基于元胞自动机和复杂网络理论的双向行人流建模

摘要

In this paper the experiment to study the features of pedestrians＇ walking preference is designed.Then the cellular automata model which considering pedestrians＇ walking preference features is built,in which the forward-parameter,right-parameter,surpass-parameter and the correction-parameters are included to mend the probability of the pedestrian getting to each neighboring cell.Based on this model and k-nearest-neighbor interaction pattern,the complex network of pedestrians is modeled.The simulation results obtained from the model well illustrate the density-speed curve and density-volume curve.Meanwhile the self-organization phenomena of the bi-direction pedestrian flow can be observed from the model simulation.In the further analysis of the pedestrian flow＇s basic parameter and the main feature parameters of pedestrians＇ complex network,it is found out that the average speed and the average path length are changed with the state of the flow.Finally it can be concluded that there is a linear negative correlation between these two parameters by fitting the data;in other words,pedestrian flow with shorter average-path length has a higher average speed.%通过设计行人行走倾向性调查实验,分析了行人的行走倾向性特征.引入前进系数、右倾系数、超越系数以及影响修正系数等对元胞自动机（CA）基本模型中的转移概率进行修正,建立了考虑行人行走倾向性特征的CA行人仿真模型.针对该模型中的行人群体,依据k-近邻作用原理,构建行人复杂网络.通过计算机仿真,揭示了行人流密度、速度和流量的关系以及仿真过程中出现的自组织现象.进一步分析仿真输出的行人流基本参数和行人复杂网络主要特征参数,发现对同一行人流,其平均速度和网络平均路径长度均随着行人流状态的改变而变化.最后,通过平均路径长度和平均速度的数据拟合,得出两者之间存在着线性负相关关系的结论,即具有较小网络平均路径长度的行人流具有较高的平均速度.