使用以情感為基礎的細胞自動機進行人群疏散模擬

Simulation of Crowd Evacuation Using an Emotion-Based Cellular Automata Model

在本文中，我們提出了一種新穎的急躁模型，其中急躁程度隨著時間的推移而動態變化。本研究使用定量公式以計算考量自我增長和急躁情緒傳播的動態急躁程度。與使用隨機更新序列或固定序列的傳統方法不同。在每個時間階段，所有行人將依據急躁程度移動到目標細胞。動態急躁模型在細胞自動機模型中呈現，其中空間和時間被離散化以模擬人群疏散過程。 本研究亦執行數值模擬，以證明該模型的可行性。模擬結果顯示，該模型可以成功地再現典型的集體行為（例如，堵塞現象）。本研究亦對動力學增長和傳播速度進行了參數靈敏度研究。結果顯示，隨著情緒傳播速度的增加，疏散效率最初急劇提升，但後續效率開始下降。另一個發現是，在某些程度之中，急躁情緒傳播的最大不耐煩程度會低於情緒未傳播的情況。這一結果顯示溝通可以在一定程度上緩解不良情緒。此外，心理上的不耐煩並非總是對疏散移動效率不利。在低急躁值時，急躁程度的提高可以提高疏散效率，而在較高的急躁程度下，隨著急躁程度的增加，疏散效率反而不斷下降。這些發現可以提供對動態疏散過程的新見解，並將有助於合理地控制和引導人群情緒（例如，急躁程度）。

 

In this paper, we present a novel impatience model where impatience level dynamically changes with time. Quantitative formulas are introduced to calculate the dynamic impatience level considering both self-growth and the impatience propagation. Unlike conventional methods using either random updated sequence or fixed sequence. At each time step, all the pedestrians will move to the target cell depending on the impatience level. The dynamic impatience model is implemented in Cellular Automata model where space and time are discretized to simulate the crowd evacuation process. Numerical simulations are conducted to demonstrate the feasibility of this model. The simulation results show that this model can successfully reproduce typical collective behavior (e.g., clogging phenomenon). We also performed parameter sensitivity study of the dynamics growth and the propagation speed. Results show that with the increase of propagation speed, the evacuation efficiency is initially promoted sharply and the efficiency begins to decline. Another finding is the psychological impatience is not always negative to the moving efficiency. At low impatience value, the increase of the impatience level can improve the evacuation efficiency, while at higher impatience value, the evacuation efficiency drops continuously with the increase of impatience level. These findings will be helpful to control pedestrian emotion (e.g.,impatience level) effectively.