Stéphane Donikian

Crowd of Virtual Humans: a New Approach for Real Time Navigation in Complex and Structured Environments

The navigation activity is an every day practice for any human being capable of locomotion. Our objective in this work is to reproduce this crucial human activity inside virtual environments. Putting together the high complexity of a realistic environment such as a city, a big amount of virtual humans and the real‐time constraint requires to optimize each aspect of the animation process. In this paper, we present a suitable topological structuring of the geometric environment to allow fast path finding as well as an efficient reactive navigation algorithm for virtual humans evolving inside a crowd.

Pedestrian Reactive Navigation for Crowd Simulation: a Predictive Approach

This paper addresses the problem of virtual pedestrian autonomous navigation for crowd simulation. It describes a method for solving interactions between pedestrians and avoiding inter‐collisions. Our approach is agent‐based and predictive: each agent perceives surrounding agents and extrapolates their trajectory in order to react to potential collisions. We aim at obtaining realistic results, thus the proposed model is calibrated from experimental motion capture data. Our method is shown to be valid and solves major drawbacks compared to previous approaches such as oscillations due to a lack of anticipation. We first describe the mathematical representation used in our model, we then detail its implementation, and finally, its calibration and validation from real data.

Experiment-based modeling, simulation and validation of interactions between virtual walkers

An interaction occurs between two humans when they walk with converging trajectories. They need to adapt their motion in order to avoid and cross one another at respectful distance. This paper presents a model for solving interactions between virtual humans. The proposed model is elaborated from experimental interactions data. We first focus our study on the pair-interaction case. In a second stage, we extend our approach to the multiple interactions case. Our experimental data allow us to state the conditions for interactions to occur between walkers, as well as each ones role during interaction and the strategies walkers set to adapt their motion. The low number of parameters of the proposed model enables its automatic calibration from available experimental data. We validate our approach by comparing simulated trajectories with real ones. We also provide comparison with previous solutions. We finally discuss the ability of our model to be extended to complex situations.

Realistic following behaviors for crowd simulation

While walking through a crowd, a pedestrian experiences a large number of interactions with his neighbors. The nature of these interactions is varied, and it has been observed that macroscopic phenomena emerge from the combination of these local interactions. Crowd models have hitherto considered collision avoidance as the unique type of interactions between individuals, few have considered walking in groups. By contrast, our paper focuses on interactions due to the following behaviors of pedestrians. Following is frequently observed when people walk in corridors or when they queue. Typical macroscopic stop‐and‐go waves emerge under such traffic conditions. Our contributions are, first, an experimental study on following behaviors, second, a numerical model for simulating such interactions, and third, its calibration, evaluation and applications. Through an experimental approach, we elaborate and calibrate a model from microscopic analysis of real kinematics data collected during experiments. We carefully evaluate our model both at the microscopic and the macroscopic levels. We also demonstrate our approach on applications where following interactions are prominent.

MODELLING VIRTUAL CITIES DEDICATED TO BEHAVIOURAL ANIMATION

In order to populate virtual cities, it is necessary to specify the behaviour of dynamic entities such as pedestrians or car drivers. 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. In this article, we present a model of virtual urban environments using structures and information suitable for behavioural animations. Thanks to this knowledge, autonomous virtual actors can behave like pedestrians or car drivers in a complex city environment. A city modeler has been designed, using this model of urban environment, and enables complex urban environments for behavioural animation to be automatically produced.

Activity-Driven Populace: A Cognitive Approach to Crowd Simulation

Simulating a natural-looking virtual populace requires modeling different behavioral levels to mimic how people choose and organize their activities. A multilayer behavior model for crowd simulation can help developers endow each entity with high-level objectives built on top of a reactive and cognitive decision system.

Environmental abstraction and path planning techniques for realistic crowd simulation

This paper treats two linked subjects underlying behavioural simulation. First, the way to describe a virtual environment through an informed hierarchical abstract graph. This graph stores some pre‐computations such as potential visibility sets, oriented grids, or densities of people, which can be used individually by simulated entities. Second, the way to use this abstract graph to perform a realistic and efficient path planning, which takes care of individual preferences as well as individual knowledge of the environment. Moreover, the path planning method we propose is reactive to some events, reflecting the perceived modifications of the environment, which allows the entity to adapt its behaviour in consequence. Copyright

Virtual humans animation in informed urban environments

In order to populate virtual cities, it is necessary to specify the behaviour of dynamic entities such as pedestrians or car drivers. Since it is not possible to construct in real time a complete mental model only from vision and image processing, we have to add higher levels of information than the geometrical one in the model of the virtual environment. In this article, a pedestrian behavioural model which exploits the information produced by VUEMS, our city modeller, is presented.

The IRIS Network of Excellence: Integrating Research in Interactive Storytelling

Interactive Storytelling is a major endeavour to develop new media which could offer a radically new user experience, with a potential to revolutionise digital entertainment. European research in Interactive Storytelling has played a leading role in the development of the field, and this creates a unique opportunity to strengthen its position even further by structuring collaboration between some of its main actors. IRIS (Integrating Research in Interactive Storytelling) aims at creating a virtual centre of excellence that will be able to progress the understanding of fundamental aspects of Interactive Storytelling and the development of corresponding technologies.

GASP: from modular programming to distributed execution

We present a generic animation and simulation platform which integrates the different animation models: descriptive, generative and behavioural models. The integration of these models in the same platform offers to each dynamic entity a more realistic and a richer environment, and thereby increases possible interactions between an actor and its environment. Therefore we describe the kernel of the platform, then we explain how it is used from the programmers point of view and we illustrate its use in the field of driving simulation.