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Incorporating Cellular Automaton based Microscopic Pedestrian Simulation and Genetic Algorithm for Spatial Layout Design Optimization

机译:结合基于细胞自动机的微观行人仿真和遗传算法进行空间布局设计优化

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Autonomous spatial layout design had become the prominent applications for early planning process for a space arrangement. The available spatial layout design applications had focused on the structural and functional demands for a trendy, cultural influences and scalable spatial design. The previous research on the autonomous spatial layout design had proved that the Genetic Algorithm (GA) with full-fledged of operators are able to design an optimal spatial layout that is scalable for the space utilization. However, in these recent years, due to many occurrences of emergency incidents, the security assurance of the pedestrian to evacuate from the spatial layout during panic situation had become the main focus in designing a spatial layout. Hence, this research had proposed the pedestrian movement simulation using Cellular Automata (CA) with the Moore Neighborhood transition movement direction as the objective function for optimizing the GA operators based spatial layout design. The results have shown that the CA based pedestrian movement simulation was able to optimize the GA operators based spatial layout design in designing a feasible and scalable space arrangement with low-risk of pedestrian casualties.
机译:自主的空间布局设计已成为空间布局早期规划过程的主要应用。可用的空间布局设计应用程序集中在结构和功能需求上,这些需求是对流行,文化影响和可扩展空间设计的要求。先前对自主空间布局设计的研究证明,具有成熟算子的遗传算法(GA)能够设计出可扩展用于空间利用的最佳空间布局。然而,近年来,由于紧急事件的发生很多,在紧急情况下行人从空间布局撤离的安全保证已成为设计空间布局的主要重点。因此,本研究提出了以元胞自动机(CA)为基础的步行运动仿真,其中以摩尔邻里过渡运动方向为目标函数,以优化基于遗传算法的空间布局设计。结果表明,基于CA的行人运动仿真能够在设计可行且可扩展的,行人伤亡风险低的空间布局时优化基于GA算子的空间布局设计。

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