...
首页> 外文期刊>Physica, A. Statistical mechanics and its applications >A continuous floor field cellular automata model with interaction area for crowd evacuation
【24h】

A continuous floor field cellular automata model with interaction area for crowd evacuation

机译:具有人群疏散的互动区域的连续地板场蜂窝自动机模型

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Discrete and continuous models are generally used to study the evacuation dynamics. Considering the low accuracy of the discrete model such as floor field cellular automata model (FFCA) and the high time complexity of the continuous model such as social force model (SFM), a continuous FFCA (CFFCA) model is proposed. Pedestrians no longer occupy cells but are treated as particles in continuous space. To reduce the time complexity caused by continuity, the social force is replaced by interactions by drawing on SFM from different perspectives. The obstacle and pedestrian interaction area are proposed to simulate the repulsion, friction and attraction between pedestrians and obstacles, and between pedestrians. By simulating different evacuation scenarios, it is found that the simulation results are close to the experiments data. CFFCA evacuation path is more reasonable than that of FFCA and the execution time is shorter than that of SFM. Because of the superiority of interaction area used in CFFCA, pedestrians can move freely without being restricted by the spatial scale of cells, and the complex psychology of pedestrians can be simulated under lower time complexity. Our study may be useful to find the trade-off between model realism and tractability. (C) 2021 Elsevier B.V. All rights reserved.
机译:离散和连续模型通常用于研究疏散动力学。考虑到地板场元胞自动机(FFCA)等离散模型的精度较低,以及社会力模型(SFM)等连续模型的时间复杂度较高,提出了一种连续FFCA(CFFCA)模型。行人不再占据细胞,而是被视为连续空间中的粒子。为了减少连续性带来的时间复杂性,从不同角度利用SFM,将社会力量替换为互动。提出了障碍物与行人相互作用区域来模拟行人与障碍物之间、行人与行人之间的排斥、摩擦和吸引。通过模拟不同的疏散场景,发现模拟结果与实验数据比较接近。CFFCA疏散路径比FFCA更合理,执行时间比SFM短。由于CFFCA中交互区域的优越性,行人可以自由移动,而不受细胞空间尺度的限制,并且可以在较低的时间复杂度下模拟行人的复杂心理。我们的研究可能有助于找到模型真实性和可处理性之间的权衡。(c)2021爱思唯尔B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号