建筑物内人员疏散算法与仿真

发布时间：2018-06-20 18:16

本文选题：应急疏散 + 网络模型　；参考：《复旦大学》2013年硕士论文

【摘要】：建筑物内的人员疏散是应急疏散问题中一个重要的研究方向。应急疏散的目的是使疏散人员在尽可能短的时间内从危险的区域转移到安全的地方。当建筑物内有火灾、有毒气体泄漏或地震等紧急情况发生时,建筑物内的人员疏散算法可以指导疏散人员在尽可能短的时间内完成疏散。通过对建筑物内人员疏散过程的建模仿真,可以研究不同的疏散环境和不同的疏散人员行为对疏散过程和疏散时间的影响。此外,对建筑物人员疏散问题的研究可以指导建筑物设计,优化建筑物的结构使其利于应急疏散。本文对建筑物人员疏散问题中基于网络模型的实时疏散算法和基于元胞自动机模型的行人疏散流仿真两个方向进行了探索,并对其中存在的问题提出了新的算法和模型。主要内容有以下两个部分： 1.基于网络模型的递推实时疏散算法针对现有的网络模型实时疏散算法只能应用在单一疏散源的疏散情形,提出可以应用在多疏散源多出口的疏散算法。该算法将递推思想引入到疏散模型中,从单个疏散人员出发,通过递推得到多疏散源多出口的疏散时间和疏散人员分配方案。同时改进随机递推顺序,按疏散人员与出口最短距离的升序安排递推顺序,从而得到优化的疏散时间和疏散人员分配方案。该算法克服了快速流动控制算法不能应用在多疏散源的局限性,同时该算法复杂度较低,能够应用在实时环境中。 2.细分元胞自动机的混合速度疏散流仿真多数元胞自动机模型中,疏散人员都按照相同的移动速度进行疏散,但在实际疏散环境中,疏散人员由于性别和年龄不同而拥有不同的移动速度。为了研究混合速度行人疏散流的疏散特征,对传统模型进行改进得到细分元胞自动机模型,然后将高速和低速两种不同速度的疏散人员加入到改进的细分模型中。在整个疏散过程中,高速和低速疏散人员可以使用不同的疏散策略,通过对使用不同疏散策略的疏散流的仿真分析,得到符合实际情况的最佳疏散策略。然后使用动态权重并结合最佳的疏散策略对多出口条件下的混合速度行人疏散流进行仿真,分析疏散流在高低速疏散人员比例不同,疏散流密度不同时的疏散时间。
[Abstract]:Evacuation in buildings is an important research direction in emergency evacuation. The purpose of emergency evacuation is to move evacuees from hazardous areas to safe places in as short a time as possible. When fire, toxic gas leakage or earthquake occur in the building, the evacuation algorithm in the building can guide the evacuees to complete the evacuation in as short a time as possible. By modeling and simulating the evacuation process in the building, the influence of different evacuation environment and behavior on the evacuation process and evacuation time can be studied. In addition, the study on the evacuation of building personnel can guide the design of buildings and optimize the structure of buildings to facilitate emergency evacuation. In this paper, the real-time evacuation algorithm based on network model and the simulation of pedestrian evacuation flow based on cellular automata model are explored, and a new algorithm and model are proposed. The main content has the following two parts: 1. Recursive real time evacuation algorithm based on network model. The existing real time evacuation algorithm of network model can only be applied in the case of a single evacuation source, and an evacuation algorithm can be applied to multiple evacuation sources and multiple exits. The algorithm introduces the recursive idea into the evacuation model and obtains the evacuation time and the evacuation allocation scheme of multiple evacuation sources and exits from a single evacuator. At the same time, the random recursive sequence is improved, and the recursive order is arranged according to the ascending order of the shortest distance between the evacuees and the exits, and the optimal evacuation time and evacuation personnel allocation scheme are obtained. The algorithm overcomes the limitation that the fast flow control algorithm can not be applied to multiple evacuation sources, and the complexity of the algorithm is low, and it can be used in real time environment. Simulation of mixed Velocity evacuation flow of subdivided Cellular Automata in most Cellular Automata models, the evacuees are evacuated at the same moving speed, but in the actual evacuation environment, Evacuees move at different speeds depending on gender and age. In order to study the evacuation characteristics of mixed velocity pedestrian evacuation flow, the subdivision cellular automata model is obtained by improving the traditional model, and then two kinds of high speed and low speed evacuees are added to the improved subdivision model. In the whole evacuation process, different evacuation strategies can be used for high speed and low speed evacuees, and the optimal evacuation strategy is obtained by simulation analysis of evacuation flow using different evacuation strategies. Then the dynamic weight and optimal evacuation strategy are used to simulate the mixed velocity pedestrian evacuation flow under the condition of multiple exits. The evacuation time of the evacuation flow with different ratio of high and low speed evacuees and different density of evacuation flow is analyzed.
【学位授予单位】：复旦大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TU998.1;TP391.9

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