Abstract
Emergency crowd evacuation, especially in congested indoor scenes, is an important issue in public areas’ daily management. Computer simulation is a widely adopted technique to study crowd evacuations and help design reasonable emergence plans due to its flexibility, convenience, and cost-effectiveness. In this paper, we propose ECEM, a novel evacuation model based on agent simulation. In ECEM, we consider a special individual behavior in the evacuation, called seeking behavior, which happens when relatives or friends (i.e., social groups) are in the crowd, and the members within a group may tend to seek each other once separated instead of evacuating alone. Moreover, we incorporate the crowd chaos based on Boltzmann entropy (i.e., crowd entropy) into ECEM to measure the evacuating population’s disorder level and present an adaptive velocity smoothing method using crowd entropy for updating individual’s velocity. Extensive simulation results demonstrate the effectiveness of ECEM and provide several insights on designing the evacuation strategies.
Highlights
Crowd evacuation caused by emergencies in congested indoor scenes is an important issue that is considered in the design of large buildings and the daily management of public areas
One category is the macroscopic evacuation model, including gas-kinetic model, route-choice model, and queuing model, which treats the population as a homogeneous flow [8], [9] and is efficient for large-scale crowd evacuation simulations
We propose an Entropy-based Crowd Evacuation Model, called ECEM, to evaluate the influence of the seeking behavior within social groups in the crowd evacuation
Summary
Crowd evacuation caused by emergencies in congested indoor scenes is an important issue that is considered in the design of large buildings and the daily management of public areas. B. VELOCITY CALCULATION Let {vi, pi, ei, Ci, PCi } be the attributes of an agent Ai in the evacuation, where vi denotes its velocity vector, pi is its current position, ei is the crowd entropy within its visual field (will be discussed in Section III-C), Ci is the set of its companions (Ci = ∅ if it has no companion), and PCi is the historical positions of its companions. By applying the adaptive entropy-based velocity smoothing, the evacuation model is more consistent with the realistic scenario: when the surrounding people are more chaotic, the individual behavior will be more likely to continue the previous inertial movement; on the contrary, when the surrounding people are more orderly, the individual can make more rational and appropriate decisions based on the current situation. An agent will continue the iteration until it finishes the evacuation (i.e., leave the exit)
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