Fire Accidents in Public Placesįires are one of the most uncontrollable calamities, especially when they happen indoors. Finally Section 4 consists of final conclusions. Section 3 presents the experiment results when the mentioned two real fire accidents were simulated. Section 2 presents the idea of forecasting the fire hazard, two real accidents’ description, and CAEva simulation method with their boundary conditions and transfer function. For this purpose authors used Cellular Automata Evaluation method, CAEva in short. In this article, the authors present the possibility of simulating real fire accident to prevent huge fire accidents. There are three structural factors which significantly influence the grid form and, as a consequence, the behavior of the entire cellular automaton : (i) the size of the space which depends on the magnitude of the studied problem, the examples of which are shown in Figure 1 (grids 1D, 2D, and 3D) (ii) the provision of regularity, which requires the grid to be filled entirely with identical cells (iii) the number of neighbors (dependent on both above-mentioned factors). Each of the cells is surrounded by the same number of neighbors and can assume the same number of states. The Grid of Cellular AutomataĪ grid or a discrete space, where cellular automata evolution takes place, consists of a set of identical cells. The aim of the proposed algorithm is to generate the simulations of patterns of human escape from the building on fire with a given number of exits and fire sources. Other examples of cellular automata implementations include image processing, generation of textures, simulation of waves, wind, and people evacuation process as well as a simulation program, developed for the purpose of this study. By introducing some modification to the algorithm, it is possible to monitor the behavior of the surrounding cells. Such simulations can be based on the well-known “Game of Life”. The aim of such simulations is to generate a model showing the size of the population at a given area in a form of a map of the forecasted population density. Another example of cellular automata application is demographic simulations for a given region.
The projects websites publish the statistical information about the studies performed on the behavior of drivers who were prewarned about possible traffic problems that might occur over several following hours. The information thus obtained is analyzed and used for preparing short-time simulations of the traffic intensity by means of cellular automata. The monitoring centers designed exclusively for that purpose collect the data from selected sections of the highways. This applies, for instance, to the traffic intensity control on highways of the Ruhr in Germany. The vehicle flow is managed basically at the specific segment of a given traffic intensity. Application of Cellular AutomataĬellular automata have been applied in practice, for example, in simulation of the street traffic, where specifically defined cellular automaton controls the traffic. Due to their versatility, cellular automata are applied in many real-life fields, such as biology, physics, and mathematics and in various fields of IT, such as cryptography or computer graphics. With the development of computers and software, optimizing methods based on this approach have been more and more frequently studied and implemented in practice. For many years cellular automata had been subject to theoretical studies only. He demonstrated, among others, that even simple machines show an ability to reproduce, which was until that time regarded as a fundamental feature of living organisms. The theory of cellular automata was first introduced by an American scientist of Hungarian descent, John von Neumann. The change of the current state of a given cell is the outcome of the above-mentioned properties and interrelations with the neighboring cells. They consist of a network of cells, each of which is distinguished by some specific state and a set of rules. IntroductionĬellular automata are used by some of the IT branches, including the field of artificial intelligence. The authors analyze some real accidents and proved that CAEva method appears as a very promising solution, especially in the cases of building renovations or temporary unavailability of escape routes. The tests performed on real accident showed that an appropriately configured program allows obtaining a realistic simulation of human evacuation. Proposed method, called Cellular Automata Evaluation (CAEva in short), is using cellular automata theory and could be used for checking buildings conditions for fire accident. There were a lot of fires in public places which kill many people. Many serious real-life problems could be simulated using cellular automata theory.