A framework for crowd simulation based on the JMonkey game engine

La simulación de multitudes juega un papel crucial cuando se trata del desarrollo de entornos inteligentes. La mayoría de los investigadores desarrollan simulaciones usando motores de juegos comerciales a través de los editores que éstos proporcionan. Esto di culta el poder realizar una experimentación profunda sobre simulaciones de multitudes, y fuerza que la línea de investigación deba atenerse al paradigma de desarrollo propuesto por la herramienta. El objetivo principal del trabajo desarrollado es la contribución de un simulador de multitudes basado en 3D, con una arquitectura modular y extensible, adecuada para la experimentación con simulaciones de multitudes. Este framework se centrará de forma especial en la navegación y la coordinación de multitudes sobre un modelo realista del entorno, capaz de reproducir situaciones del mundo real. El simulador incluye implementaciones de algoritmos conocidos para el movimiento de multitudes, integrando también implementaciones de terceros. El trabajo tiene en cuenta la necesidad de representaciones visualmente convincentes de la simulación más allá de las representaciones 2D, utilizadas regularmente en la literatura. Para ello, se contribuye con extensiones a herramientas de terceros que permiten importar texturas, animaciones y mallas que mejoran la calidad de la simulación. El desempeño de la simulación se demuestra en un caso de estudio donde el desafío es encontrar una población cuyo comportamiento, dentro del simulador, reproduce un determinado tráfico entrante / saliente medido en áreas específicas de un edificio. Este trabajo ha sido financiado por el proyecto MOSI-AGIL (S2013 / ICE-3019) a través de la Gobierno de la Comunidad de Madrid y Fondos Estructurales Europeos (FEDER)

Requirement Engineering Activities in Smart Environments for Large Facilities

Developing a large, but smart environment is a complex task that requires the collaboration of experts of different disciplines. How to successfully attain such collaboration is not a trivial matter. The paper illustrates the problem with a case study where the manager of the facility intends to influence pedestrians so that they choose a task that requires certain effort, e.g. using staircases, instead of the current one that requires less effort, e.g. using the elevator. Defining requirements for such scenarios requires a strong multidisciplinary collaboration which is not currently well supported. This paper contributes with an approach to provide non-technician experts with tools so that they can provide feedback on the requirements and verify them in a systematic way

MASSIS: Multi-agent system simulation of indoor scenarios

Testing applications for smart environments is a difficult task. It requires the installation of sensors and actuators, the communications and the software for the control system, and the participation of people playing different scenarios. This is costly, both in economic sense as well as in time. Also, there are some situations that cannot be tested for practical reasons (such as emergencies). The use of simulation tools that provide some support for the development of smart environment applications is interesting, at least for these reasons. One of the most relevant aspects to be considered in this kind of tests is the human and social behavior of individuals when simulating how people interact with their environment, including other individuals. If the simulation framework has to be used for different purposes and by other developers, it should have a clear agent model, with some support for the design at a higher level of abstraction that can be easily translated to an implementation. This is the main purpose of MASSIS (Multi-agent system simulation of InDoor Scenarios), an efficient framework for modeling and simulation of the decision-making process of agents in multiple situations in indoor scenarios domain. It extends the SweetHome3D environment with plugins for linking agent’s behavior in the simulation. Other functionality provided by MASSIS is the ability to visualize the simulation in 2D and 3D, and a rich log capability, which can be the basis for further analysis of the scenarios