论文标题
使用增强现实设备的拥堵感知疏散路线
Congestion-aware Evacuation Routing using Augmented Reality Devices
论文作者
论文摘要
我们提出了一种用于室内疏散的拥拥式路由解决方案,该解决方案在多个目的地之间产生了实时的个人疏散路线,同时可以跟踪所有撤离者的位置。人口密度图通过从用户端增强现实(AR)设备汇总的撤离器位置来实现的人口密度图用于建模建筑物内的拥塞分布。为了有效地搜索所有目的地之间的疏散路线,设计了一种算法的变体,以在单个通过中获得最佳解决方案。在一系列模拟研究中,我们表明,与经典路径计划算法相比,所提出的算法在计算中更优化。它为每个人产生了更及时的疏散路线,以最大程度地减少整体拥塞。使用AR设备的完整系统用于在现实世界环境中进行试点研究,以证明所提出的方法的功效。
We present a congestion-aware routing solution for indoor evacuation, which produces real-time individual-customized evacuation routes among multiple destinations while keeping tracks of all evacuees' locations. A population density map, obtained on-the-fly by aggregating locations of evacuees from user-end Augmented Reality (AR) devices, is used to model the congestion distribution inside a building. To efficiently search the evacuation route among all destinations, a variant of A* algorithm is devised to obtain the optimal solution in a single pass. In a series of simulated studies, we show that the proposed algorithm is more computationally optimized compared to classic path planning algorithms; it generates a more time-efficient evacuation route for each individual that minimizes the overall congestion. A complete system using AR devices is implemented for a pilot study in real-world environments, demonstrating the efficacy of the proposed approach.