Context-aware heatstroke relief station placement and route optimization for large outdoor events

International Journal of Health Geographics

Adam Jatowt¹  Kyoung-Sook Kim¹  Ryosuke Shibasaki²  Haoran Zhang²  Tianqi Xia²  Yan Wu²  Xiao Feng³ 

[1] National Institute of Advanced Industrial Science and Technology;The University of Tokyo;Xi’an Jiaotong University;

关键词: Optimization;    Context-aware;    Pedestrian flow;    Olympic games;   

DOI  :  10.1186/s12942-021-00275-z

来源: DOAJ

【 摘 要 】

Abstract Background 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. Results 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. Conclusions 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.

【 授权许可】

Unknown