论文标题
优化空间距离的室内导航政策
Optimizing Indoor Navigation Policies For Spatial Distancing
论文作者
论文摘要
在本文中，我们专注于改变运动模式和乘员的方向指导的政策的修改，这些占用者在3D模拟引擎中被表示为代理。我们展示了一种优化方法，该方法通过引入剂量的空间距离来改善导航图，从而改善空间距离度量，这是代理密度的函数（即占用）。我们的优化框架利用遗传算法和模拟退火的混合方法利用了诸如目标函数之类的指标。我们表明，在我们的框架内，模拟优化过程可以通过优化给定室内环境的导航策略来帮助改善代理之间的空间距离。
In this paper, we focus on the modification of policies that can lead to movement patterns and directional guidance of occupants, which are represented as agents in a 3D simulation engine. We demonstrate an optimization method that improves a spatial distancing metric by modifying the navigation graph by introducing a measure of spatial distancing of agents as a function of agent density (i.e., occupancy). Our optimization framework utilizes such metrics as the target function, using a hybrid approach of combining genetic algorithm and simulated annealing. We show that within our framework, the simulation-optimization process can help to improve spatial distancing between agents by optimizing the navigation policies for a given indoor environment.
