Using agent-based modeling to evaluate the effects of Hurricane Sandy’s recovery timeline on the ability to work
Using agent-based modeling to evaluate the effects of Hurricane Sandy’s recovery timeline on the ability to work
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DOI：
10.1016/j.trd.2019.08.011
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发表时间：
2019-12
影响因子：
7.6
通讯作者：
Elham Hajhashemi;Pamela M. Murray-Tuite;Susan Hotle;K. Wernstedt
中科院分区：
文献类型：
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作者：
Elham Hajhashemi;Pamela M. Murray-Tuite;Susan Hotle;K. Wernstedt
2012年，飓风桑迪严重破坏了纽约市地区的交通系统、电力系统、工作场所和学校。本研究使用纽约市大都会区居民的调查响应，开发了一个基于代理的模型，描述了中断后的通勤出行行为和适应。测试了六种情况，以量化哪些系统对于更早恢复生产力（定义为雇主工作的能力）更重要。建议的系统恢复顺序取决于正常通勤行为的模式。在纽约大都会地区，通勤者使用交通工具通勤的比例比美国任何其他大都市地区都要大。这导致模型表明地铁/铁路系统的恢复是使大多数人恢复生产力的最重要因素。第二个最重要的因素是广泛的电力恢复本身，这使得居民在等待交通系统恢复时可以远程工作。下一个最重要的因素是学校和日托中心（以及相关的基础设施系统）的重新开放，使父母能够通勤。使用基于代理的模型测试的其余加速系统恢复场景比基线更快地恢复生产力，但程度低于地铁/铁路，电力和儿童保育系统场景。对恢复情况的进一步分析表明，与收入较低的家庭相比，年收入较高的家庭从电力恢复中受益更多。此外，恢复方案的有效性可能因居住地点和该地点的中断程度而异。
Hurricane Sandy greatly disrupted the New York City (NYC) region’s transportation systems, electric power systems, work locations, and schools in 2012. This study uses survey responses from NYC Metropolitan Area residents to develop an agent-based model that depicts commuter travel behavior and adaptation after the disruption. Six scenarios were tested to quantify which systems were more critical to recover for an earlier return to productivity - defined as the ability to work for one’s employer. The recommended system restoration order depends on the pattern of normal commuting behavior. In the NYC Metropolitan Area, a larger share of commuters use transit to commute than in any other US metropolitan area. This resulted in the model indicating the subway/rail system recovery as the most important factor for returning the most people to productivity. The second most important factor is widespread power restoration itself, which allows residents to telework while waiting for the transportation system to recover. The next most important factor is the reopening of schools and daycares (with associated infrastructure systems), freeing parents to commute. The remaining expedited system recovery scenarios tested using the agent-based model resulted in a faster return to productivity than the baseline, but to a lesser degree than the subway/rail, power, and childcare systems scenarios. Additional analysis of recovery shows that households with higher annual income benefit more from power recovery compared to those with lower incomes. Moreover, the effectiveness of recovery scenarios can differ based on residential location and the extent of disruption in that location.