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A discrete element crowd model is coupled with a dynamical system.
In this paper a discrete element crowd model is coupled with a dynamic bridge model in a time-stepping framework.
Furthermore, this guided crowd model is applied to the simulation system of Beijing South Railway Station for predictive evacuation experiments.
This guided crowd model is validated by explicitly comparing its density speed and density flow diagrams with fundamental diagrams.
In the present paper, a detailed crowd model is applied to investigate the impact of vertical human-structure interaction (HSI) on the dynamic response of footbridges to pedestrian excitation.
The controller of moving target crowd model is composed of crowd model and mapping model.
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One important issue in crowd modeling is model calibration through parameter tuning, so as to produce desired crowd behaviors.
The moving target crowd models are extended to the control problem of the moving optimization of the mapping object according to the prediction, optimization, and correction.
According to the method of Fig. 3, based on mobile positioning and crowd control, crowd optimization model is obtained for predicting and optimizing the moving goal, as well as the crowd acquisition.
Crowd mapping model is based on the combination of end-to-end wireless path and crowd cloud propagation path.
The crowd dynamics model is based on simulating the global movement of each individual under the influence of the surrounding crowd.
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