of the concentration of individuals in public places such as squares, shopping malls, parks, gardens, etc., is an open study field in the different disciplines of science, that leads to the need of having systems that allow to forecast and to predict eventualities in uncontrolled situations, as it is the case of an earthquake. From that assumption, artificial intelligence, as a branch of computational sciences, studies the human behavior in a virtual way in order to obtain simulations based on social, psychological, neuro-scientific areas, among others, with the purpose of linking these theories to the area of artificial intelligence. This paper presents a way to generate virtual multitudes with heterogeneous behaviors, in such a way that the individuals that form the multitude present different behaviors

Authoring Multi-Actor Behaviors in Crowds With Diverse Personalities

Multi-actor simulation is critical to cinematic content creation, disaster and security simulation, and interactive entertainment. A key challenge is providing an appropriate interface for authoring high-fidelity virtual actors with featurerich control mechanisms capable of complex interactions with the environment and other actors. In this chapter, we present work that addresses the problem of behavior authoring at three levels: Individual and group interactions are conducted in an event-centric manner using parameterized behavior trees, social crowd dynamics are captured using the OCEAN personality model, and a centralized automated planner is used to enforce global narrative constraints on the scale of the entire simulation. We demonstrate the benefits and limitations of each of these approaches and propose the need for a single unifying construct capable of authoring functional, purposeful, autonomous actors which conform to a global narrative in an interactive simulation

An Event-Centric Planning Approach for Dynamic Real-Time Narrative

In this paper, we propose an event-centric planning framework for directing interactive narratives in complex 3D environments populated by virtual humans. Events facilitate precise authorial control over complex interactions involving groups of actors and objects, while planning allows the simulation of causally consistent character actions that conform to an overarching global narrative. Events are defined by preconditions, postconditions, costs, and a centralized behavior structure that simultaneously manages multiple participating actors and objects. By planning in the space of events rather than in the space of individual character capabilities, we allow virtual actors to exhibit a rich repertoire of individual actions without causing combinatorial growth in the planning branching factor. Our system produces long, cohesive narratives at interactive rates, allowing a user to take part in a dynamic story that, despite intervention, conforms to an authored structure and accomplishes a predetermined goal

Generation of crowd arrival and destination locations/times in complex transit facilities

In order to simulate virtual agents in the replica of a real facility across a long time span, a crowd simulation engine needs a list of agent arrival and destination locations and times that reflect those seen in the actual facility. Working together with a major metropolitan transportation authority, we propose a specification that can be used to procedurally generate this information. This specification is both uniquely compact and expressive—compact enough to mirror the mental model of building managers and expressive enough to handle the wide variety of crowds seen in real urban environments. We also propose a procedural algorithm for generating tens of thousands of high-level agent paths from this specification. This algorithm allows our specification to be used with traditional crowd simulation obstacle avoidance algorithms while still maintaining the realism required for the complex, real-world simulations of a transit facility. Our evaluation with industry professionals shows that our approach is intuitive and provides controls at the right level of detail to be used in large facilities (200,000+ people/day)

SPREAD: Sound Propagation and Perception for Autonomous Agents in Dynamic Environments

The perception of sensory information and its impact on behavior is a fundamental component of being human. While visual perception is considered for navigation, collision, and behavior selection, the acoustic domain is relatively unexplored. Recent work in acoustics focuses on synthesizing sound in 3D environments; however, the perception of acoustic signals by a virtual agent is a useful and realistic adjunct to any behavior selection mechanism. In this paper, we present SPREAD, a novel agent-based sound perception model using a discretized sound packet representation with acoustic features including amplitude, frequency range, and duration. SPREAD simulates how sound packets are propagated, attenuated, and degraded as they traverse the virtual environment. Agents perceive and classify the sounds based on the locally-received packet set using a hierarchical clustering scheme, and have individualized hearing and understanding of their surroundings. Using this model, we demonstrate several simulations that greatly enrich controls and outcomes

Generacion de multitudes heterogeneas con comportamientos inteligentes en ambientes virtuales

La simulaci ́on de multitudes consiste en representar a grupos de personajes auto ́no- mos llamados agentes virtuales, con reglas y entornos que simulan a aquellos encontrados en la vida real. Entre los objetivos de las simulaciones virtuales tam- bi ́en se encuentra el generar algoritmos capaces de producir visualizaciones de manera fluida, esto es no tener retrasos en la visualizacio ́n de la simulacio ́n. Las simulaciones de multitudes son herramientas utilizadas por organizaciones, por ejemplo una constructora, para realizar pruebas virtuales a determinadas estruc- turas como lo puede ser un estadio de fu ́tbol, las multitudes utilizadas en este tipo de simulaciones carecen de comportamientos diferentes, es decir todos los individuos de la multitud se comportan de la misma manera aunque visualmente sean diferentes. La tesis presenta una propuesta para generar multitudes virtuales heterog ́eneas, de tal forma que los individuos que conforman la multitud exhiban distintos comportamientos, y no como se hace hasta el momento donde un mismo comportamiento que se aplica a todos los agentes. Se propone tambi ́en una t ́ecnica de agrupamiento en distintas regiones del a ́rea a poblar utilizando diagramas de Voronoi, posibilitando la caracterizaci ́on de zonas en donde existe una concentra- cio ́n selectiva dependiendo de los distintos roles que asumen los individuos de la multitud. Se introducen los LCP (Lugares de concentraci ́on de la poblacio ́n) que son los lugares donde distintos grupos de la poblacio ́n se agrupan, lo que genera un comportamiento de agrupacio ́n en las multitudes. Los resultados observados permiten distinguir distintos comportamientos debido a que se generan diferentes velocidades de desplazamiento, taman ̃os y pesos. La utilizacio ́n de los LCP emula un comportamiento de agrupaci ́on dependiendo del rol que cada agente virtual tenga, lo cual permite que se agrupe en distintas zonas del ambiente virtual

Real-Time Storytelling with Events in Virtual Worlds

We present an accessible interactive narrative tool for creating stories among a virtual populace inhabiting a fully-realized 3D virtual world. Our system supports two modalities: assisted authoring where a human storyteller designs stories using a storyboard-like interface called CANVAS, and exploratory authoring where a human author experiences a story as it happens in real-time and makes on-the-fly narrative trajectory changes using a tool called Storycraft. In both cases, our system analyzes the semantic content of the world and the narrative being composed, and provides automated assistance such as completing partially-specified stories with causally complete sequences of intermediate actions. At its core, our system revolves around events -â?? pre-authored multi-actor task sequences describing interactions between groups of actors and props. These events integrate complex animation and interaction tasks with precision control and expose them as atoms of narrative significance to the story direction systems. Events are an accessible tool and conceptual metaphor for assembling narrative arcs, providing a tightly-coupled solution to the problem of converting author intent to real-time animation synthesis. Our system allows simple and straightforward macro- and microscopic control over large numbers of virtual characters with diverse and sophisticated behavior capabilities, and reduces the complicated action space of an interactive narrative by providing analysis and user assistance in the form of semi-automation and recommendation services