论文标题
基于贝叶斯纳什平衡的行人疏散的基于代理的模拟模型
An agent-based simulation model of pedestrian evacuation based on Bayesian Nash Equilibrium
论文作者
论文摘要
这项研究将贝叶斯游戏理论纳入了基于代理的模型中的人行道疏散。比较了三种行人行为：随机跟随，最短路线和贝叶斯nash平衡（BNE），以及这些均衡。结果表明，BNE的行人能够在预测下一步的交通拥堵水平并调整方向以避免交通拥堵的情况下更快地撤离，与现实中撤离行人的行为紧密相匹配。进行了一系列模拟实验，以评估BNE是否以及如何影响行人疏散程序。结果表明：1）BNE对减少疏散时间的影响很大； 2）BNE行人表现出更聪明，有效的撤离行为； 3）随着BNE使用者的比例上升，平均疏散时间减少，平均舒适度增加。本文提供了模型和相关实验结果的详细描述。还确定了一些局限性以及进一步的工作。
This research incorporates Bayesian game theory into pedestrian evacuation in an agent-based model. Three pedestrian behaviours were compared: Random Follow, Shortest Route and Bayesian Nash Equilibrium (BNE), as well as combinations of these. The results showed that BNE pedestrians were able to evacuate more quickly as they predict congestion levels in their next step and adjust their directions to avoid congestion, closely matching the behaviours of evacuating pedestrians in reality. A series of simulation experiments were conducted to evaluate whether and how BNE affects pedestrian evacuation procedures. The results showed that: 1) BNE has a large impact on reducing evacuation time; 2) BNE pedestrians displayed more intelligent and efficient evacuating behaviours; 3) As the proportion of BNE users rises, average evacuation time decreases, and average comfort level increases. A detailed description of the model and relevant experimental results is provided in this paper. Several limitations as well as further works are also identified.
