United States Department of Transportation
i
Big data analytics to aid developing livable communities.
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2015-12-31
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[PDF-1.17 MB]
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Abstract:In transportation, ubiquitous deployment of low-cost sensors combined with powerful
computer hardware and high-speed network makes big data available. USDOT defines big
data research in transportation as a number of advanced techniques applied to the capture,
management and analysis of very large and diverse volumes of data. Data in transportation
are usually well organized into tables and are characterized by relatively low dimensionality
and yet huge numbers of records. Therefore, big data research in transportation has unique
challenges on how to effectively process huge amounts of data records and data streams.
The purpose of this study is to conduct research on the problems caused by large data
volume and data streams and to develop applications for data analysis in transportation. To
process large number of records efficiently, we have proposed to aggregate the data at
multiple resolutions and to explore the data at various resolutions to balance between
accuracy and speed. Techniques and algorithms in statistical analysis and data visualization
have been developed for efficient data analytics using multiresolution data aggregation.
Results will be helpful in setting up a primitive stage towards a rigorous framework for general
analytical processing of big data in transportation.
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