Research On Modeling And Simulation Of Crowd Distribution Based On Interest Model

In recent years,with the development of China's urbanization process,large public places gradually rise,provides an important guarantee for the people's social activities.Meanwhile,with the improvement of people's living standards,the travel frequency of people increased gradually,pedestrian scale within various public places have gradually increased,especially when it comes to the peak commute in the morning and evening,large gatherings in the major festivals,sporting events or other cultural public events,the crowd inside the facilities are often in dense and crowded state.When the high intensity of the groups inside the building,pedestrian flow interwoven and squeezing each other,small perturbations may cause people to enter an unstable state.If you cannot prevent and control effectively in advance,could easily lead to trample and the other accidents.Therefore,in-depth and meticulous research on the behavior of shunt crowd,more reasonable restrictions on large establishments Stroke is one of the important ways to ensure the safety and reduce the malignant accidents.This topic takes individual interest as the main point of entry,and models to generate SELID interest model,combined with the famous character analysis method Five Model Big,synthesize the macro and micro layers of the crowd behavior in the process of shunt to model and analyze comprehensively in the scene of simulation,research the dynamic fluid characteristic of the crowd behavior in the process of shunt in-depth,obtain behavior characteristics and fluid characteristics of the pedestrian,grasp the movement of pedestrians,put forward specific guidelines to improve the crowd shunt,thus provide the basis for manager to plan a large place.Deployment tests show that,in this paper,the system can achieve design features,good performance and stable operation.The deployment of the application,will enable large-scale public places crowd segregation phenomenon to be improved,and provide a solid and reliable scientific basis for the prevention and management of large-scale group injury event.