Research On Virtual Crowd Path Planning Method Based On Swarm Intelligence

In recent years, economic, social and cultural aspects are developed continuously. The more rapid the process of urbanization is, the more prominent the problems and advantages are. Either rehearsal of group calisthenics or safety emergency drills is costing and difficult. The appearance of computer simulation technology could overcome the shortcomings of traditional methods. Computer technology could simulate crowd behavior with a quick and safe way. It provides an effective means of high-tech tools to solve this problem.The crowd simulation in virtual scene includes environment modeling, path planning and crowd motion simulation. Aiming at the problems of high cost and large amount of information, the paper proposed an environment modeling based on cellular automaton or topology structure. According to different types of scenes, these methods could extract and storage information which are required in process of path planning. They meet the requirements of high accuracy and high precision. At present, the more extensive research method of path planning exist the problems of slow convergence speed, cannot support large scale population, ignore the relationship between group members of the crowd motion, and so on. Therefore, aiming at these problems, this paper introduced a global path planning algorithm based on swarm intelligence algorithm and a local path planning algorithm based on social force model. They are applied to the gymnastics program arrangement and safety emergency drills under virtual scene.The main work and innovation of this paper are summarized as follows:1. The multi-objective particle swarm optimization algorithm based on cellular automata, called MOPSO-CA for short, is proposed to plan global path. The simple rule scene would be divided into amounts of cellular spaces. In this way, the problem of complex process and large amount of information can be solved. The collision avoidance process is improved to detect the state of neighbor cellular space. It can reduce the complexity of the algorithm and improve the performance of the algorithm.2. Path planning method based on topology and artificial bee colony algorithm, called TP-ABC for short, are proposed to plan global path. In TP-ABC, the environment modeling based on topology structure is applied. In process of path planning, the lead selection mechanism and multi-factor fitness evaluation mechanism are improved. It takes costs and crowding into consideration. The perception ability of the crowd to the real time state is improved. The crowd motions would be simulated more actually.3. A novel crowd evacuation model based on grouping and guiding is proposed. The improved model optimized leader's speed adjustment mechanism, pedestrian's trend selecting strategy and added relationship attractive force. This proposed model can realize the phenomenon that pedestrians who have intimate relationships with others will get together gradually in process of crowd evacuation. It provides a reference to solve the problem that pedestrians would cooperate and coordinate with each other in the process of movement.Combined with corresponding research project, we applied the above theory to the design of scene modeling and crowd simulation in the crowd motion modeling and simulation system. There are four modular such as scene modeling, semantic extraction, path planning and photorealistic rendering in this system. With the help of this system, we have a research on crowd simulation in the situation either rehearsal of group calisthenics or safety emergency drills. Through crowd simulation experiments and analysis on this system, we conclude the impacts of population density, group relationship and the count of exit on evacuation time. Experiments show that the method proposed in this paper is practical and efficient.