A paradigm for controlling virtual humans in urban environment simulations

Abstract

T his paper presents a new architecture for simulating virtual humans in complex urban environments. The approach is based on the integration of six modules. Four key modules are used in order to manage environmental data, simulate human crowds, control interactions between virtual humans and objects, and generate tasks based on a rule± based behavioral model. T he communication between these modules is made through a client/server system. Finally, all low± level virtual human actions are delegated to a single motion and behavioral control module. Our architecture combines various human and object simulation aspects, based on the coherent extraction and classi cation of information from a virtual city dat abase. T his architecture is discussed in this paper, together with a detailed case study example.For several years, the authors have been working on modeling and simula± tions of realistic virtual humans. A most important aspect of the work was to investigate virtual human behaviors (for instance, Becheiraz and Thal± mann (1996)) and Noser and Thalmann (1996) and body motion control (Boulic et al., 1997). However, less attention has been given toward the inte± gration of these techniques in larger applications, where interaction with the virtual environment is needed. This paper presents an architecture inte± grating diOE erent aspects of human and object simulations in an urban environment using information extracted from a virtual city database. All such issues are addressed within the scope of our current application± populating virtual environments with virtual humans who can interact with objects and can walk within speci ed environmental constraints. One key aspect is the management of numerous virtual humans with the crowd module.

Visualization of crowd synchronization on footbridges

“…As well as examining crowd behavior, pedestrian simulation is also important for urban planning (Farenc et al 2000;Schreckenber 2001). A complex pedestrian animation system, which incorporates perceptual, behavioral and cognitive control components, has been introduced recently as a combination of rule-based and cognitive models (Shao and Terzopoulos 2007).…”

Parallelized egocentric fields for autonomous navigation

“…They are often tackled as separate problems that need to be interfaced for a fully functional navigation system [10,42]. Approaches such as A* [16] and potential fields [61,45] are popular planning methods for pedestrian simulations.…”

Environmental Modeling for Autonomous Virtual Pedestrians

“…The field of computer graphics, in which virtual human animation has been an important research interest for decades [2,1,8], has contributed technologies fundamental to the computer-assisted visualization of planned architectural projects, including the automatic animation of pedestrians [3,7,9].…”