Zale Joslyn, Kar Bandana, Cochran David
Department of Geography and Geology, The University of Southern Mississippi, Hattiesburg, Mississippi.
Research Scientist, Critical Infrastructure and Climate Team, Urban Dynamics Institute, Geographic Information Science and Technology Group, Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee.
J Emerg Manag. 2018 Mar/Apr;16(2):81-93. doi: 10.5055/jem.2018.0357.
Football is culturally and economically important in the United States, and football stadiums are part of the country's critical infrastructure, thus receiving government protection against hazard events. In this project, an agent-based evacuation model was implemented to optimize evacuation time from The University of Southern Mississippi's M.M. Roberts Stadium (football) by accounting for evacuees' age, gender, physical fitness, alcohol consumption, and prior experience with hazard events. The findings revealed that (i) the age and gender of an individual impact his/her locomotion speed and (ii) evacuation route choice is influenced by evacuees' perception of its safety and effectiveness. The estimated evacuation times for all evacuees to exit only the stadium and the stadium plus the surrounding campus were 20.82 and 165.01 minutes, respectively. Both of these times were shorter than the evacuation times determined by models employing location-unspecific locomotion speeds. One-way analysis of variance revealed that there were statistically significant differences between use of location-specific and location-unspecific within-stadium evacuation times (p ≤ 0.001 with α = 0.05). These results suggest that using local data is vital to accurately estimate evacuation time.
美式足球在美国具有重要的文化和经济意义，足球场是该国关键基础设施的一部分，因此受到政府针对灾害事件的保护。在本项目中，实施了一种基于智能体的疏散模型，通过考虑疏散人员的年龄、性别、身体素质、酒精摄入量以及以往应对灾害事件的经验，来优化南密西西比大学M.M. 罗伯茨体育场（足球场）的疏散时间。研究结果表明：（i）个人的年龄和性别会影响其移动速度；（ii）疏散路线的选择受疏散人员对其安全性和有效性的认知影响。所有疏散人员仅从体育场疏散以及从体育场加周边校园疏散的估计时间分别为20.82分钟和165.01分钟。这两个时间均短于采用非特定位置移动速度的模型所确定的疏散时间。单因素方差分析表明，特定位置和非特定位置的场内疏散时间之间存在统计学上的显著差异（α = 0.05时，p≤0.001）。这些结果表明，使用本地数据对于准确估计疏散时间至关重要。
