SI2-SSE: Collaborative Research: TrajAnalytics: A Cloud-Based Visual Analytics Software System to Advance Transportation Studies Using Emerging Urban Trajectory Data

SI2-SSE：合作研究：TrajAnalytics：基于云的视觉分析软件系统，利用新兴城市轨迹数据推进交通研究

• 批准号: 1535081
• 负责人: Jing Yang
• 金额: $ 20.1万
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1535081&HistoricalAwards=false
• 关键词: SI2; SSE; Collaborative; Research; TrajAnalytics

Advanced technologies in sensing and computing have created urban trajectory datasets of humans and vehicles travelling over urban networks. Understanding and analyzing the large-scale, complex data reflecting city dynamics is of great importance to enhance both human lives and urban environments. Domain practitioners, researchers, and decision-makers need to manage, query and visualize such big and dynamics data to conduct both exploratory and analytical tasks. To support these tasks, this project develops a open source software tool, named TrajAnalytics, which integrates computational techniques of scalable trajectory database, intuitive and interactive visualization, and high-end computers, to explicitly facilitate interactive data analytics of the emerging trajectory data.The software provides a new platform for researchers in transportation assessment and planning to directly study moving populations in urban spaces. Researchers in social, economic and behavior sciences can use the software to understand the complicated mechanisms of urban security, economic activities, behavior trends, and so on. Specifically, this software advances the research activities in the community of transportation studies. The software also acts as an outreach platform allowing government agencies to communicate more effectively with the public with the real-world dynamics of city traffic, vehicles, and networks. The integration of research and education prepares the next generation workforce, where students across multi-disciplines can benefit through their participation in the development and use of the software.In order to lay the foundations for effective analysis of urban trajectory datasets, this software (1) facilitates easy access and unprecedented capability for researchers and analysts with a cloud-based storage and computing infrastructure; (2) develops a parallel graph based data model, named TrajGraph, where massive trajectories are managed on a large-scale graph created from urban networks which is naturally amenable for studying urban dynamics; and (3) provides a visualization interface, named TrajVis, which supports interactive visual analytics tasks with a set of visualization tools and interaction functions. A variety of transportation-related researchers from geography, civil engineering, computer science participate in the design, evaluation, and use of the software. This robust and easy-to-use software enables the users to conduct iterative, evolving information foraging and sense making.

传感和计算方面的先进技术创建了人类的城市轨迹数据集，并在城市网络上传播的车辆。理解和分析反映城市动态的大规模，复杂的数据对于增强人类生活和城市环境至关重要。领域从业人员，研究人员和决策者需要管理，查询和可视化如此大的动态数据，以执行探索性和分析任务。为了支持这些任务，该项目开发了一种名为Trajanalytics的开源软件工具，该工具集成了可扩展轨迹数据库，直观和交互式可视化以及高端计算机的计算技术，以明确促进互动数据分析，以促进新兴轨迹数据的交互性数据分析。软件为研究人员提供了一个新的平台，可以在运输评估和计划方面进行研究，并在整个培养过程中进行了研究。社会，经济和行为科学领域的研究人员可以使用该软件来了解城市安全，经济活动，行为趋势等复杂机制。具体而言，该软件在运输研究社区中推进了研究活动。该软件还充当外展平台，允许政府机构与城市交通，车辆和网络的现实世界动态更有效地与公众进行沟通。研究和教育的整合为下一代劳动力做准备，跨学科的学生可以通过参与和使用该软件来受益。为了为有效分析城市轨迹数据集的基础，该软件（1）促进了易于访问的访问和云基于云基于基于云的基于云的基于基于云的基于云的储存和分析的能力。 （2）开发了一个基于平行图的数据模型，称为Trajgraph，其中在城市网络创建的大规模图上进行了大规模的轨迹，该图自然是可以研究城市动态的； （3）提供了一个名为Trajvis的可视化接口，该接口使用一组可视化工具和交互功能支持交互式可视化分析任务。来自地理，土木工程，计算机科学的各种与运输相关的研究人员参与了该软件的设计，评估和使用。这种强大且易于使用的软件使用户能够进行迭代，不断发展的信息觅食和感知。