The crowd simulation for interactive virtual environments

Virtual Reality Software and Technology, 1998

This paper presents a crowd modelling method in Collaborative Virtual Environment (CVE) which aims to create a sense of group presence to provide a more realistic virtual world An adaptive display is also presented as a key element to optimise the needed information to keep an acceptable frame rate during crowd visualisation This system has been integrated in the

2013

Crowd is an emergent phenomenon raised by the local interactions of a large number of individuals. Managing these interactions implies both low level mechanisms such as navigation and path planning in virtual environments, and high level behaviors qualified as social behaviors. Most existing simulation models deal with the navigation process, leading to the emergence of macroscopically identifiable groups. However, these models do not provide means to individuals to reason about groups, and so to take into account groups in social behaviors. In this paper, we propose a novel behavioral approach to simulate high-level decision mechanisms based on social characteristics. These mechanisms enable the support of social agents evolving in informed virtual geospatial environments. We show that this agent-based model allows taking into account different psychological and sociological theories in order to provide realistic and sophisticated groups management. Finally, we show the interest of...

Simulation of crowd behaviors is a widely discussed topic for over a decade for computer games, architecture and entertainment. The most important thing is that agents should execute the human like behaviors in real life scenarios. This situation becomes very complex with dense crowds. Our proposed Realistic Behavior Agent Simulation (RBAS) model simulates the agents from the knowledge of empirical findings of crowd physical behaviors and crowd psychology. This paper presents a novel technique to design the agents to with following modules 1) Path planning behavior for collision avoidance 2) Situation awareness during herding behavior and turbulent flow in high density crowds. 3) Personal Reaction bubble (PRB) based response and perceptions. The evaluation with real life situations is performed to validate the RBAS model. The RBAS model allows the agents to use cognitive understandings to plan ahead their path using the visual perception information. This model encapsulates the emergent crowd behaviors such as self-organization behavior in herding situation. During turbulent high density flows, most of the existing models fail to predict the behavior of agents, the evaluations show the RBAS model mimics the same behavior of the crowd in different situations.

Journal of Network and Computer Applications, 2009

Crowd simulation requires both rendering visually plausible images and managing the behavior of autonomous agents. Therefore, these applications need an efficient design that allows them to simultaneously handle these two requirements. Although several proposals have focused on the software architectures for these systems, no proposals have focused on the computer systems supporting them.

Synthesis Lectures on Computer Graphics and Animation, 2008

There are many applications of computer animation and simulation where it is necessary to model virtual crowds of autonomous agents. Some of these applications include site planning, education, entertainment, training, and human factors analysis for building evacuation. Other applications include simulations of scenarios where masses of people gather, flow, and disperse, such as transportation centers, sporting events, and concerts. Most crowd simulations include only basic locomotive behaviors possibly coupled with a few stochastic actions. Our goal in this survey is to establish a baseline of techniques and requirements for simulating large-scale virtual human populations. Sometimes, these populations might be mutually engaged in a common activity such as evacuation from a building or area; other times they may be going about their individual and personal agenda of work, play, leisure, travel, or spectator. Computational methods to model one set of requirements may not mesh well with good approaches to another. By including both crowd and individual goals and constraints into a comprehensive computational model, we expect to simulate the visual texture and contextual behaviors of groups of seemingly sentient beings.

Lecture Notes in Electrical Engineering, 2010

Crowds must be simulated believable in terms of their appearance and behavior to improve a virtual environment's realism. Due to the complex nature of human behavior, realistic behavior of agents in crowd simulations is still a challenging problem. In this paper, we propose a novel behavioral model which builds analytical maps to control agents' behavior adaptively with agent-crowd interaction formulations. We introduce information theoretical concepts to construct analytical maps automatically. Our model can be integrated into crowd simulators and enhance their behavioral complexity. We made comparative analyses of the presented behavior model with measured crowd data and two agent-based crowd simulators.

Crowd simulation can be considered as a special case of Virtual Environments where avatars are intelligent agents instead of user-driven entities. These applications require both rendering visually plausible images of the virtual world and managing the behavior of autonomous agents. The sum of these two requirements results in a computational cost that exponentially increases with the number of agents in the system. Thus, crowd simulation requires a scalable design that can handle large simulations in a feasible way. In this paper, we propose a system design that can manage the simulation of large crowds of autonomous agents at interactive rates.