基于情绪决定模型的路径选择行为模拟

Meng Shi, Eric Wai Ming Lee, R. Cao, Yi Ma, Wei Xie
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引用次数: 0

摘要

提出了一种新的基于不耐烦的路径选择仿真模型。引入了自生长率和不耐传播速度两个参数来计算动态不耐水平。通过综合考虑距离、出口周围的密度和不耐烦程度来确定目标细胞。在每一个时间步,行人会根据他们不耐烦程度的降序依次进入目标单元。为了检验该模型的可行性,我们将该模型应用于典型场景(即有两个出口的方形房间),并对两个模型参数进行敏感性分析。仿真结果表明,该模型可以成功地再现典型的集体行为(即堵塞)。与以往只考虑距离的模型相比,该模型充分利用了两个出口,提高了疏散效率。参数分析结果表明,在该仿真场景中,自生长速度是主导因素。随着自生长速率的增大,疏散时间缩短。此外,疏散时间与最大不耐烦程度的散点图显示,不不耐烦和过高的不耐烦程度都会导致疏散时间的增加。通过不耐烦确定模型与Pathfinder模型的比较,说明不耐烦确定模型使得疏散过程更加平滑,该模型适用于多出口疏散过程的预测。
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The Simulation of Route Choice Behaviour with an Emotion-determined Model
This study presents a novel impatience-based model on the route choice simulations. Two parameters: self-growth rate and propagation speed of impatience are introduced to calculate the dynamic impatience level. The target cell is determined by comprehensively considering distance, density around exits, and the impatience level. At each time step, pedestrians will move into the target cell in turn depending on the descending order of their impatience level. To test the feasibility of this model, we apply this model into the typical scenario (i.e., square room with two exits) and conduct the sensitivity analysis of two model parameters. The simulation results illustrate that this proposed model can successfully reproduce typical collective behaviour (i.e., clogging). Compared with the previous model in which only distance is considered, this model has two exits fully used and then improves evacuation efficiency. The parameter analysis results show that in this simulation scenario, self-growth speed is the dominated factor. With the increase of self-growth rate, evacuation time is shortened. In addition, scatter plots of evacuation time against maximum impatience level shows both no impatience and an excessive impatience level will lead to an increase in evacuation time. The comparison between impatience-determined model and Pathfinder illustrates the impatience-determined model leads to a smoother evacuation process, and this model is applicable in predicting the evacuation process with multiple exits.
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