III-CXT: Spatio-temporal Graph Databases for Transportation Science

随着飓风丽塔和卡特里娜逼近墨西哥湾沿岸，最近的生命损失和长达数十英里的交通堵塞表明了疏散城市地区的困难。大规模疏散是交通科学中最困难的问题之一，因为它们违反了传统理论的关键假设，例如，自私通勤者的沃卓普均衡。在这一领域的一个关键挑战是发展的非平衡交通动力学的交通网络，以帮助设计的紧急交通管理技术的理解。这是一个艰巨的任务，由于数据密集型的性质的问题，以及当前的数据库管理系统和交通科学之间的语义差距。该项目的目标是研究新的和可扩展的数据管理概念，与新的交通科学模型和理论的发展合作，以了解紧急交通。新的协作计算机科学研究提出了探索创新的数据库概念的基础网络非平衡动力学数据和queries.Intellectual MeritThese方法的时变图和时空数据库支持流网络显着不同的传统方法在数据库文献。该项目预计将在以下领域创造创新：1）图聚合，时变图的新表示，2）流网络操作的数据库支持，例如最小切割和最大流，3）拟议的数据库概念将与领域科学家和专业人士合作设计和评估，使用大挑战问题（例如，紧急交通管理）和数据集（例如，大型城市疏散场景、人口分布和流量网络）。希望能大大提高科学家理解和管理非平衡网络行为的能力，不仅在运输科学领域，而且在许多其他重要领域，包括物流，电信网络，电网和天然气，水等的分配网络。幻灯片，软件原型），以便将研究成果纳入课程和课堂活动。该项目将扩大代表性不足群体在许多层面上的参与：一名PI有参加暑期学院的记录，该学院有来自历史上的黑人学院和大学的本科生。如果成功，其结果将有利于社会，减少疏散时间，这可能会挽救生命，并减少易受伤害人口在人为和/或自然灾害面前的风险。

ContextThe recent loss of lives, and traffic jams stretching for tens of miles as hurricanes Rita and Katrina approached the Gulf Coast demonstrate the difficulty of evacuating urban areas. Mass evacuations are among the most difficult problem areas in Transportation Science because they violate key assumptions underlying traditional theories, e.g., Wardrop equilibrium among selfish commuters. A key challenge in this domain is to develop an understanding of non-equilibrium traffic dynamics over transportation networks to aid in the design of emergency traffic management techniques. This is a formidable task due to the data-intensive nature of the problem, and the semantic gap between current database management systems and transportation science. The goal of this project is to research novel and scalable data management concepts in partnership with the development of novel transportation science models and theories to understand emergency traffic. New collaborative computer science research is proposed to probe innovative database concepts underlying network non-equilibrium dynamics data and queries.Intellectual MeritThese approaches to time-variant graphs and spatio-temporal database support for flow networks significantly differ from the traditional approaches in the database literature. Th project is expected to create innovations in the following areas: 1) graph-aggregates, a novel representation of time-varying graphs, 2) database support for flow network operations, e.g. min-cut, and max-flow, 3) the proposed database concepts will be designed and evaluated in collaboration with domain scientists and professionals using grand challenge problems (e.g., emergency traffic management) and datasets (e.g. large urban evacuation scenarios, population distributions, and flow networks). The hope is to significantly enhance scientists' ability to understand and manage non-equilibrium network behavior, not only in Transportation Science, but also in many other important domains including logistics, telecommunication networks, electric power grids, and distribution networks for gas, water, etc. Broader ImpactTeaching materials (e.g., slides, software prototypes) to facilitate incorporation of research results in courses and classroom activities will be prepared. This project will broaden the participation of underrepresented groups at many levels: one PI has a track record of participation in summer institutes involving undergraduate students from historically black colleges and universities. If successful, the results wil benefit society by reducing evacuation time, which may save lives and reduce exposure of vulnerable populations in the face of man-made and/or natural disasters.