Collaborative Research: RIPS Type 1: Human Geography Motifs to Evaluate Infrastructure Resilience

合作研究：RIPS 类型 1：评估基础设施弹性的人文地理学主题

• 批准号: 1664275
• 负责人: Paul Torrens
• 金额: $ 11.38万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-30 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1664275&HistoricalAwards=false
• 关键词: Collaborative; Research; RIPS; Type; Human

This project will examine how shifting motifs in the everyday rhythms and tempo of people form, interdependently, with mobile transport and communications infrastructure. The resilience between dynamics of human and engineered systems is often challenged by small wrinkles in the motifs of human geography that may shift the timing and geography of populations and infrastructure off-normal. For example, delayed starts to the workday because of winter weather can bump peak commuting off-rhythm, delay the logistics of citywide delivery systems, or produce bursts in communications activity. While these may form as small local shifts from normal in particular places and times, they can transfer, diffuse, and adapt with unforeseen consequences and serious impacts on broader phenomena as diverse as commuting, the labor market, logistics, and urban management. Understanding how these dynamics arise, form, and spread through increasingly connected systems, as well as measuring and modeling them is critical if we are to plan for them, mitigate them, and manage them. Building this understanding requires an interdisciplinary approach that bridges engineering, informatics and computing, and the socio-behavioral sciences: a multipronged challenge that is indicative of the problems that a next-generation of students and engineers will face in designing, constructing, maintaining, and managing urban systems that are increasingly intertwined with, dependent upon, and adapting to the shifting and ever-evolving patterns of our activities. Similarly, getting the right data, metrics, and models to diverse groups of urban managers, engineers, and the public-at-large in ways that can usefully inform their understanding of interdependency will be critical in fashioning systems that can better weather such challenges. A starting point in investigating these connections is to explore conventional sources of data on human geography, but to also develop extensible systems that can use newly-forming data from location-aware technologies that produce rapid snapshots of whole populations in the messy context and complexity of everyday urban life. Novel analyses on these data can produce dynamically-evolving atlases and censuses of interdependency, from which motifs of behavior can be extracted and resolved, as land-use, activity, mobility, and sociality. These motifs can inform computer models designed to explore what-if dynamics between people, place, process, and infrastructure, that better frame and describe interdependency in activity, movement, access, and information. To assist in translating this research into the public domain, the project will formalize several outputs: a set of reusable data and model outputs accessible via a community Web portal, a pilot demonstration for winter weather scenarios in Washington DC that will fully explore scenarios of interdependency between human geography and mobile transport and communications infrastructure, and a set of code libraries for use in allied model systems. Through application to substantive issues of relevance in geography, informatics, and engineering, these outputs will enable other communities to apply and adapt these methods to their cities, data, and infrastructure.

该项目将研究人们的日常节奏和节奏中的变化主题如何与移动交通和通信基础设施相互依存地形成。人类与工程系统动态之间的弹性经常受到人文地理学主题中的小皱纹的挑战，这些小皱纹可能会使人口和基础设施的时间和地理发生异常。例如，由于冬季天气而延迟上班可能会打乱高峰通勤节奏，延迟全市配送系统的物流，或导致通信活动爆发。虽然这些可能在特定地点和时间形成为与正常情况相比的微小局部变化，但它们可以转移、扩散和适应，从而产生不可预见的后果，并对通勤、劳动力市场、物流和城市管理等更广泛的现象产生严重影响。如果我们要规划、缓解和管理这些动态，那么了解这些动态如何在日益互联的系统中产生、形成和传播，并对它们进行测量和建模至关重要。建立这种理解需要一种跨学科的方法，将工程、信息学和计算以及社会行为科学联系起来：这是一个多管齐下的挑战，它表明了下一代学生和工程师在设计、建造、维护和维护过程中将面临的问题。管理与我们活动的不断变化和不断发展的模式日益交织、依赖和适应的城市系统。同样，为不同的城市管理者、工程师和广大公众群体提供正确的数据、指标和模型，以帮助他们理解相互依存关系，对于构建能够更好地应对此类挑战的系统至关重要。研究这些联系的起点是探索人文地理学的传统数据源，同时开发可扩展的系统，该系统可以使用来自位置感知技术的新形成的数据，这些技术可以在混乱的环境和复杂的环境中快速生成整个人口的快照。日常城市生活。对这些数据的新颖分析可以产生动态发展的相互依赖地图集和普查，从中可以提取和解决行为主题，如土地利用、活动、流动性和社会性。这些主题可以为旨在探索人、地点、流程和基础设施之间的假设动态的计算机模型提供信息，从而更好地构建和描述活动、运动、访问和信息的相互依赖性。为了帮助将这项研究转化为公共领域，该项目将正式确定几个输出：一组可通过社区门户网站访问的可重复使用的数据和模型输出、华盛顿特区冬季天气场景的试点演示，该演示将充分探索相互依赖的场景人文地理与移动运输和通信基础设施之间的关系，以及一组用于联合模型系统的代码库。通过应用于地理、信息学和工程相关的实质性问题，这些成果将使其他社区能够将这些方法应用和调整到他们的城市、数据和基础设施中。