Modeling Bi-direction Pedestrian Flow by Cellular Automata and Complex Networks Theories
Modeling Bi-direction Pedestrian Flow by Cellular Automata and Complex Networks Theories
复制标题
DOI：
10.7498/aps.61.144501
复制
发表时间：
2012
影响因子：
24.1
通讯作者：
Lili Lu;Gang Ren;Wei Wang;Chen Yu;Zhang Yong
中科院分区：
文献类型：
--
作者：
Lili Lu;Gang Ren;Wei Wang;Chen Yu;Zhang Yong
由于行人流具有多样性、低速性、随机性和自组织等特点，研究行人的行为具有很大的难度。本文提出了一种应用元胞自动机（CA）结合复杂网络理论来研究双向行人流的新方法。本文设计了调查实验来研究行人步行偏好的特征。然后建立考虑行人步行偏好特征的元胞自动机模型，其中引入前向参数、右向参数、超越参数和周围校正参数来修正转移概率。基于k近邻交互模式，CA模型的双向行人流被抽象为复杂的行人网络。仿真结果显示了人流的相变、密度-速度、密度-体积曲线。同时生成行人复杂网络的参数。然后，发现双向人流的平均速度与作为网络结构特征参数的平均路径长度之间的相关性，即平均路径长度较短的人流以较高的平均速度运行。
Due to such characters as diversity, low-speed, randomicity and self-organization of pedestrian flow, it is of great difficulty to study the behavior of pedestrians. This paper proposes a new method to study the bi-direction pedestrian flow by applying cellular automata (CA) combined with complex network theory. This paper designs the survey experiment to study the features of pedestrians' walking preference. Then the cellular automata model considering pedestrians' walking preference features is built in which the forward-parameter, right-parameter, surpass-parameter and the surrounding-correction parameters are brought to mend the transition probability. Based on the k-Nearest-Neighbor interaction pattern, the bi-direction pedestrian flow of the CA model is abstracted as complex network of pedestrians. The simulation results show the phase transition, and density-speed, density-volume curves of pedestrian flow. At the same time, the parameter of pedestrian complex network is generated. Then, the correlation between the average speed of the bi-direction pedestrian flow and the average path length as a parameter of the network's structure characteristic is found, that is the pedestrian flow with shorter average-path length operates with higher average speed.