United States Department of Transportation
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Interactive Web-Based Platform for Analyzing Freight Data-Phase I
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2020-10-01
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[PDF-1.85 MB]
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Edition:Final Report
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Abstract:An exponential growth in relevant data streams has brought new opportunities and challenges in the realm of data warehousing. Increased data enables improved planning, monitoring, prediction, and management of transportation systems, but only if the manipulation of such gigantic datasets could be efficiently automated. With the increasing demand for modern data warehousing, there has been a significant growth in commercial and open-source tools. The current research seeks to develop a user-friendly, interactive, web-based prototype platform that takes advantage of recent advances in spatial data analysis, big data and user-centered visualization to integrate freight data across different private and public databases for the purpose of improving freight planning activities and data driven decision making. The methodology includes a spatio-temporal conflation framework that enables seamless integration of three key freight data sources including: weigh-in-motion (WIM), freight facility, and traffic flow data. A massively parallel database is subsequently designed to store the integrated data on a cluster of servers enabled with Graphical Processing Units (GPUs). The authors leverage the immense computational power of the GPUs to carry out analytics and visual rendering on-the-fly via a Structured Query Language (SQL) which interacts with the underlying database. A web interface is designed for near-instant rendering of queries on simple charts and maps to enable decision makers to drill down insights quickly. The framework is capable of powering big freight performance data applications with over 100 million rows. Performance benchmarking experiments conducted showed that the framework developed is able to provide real time visual updates for big datasets in less than 100 milliseconds.
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