The University of Tokyo, Kashiwanoha 5-1-5, Kashiwa, 277-0882, Japan.
Xi'an Jiaotong University, 28 Xianning West Road, Xi'an, 710049, Shaanxi, China.
Int J Health Geogr. 2021 May 25;20(1):23. doi: 10.1186/s12942-021-00275-z.
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.
中暑对户外活动来说是一个日益严重的威胁，尤其是在夏季举办大型活动期间，例如奥运会或迪士尼乐园或其他热门场馆的各种游乐园活动。中暑的风险不仅受高温的影响，还取决于其他各种环境因素，例如旅行路线上是否有遮荫区或救援站的分布情况。本研究旨在通过优化救援站的位置、容量调度和路线，开发一种降低大型户外活动中行人中暑风险的方法。
我们在东京奥运会的规划场地进行的实验以及在奥运会两周期间进行的模拟表明，使用我们提出的优化模型规划路线和设置救援站可以有效降低中暑风险。此外，结果表明，供应容量调度优化可以进一步降低中暑风险。最短长度的路线不一定是风险最小的路线，需要考虑救援站和物理环境，而提出的方法可以平衡这些因素。
本研究提出了一种新的紧急服务问题，可以应用于具有多个步行流的大型户外活动场景。为了解决这个问题，我们开发了一种有效的方法，并利用包括设施、道路网络和街景图像在内的大型和异构数据来确定户外空间的中暑风险。我们提出了一个混合整数非线性规划模型，用于优化行人的路线、确定救援站的位置和每个救援站的供应容量。该方法可以帮助组织者更好地为活动做准备，使行人更安全地参与活动。
