一种元胞自动机与类电磁法相结合的行人流模型
A Pedestrian Evacuation Model based on Cellular Automaton and Electromagnetism Mechanism

针对室内空间的行人流疏散过程，在元胞自动机的基础上，利用类电磁法和模糊神经网络建立了一种新的行人流优化模型。该模型首先基于静态影响因素和动态影响因素给出了行人移动概率的计算公式，以及行人流演化过程。同时，结合疏散时间、系统平均速度、出口处流率给出了目标优化函数，并通过类电磁法和模糊神经网络对上述目标函数进行求解。最后，利用仿真平台进行实验，深入分析了疏散时间、出口宽度和初始行人密度之间的关系。结果表明，疏散时间与出口宽度呈现负相关，并且适当提高系统平均速度有利于降低疏散时间。
In order to effectively depict the pedestrian evacuation process, based on the cellular automaton, a novel evacuation model was proposed by electromagnetism mechanism and fuzzy neural network. Combined the static factor and dynamic factor, the calculation formula of transition probability and evacuation strategy were given. Meanwhile, the optimization function is given with evacuation time, average system velocity and flow rate, and it is solved by electromagnetism mechanism and fuzzy neural network. At last, experiments were conducted with the simulation platform to study the relationships of evacuation time, exit width as well as initial pedestrian density. The results showed that evacuation time had a negative correlation with exit width, and an appropriate increasing for average system velocity would reduce the evacuation time