Pedestrian Flow Optimization to Reduce the Risk of Crowd Disasters Through Human–Robot Interaction
Pedestrian Flow Optimization to Reduce the Risk of Crowd Disasters Through Human–Robot Interaction
复制标题
DOI：
10.1109/tetci.2019.2930249
复制
发表时间：
2020-06
影响因子：
5.3
通讯作者：
Chao Jiang;Z. Ni;Yi Guo;Haibo He
中科院分区：
文献类型：
--
作者：
Chao Jiang;Z. Ni;Yi Guo;Haibo He
在人口密集或拥挤区域，行人流由于个体竞争行为的影响，往往呈现不规则或湍流的运动状态，降低了流动效率，增加了发生人群事故的风险。有效的人流调控策略对人流优化具有重要价值。现有的研究寻求优化设计的室内建筑特色和空间布局的行人设施的流动优化的目的。然而，一旦放置，固定设施不适应实时流量变化。在本文中，我们研究的问题，调节两个合并的行人流在一个瓶颈区使用移动的机器人之间的行人流移动。在行人集体运动过程中，通过动态人机交互（HRI）来调节行人流量。我们采用自适应动态规划（ADP）的方法来学习的最佳运动参数的机器人在真实的时间，并通过瓶颈的流出最大化与人群压力减少，以避免潜在的人群灾难。该算法是一种数据驱动的方法，只使用摄像机观察的行人流量没有明确的行人动力学模型和HRI。在MATLAB和机器人仿真器中进行了广泛的仿真研究，以验证所提出的方法和评估性能。
Pedestrian flow in densely populated or congested areas usually presents irregular or turbulent motion state due to competitive behaviors of individual pedestrians, which reduces flow efficiency and raises the risk of crowd accidents. Effective pedestrian flow regulation strategies are highly valuable for flow optimization. Existing studies seek for optimal design of indoor architectural features and spatial placement of pedestrian facilities for the purpose of flow optimization. However, once placed, the stationary facilities are not adaptive to real-time flow changes. In this paper, we investigate the problem of regulating two merging pedestrian flows in a bottleneck area using a mobile robot moving among the pedestrian flows. The pedestrian flows are regulated through dynamic human-robot interaction (HRI) during their collective motion. We adopt an adaptive dynamic programming (ADP) method to learn the optimal motion parameters of the robot in real time, and the resulting outflow through the bottleneck is maximized with the crowd pressure reduced to avoid potential crowd disasters. The proposed algorithm is a data-driven approach that only uses camera observation of pedestrian flows without explicit models of pedestrian dynamics and HRI. Extensive simulation studies are performed in both MATLAB and a robotic simulator to verify the proposed approach and evaluate the performances.