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A half hour comedy pilot about a guy that crowd sources his life.

Ever since the first use of crowds in films and videogames there has been an interest in larger, more efficient and more realistic simulations of crowds. Most crowd simulation algorithms are able to satisfy the viewer from a distance but when inspected from close up the flaws in the individual agent's movements become noticeable. One of the bigger challenges faced in crowd simulation is finding a solution that models the actual movement of an individual in a crowd. This paper simulates a more realistic crowd by using individual motion capture data as well as traditional crowd control techniques to reach an agent's desired goal. By augmenting traditional crowd control algorithms with the use of motion capture data for individual agents, we can simulate crowds that mimic more realistic crowd motion, while maintaining real-time simulation speed.

Recently, a considerable amount of research has been performed on simulating the collective behavior of pedestrians in the street or people finding their way inside a building or a room. Comprehensive reviews of the state of the art can be found in Schreckenberg and Deo (2002) and Batty, M., DeSyllas, J. and Duxbury, E. (2003). In all these simulation studies, one area that is lacking is accounting for the effects of human personalities on the outcome. As a result, there is a growing emphasis on researching the effects of human personalities and adding the results to the simulations to make them more realistic. This research investigated the possibility of incorporating personality factors into the crowd simulation model. The first part of this study explored the extraction of quantitative crowd motion from videos and developed a method to compare real video with the simulation output video. Several open source programs were examined and modified to obtain optical flow measurements from real videos captured at sporting events. Optical flow measurements provide information such as crowd density, average velocity with which individuals move in the crowd, as well as other parameters. These quantifiable optical flow calculations provided a strong method for comparing simulation results with those obtained from video footage captured in real life situations. The second part of the research focused on the incorporation of the personality factors into the crowd simulation. Existing crowd models such as HelbingU-Molnar-Farkas-Vicsek (HMFV) do not take individual personality factors into account. The most common approach employed by psychologists for studying personality traits is the Big Five factors or dimensions of personality (NEO: Neuroticism, Extroversion, Openness, Agreeableness and Conscientiousness). In this research forces related to the personality factors were incorporated into the crowd simulation models. The NEO-based forces were incorporated into an existing HMFV simulated implemented in the MASON simulation framework. The simulation results were validated using the quantification procedures developed in the first phase. This research reports on a major expansion of a simulation of pedestrian motion based on the model (HMFV) by Helbing, D., I. J. Farkas, P. Molnár, and T. Vicsek (2002). Example of actual behavior such as a crowd exiting church after service were simulated using NEO-based forces and show a striking resemblance to actual behavior as rated by behavior scientists.

The aim of the research is to evaluate crowd violence as it pertains to sports and its spectators. In particular, the research examines sports riots. "A sports riot is defined as violence-vandalism, throwing/shooting missiles, rushing the field or court, committing arson, and/or fighting- committed by five or more individuals in a crowd of one hundred people associated with a formally organized sporting event" (Lewis, 2007). On a micro level, the most prevalent form of spectator violence is the act of Hooliganism in relation to football (soccer). The research on this aggression has been primarily inherent in Europe and South and Central America in concert with soccer matches. One of the goals of the research is to see if this unique type violence has the potential to occur in North America when comparing it to Europe and more specifically the United Kingdom. Currently, the average Major League Soccer (MLS) teams are capturing slightly higher attendance numbers than the NBA and the NHL. In the 2010-11 season, the average MLS attendance was 17,869, compared to 17,319 and 17,126 respectively (ESPN.com, 2011). With the expansion and globalization of the sport when traveling groups from Europe and South/Central America play United States teams (municipalities or the National team) in a "friendly" (exhibition match) or a World Cup qualifiers stateside, it is understood that supporter firms (hooligan gangs) will travel to support their team. Are hooligans simply looking for a violent result under the guise of being football supporters? "It's a lot more widespread than the general public realize. They might hear of one or two big incidences a year. But this thing happens week in week out at different grounds around England" (Hooligans: No one likes us, 2002). Collective behavior is the most apparent theoretic way to view these outbursts. This research however will examine this social phenomenon through symbolic interaction perspective as well.; The hooligan culture is embedded with symbols of social disorder and rebellion. Racism, xenophobia homophobia and even patriotism are the tent poles of this social phenomenon. Additionally, from firm (gang) to firm (gang), socially constructed deviance such as rival history, improper police conduct, the media and alcohol are overarching factors. The final facet of the research examines how to curb the violence. Since Hooliganism is surprisingly tactical in and of itself, how authorities can potentially identify trouble makers and anticipate violence will be assessed. Since the English have customarily been deemed by the international community as some of the worst cohort participants, the tactics that authorities abroad have utilized (successful and otherwise) will be evaluated. Recommendations to prevent and combat this problem will be made in the hopes that a proactive approach can be developed domestically.

