论文标题
使用救援指南将人群从复杂建筑物中的人群降至最低
Minimizing the evacuation time of a crowd from a complex building using rescue guides
论文作者
论文摘要
在紧急情况下，如果没有工作的疏散计划，从复杂建筑物中撤离大型人群可能会变得缓慢甚至危险。将人群带出建筑物的救援指南的使用可以提高疏散效率。一个重要的问题是如何选择这些指南的数量，位置和退出任务，以最大程度地减少人群的疏散时间。在这里，我们将疏散的人群建模为一种多代理系统，并使用社会力量模型以及对指南及其追随者的简单互动规则。我们制定了使用救援指南作为随机控制问题最小化疏散时间的问题。然后，我们通过结合数值模拟和遗传算法（GA）的程序来解决它。 GA迭代地搜索最佳撤离计划，而数值模拟评估了计划的撤离时间。我们将程序应用于测试案例和虚构会议大楼的撤离。该过程能够在单个复杂的优化中解决指南数量，其初始位置和退出分配。所达到的结果表明，该过程会融合到最佳撤离计划，该计划可以最大程度地减少疏散时间并减轻拥塞以及随机偏差在代理运动中的影响。
In an emergency situation, the evacuation of a large crowd from a complex building can become slow or even dangerous without a working evacuation plan. The use of rescue guides that lead the crowd out of the building can improve the evacuation efficiency. An important issue is how to choose the number, positions, and exit assignments of these guides to minimize the evacuation time of the crowd. Here, we model the evacuating crowd as a multi-agent system with the social force model and simple interaction rules for guides and their followers. We formulate the problem of minimizing the evacuation time using rescue guides as a stochastic control problem. Then, we solve it with a procedure combining numerical simulation and a genetic algorithm (GA). The GA iteratively searches for the optimal evacuation plan, while numerical simulations evaluate the evacuation time of the plans. We apply the procedure on a test case and on an evacuation of a fictional conference building. The procedure is able to solve the number of guides, their initial positions and exit assignments in a single although complicated optimization. The attained results show that the procedure converges to an optimal evacuation plan, which minimizes the evacuation time and mitigates congestion and the effect of random deviations in agents' motion.
