DHB - Modeling in Social Dynamics: A Differential Approach

DHB - 社会动态建模：差异化方法

• 批准号: 0527545
• 负责人: David Kaup
• 金额: --
• 依托单位: The University of Central Florida Board of Trustees
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0527545&HistoricalAwards=false
• 关键词: DHB; Modeling; Social; Dynamics; Differential

NSF ABSTRACT for:MODELING IN SOCIAL SYNAMICS: A DIFFERENTIAL APPROACHThis research proposes a major expansion of a simulation of pedestrian motion based on the model of pedestrian motion by Helbing-Moln ar-Farkas-Vicsek (HMFV). This model uses a combination of social and physical forces to determine how the individuals in the model move and interact. The purpose of this expansion is to fold characteristics concerning age, gender, ethnicity, and culture differences into the model, so as to be able to capture reliable differences due to these four factors. Such results could then be used to improve our ability to model social dynamics. This will be done by giving each individual in the simulation, certain traits and characteristics, related to culture, ethnicity, gender, and age. The simulations would then demonstrate how these variations in individual characteristics can affect individual behavior and group behavior, as in a crowd. These four factors (culture, ethnicity, gender, and age) will certainly provide a sufficient space to be interesting. However, there are also interesting cases wherein one would want to model groups of individuals with similar characteristics. These shall be concentrated on at first, expanding the dimension of the space as experience is gained. The distribution of these traits in the simulated populations will be stochastic so as to have flexibility to model a variety of situations (e.g. night club fire, a sporting event, a subway platform). Having stochastic distributions of traits will allow the opportunity to determine how sensitive the overall crowd behavior is to small changes in distributions of the traits. It will also allow us to model "worst case" scenarios so that those engaged in crowd control (or building design) can prepare for the most detrimental outcome.Recent world events prompt research in understanding crowd behavior in emergencies such as nightclub fires, stadium accidents, and subway bombings. The continual threat of global terror and the potential for mass panic could lead to more fatalities of people who are crushed or trampled. This project will use mathematical modeling and simulations to construct models of pedestrian interactions under various situations. The results will be validated using actual crowd movement data obtained from videos from various scenarios. The findings will provide understanding of the influence and importance of social variability under various conditions. The goal of this effort is to provide a more realistic simulation model of crowd behavior under both panic and non-panic conditions by considering individual differences in age, gender, culture and ethnicity. This would be a valuable tool for police departments, the military, and others to use for event handling or in terrorist situations. It could also be used for building design to accommodate cultural differences.

NSF摘要：Modelin in Social SYNAMICS：A Differential APPROACH他的研究提出了一种对行人运动的模拟的主要扩展，该模型基于Helping-Moln ar-Farkas-Vicsek(HMFV)的行人运动模型。该模型使用社会和物理力量的组合来确定模型中的个体如何移动和交互。这一扩展的目的是将关于年龄、性别、种族和文化差异的特征纳入模型，以便能够捕获由于这四个因素而产生的可靠差异。然后，这些结果可以用来提高我们对社会动态进行建模的能力。这将通过向模拟中的每个人提供与文化、种族、性别和年龄相关的某些特征和特征来实现。然后，这些模拟将展示这些个体特征的变化如何影响个体行为和群体行为，就像在人群中一样。这四个因素(文化、种族、性别和年龄)肯定会提供足够的有趣空间。然而，也有一些有趣的案例，在这些案例中，人们想要为具有相似特征的个体群体建模。这些应该首先集中在空间的维度上，随着经验的积累而扩展。这些特征在模拟人群中的分布将是随机的，以便能够灵活地模拟各种情况(例如，夜总会火灾、体育赛事、地铁站台)。拥有特征的随机分布将使我们有机会确定总体人群行为对特征分布的微小变化的敏感度。它还将使我们能够对“最坏的情况”进行建模，以便那些从事人群控制(或建筑设计)的人能够为最有害的结果做好准备。最近的世界事件促使人们研究了解紧急情况下的人群行为，如夜总会火灾、体育场事故和地铁爆炸事件。持续不断的全球恐怖威胁和大规模恐慌的可能性可能会导致更多被碾压或踩踏的人死亡。该项目将使用数学建模和模拟来构建各种情况下行人相互作用的模型。结果将使用从各种场景的视频中获得的实际人群运动数据进行验证。这些发现将有助于理解不同条件下社会变异性的影响和重要性。这项工作的目标是通过考虑年龄、性别、文化和种族的个体差异，为恐慌和非恐慌条件下的人群行为提供一个更现实的模拟模型。对于警察部门、军方和其他人来说，这将是一个宝贵的工具，可以用来处理事件或处理恐怖事件。它还可以用于建筑设计，以适应文化差异。