Simulation of an escape pathfinding algorithm based on fuzzy theory for use in a spreading fire

Traditional escape route algorithms do not take into consideration the dynamic and random characteristics of a fire and cannot predict the development of the fire. As a result, the selected escape route obtained using traditional algorithms is not effective. In order to cope with these problems, this paper proposes an escape pathfinding algorithm based on fuzzy theory for use in a spreading fire. In the proposed algorithm, an abstract scene is first built and each fuel's burning time is calculated. In addition, the shortest arrival time at the fuel is estimated and then the behavior of these fuels as the fire spreads and humans arrive can be classified by fuzzy theory. Finally, the safe critical point can be obtained by using a fire model and geometric methods, and the next intermediate escape target can also be selected by means of the greedy strategy. Simulation results using virtual reality(VR) technology showed that the proposed algorithm was able to select a safer and more efficient escape route with a shorter path than those given by traditional escape route algorithms.