Macroscopic modeling and simulations of room evacuation

We analyze numerically two macroscopic models of crowd dynamics: the classical Hughes model and the second order model being an extension to pedestrian motion of the Payne-Whitham vehicular traffic model. The desired direction of motion is determined by solving an eikonal equation with density dependent running cost, which results in minimization of the travel time and avoidance of congested areas. We apply a mixed finite volume-finite element method to solve the problems and present error analysis for the eikonal solver, gradient computation and the second order model yielding a first order convergence. We show that Hughes' model is incapable of reproducing complex crowd dynamics such as stop-and-go waves and clogging at bottlenecks. Finally, using the second order model, we study numerically the evacuation of pedestrians from a room through a narrow exit.Comment: 22 page

Emergency Evacuation Software Model For Simulation Of Physical Changes

Public space such as schools, cinemas, shopping malls, etc. must have an emergency evacuation system in place. Such places are also required to follow certain regulations and protocols for emergency evacuation to assure the safety of their occupants inside from any unpredictable incident. For nearly two decades, companies/organizations are using simulation models/software for evacuation planning. Researchers are working on these software models to improve the efficiency using latest algorithms. This thesis focuses on creating a base software model of evacuation systems for 3D indoor environments to simulate physical changes such as retractable chairs, movable walls etc., to evaluate their effectiveness before committing to those changes. This research tries to address various flaws and shortcomings of previous software. We are using tools like Unity 3D and Autodesk Maya to simulate suggested changes. It provides planners as well as researchers a new perspective to work on new recommended physical changes to design public venues

Vadere: An Open-Source Simulation Framework to Promote Interdisciplinary Understanding

Pedestrian dynamics is an interdisciplinary field of research. Psychologists, sociologists, traffic engineers, physicists, mathematicians and computer scientists all strive to understand the dynamics of a moving crowd. In principle, computer simulations offer means to further this understanding. Yet, unlike for many classic dynamical systems in physics, there is no universally accepted locomotion model for crowd dynamics. On the contrary, a multitude of approaches, with very different characteristics, compete. Often only the experts in one special model type are able to assess the consequences these characteristics have on a simulation study. Therefore, scientists from all disciplines who wish to use simulations to analyze pedestrian dynamics need a tool to compare competing approaches. Developers, too, would profit from an easy way to get insight into an alternative modeling ansatz. Vadere meets this interdisciplinary demand by offering an open-source simulation framework that is lightweight in its approach and in its user interface while offering pre-implemented versions of the most widely spread models

Agent-based Crowd Simulation Modelling for a Gaming Environment

Crowd simulation study has become a favorite subject in the computer graphics community in the past three decades. It usually is a sub-function within many applications such as video games, films, and public security. This thesis proposes an independent crowd simulation model that is capable of running an Agent-based method through a gaming environment. It can simulate realistic human crowds with user-controllable features to provide a gaming-like experience. Our approach features an enhanced rendering system based on Distinguishable Agents Generating Method (DAGM). This method can generate distinguishable and scalable 3D human models in real-time. We also introduce our Multi-layer Collision System (MCS), which features a collision-message collection system and an evaluation processing system. We also introduce Building & City-planning Generating System (BCGS) for the purpose of setting up obstacles for the crowd during an evacuation simulation. Moreover, in this thesis, we also extend the study to other aspects such as crisis training and human animations to provide a complete agent-based crowd simulation model

Heuristic search methods and cellular automata modelling for layout design

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Spatial layout design must consider not only ease of movement for pedestrians under normal conditions, but also their safety in panic situations, such as an emergency evacuation in a theatre, stadium or hospital. Using pedestrian simulation statistics, the movement of crowds can be used to study the consequences of different spatial layouts. Previous works either create an optimal spatial arrangement or an optimal pedestrian circulation. They do not automatically optimise both problems simultaneously. Thus, the idea behind the research in this thesis is to achieve a vital architectural design goal by automatically producing an optimal spatial layout that will enable smooth pedestrian flow. The automated process developed here allows the rapid identification of layouts for large, complex, spatial layout problems. This is achieved by using Cellular Automata (CA) to model pedestrian simulation so that pedestrian flow can be explored at a microscopic level and designing a fitness function for heuristic search that maximises these pedestrian flow statistics in the CA simulation. An analysis of pedestrian flow statistics generated from feasible novel design solutions generated using the heuristic search techniques (hill climbing, simulated annealing and genetic algorithm style operators) is conducted. The statistics that are obtained from the pedestrian simulation is used to measure and analyse pedestrian flow behaviour. The analysis from the statistical results also provides the indication of the quality of the spatial layout design generated. The technique has shown promising results in finding acceptable solutions to this problem when incorporated with the pedestrian simulator when demonstrated on simulated and real-world layouts with real pedestrian data.This study was funded by the University Science of Malaysia and Kementerian Pengajian Tinggi Malaysia

