Collaborative Research: Flexible Multi-Scale Models of Transportation Network Service Recovery

合作研究：交通网络服务恢复的灵活多尺度模型

• 批准号: 1361116
• 负责人: Joost Santos
• 金额: $ 21.59万
• 依托单位: George Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1361116&HistoricalAwards=false
• 关键词: Collaborative; Research; Flexible; Multi; Scale

The objective of this award is to transform emergency response planning for transportation service disruptions through the formulation and integration of hierarchical multi-scale models: (i) network optimization and expected covering models to evaluate strategies for allocating emergency responders across highway networks, and (ii) an economic interdependency model to optimize the multi-sector, multi-regional impacts of emergency response strategies on overarching productivity objectives. In the first tier of the modeling hierarchy, the PIs will formulate new transportation network optimization models to identify optimal configurations of emergency responders and dispatching protocols for resolving prioritized incidents based on utility and coverage metrics. In the second tier of the modeling hierarchy, the PIs will formulate an economic interdependency model to evaluate the efficacy of transportation network service strategies in minimizing congestion and higher-level objectives such as disruptions to workforce and commodity flows, economic loss, and sector inoperability. If successful, the results of this research will enhance the capability of transportation planners and emergency managers through flexible models for deploying emergency responders to resolve varying incident priorities, as well as expanding the optimization focus to include large-scale interdependent impacts due to disruptions in workforce and commodity flows. This research will benefit society through an integrated framework for managing transportation resources from tactical (response) to strategic (multi-sector, multi-region impact) levels. The results have the potential to inform national guidelines for managing disruptions to critical interdependent infrastructure systems. Broader dissemination to the general public will be achieved via the creation of Internet-based research blogs and videos to explain the role of optimization, probability modeling, queuing, and regional economic analysis in modeling important service enterprise and public safety applications.

该奖项的目的是通过制定和整合分层多尺度模型来改变交通服务中断的应急规划：(I)网络优化和预期覆盖模型，以评估在公路网上分配应急人员的战略，以及(Ii)经济相互依存模型，以优化应急战略对总体生产力目标的多部门、多区域影响。在建模层次的第一层，PI将制定新的交通网络优化模型，以确定紧急响应器的最佳配置和调度协议，以基于效用和覆盖指标解决优先事件。在建模层次的第二层，PIS将制定一个经济相互依存模型，以评估交通网络服务策略在最大限度地减少拥堵和更高级别目标(如对劳动力和商品流动的中断、经济损失和部门不可操作)方面的有效性。如果成功，这项研究的结果将通过灵活的模型部署应急人员来解决不同的事件优先级，并将优化重点扩大到包括因劳动力和商品流动中断而产生的大规模相互依存的影响，从而增强交通规划者和应急管理人员的能力。这项研究将通过一个综合框架，从战术(应对)到战略(多部门、多区域影响)管理运输资源，使社会受益。这一结果有可能为管理相互依存的关键基础设施系统中断的国家指导方针提供参考。通过创建基于互联网的研究博客和视频，解释优化、概率建模、排队和区域经济分析在模拟重要的服务企业和公共安全应用中的作用，将实现对普通公众的更广泛传播。