text: To minimize property loss and death count in terror attacks and other emergent scenarios, attention given to timely and effective evacuation cannot be enough. Due to limited evacuation resource, i.e., number of available exits, there exists interdependence among pedestrians such as cooperation, competition and herd effect. Thus human factors - more specifically, pedestrians' behavior in emergency evacuation - play a significant role in evacuation research. Effective evacuation can only be reached when route planning are considered in conjunction with psychological dynamics, which is often ignored. As another drawback, previous research assumes the environment including available exits as stationary. However, we note that during emergency, some exits which are not often utilized in normal times are opened, which potentially helps if pedestrians are aware of them. In this paper, we analyze the effect of pedestrians' behavior, i.e., herd effect and knowledge of changing environment with Cellular Automata (CA) simulation. Results of the simulation show the harmful effect of herd effect as well as highlight the importance of timely informing pedestrians of environmental change. Accordingly, we propose policy and procedural recommendations for emergency management of large, crowded structures. Our future work includes considering more human factors and applying our model to log data provided by videos in public venues, which can further show effectiveness of our model in real scenarios.
  @cite_11: Pedestrian evacuation is one open question in a myriad of scientific disciplines and has attracted considerable attention during the past decades. Aim to issue, various research approaches, such as mathematical modeling and simulation, experimental studied and socio-psychology surveys, have been extensively employed. Different from previous frameworks, here a behavior-based cellular automaton model is proposed, which involves the environmental characteristics and neighbors' behaviors. Given the certain range of degree of emergency, it is shown that enhancing the degree of emergency will shorten evacuation time yet decrease cooperation enthusiasm. The larger the degree of familiarity is, the shorter the evacuation time will be. In variance, larger the dependence of pedestrians will prolong the evacuation time. Besides, the novel model also produces some interesting self-organization phenomena, such as the collective behavior at the beginning of the evacuation and arch-like blocking at the end of the evacuation. When our model is finally applied to the evacuation scenario where a room has two symmetrically located exits, the symmetry breaking effect takes place. Our model may shed new light to the study of pedestrian dynamics in realistic world.
summary: @cite_11 proposes a behavior-based cellular automaton (CA) model for pedestrian dynamics and show that for a given range of emergency degree, the enlarged emergency degree can shorten the evacuation time yet depresses cooperation enthusiasm. On the contrary, as dependence (familiarity) of pedestrians increases, the evacuation time and the fraction of cooperation increase.