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

最近，飓风丽塔和卡特里娜逼近墨西哥湾沿岸，造成数十英里的人员伤亡和交通堵塞，这表明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领域之一，因为它违反了传统理论的关键假设，例如自私的通勤者之间的Wardrop均衡。该领域的一个关键挑战是发展对交通网络非平衡交通动态的理解，以帮助设计应急交通管理技术。这是一项艰巨的任务，因为这个问题的数据密集型性质，以及当前数据库管理系统与交通科学之间的语义差距。该项目的目标是研究新颖和可扩展的数据管理概念，并与发展新的交通科学模型和理论合作，以了解紧急交通。提出了新的协同计算机科学研究，以探索网络非平衡动态数据和查询的创新数据库概念。这些时变图和时空数据库支持流网络的方法与数据库文献中的传统方法有很大不同。该项目预计将在以下领域进行创新：1)图形聚合，时变图形的新颖表示；2)流量网络操作的数据库支持，例如最小切和最大流量；3)拟议的数据库概念将与领域科学家和专业人员合作，使用重大挑战问题（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）进行设计和评估。希望能够显著提高科学家理解和管理非平衡网络行为的能力，不仅在交通科学领域，而且在许多其他重要领域，包括物流、电信网络、电网和燃气、水的分配网络等。更广泛的影响将准备教材（如幻灯片、软件原型），以便将研究成果纳入课程和课堂活动。该项目将在许多层面上扩大代表性不足群体的参与：一名PI有参与暑期学院的记录，该学院有来自传统黑人学院和大学的本科生。如果成功，其结果将通过缩短疏散时间而造福社会，这可能挽救生命并减少弱势群体在面对人为和/或自然灾害时的暴露。

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.