Research On Cellular Automata Evacuation Model Based On Ant Colony Algorithm And Artificial Potential Field

With the development of national economy, more and more large buildings exist around our country over the past twenty years. Evacuation plan for the buildings is an important basis to protect the safety of people in buildings. There is a great realistic significance to make scientific and effective evacuation plan which is also a matter of concern research topic in recent years. Teaching building is a representative of public buildings, due to its high bearing capacity of people and complex structure, teaching building is also the focus of research. The teaching building evacuation plan is the objectives of the study in this thesis. This thesis mainly researches on application of ant colony optimization algorithm and the artificial potential field in the cellular automata evacuation model. The work of this thesis can be described as follows:(1) The evacuation model based on cellular automata is set up. The indoor teaching building evacuation model is designed by using the advantage of cellular automata in micro-simulation and adding rules of obstacle avoidance and conflict resolving. Then the thesis simulates the interaction between people, people and environment in evacuation process, explores the pedestrian’s psychological behavior in emergency evacuation by simulation experiments, in addition, it uses the two-dimension figures to show the evacuation process.(2) An improved cellular automata evacuation model based on ant colony algorithm is designed. On the basis of cellular automata model, the improved teaching building evacuation model is built by using ant colony algorithm to optimize pedestrians’ evacuation paths. Ant colony optimization algorithm optimizes the people evacuation routes in teaching building. We propose an improved evacuation model for teaching building. The individual evacuation paths from the microcosmic are compared in experiment, and this model shortens the overall personnel evacuation empty time and gets the optimized paths.(3) An artificial potential field evacuation model based on ant colony algorithm is designed. The artificial potential field is combined with ant colony algorithm, evacuation simulation of personnel congestion is made more intuitive with macro view. Through the two evacuation evaluation indexes, evacuation empty time and personnel evacuation path length, the contrast analysis, the model is compared with the first two models and shows the better experimental results than others.Evacuation simulation model is designed based on the cellular automata model, using the evolving rules of cellular automata to simulate the real scene of personnel evacuation process; based on the established simulation model, the use of ant colony optimization algorithm and artificial potential field for simulating personnel evacuation routes. From the above research, the second teaching building in Hubei University of Technology is utilized as the simulating object; the personnel evacuation process is simulated. And the evacuation empty time and people’s evacuation path length are optimized, the experimental results demonstrate that evacuation model based on ant colony optimization and artificial potential field has a better effect of evacuation.