While many human computation (human-in-the-loop) systems exist in the field of Artificial Intelligence (AI) to solve problems that can't be solved by computers alone, comparatively fewer platforms exist for collecting human knowledge, and evaluation of various techniques for harnessing human insights in improving forecasting models for infectious diseases, such as Influenza and Ebola. In this thesis, we present the design and implementation of My4Sight, a human computation system developed to harness human insights and intelligence to improve forecasting models. This web-accessible system simplifies the collection of human insights through the careful design of the following two tasks: (i) asking users to rank system-generated forecasts in order of likelihood; and (ii) allowing users to improve upon an existing system-generated prediction. The structured output collected from querying human computers can then be used in building better forecasting models. My4Sight is designed to be a complete end-to- end analytical platform, and provides access to data collection features and statistical tools that are applied to the collected data. The results are communicated to the user, wherever applicable, in the form of visualizations for easier data comprehension. With My4Sight, this thesis makes a valuable contribution to the field of epidemiology by providing the necessary data and infrastructure platform to improve forecasts in real time by harnessing the wisdom of the crowd. / Master of Science

No / The first recorded crowdsourcing activity was in 1714 [1], with intermittent public event occurrences up until the millennium when such activities become widespread, spanning multiple domains. Crowdsourcing, however, is relatively novel as a methodology within virtual environment studies, in archaeology, and within the heritage domains where this research is focused. The studies that are being conducted are few and far between in comparison to other areas. This paper aims to develop a recent concept in crowdsourcing work termed `crowd behaviour mining' [2] using virtual environments, and to develop a unique concept in crowdsourcing activities that can be applied beyond the case studies presented here and to other domains that involve human behaviour as independent variables. The case studies described here use data from experiments involving separate heritage projects and conducted during two Royal Society Summer Science Exhibitions, in 2012 and 2015 respectively. `Crowd Behaviour Mining' analysis demonstrated a capacity to inform research in respect of potential patterns and trends across space and time as well as preferences between demographic user groups and the influence of experimenters during the experiments.

