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.
翻译:这项研究将贝叶西亚游戏理论纳入代理人型的行人后送模式中。比较了三种行人行为:随机跟踪、最短路线和巴伊西亚纳什平衡(BNE)以及这些组合。结果显示,BNE行人能够更快地撤离,因为他们预测了下一步的拥挤程度,并调整了方向以避免拥挤,与实际中撤离行人的行为密切匹配。进行了一系列模拟实验,以评价行人后送程序是否以及如何受到影响。结果显示:1) BNE对减少疏散时间有重大影响;2) BNE行人表现出更聪明、更有效的疏散行为;3) BNE用户比例上升、平均疏散时间减少和平均舒适程度增加。本文详细介绍了模型和相关实验结果。还确定了若干限制和进一步工程。