Extended Cellular Automata Simulation Model For Fire Crowd Evacuation

Alidmat, Omar Khair Alla Abdel Rahman (2021) Extended Cellular Automata Simulation Model For Fire Crowd Evacuation. PhD thesis, Universiti Sains Malaysia..

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In recent years, crowd evacuation in case of fire accidents has attracted considerate attention. Fire accidents occur in crowded buildings may cause heavy casualties. The study of fire crowd evacuation has become extremely necessary to minimize the loss of life and property. Large fires pose dangers; hence, computer simulations are conducted as alternative tools to the deficiencies in conducting actual fire evacuation experiments. Researchers have simulated evacuees’ movements in panic situations, such as fires, using the cellular automata (CA) model to predict and analyze evacuees’ behaviors during these panic situations. This could help minimize accidents and save lives. However, those researchers have either investigated fire accidents in a static scenario or propagate inaccurate fire circular fronts shape, such as the adoption of a square fire front shape. They have also applied a lot of constraints on the environmental and accident factors, such as fire location, fire spread speed, obstacles, which could show evacuees movements appeared unrealistic. In addition, the models used by those researchers ignored the effects of crowd pressure applied on evacuees around overcrowded exits during fire evacuation. In this research, the spiral fire movement technique was adopted using CA model to simulate the fire circular surface propagation shape, which presents a non-static fire-spreading behavior that able to estimate the average number of evacuees could be injured or killed by fire. In addition, the new extended CA parameters (fire spreading, congestion and path), the set of mathematics formulas, were introduced to simulate the decision-making of evacuees in terms of movements and judgments and their choices of actions.

Item Type: Thesis (PhD)
Subjects: Q Science > Q Science (General)
Divisions: Pusat Pengajian Sains Komputer (School of Computer Sciences) > Thesis
Depositing User: Mr Noor Azizan Abu Hashim
Date Deposited: 30 Sep 2022 07:00
Last Modified: 30 Sep 2022 07:00
URI: http://eprints.usm.my/id/eprint/55028

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