Potential field cellular automata model for pedestrian flow.
Potential field cellular automata model for pedestrian flow.
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DOI：
10.1103/physreve.85.021119
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发表时间：
2012-02
期刊：
影响因子：
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通讯作者：
Peng Zhang;Xiao-xia Jian;S. Wong;Keechoo Choi
中科院分区：
文献类型：
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作者：
Peng Zhang;Xiao-xia Jian;S. Wong;Keechoo Choi
本文提出了一种行人流的元胞自动机模型，该模型定义了一个考虑行人移动到空的相邻单元所需花费时间和不适的代价势场。该公式是基于密度分布和底层物理的重建，包括解决冲突的规则，这与地板场元胞自动机模型相当。然而，我们假设每个行人都熟悉周围的环境，从而最小化他或她的瞬时成本。这反过来又有助于减少选择目标细胞的随机性，从而改进现有的元胞自动机建模，同时提高计算效率。当存在以目的地区分的两组行人时，由于两组之间的强交互作用，每组的成本分配被放大。作为一种典型现象，逆流中车道的形成得到了再现。
This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.