Développer un modèle de mouvement de foule capable de simuler l'évacuation d'un lieu public de moyenne ou forte affluence devient utile, voire nécessaire, afin que les futures constructions ou aménagements publics puissent offrir une qualité de sécurité optimale à leurs usagers. Les effets des piétons sur les structures du génie civil, comme l'interaction dynamique foule-structure, doivent aussi être pris en compte et modélisés. Dans le cadre de cette thèse, un modèle de foule 2D discret est proposé dans lequel les actions et les décisions de chaque piéton sont traitées individuellement. Ce modèle est aussi capable de modéliser le chargement dynamique d'un piéton sur une structure vibrante. Trois étapes sont nécessaires à l'établissement du modèle proposé. La première concerne la gestion du mouvement et des interactions piéton-piéton et piéton-obstacle. Nous nous sommes inspirés des milieux granulaires pour modéliser les interactions au sein de la foule. Nous avons étudié, implémenté et adapté dans l'environnement MATLAB, le modèle granulaire proposé par Frémond, entrant dans un cadre thermodynamique rigoureux dans lequel les interactions locales sont gérées par l'utilisation de pseudo-potentiels de dissipation, et dans lequel les collisions entre particules peuvent être élastiques ou inélastiques. Une comparaison de ce modèle à deux autres approches déjà adaptées aux mouvements de foule est présentée.La seconde étape consiste à gérer le comportement des piétons. Cette gestion du comportement se fait en plusieurs niveaux de complexité. Dans le premier niveau qui est nécessaire, une stratégie de déplacement est affectée à chaque piéton. La stratégie du chemin le plus court pour qu'un piéton se déplace d'un lieu à un autre a été choisie. Elle a été implémentée à l'aide d'un algorithme de Fast Marching et utilisée pour obtenir la direction souhaitée de chaque piéton au cours du temps. Les autres niveaux de complexité permettent de décrire des comportements plus élaborés tels que l'évitement entre piétons ou le déplacement en sous-groupe, grâce à l'introduction de forces sociales. Une approche originale permettant de former des sous-groupes de piétons à l'aide d'un pseudo-potentiel de dissipation est proposée. La dernière étape concerne le couplage piéton-structure, nous avons cherché à modéliser le chargement dynamique d'un piéton sur une structure vibrante. L'action du piéton sur le sol a été représentée par une force sinusoïdale qui modélise le mouvement d'oscillation de l'individu pendant la marche. En fixant notre attention sur les passerelles, on s'est intéressé au phénomène de synchronisation en fréquence qui peut apparaître entre la fréquence de marche de chaque piéton et la fréquence d'oscillation du système "foule-passerelle". Ce phénomène a été modélisé grâce à l'utilisation d'une équation différentielle de type Kuramoto qui gère la phase de la force de marche de chaque piéton. Un développement analytique du modèle proposé permet d'obtenir les expressions de certains paramètres liés à la synchronisation. Des simulations numériques appliquent ce modèle de foule à l'évacuation des structures du génie civil et à l'interaction foule-passerelle / The development of a model for crowd movement simulating the evacuation of public spaces becomes useful and necessary to determine the effectiveness of transportation infrastructures. The effects of pedestrians on civil engineering structures, such as crowd-structure dynamic interaction, must also be considered and modeled. In this thesis, a 2D crowd model is proposed in which the movement of each pedestrian is represented both in time and space. This model is able to take into account the dynamical pedestrians' action on a moving floor. Three steps are needed to assemble the proposed model. The first concerns the management of pedestrian-pedestrian and pedestrian-obstacle interactions. The non-smooth granular model proposed by Frémond to manage collisions between rigid particles is studied and implemented in a MATLAB environment. This discrete approach applies a rigorous thermodynamic framework in which the local interactions between particles are managed using pseudo-potentials of dissipation. A comparison between this model and two others, already adapted to the crowd, is performed. The second step concerns the management of pedestrians' behavior. A displacement strategy has to be defined for each pedestrian. The strategy of the shortest path to get from one point to another is implemented through a Fast Marching algorithm and is used to obtain the instantaneous desired direction of each pedestrian. Social forces are also introduced in order to manage the interaction between each pedestrian and his nearest environment. An original approach allowing us to create and control subgroups, using pseudo-potentials of dissipation, is implemented. The last step deals with the crowd-footbridge coupling for lateral and vertical oscillations of the structure. An alternating (sinusoidal) sideways force is used in order to take into account the pedestrian's oscillations around his trajectory. This force, due to his walking and his action on the bridge, allows one to define the acceleration of each pedestrian's oscillations around his trajectory. The synchronization of the walking frequency of each pedestrian with the oscillations frequency of the system "crowd-footbridge" is managed via a Kuramoto type differential equation which allows one to govern the evolution of the total phase of the walking force generated by each pedestrian on the bridge. An analytical study is also developed to determine the key parameters of the synchronization phenomenon. Numerical simulations using the proposed model dealing with crowd evacuation of civil engineering structures and pedestrians-footbridge interaction are finally presented

過去四十年， 我國經濟快速成長， 國民所得不斷提高，　公共部門的經 費不斷增加， 但所提供的公共財貨與勞務的數量與品質，卻遠落後於人 民期望之後， 這是造成投資環境惡化、 私人投資(private investment) 意願低落、 及生活素質低落的主要因素之一。 目前台灣地區諸多經濟與 社會結構失衡問題的癥結，在於公共投資(public investment)政策反應 社會需求的速度過於遲緩。因此， 深入了解台灣地區公共投資的情形， 對於我國解決目前所面臨的經濟問題、 追求進一步的經濟成長、及提升 生活素質將有很大的助益。然公共投資是整體投資活動的一環， 與私人 投資同是支持經濟成長的重要角色。 公共投資增加是否會排擠私人投資 ， 需視兩種相對力量大小而定。 一方面較高水準公共投資對私人投資產 出排擠(cro wd-out)；但某些公共資本主要在提供公共基礎設施，藉此可 降低私人的生產成本， 提升私人投資意願。 若公共投資增加， 致使私 人投資減少則排擠產生； 再者公共投資提供的公共基礎設施， 輔助私經 濟的運作， 使私人的邊際生產力提升， 進而使私人投資增加， 則誘導( crowd-in)產生。本篇論文共分為五個部分， 依序為諸論、 公共投資與 私人投資之文獻回顧 、 台灣地區公共投資的回顧、 公共投資與私人投 資關係的實證分析、 及結論。

