论文标题
解决冠状病毒大流行期间飞机乘客登机问题的分析方法
Analytical approach to solve the problem of aircraft passenger boarding during the coronavirus pandemic
论文作者
论文摘要
我们使用随机蜂窝自动机模型设计了一种最佳的组登机方法，用于乘客运动，该模型通过病毒传播方法扩展。此外，开发了一个新的数学模型，以确定组的适当座位布局。拟议的座位布局是基于允许小组成员保持密切联系的想法，并且小组应彼此之间有距离。单个传输速率的总和被视为具有低级别传输风险的方案的目标函数。确定适当的座椅布局后，蜂窝自动机被用于得出和评估相应的登机序列，以涉及短登机时间和病毒传播的低风险。我们发现，在大流行的情况下，对群体的考虑将显着导致更快的登机（将时间减少约60％）和更少的传播风险（减少了85％），这在流行前场景中达到了登机时间水平。
We design an optimal group boarding method using a stochastic cellular automata model for passenger movements, which is extended by a virus transmission approach. Furthermore, a new mathematical model is developed to determine an appropriate seat layout for groups. The proposed seating layout is based on the idea that group members are allowed to have close contact and that groups should have a distance among each other. The sum of individual transmission rates is taken as the objective function to derive scenarios with a low level transmission risk. After the determination of an appropriate seat layout, the cellular automata is used to derive and evaluate a corresponding boarding sequence aiming at both short boarding times and low risk of virus transmission. We find that the consideration of groups in a pandemic scenario will significantly contribute to a faster boarding (reduction of time by about 60%) and less transmission risk (reduced by 85%), which reaches the level of boarding times in pre-pandemic scenarios.