Pedestrian flow characteristics through different angled bends: Exploring the spatial variation of velocity

Common geometrical layouts could potentially be bottlenecks, particularly during emergency and high density situations. When pedestrians are interacting with such complex geometrical settings, the congestion effect might not be uniform over the bottleneck area. This study uses the trajectory data collected through a controlled laboratory experiment to explore the spatial variation of speeds when a group of people navigates through bends. Four turning angles, i.e., 45°, 90°, 135° and 180°, with a straight corridor and two speed levels, i.e., normal speed walking and slow running (jogging), were considered in these experiments. Results explained that the speeds are significantly different over the space within the bend for all angles (except 0°) under both speed levels. In particular, average walking speeds are significantly lower near the inner corner of the bend as compared to the outer corner. Further, such speed variations are magnified when the angle of the bend and desired speed increase. These outcomes indicate that even smaller turning angles, e.g., 45° could create bottlenecks near the inner corner of the bend, particularly when the walking speeds are high. The findings of this study could be useful in understanding the congestion and bottleneck effects associated with complex geometrical settings, and calibrating microscopic simulation tools to accurately reproduce such effects.Open access funding was provided by the Qatar National Library

Integration of micro- and macroscopic models for pedestrian evacuation simulation

Simulation of pedestrian evacuations of smart buildings in emergency is a powerful tool for building analysis, dynamic evacuation planning and real-time response to the evolving state of evacuations. Macroscopic pedestrian models are low-complexity models that are and well suited to algorithmic analysis and planning, but are quite abstract. Microscopic simulation models allow for a high level of simulation detail but can be computationally intensive. By combining micro- and macro- models we can use each to overcome the shortcomings of the other and enable new capability and applications for pedestrian evacuation simulation that would not be possible with either alone. We develop the EvacSim multi-agent pedestrian simulator and procedurally generate macroscopic flow graph models of building space, integrating micro- and macroscopic approaches to simulation of the same emergency space. By “coupling” flow graph parameters to microscopic simulation results, the graph model captures some of the higher detail and fidelity of the complex microscopic simulation model. The coupled flow graph is used for analysis and prediction of the movement of pedestrians in the microscopic simulation, and investigate the performance of dynamic evacuation planning in simulated emergencies using a variety of strategies for allocation of macroscopic evacuation routes to microscopic pedestrian agents. The predictive capability of the coupled flow graph is exploited for the decomposition of microscopic simulation space into multiple future states in a scalable manner. By simulating multiple future states of the emergency in short time frames, this enables sensing strategy based on simulation scenario pattern matching which we show to achieve fast scenario matching, enabling rich, real-time feedback in emergencies in buildings with meagre sensing capabilities

