arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2007.00509physics.soc-ph
收藏

使用救援指南最小化人群从复杂建筑物的疏散时间

Minimizing the evacuation time of a crowd from a complex building using rescue guides

Anton von Schantz, Harri Ehtamo

摘要:

在紧急情况下,如果没有有效的疏散计划,从复杂的建筑物中疏散大量人群可能会变得缓慢甚至危险。使用引导人群离开建筑物的救援指南可以提高疏散效率。一个重要的问题是如何选择这些指南的数量,位置和出口分配,以最大限度地减少人群的疏散时间。在这里,我们模拟疏散人群作为一个多智能体系统的社会力量模型和简单的互动规则的指南和他们的追随者。我们制定的问题,最大限度地减少疏散时间,使用救援指南作为一个随机控制问题。然后,我们解决了它的程序相结合的数值模拟和遗传算法(GA)。遗传算法迭代搜索最优疏散方案,而数值模拟评估疏散时间的计划。我们应用程序的一个测试案例和一个虚构的会议大楼的疏散。该程序能够解决的数量的指南,他们的初始位置和出口分配在一个单一的,但复杂的优化。结果表明,该方法收敛于最优疏散方案,使疏散时间最短,缓解了拥挤和智能体运动随机偏差的影响。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