DRIVE Net的新进展:一个用于数据共享、可视化、建模和分析的电子科学交通平台

Zhiyong Cui, Shen Zhang, Kristian C. Henrickson, Yinhai Wang
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引用次数: 10

摘要

大数据代表了数据探索和利用的新时代。随着从智能交通系统和其他传感器收集的数据数量和种类的不断增加,数据驱动的交通研究将依赖于新一代工具来分析和可视化这些数据。为了满足这一需求,开发了数字道路交互式可视化和评估网络(DRIVE Net),以实现大规模的在线数据共享、可视化、建模和分析。通过整合来自不同传感和采集技术的越来越多的数据集,新的DRIVE Net系统提供了一个更稳定、更强大的交互式平台,现在能够处理更复杂的计算任务,可视化大规模空间数据,并支持数据共享服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New progress of DRIVE Net: An E-science transportation platform for data sharing, visualization, modeling, and analysis
Big data represents a new era in data exploration and utilization. With the growing quantity and variety of data being collected from intelligent transportation systems and other sensors, data-driven transportation research will rely on a new generation of tools to analyze and visualize those data. To address this need, the Digital Roadway Interactive Visualization and Evaluation Network (DRIVE Net) was developed to enable large-scale online data sharing, visualization, modeling and analysis. By incorporating an increasing variety of data sets from different sensing and acquisition technologies, the new DRIVE Net system provides a more stable, powerful, and interactive platform, and is now able to handle more complex computational tasks, visualize large-scale spatial data, and support data sharing services.
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