A dynamic impatience-determined cellular automata model for evacuation dynamics

In this paper, a novel impatience-determined model was proposed for qualitative and quantitative characterization of the impatience level during evacuation. We firstly developed a comprehensive algorithm to calculate the dynamic impatience level considering both the self-growth and the impatience propagation among pedestrians. More specifically, unlike the traditional methods using randomly generated update sequence or fixed sequence, in this model, each pedestrian moves to the target cell in turn for each time step depending on the descending order of their impatience level. As a proof of principle, we initially implemented it to cellular automata model and performed parameter sensitivity study of self-growth rate and impatience propagation speed. The result shows that the impatience propagation only promotes the evacuation efficiency when the self-growth rate of impatience is relatively low. When the impatience and patience pedestrians are mixed, the evacuation time can be shortened and then the efficiency can be improved compared with every pedestrian in patience. Note that, any excessive impatience level or insufficient impatience level will lead to the increase of evacuation time. In addition, the investigation toward obstacles shows reasonably placing the obstacles can reduce the impatience propagation among pedestrians and then improve the evacuation efficiency.