Heatstroke is becoming an increasingly serious threat to outdoor activities, especially, at the time of large events organized during summer, including the Olympic Games or various types of happenings in amusement parks like Disneyland or other popular venues. The risk of heatstroke is naturally affected by a high temperature, but it is also dependent on various other contextual factors such as the presence of shaded areas along traveling routes or the distribution of relief stations. The purpose of the study is to develop a method to reduce the heatstroke risk of pedestrians for large outdoor events by optimizing relief station placement, volume scheduling and route. Our experiments conducted on the planned site of the Tokyo Olympics and simulated during the two weeks of the Olympics schedule indicate that planning routes and setting relief stations with our proposed optimization model could effectively reduce heatstroke risk. Besides, the results show that supply volume scheduling optimization can further reduce the risk of heatstroke. The route with the shortest length may not be the route with the least risk, relief station and physical environment need to be considered and the proposed method can balance these factors. This study proposed a novel emergency service problem that can be applied in large outdoor event scenarios with multiple walking flows. To solve the problem, an effective method is developed and evaluates the heatstroke risk in outdoor space by utilizing context-aware indicators which are determined by large and heterogeneous data including facilities, road networks and street view images. We propose a Mixed Integer Nonlinear Programming model for optimizing routes of pedestrians, determining the location of relief stations and the supply volume in each relief station. The proposed method can help organizers better prepare for the event and pedestrians participate in the event more safely.

中文翻译：

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大型户外活动的情景感知中暑救灾站位置和路线优化

中暑正日益成为户外活动的严重威胁，特别是在夏季举办大型活动时，包括奥运会或迪士尼乐园或其他热门场所等游乐园中发生的各种事件。中暑的风险自然会受到高温的影响，但它还取决于其他各种环境因素，例如行驶路线上存在阴影区域或救济站的分布。该研究的目的是开发一种方法，以通过优化救援站的位置，安排交通量和路线来减少大型户外活动中行人的中暑风险。我们在东京奥运会计划的场地上进行的实验以及在奥运会计划的两周内进行的模拟表明，使用我们提出的优化模型来规划路线和设置救援站可以有效降低中暑的风险。结果表明，供应量调度的优化可以进一步降低中暑的风险。长度最短的路线可能不是风险最小的路线，需要考虑救济站和自然环境，所提出的方法可以平衡这些因素。这项研究提出了一种新颖的紧急服务问题，该问题可以应用在具有多个人流的大型户外事件场景中。为了解决这个问题 开发了一种有效的方法，并利用情境感知指标来评估室外空间中暑的风险，该情境感知指标是由大型，异构数据（包括设施，道路网络和街景图像）确定的。我们提出了一种混合整数非线性规划模型，用于优化行人的路线，确定救济站的位置以及每个救济站的供应量。所提出的方法可以帮助组织者更好地为活动做准备，并使行人更安全地参加活动。