Open AccessA Multistory Building Evacuation Model Based on Multiple-Factor Analysis
Author(s) -
Yang Zhang,
Tanghong Wu,
Gaofan Zhang,
Zhiping Fan
Publication year - 2019
Publication title -
advances in civil engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.379
H-Index - 25
eISSN - 1687-8094
pISSN - 1687-8086
DOI - 10.1155/2019/6585102
Subject(s) - emergency evacuation , bottleneck , cellular automaton , computer science , adaptability , pedestrian , population , simulation , operations research , transport engineering , engineering , algorithm , geography , ecology , demography , sociology , meteorology , biology , embedded system
Emergency evacuation is an important issue in public security. To make a considerate plan, various situations are presented including blocking the accident area and letting the emergency access path available. In order to offer dynamic evacuation routes due to different circumstances, a multistory building evacuation model is proposed. Firstly, to analyse the patency of the building, an evacuation formula is applied after binary processing. The function of evacuation time and some other parameters is given by means of regression analysis. Secondly, the cellular automata (CA) algorithm was applied to illustrate the effect of the bottleneck. The response of evacuation time could be approximately optimized through calculating time step of the CA simulation. Finally, the value of maximum evacuation population density could be determined according to the analysis of CA simulation results, which was related to the switch state of the emergency channel. The emergency evacuation model was simulated by using the Louvre museum as an example. The results of the simulation presented some feasible evacuation routes in all kinds of situations. Furthermore, the functional relationship would also be given among evacuation time with the diversity of tourists, pedestrian density, and width of exits. It can give a different perspective that the multistory building evacuation model shows excellent adaptability to different circumstances.