A Simulation Model for Pedestrian Crowd Evacuation Based on Various AI Techniques
This work addresses building evacuation system design, but it is incremental as it combines existing AI techniques without introducing a new paradigm.
The paper tackled pedestrian crowd evacuation by designing an intelligent simulation model that integrates cellular automata with fuzzy logic, KNN, and statistical equations, and it showed the model can predict evacuation time and emergency behavior in various building interiors and pedestrian distributions.
This paper attempts to design an intelligent simulation model for pedestrian crowd evacuation. For this purpose, the cellular automata(CA) was fully integrated with fuzzy logic, the kth nearest neighbors (KNN), and some statistical equations. In this model, each pedestrian was assigned a specific speed, according to his/her physical, biological and emotional features. The emergency behavior and evacuation efficiency of each pedestrian were evaluated by coupling his or her speed with various elements, such as environment, pedestrian distribution and familiarity with the exits. These elements all have great impacts on the evacuation process. Several experiments were carried out to verify the performance of the model in different emergency scenarios. The results show that the proposed model can predict the evacuation time and emergency behavior in various types of building interiors and pedestrian distributions. The research provides a good reference to the design of building evacuation systems.