Crowd simulation and visualization

Large-scale simulation and visualization are essential topics in areas as different as sociology, physics, urbanism, training, entertainment among others. This kind of systems requires a vast computational power and memory resources commonly available in High Performance Computing HPC platforms. Currently, the most potent clusters have heterogeneous architectures with hundreds of thousands and even millions of cores. The industry trends inferred that exascale clusters would have thousands of millions. The technical challenges for simulation and visualization process in the exascale era are intertwined with difficulties in other areas of research, including storage, communication, programming models and hardware. For this reason, it is necessary prototyping, testing, and deployment a variety of approaches to address the technical challenges identified and evaluate the advantages and disadvantages of each proposed solution. The focus of this research is interactive large-scale crowd simulation and visualization. To exploit to the maximum the capacity of the current HPC infrastructure and be prepared to take advantage of the next generation. The project develops a new approach to scale crowd simulation and visualization on heterogeneous computing cluster using a task-based technique. Its main characteristic is hardware agnostic. It abstracts the difficulties that imply the use of heterogeneous architectures like memory management, scheduling, communications, and synchronization — facilitating development, maintenance, and scalability. With the goal of flexibility and take advantage of computing resources as best as possible, the project explores different configurations to connect the simulation with the visualization engine. This kind of system has an essential use in emergencies. Therefore, urban scenes were implemented as realistic as possible; in this way, users will be ready to face real events. Path planning for large-scale crowds is a challenge to solve, due to the inherent dynamism in the scenes and vast search space. A new path-finding algorithm was developed. It has a hierarchical approach which offers different advantages: it divides the search space reducing the problem complexity, it can obtain a partial path instead of wait for the complete one, which allows a character to start moving and compute the rest asynchronously. It can reprocess only a part if necessary with different levels of abstraction. A case study is presented for a crowd simulation in urban scenarios. Geolocated data are used, they were produced by mobile devices to predict individual and crowd behavior and detect abnormal situations in the presence of specific events. It was also address the challenge of combining all these individual’s location with a 3D rendering of the urban environment. The data processing and simulation approach are computationally expensive and time-critical, it relies thus on a hybrid Cloud-HPC architecture to produce an efficient solution. Within the project, new models of behavior based on data analytics were developed. It was developed the infrastructure to be able to consult various data sources such as social networks, government agencies or transport companies such as Uber. Every time there is more geolocation data available and better computation resources which allow performing analysis of greater depth, this lays the foundations to improve the simulation models of current crowds. The use of simulations and their visualization allows to observe and organize the crowds in real time. The analysis before, during and after daily mass events can reduce the risks and associated logistics costs.La simulación y visualización a gran escala son temas esenciales en áreas tan diferentes como la sociología, la física, el urbanismo, la capacitación, el entretenimiento, entre otros. Este tipo de sistemas requiere una gran capacidad de cómputo y recursos de memoria comúnmente disponibles en las plataformas de computo de alto rendimiento. Actualmente, los equipos más potentes tienen arquitecturas heterogéneas con cientos de miles e incluso millones de núcleos. Las tendencias de la industria infieren que los equipos en la era exascale tendran miles de millones. Los desafíos técnicos en el proceso de simulación y visualización en la era exascale se entrelazan con dificultades en otras áreas de investigación, incluidos almacenamiento, comunicación, modelos de programación y hardware. Por esta razón, es necesario crear prototipos, probar y desplegar una variedad de enfoques para abordar los desafíos técnicos identificados y evaluar las ventajas y desventajas de cada solución propuesta. El foco de esta investigación es la visualización y simulación interactiva de multitudes a gran escala. Aprovechar al máximo la capacidad de la infraestructura actual y estar preparado para aprovechar la próxima generación. El proyecto desarrolla un nuevo enfoque para escalar la simulación y visualización de multitudes en un clúster de computo heterogéneo utilizando una técnica basada en tareas. Su principal característica es que es hardware agnóstico. Abstrae las dificultades que implican el uso de arquitecturas heterogéneas como la administración de memoria, las comunicaciones y la sincronización, lo que facilita el desarrollo, el mantenimiento y la escalabilidad. Con el objetivo de flexibilizar y aprovechar los recursos informáticos lo mejor posible, el proyecto explora diferentes configuraciones para conectar la simulación con el motor de visualización. Este tipo de sistemas tienen un uso esencial en emergencias. Por lo tanto, se implementaron escenas urbanas lo más realistas posible, de esta manera los usuarios estarán listos para enfrentar eventos reales. La planificación de caminos para multitudes a gran escala es un desafío a resolver, debido al dinamismo inherente en las escenas y el vasto espacio de búsqueda. Se desarrolló un nuevo algoritmo de búsqueda de caminos. Tiene un enfoque jerárquico que ofrece diferentes ventajas: divide el espacio de búsqueda reduciendo la complejidad del problema, puede obtener una ruta parcial en lugar de esperar a la completa, lo que permite que un personaje comience a moverse y calcule el resto de forma asíncrona, puede reprocesar solo una parte si es necesario con diferentes niveles de abstracción. Se presenta un caso de estudio para una simulación de multitud en escenarios urbanos. Se utilizan datos geolocalizados producidos por dispositivos móviles para predecir el comportamiento individual y público y detectar situaciones anormales en presencia de eventos específicos. También se aborda el desafío de combinar la ubicación de todos estos individuos con una representación 3D del entorno urbano. Dentro del proyecto, se desarrollaron nuevos modelos de comportamiento basados ¿¿en el análisis de datos. Se creo la infraestructura para poder consultar varias fuentes de datos como redes sociales, agencias gubernamentales o empresas de transporte como Uber. Cada vez hay más datos de geolocalización disponibles y mejores recursos de cómputo que permiten realizar un análisis de mayor profundidad, esto sienta las bases para mejorar los modelos de simulación de las multitudes actuales. El uso de simulaciones y su visualización permite observar y organizar las multitudes en tiempo real. El análisis antes, durante y después de eventos multitudinarios diarios puede reducir los riesgos y los costos logísticos asociadosPostprint (published version

