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International audience; Navigation in virtual environments relies on an accurate spatial rendering. A virtual object is localized according to its position in the environment, which is usually defined by the following three coordinates: azimuth, elevation and distance. Even though several studies investigated the perception of auditory and visual cues in azimuth and elevation, little has been made on the distance dimension. This study aims at investigating the way humans estimate visual and auditory egocentric distances of virtual objects. Subjects were asked to estimate the egocentric distance of 2–20 m distant objects in three contexts: auditory perception alone, visual one alone, combination of both perceptions (with coherent and incoherent visual and auditory cues). Even though egocentric distance was under-estimated in all contexts, the results showed a higher influence of visual information than auditory information on the perceived distance. Specifically, the bimodal incoherent condition gave perceived distances equivalent to those in the visual-only condition only when the visual target was closer to the subject than the auditory target.

International audience; L'objectif de cette étude était de vérifier comment se déroule l'apprentissage d'une procédure en environnement virtuel d'apprentissage d'opérations de maintenance de chars : GVT (Generic Virtual Training). Des mesures comportementales (temps de réalisation de la tâche, nombre et durée de consultation des instructions, nombre d'actions incorrectes) et des mesures subjectives de la charge de travail (réalisées avec NASATLX) ont été recueillies chez 15 individus lors de l'exécution d'une procédure. Celle-ci faisait l'objet de 10 répétitions successives par les participants puis 3 nouvelles répétitions après quatre jours d'intervalle. En accord avec les théories proposées par Fitts (1964) et Anderson (1983, 1995), les résultats montrent que l'apprentissage de la procédure s'effectue selon 3 phases (cognitive, associative et autonome). Au plan factuel, l'évolution des performances prend l'allure d'une courbe d'apprentissage et s'accompagne d'une diminution de différents facteurs constitutifs de la charge de travail. Les performances observées lors de la réalisation de la procédure après délai attestent de son stockage en mémoire à long terme.

Many Virtual Reality (VR) applications, such as Virtual Learning Environments or Interactive Virtual Tours, are based on a rich semantic description of the environment and tasks that users have to perform. These applications are built upon Virtual Environments (VEs) in which artificial agents act autonomously while interacting in realtime with users. Semantic modelling of a VR environment makes it possible the knowledge-driven access from the description of VEs that simplifies the development of VR applications. It eases the development of these types of applications. Semantic modelling should provide a consistent representation of the following aspects: 1) The simulated world, its structure and the behavior of its entities, 2) Interactions and tasks, that users and agents can perform in the environment, 3) Knowledge items, that autonomous agents can use for decision-making or for communication with users. This paper presents MASCARET, a model-based approach, for the design of semantic VR environments. This approach is based on the Unified Modeling Language (UML). In this approach, UML is used to provide a knowledge-driven access to the semantic contents of the VE and not for code generation, as in classical software development process. Interests of a UML-based approach are that its metamodel covers different views of the semantic modelling: ontology, structure, behaviors, interactions, activities. It is also an extensible language that can be specialized to provide formal operational semantics. We also present how MASCARET can be used to develop content-rich interactive applications that can be deployed over various VR platforms. Finally, we discuss the benefits of such a metamodel-based approach and show how the multi-layer semantic model can be used in different VR applications, in which adaptive behaviors of artificial agents acting within complex environments have to be simulated.

Behavioural animation techniques provide autonomous characters with the ability to react credibly in interactive simulations. The direction of these autonomous agents is inherently complex. Typically, simulations evolve according to reactive and cognitive behaviours of autonomous agents. The free flow of actions makes it difficult to precisely control the happening of desired events. In this paper, we propose a scenario language designed to support direction of semi-autonomous characters. This language offers temporal management and character communication tools. It also allows parallelism between scenarios, and a form of competition for the reservation of characters.

Behavioural models offer the ability to simulate autonomous agents like organisms and living beings. Psychological studies have shown that human behaviour can be described by a perception–decision–action loop, in which the decisional process should integrate several programming paradigms such as real time, concurrency and hierarchy. Building such systems for interactive simulation requires the design of a reactive system treating flows of data to and from the environment, and involving task control and preemption. Since a complete mental model based on vision and image processing cannot be constructed in real time using purely geometrical information, higher levels of information are needed in a model of the virtual environment. For example, the autonomous actors of a virtual world would exploit the knowledge of the environment topology to navigate through it. Accordingly, in this paper we present our programming environment for real-time behavioural animation which is compounded of a general animation and simulation platform, a behavioural modelling language and a scenario-authoring tool. Those tools has been used for different applications such as pedestrian and car driver interaction in urban environments, or a virtual museum populated by a group of visitors. Copyright © 2002 John Wiley & Sons, Ltd.

By scenario programs, we mean the code that determines what objects are in the simulation environment at each step and how object behaviours are coordinated to produce predictable experiences for the user in the loop. The code that controls a simulation scenario can be treated as the behaviour of a disembodied object. In the past, we have proposed HPTS as an efficient model to represent the decisional part of the behavioural model. Accordingly, in this paper we present the objective of our scenario authoring tool and we address the adequateness of an extended version of HPTS for the representation of scenario.