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A Fuzzy Logic Inspired Cellular Automata Based Model for Simulating Crowd Evacuation Processes

机译:基于模糊逻辑启发的细胞自动机的模型模拟人群疏散过程

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This work investigates the incorporation of fuzzy logic principles in a cellular automata (CA) based model that simulates crowd dynamics and crowd evacuation processes with the usage of a Mamdani type fuzzy inference system. Major attributes of the model that affect its response, such as orientation, have been deployed as linguistic variables whose values are words rather than numbers. Thus, a basic concept of fuzzy logic is realised. Moreover, fuzzy if-then rules constitute the mechanism that deals with fuzzy consequents and fuzzy antecedents. The proposed model also maintains its CA prominent features, thus exploiting parallel activation of transition rules for all cells and efficient use of computational resources. In case of evacuation, the selection of the appropriate path is primarily addressed using the criterion of distance. To further speed up the execution of the Fuzzy CA model the concept of the inherent parallelization was considered through the GPU programming principles. Finally, validation process of the proposed model incorporates comparison of the corresponding fundamental diagram with those from the literature for a building that has been selected for hosting the museum 'CONSTANTIN XENAKIS', in Serres, Greece.
机译:这项工作研究了模糊逻辑原理在基于细胞自动机(CA)的模型中的结合,该模型使用Mamdani型模糊推理系统模拟人群动态和人群疏散过程。影响模型响应的主要属性(例如方向)已被部署为语言变量,其值是单词而不是数字。因此,实现了模糊逻辑的基本概念。此外,模糊的if-then规则构成了处理模糊结果和模糊前因的机制。所提出的模型还保持其CA突出的特征,从而为所有单元利用并行激活转换规则并有效利用计算资源。在疏散的情况下,主要使用距离标准来选择合适的路径。为了进一步加快Fuzzy CA模型的执行速度,通过GPU编程原理考虑了固有并行化的概念。最后,所提出模型的验证过程包括将相应的基本图与文献中的基本图进行比较,该图已被选为希腊Serres的“ CONSTANTIN XENAKIS”博物馆的举办地。

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