导　　师： 纪庆革

学科专业： H1204

授予学位： 硕士

作　　者： ;

机构地区： 中山大学

摘　　要： 近年来国内外安全事故频发,如何在短时间内将聚集的人群疏散显得至关重要。那么,如何评价一次疏散的效率,或是如何评价一座公众场所的建筑设计是否成分考虑了安全问题也显得十分重要。最直接的方法就是进行疏散演练。然而疏散演练存在着几个不足之处/[1/]。首先疏散演练通常是很危险的,尤其是当参与者的数量很大时;其次疏散演练需要大量的时间和财力物力来操作;而且,由于消耗很大的原因,疏散演练只能很有限次的进行。一种实际可行的方法就是利用计算机进行人群疏散仿真。 目前国内外所研究的人群疏散仿真技术大多是基于Agent的微观仿真,这种仿真重点关注个体的决策过程及行为,但没有体现出个体之间足够的交互性。由于考虑到在发生突发事件时,人们往往表现出恐慌、不知所措的行为,表现出一种动物本能,联系到Particle Swarm Optimization/(PSO/)算法提出的背景和思想,本文考虑将PSO算法运用于人群疏散仿真,控制人群疏散过程中的行人移动,进行路径选择。原始PSO算法中的粒子可以在解空间中绝对自由的飞行,而现实中的行人除了避免与其他行人的碰撞外,还要避免与障碍物的碰撞,而且并不是直到遇到了障碍物或行人后才改变行动路径,而是在与障碍物或行人有一定距离时就开始转向,因此行人在空间中行走时不会毫无规则摇摆不定奇怪地行走,行走路线必须合理、合适。为了解决原始PSO算法求解和现实中人员寻找路径的不一致性,需要对原始的PSO算法进行修改,以适用于人群疏散仿真。 本文首先分析了当前国内外一些比较流行的仿真技术,总结了各自的建模特点、适用场景及优缺点,结合实际情况,建立适当的仿真模型;将PSO算法应用于个体的路径选择;最后开发出一个仿真原型系统EvacuaSim,并对两个实际场景进行建模、仿真。仿真系统能很好的满足人群疏散仿真的需求,能比较直观的显示疏散仿真过程,仿真结果逼真,能给疏散仿真的分析提供帮助,为设计实际的疏散预案提供指导和支持。 These years more and more accidents took place at home and abroad. It is very important to evacuate crowding people in a short time. How to estimate the evacuation efficiency, or how to judge whether a building design accords to the safe standard? The most direct approach is to arrange evacuation drills. However, there are some disadvantages associated with these drills. Firstly, these drills are usually dangerous, especially when a large number of participants are involved in the drills. Secondly, these drills usually require relatively much time and a lot of money to prepare and operate. Furthermore, the cost increases dramatically when the number of participants increases or when the drill fails and a new one needs to be redesigned. Lastly but not least, it is typically the case that only limited number of trials can be performed in each evacuation drill due to the time-consuming planning and enormous cost. Actually, a practical approach is to simulate the crowd evacuation in computer. At present most crowds evacuation simulation techniques at home and abroad are based on Agents, they are called micro-simulation. These techniques focus on the decision process and behavior of the agents, but neglect the interaction of the agents. Because people usually feel scared and exert animal’s attributes at danger and urgent situations, plus considering the background and idea of Particle Swarm Optimization, this article apply the idea of PSO to the crowds evacuation simulation, to control pedestrians’movement and make the path choice of pedestrians. The original PSO allows particles to fly in the solution space absolutely freely, but the pedestrians in the reality should avoid the conflict with obstacles and other pedestrians. Furthermore, it is not the fact that the pedestrians don’t change the path until they run into the obstacle, actually they change the path when they have a distance with obstacles. Therefore, people don’t walk strangely and swing left and right, the path should reasonable and appropriate. To resolve the aforementioned incompatibility issues between original PSO and people’s finding path in reality, we should modify the original PSO to be compliant to the crowds evacuation simulation. This paper, firstly, analyzes some popular stimulation technology at home and abroad at present, summaries the characteristics of each model, the suitable scene and the advantages as well as the disadvantages and establishes appropriate simulation model according to the actual situation. And then, PSO algorithm is applied to individual routing. Finally, a simulation prototype system EvacuaSim is developed, which applied to the simulation and model in two real scene. This simulation system can meet the requirements of the crowd evacuation simulation, displaying the process directly, and offering necessary data for analyzing and guidance for the practical plan.

关 键 词： 人群疏散 多智能体 算法 软件平台

分 类 号： [F2]

领　　域： [经济管理]