Simulation models that replicate realistic crowd behaviours and dynamics are of great societal use in a variety of fields of research and entertainment. In order to evaluate the accuracy of such models there is a demand for metrics and evaluation solutions that measure how well they simulate the dynamics of real crowds. A crowd similarity metric is a performance indicator which quantifies the similarity of crowd trajectories. Similarity metrics may be used to evaluate the validity of simulation models by comparing the content they produce to real-world crowd trajectory data. This thesis presents and evaluates a similarity metric which employs an approach based on the Sum of Absolute Differences to compare two-dimensional crowd trajectories. The metric encapsulates the similarity of crowd trajectories by iteratively summing time-wise positional differences on a per-agent basis. The resulting metric is simple, highly reproducible and simulatorindependent. Its accuracy in quantifying similarity is evaluated by means of a user study investigating the correlation between metric values and human perception of similarity for real and simulated crowd scenarios of varying density, trajectory, speed, and presence of environmental obstacles. The user study explores different aspects of crowd perception by dividing similarity ratings on a five-point Likert scale into four categories: overall, in terms of trajectories, speeds, and positions. Scenarios and rating categories that indicate high and low degrees of correlation between metric values and perceived similarity are identified and discussed. Furthermore, the findings are compared to previous research on crowd trajectory similarity metrics. The results indicate that the metric shows promising potential for accurate similarity measurement in simple and sparse scenarios across all rated categories. Moreover, the metric is strongly correlated with the trajectory-ratings of crowd motion similarity. However, it appears to not correlate well with the perception of overall similarity for large and dense crowds. / Simuleringsmodeller som efterhärmar realistiskt beteende och dynamik bland folkmassor är av stor samhällelig nytta i flertalet forskningsområden och i underhållningsbranschen. För att utvärdera sådana modellers noggrannhet finns det en efterfrågan av metriker och bedömningslösningar som mäter hur väl modeller simulerar verklig folkmassadynamik. En likhetsmetrik för folkmassautvärdering är en prestationsindikator som kvantifierar likheten mellan folkmassarörelser. Likhetsmetriker kan användas för att utvärdera simuleringsmodellers validitet genom att jämföra beteendet de producerar med rörelsedata från verkliga folkmassor. Följande examensarbete presenterar och utvärderar en likhetsmetrik för folkmassor som utnyttjar en metod baserad på ”Summan av Absoluta Skillnader” för att jämföra par av två-dimensionella folkmassarörelser. Metriken uppskattar likheten mellan två folkmassors rörelser genom att iterativt summera skillnaderna mellan folkmassornas positioner baserat på de individuella virtuella agenterna. Resultatet är en simpel, kraftigt reproducerbar och simulator-oberoende metrik. Dess noggrannhet avseende likhetsestimering utvärderas med en perceptuell användarstudie som undersöker korrelationen mellan metrikvärden och mänsklig perception av visuell likhet för flertalet verkliga och simulerade folkmassor av varierande densitet, färdväg, hastighet, och förekomst av hinder. Användarstudien utforskar olika aspekter av folkmassaperception genom att dela upp likhetsgradering på en femgradig skala i fyra kategorier: övergripande, avseende färdvägar, hastigheter, och positioner. Folkmassascenarier och graderingskategorier som indikerar höga och låga nivåer av korrelation mellan metrikvärden och uppfattad likhet identifieras och diskuteras. Fortsättningsvis jämförs resultaten med tidigare forskning om likhetsmetriker för folkmassautvärdering. Resultaten tyder på att metriken har lovande potential för noggrann likhetsestimering i enkla och glesa scenarier oavsett graderingskategori. Dessutom korrelerar metriken starkt med färdvägs-graderingar av likhet. Däremot verkar den inte korrelera väl med perceptionen av övergripande likhet för stora och täta folkmassor