Agent-Based Simulation of Crowd Evacuation Through Complex Spaces

In this paper, we have developed a description of an agent-based model for simulating the evacuation of crowds from complex physical spaces for escaping dangerous situations.The model describes a physical space containing a set of differently shaped fences, and obstacles, and an exit door.The pedestrians comprising the crowd and moving in this space in order to be evacuated are described as intelligent agents with supervised machine learning using perception-based data to perceive a particular environment differently.The description of this model is developed with the Python language where its execution represents its simulation.Before the simulation, the model can be validated using an animation written with the same language to fix possible problems in the model description.A model performance evaluation is presented using an analysis of simulation results, showing that these results are very encouraging.