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Fengqiang Gao

Publications and source records attributed to Fengqiang Gao.

2 recordsLinked to original sources

Effect of density control in partially observable asymmetric-exit evacuation under guidance: Strategic suggestion under time delay

To enhance the evacuation efficiency in partially observable asymmetric-exit evacuation under guidance, a general framework of the dynamic guiding assistant system is presented to investigate the effect of density control. In this framework, several evacuation assistants are established to observe the partial information of pedestrians' location and adjust the guiding signals of the dynamic guiding assistant systems. A simple on-off-based density control algorithm is proposed for the evacuation assistants according to the delayed data of the observed information (i.e., pedestrian densities in the observed regions near the corresponding exits). This paper provides strategic suggestions on how to set the observed region and the target density by involving a force-driven cellular automaton model. It is observed that the proposed density control algorithm can control (positively affect) the global distribution of the pedestrians' locations and suppress arching phenomena in the evacuation process even using the observed partial information under time delays. By imposing a moderate target density, the dynamic guiding assistant system also suppresses the triggers of collisions around the exits and avoids inefficiently separating the pedestrians. To enhance evacuation efficiency, we reveal an interesting fact without loss of generality that we only need to observe the pedestrians' location from a small region near the exit instead of a large region when the time delay of the observed information is slight enough. Our numerical findings are expected to provide new insights into designing computer-aided guiding strategies in real evacuations.

physics.soc-ph

Variable guiding strategies in multi-exits evacuation: Pursuing balanced pedestrian densities

Evacuation assistants and their guiding strategies play an important role in the multi-exits pedestrian evacuation. To investigate the effect of guiding strategies on evacuation efficiency, we propose a force-driven cellular automaton model with adjustable guiding attractions imposed by the evacuation assistants located in the exits. In this model, each of the evacuation assistants tries to attract the pedestrians in the evacuation space towards its own exit by sending a quantifiable guiding signal, which may be adjusted according to the values of pedestrian density near the exit. The effects of guiding strategies pursuing balanced pedestrian densities are studied. It is observed that the unbalanced pedestrian distribution is mainly yielded by a snowballing effect generated from the mutual attractions among the pedestrians, and can be suppressed by controlling the pedestrian densities around the exits. We also reveal an interesting fact that given a moderate target density value, the density control for the partial regions (near the exits) could yield a global effect for balancing the pedestrians in the rest of the regions and hence improve the evacuation efficiency. Our findings may contribute to give new insight into designing effective guiding strategies in the realistic evacuation process.

physics.soc-ph