Agora : unified framework for crowd simulation research

Crowd simulation focuses on modeling the movements and behaviors of large groups of people. This area of study has become increasingly important because of its several applications in various fields such as urban planning, safety, and entertainment. In each of these domains, the presence of virtual agents exhibiting realistic behavior greatly enhances the quality of the simulations. However, the inherently multifaceted and intricate nature of human behavior presents a unique challenge, necessitating the effective combination of multiple behavior models. This thesis introduces a novel theoretical framework for modeling human behavior in crowd simulations, addressing the unresolved issue of combining a plethora of behavior models, often developed in isolation. The proposed framework decomposes human behavior into fundamental driving stimuli, which are then represented graphically through the heatmap paradigm. Subsequently, the agent behavior is influenced by the heatmaps, which guide them toward attractive areas and steer them away from repulsive locations based on the encoded stimuli. A key advantage of this approach lies in the ability to combine heatmaps using well-defined color operations, effectively integrating different aspects of human behavior. Furthermore, the heatmap paradigm facilitates objective comparison of simulation output with real-world data, employing image similarity metrics to evaluate model accuracy. To realize this framework, the thesis presents a modular software architecture designed to support various tasks involved in crowd simulation, emphasizing the separation of concerns for each task. This architecture comprises a collection of abstract modules, which are subsequently implemented using appropriate software components to realize the underlying features, resulting in the Agora framework. To assess the ability of Agora to support the various tasks involved in crowd simulation, two case studies are implemented and analyzed. The first case study simulates tourists visiting Þingvellir national park in Iceland, examining how their behavior is influenced by the visibility of the surrounding environment. The second case study employs Agora to model the thermal and density comfort levels of virtual pedestrians in an urban setting. The results demonstrate that Agora successfully supports the development, combination, and evaluation of crowd simulation models against real-world data. The authoring process, assisted by Agora, is significantly more streamlined compared to its native counterpart. The integration of multiple models is achieved by combining the heatmaps, resulting in plausible behavior, and the model assessment is made convenient through the evaluator within the framework. The thesis concludes by discussing the implications of these findings for the field of crowd simulation, highlighting the contributions and potential future directions of the Agora framework.Mannfjöldahermun fæst við gerð líkana af hreyfingu og hegðun stórra hópa af fólki. Mikilvægi þessa rannsóknasviðs hefur vaxið stöðugt vegna hagnýtingar á margvíslegum vetvangi, eins og til dæmis á vetvangi borgarskipulags, öryggis og afþreyingar. Þegar sýndarmenni hegða sér á sannfærandi hátt, leiðir það til betri hermunar fyrir þessi notkunarsvið. En mannleg hegðun er í eðli sínu margbrotin og flókin og því er það sérstök áskorun við smíði sýndarmenna að sameina, með áhrifaríkum hætti, mörg mismunandi hegðunarlíkön. Þessi ritgerð kynnir nýja fræðilega umgjörð líkanasmíði mannlegrar hegðunar fyrir mannfjöldahermun, sem tekur á þeim óleysta vanda að sameina fjölda hegðunarlíkana, sem oft eru þróuð með aðskildum hætti. Umgjörðin brýtur mannlega hegðun niður í grundvallar drifáreiti, sem eru sett fram grafískt útfrá hugmyndafræði hitakorta. Sýndarmennin hegða sér síðan undir áhrifum frá hitakortunum, sem vísa þeim í áttina að aðlaðandi svæðum og stýra þeim burt frá fráhrindandi svæðum, útfrá hinu umritaða áreiti. Lykilkostur þessarar nálgunar er sá eiginleiki að geta blandað saman hitakortum með vel skilgreindum litaaðgerðum, sem eru þá í raun samþætting mismunandi hliða mannlegrar hegðunar. Hitakortshugmyndafræðin auðveldar ennfremur hlutlægan samanburð hermunarúttaks og raungagna með notkun myndsamanburðarmælinga, til að meta nákvæmni líkana. Varðandi útfærslu, þá kynnir þessi ritgerð einingadrifna hugbúnaðarhögun sem er hönnuð til að styðja við ýmsa ferla mannfjöldahermunar, með áherslu á aðskilnað helstu viðfangsefna hvers ferlis. Þessi högun inniheldur safn huglægra eininga, sem síðan eru útfærðar með viðeigandi hugbúnaðarhlutum, sem raungera undirliggjandi eiginleika. Útkoman er sjálf Agora umbjörðin. Tvö sýnidæmi eru útfærð og greind til að meta getu Agoru til að styðja við ýmis mannfjöldahermunarverkefni. Fyrra dæmið hermir eftir ferðamönnum sem heimsækja Þingvallaþjóðgarð, og skoðar hvernig hegðun þeirra verður fyrir áhrifum sýnileika umhverfisins sem umleikur þá. Seinna dæmið nýtir Agoru til að smíða líkan af hitauppstreymis- og þéttleikaþægindum hjá sýndarvegfarendum í borgarumhverfi. Niðurstöðurnar sýna góðan árangur Agoru við að styðja þróun, samþættingu og mat mannfjöldahermunarlíkana gagnvart raungögnum. Þróunarferlið er verulega þjálla með Agoru en með hefðbundnum aðferðum. Samþætting margra líkana tókst með blöndun hitakorta, möguleg hegðun var framkölluð og mat á líkönunum varð þægilegra með umgjörðinni. Ritgerðinni lýkur með því að fjalla um áhrif þessara niðurstaðna á svið mannfjöldahegðunar, með áherslu á nýstálegt framlag þessarar rannsóknar og mögulega framtíðarþróun Agora umgjarðarinnar