11 research outputs found
Crowd evacuation navigation for evasive maneuver of brownian based dynamic obstacles using reciprocal velocity obstacles
This paper presents an approach for evasive maneuver against dynamic obstacles in multi-agent navigation in a crowd evacuation scenario. Our proposed approach is based on reciprocal velocity obstacles (RVO) with a different manner to treat the obstacles. We treat all possible hindrances in velocity space reciprocally thus all collision cones generated by other agents and obstacles are treated in the same RVO manner with the key difference in the effort of avoidance. Our approach assumes that dynamic obstacles bear no awareness of navigation space unlike agents thus the avoidance effort lies on behalf of the mobile agents, creating unmutual effort in an evasive maneuver. We display our approach in an evacuation scenario where a crowd of agents must navigate through an evacuation area trespassing zone filled with dynamic obstacles. These dynamic obstacles consist of random motion built based on Brownian motion thus posses an immense challenge for the mobile agent in order to overcome this hindrance and safely navigate to their evacuation area. Our experimentation shows that 51.1% fewer collisions occurred which is denote safer navigation for agents in approaching their evacuation point
Modeling Family Behaviors in Crowd Simulation
Modeling human behavior for a general situation is difficult, if not impossible. Crowd simulation represents one of the approaches most commonly used to model such behavior. It is mainly concerned with modeling the different human structures incorporated in a crowd. These structures could comprise individuals, groups, friends, and families. Various instances of these structures and their corresponding behaviors are modeled to predict crowd responses under certain circumstances and to subsequently improve event management, facility and emergency planning.
Most currently existing modeled behaviors are concerned with depicting individuals as autonomous agents or groups of agents in certain environments. This research focuses on providing structural and state-based behavioral models for the concept of a family incorporated in the crowd. The structural model defines parents, teenagers, children, and elderly as members of the family. It also draws on the associated interrelationships and the rules that govern them. The behavioral model of the family encompasses a number of behavioral models associated with the triggering of certain well-known activities that correspond to the family鈥檚 situation. For instance, in normal cases, a family member(s) may be hungry, bored, or tired, may need a restroom, etc. In an emergency case, a family may experience the loss of a family member(s), the need to assist in safe evacuation, etc. Activities that such cases trigger include splitting, joining, carrying children, looking for family member(s), or waiting for them. The proposed family model is implemented on top of the RVO2 library that is using agent-based approach in crowd simulation. Simulation case studies are developed to answer research questions related to various family evacuation approaches in emergency situations
Dise帽o de planes de evacuaci贸n ante emergencias considerando el comportamiento din谩mico de peatones basado en simulaci贸n microsc贸pica
Muchas personas mueren cada a帽o en situaciones de emergencia por la ausencia de planes de evacuaci贸n eficientes. No contar con un plan de acci贸n o contar con uno pero con errores en su dise帽o, implican mayores tiempos de evacuaci贸n que pueden poner en riesgo muchas vidas. Adem谩s, es com煤n que las personas no acaten las se帽ales de seguridad, ya que en condiciones de riesgo, estas reaccionan de manera imprevista a causa del p谩nico y la ansiedad por querer evacuar el lugar. Actualmente, los planes de evacuaci贸n indican una ruta de salida espec铆fica y no consideran la posibilidad de proponer rutas alternas en caso de bloqueos. Esta investigaci贸n tiene como objetivo el dise帽o de un plan de evacuaci贸n considerando aspectos del comportamiento de la persona y m煤ltiples estrategias de enrutamiento. Se escogi贸 el enfoque de modelaci贸n basado en agentes para representar el comportamiento heterog茅neo de las personas y la interacci贸n entre ellos mismos y el entorno. Este plan de evacuaci贸n din谩mico incorpora una se帽alizaci贸n especial para guiar a las personas a tomar rutas alternativas en situaciones de congesti贸n. El plan din谩mico tambi茅n incluye la creaci贸n de salidas de emergencia como modificaci贸n a la estructura del edificio.Maestr铆aMagister en Ingenier铆a Industria
A framework for crowd simulation based on the JMonkey game engine
La simulaci贸n de multitudes juega un papel crucial cuando se trata del desarrollo de entornos inteligentes. La mayor铆a de los investigadores desarrollan simulaciones usando motores de juegos comerciales a trav茅s de los editores que 茅stos proporcionan. Esto di culta el poder realizar una experimentaci贸n profunda sobre simulaciones de multitudes, y fuerza que la l铆nea de investigaci贸n deba atenerse al paradigma de desarrollo propuesto por la herramienta. El objetivo principal del trabajo desarrollado es la contribuci贸n de un simulador de multitudes basado en 3D, con una arquitectura modular y extensible, adecuada para la experimentaci贸n con simulaciones de multitudes. Este framework se centrar谩 de forma especial en la navegaci贸n y la coordinaci贸n 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 tambi茅n implementaciones de terceros.
El trabajo tiene en cuenta la necesidad de representaciones visualmente convincentes de la simulaci贸n m谩s all谩 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 simulaci贸n.
El desempe帽o de la simulaci贸n se demuestra en un caso de estudio donde el desaf铆o es encontrar una poblaci贸n cuyo comportamiento, dentro del simulador, reproduce un determinado tr谩fico entrante / saliente medido en 谩reas espec铆ficas de un edificio.
Este trabajo ha sido financiado por el proyecto MOSI-AGIL (S2013 / ICE-3019) a trav茅s de la Gobierno de la Comunidad de Madrid y Fondos Estructurales Europeos (FEDER)
Recommended from our members
Physical crowds and psychological crowds: applying self-categorization theory to computer simulation of collective behaviour
Computer models are used to simulate pedestrian behaviour for safety at mass events. Previous research has indicated differences between physical crowds of co-present individuals, and psychological crowds who mobilise collective behaviour through a shared social identity. This thesis aimed to examine the assumptions models use about crowds, conduct two studies of crowd movement to ascertain the behavioural signatures of psychological crowds, and implement these into a theoretically-driven model of crowd behaviour.
A systematic review of crowd modelling literature is presented which explores the assumptions about crowd behaviour being used in current models. This review demonstrates that models portray the crowd as either an identical mass with no inter-personal connections, unique individuals with no connections to others, or as small groups within a crowd. Thus, no models have incorporated the role of self-categorisation theory needed to simulate collective behaviour.
The empirical research in this thesis aimed to determine the behavioural effects of self-categorisation on pedestrian movement. Findings from a first study illustrate that, in comparison to a physical crowd, perception of shared social identities in the psychological crowd motivated participants to maintain close proximity with ingroup members through regulation of their speed and distance walked. A second study showed that collective self-organisation seemed to be increased by the presence of an outgroup, causing ingroup members to tighten formation to avoid splitting up.
Finally, a computer model is presented which implements the quantified behavioural effects of self-categorisation found in the behavioural studies. A self-categorisation parameter is introduced to simulate ingroup members self-organising to remain together. This is compared to a physical crowd simulation with group identities absent. The results demonstrate that the self-categorisation parameter provides more accurate simulation of psychological crowd behaviour. Thus, it is argued that models should implement self-categorisation into simulations of psychological crowds to increase safety at mass events
Approches organisationnelles pour la conception de syst猫mes multi-agents d茅di茅s 脿 la gestion des connaissances; Application aux projets d'ing茅nierie et d'innovation Composition du jury
Approches organisationnelles pour la conception de syst猫mes multi-agents d茅di茅s 脿 la gestion des connaissances; Application aux projets d鈥檌ng茅nierie et d鈥檌nnovatio