CRISP Type 2/Collaborative Research: Coordinated, Behaviorally-Aware Recovery for Transportation and Power Disruptions (CBAR-tpd)

CRISP 类型 2/合作研究：针对交通和电力中断的协调、行为感知恢复 (CBAR-tpd)

• 批准号: 1638207
• 负责人: Pamela Murray-Tuite
• 金额: $ 87.69万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638207&HistoricalAwards=false
• 关键词: CRISP; Type; Collaborative; Research; Coordinated

This project will develop an approach for coordinated restoration of infrastructure services following disruptive events in interdependent power and transportation systems. This approach accommodates behavior adaptation in the recovery of physical aspects of infrastructure. This adaptation is not well understood or integrated with current restoration plans. By better understanding adaptive behaviors and their dependence on different infrastructures and coordinating recovery across these infrastructures, such a framework can help households return to productive activities faster. For instance, if employees cannot commute, they may work remotely if power is available. This approach to infrastructure restoration has the potential to substantially improve the efficiency of post-disaster return to productive daily life. If infrastructure recovery is coordinated and focuses on actual needs, restoration also may be more cost effective. To help realize these benefits, the project's team of civil engineers, social scientists, and computer scientists will convey research results through practitioner-oriented seminars held with FEMA, state emergency management agencies, transportation authorities, and electric power utilities. The multi-disciplinary approach and outreach activities developed for Virginia Tech's Center for the Enhancement of Engineering Diversity and the University of Michigan's Detroit-Area Pre-College Engineering Program will help broaden the research participation of underrepresented groups and attract new students to the respective fields. Technically, the project's objectives include: developing improved methods for collecting, analyzing, and archiving tweets and webpages - integrated with data collected from official or specialized sources - in support of understanding the interplay of behavior and power and transportation infrastructures in disruptions; collecting novel data with activity diaries that incorporate adaptation and use of technologies; determining how the nature of information about infrastructure disruptions and the way in which individuals process this information shape responses to disruptions and preferred tradeoffs; identifying how these behavior adaptations induce or magnify substitutive interdependencies between transportation and power systems; and developing recovery strategies that coordinate among the infrastructures and account for adaptation. To achieve these objectives, the study will use social media, official utility and transport information, and activity panel surveys to develop behavioral and infrastructure outage models that feed a coordinated, behaviorally-aware power and transport recovery model using optimization and agent based modeling. The project team's approach specifically examines the adaptation of individuals who pursue alternate means to accomplish an activity goal and the interdependence between power and transportation infrastructure that results from this adaptation during disruptions. This approach is applied to a case study in a metropolitan area.

该项目将在相互依存的电力和运输系统中的破坏性事件后，开发一种协调基础设施服务的方法。这种方法可适应基础设施的物理方面的恢复。这种适应尚未充分理解或与当前的恢复计划融合。通过更好地理解适应性行为及其对不同基础设施的依赖并协调这些基础设施的恢复，这种框架可以帮助家庭更快地恢复生产活动。例如，如果员工无法通勤，则如果有电源，他们可能会远程工作。这种基础设施恢复方法有可能大大提高灾后恢复生产力的日常生活效率。如果基础设施恢复是协调的，并且专注于实际需求，那么恢复也可能更具成本效益。为了帮助实现这些好处，该项目的土木工程师，社会科学家和计算机科学家团队将通过与FEMA，州紧急管理机构，运输当局和电力公用事业公司举行的以从业人员为导向的研讨会一起传达研究结果。 为弗吉尼亚理工大学增强工程多样性和密歇根大学的底特律地区大学前工程工程计划开发的多学科方法和外展活动将有助于扩大代表性不足的群体的研究参与，并吸引新学生进入各自领域。 从技术上讲，项目的目标包括：开发用于收集，分析和归档推文和网页的改进方法（与从官方或专业来源收集的数据集成在一起），以支持理解中断行为，权力以及权力和运输基础设施的相互作用；通过活动日记收集新的数据，并结合了技术的适应和使用；确定有关基础设施中断的信息的性质以及个人处理此信息对中断和首选权衡的响应方式的方式；确定这些行为适应如何诱导或放大运输和动力系统之间的替代相互依赖性；并制定恢复策略，以协调基础设施并解释适应性。为了实现这些目标，该研究将使用社交媒体，官方公用事业和运输信息以及活动面板调查来开发行为和基础设施中断模型，以使用基于优化和基于代理的建模为协调的，行为意识的权力和运输恢复模型。项目团队的方法专门研究了采用替代手段的个人的适应，以实现活动目标以及权力和运输基础设施之间的相互依赖性，这些基础设施是由于这种调整过程中这种适应而产生的。这种方法应用于大都市地区的案例研究。

项目成果

US State Tourism Websites

美国各州旅游网站

• 发表时间: 2020
• 期刊: and Information Access
• 作者: Shere, Danya;Ayub, Ahmad;Mueller, Rebecca;Fabian, Lexi;Shah, Akshat;Fox, Edward A.
• 通讯作者: Fox, Edward A.

Twitter-Based Knowledge Graph for Researchers

为研究人员提供基于 Twitter 的知识图谱

• 发表时间: 2020
• 期刊: Virginia tech
• 作者: Vincent, Kyle;Meno, Emma
• 通讯作者: Meno, Emma

Integration and Implementation (INT) CS 5604 F2020

集成和实施 (INT) CS 5604 F2020

• 发表时间: 2020
• 期刊: Information storage and retrieval
• 作者: Hicks, Alexander;Thazhath, Mohit;Gupta, Suraj;Long, Xingyu;Poland, Cherie;Hsieh, Hsinhan;Mahajan, Yash;Chandrasekar, Prashant;Fox, Edward A.
• 通讯作者: Fox, Edward A.

Hurricane Irma: Multiple Avenues of Study.

飓风艾尔玛：多种研究途径。

• 发表时间: 2020
• 期刊: Proceedings of the International ISCRAM Conference
• 作者: Chandrasekar, Prashant;Wernstedt, Kris;Fox, Edward A.;Murray-Tuite, Pamela
• 通讯作者: Murray-Tuite, Pamela

CS 5604 2020: Information Storage and Retrieval TWT - Tweet Collection Management Team

CS 5604 2020：信息存储和检索 TWT - 推文收集管理团队

• 发表时间: 2020
• 期刊: Information storage and retrieval
• 作者: Baadkar, Hitesh;Chimote, Pranav;Hicks, Megan;Juneja, Ikjot;Kusuma, Manisha;Mehta, Ujjval;Patil, Akash;Sharma, Irith;Wang, Xinyue;Fox, Edward A.
• 通讯作者: Fox, Edward A.