Crowd Behavior Simulation And Evacuation Based On Path Planning Algorithm

Since the beginning of the new century,the living standards of residents have significantly improved,and large-scale gathering activities are also increasing.This has brought enormous pressure to public places in cities,especially schools,subways,shopping malls,and other places that are often overcrowded.It is extremely important to quickly take corresponding measures or predict potential unexpected accidents in advance when accidents occur.Organizing volunteers for evacuation exercises poses safety risks and is not reusable.Therefore,simulating evacuation behavior in corresponding scenarios through computer simulation technology has important reference value for preventing potential sudden disasters in crowd gathering places and how to scientifically and effectively disperse crowds in case of emergencies.In the research of crowd evacuation simulation,it is more important to make the simulation results more natural than to make them conform to statistical characteristics.This article mainly studies the impact of crowd heterogeneity,chaos,and crowding degree on evacuation during the evacuation process.The social force model is widely used in crowd evacuation research due to its excellent performance in the interaction between pedestrians and the environment.However,traditional social force models treat all pedestrians as independent homogeneous particles,lacking representation of heterogeneous pedestrians and crowded populations.Moreover,they lack a routing mechanism,which leads to simulated populations falling into local minima in complex scenarios.To improve the rationality of the simulation,this paper is based on the social force model,Combine fractional order potential fields and path planning algorithms to solve the above two problems.The main research work and innovative points of this article are as follows:1.Classify heterogeneous populations,assign different attributes to heterogeneous pedestrians,and combine fractional potential fields to generate different potential forces for different heterogeneous pedestrians.Then,combine this potential force into a social force model to propose a driving mechanism that considers heterogeneous pedestrians.This driving mechanism allows pedestrians to retain the advantages of the social force model in the interaction between pedestrians and the environment during the evacuation process,The characterization of heterogeneous pedestrians has also been added.2.Use velocity entropy to describe the degree of crowd chaos and quantitatively describe the impact of crowd congestion on path planning based on congestion cost.Combining the degree of chaos,congestion,and the cost function of the A * algorithm to construct a routing mechanism,in order to plan a shortest path that avoids chaos and congestion as much as possible.3.A reprogramming mechanism based on speed entropy and spatiotemporal congestion is proposed,which makes the routing mechanism in this paper meet real-time requirements and improves the disadvantage of traditional A * algorithm as a static algorithm that does not meet realtime changes in the scene.The simulation results show that the crowd evacuation method proposed in this article not only improves the problem of the lack of pathfinding mechanism in the social force model,but also considers the impact of crowd heterogeneity and crowding on the evacuation path.Through analysis of evacuation data,the following conclusions are drawn: as the number of exits increases,the probability of crowd chaos and crowding decreases,and the impact of crowd heterogeneity and pedestrian interaction on crowd evacuation simulation decreases,The importance of pathfinding mechanisms has also decreased.This article aims to discover potential hazards during the actual evacuation process based on simulation results,in order to take corresponding preventive measures in advance.