A Cyberinfrastructure for Big Data Transportation Engineering
Big data-driven transportation engineering has the potential to improve utilization of road infrastructure, decrease traffic fatalities, improve fuel consumption, and decrease construction worker injuries, among others. Despite these benefits, research on big data-driven transportation engineering is difficult today due to the computational expertise required to get started. This work proposes BoaT, a transportation-specific programming language, and its big data infrastructure that is aimed at decreasing this barrier to entry. The evaluation, that uses over two dozen research questions from six categories, shows that research is easier to realize as a BoaT computer program, an order of magnitude faster when this program is run, and exhibits 12–14× decrease in storage requirements.
- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/25233556
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Supplemental Notes:
- © Springer Nature Singapore Pte Ltd. 2019.
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Authors:
- Islam, Md
- 0000-0003-0034-9395
- Sharma, Anuj
- Rajan, Hridesh
- Publication Date: 2019-6
Language
- English
Media Info
- Media Type: Web
- Pagination: pp 83-94
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Serial:
- Journal of Big Data Analytics in Transportation
- Volume: 1
- Issue Number: 1
- Publisher: Springer Publishing
- ISSN: 2523-3556
- EISSN: 2523-3564
- Serial URL: https://link.springer.com/journal/42421
Subject/Index Terms
- TRT Terms: Computer programming languages; Data analysis; Highway safety; Infrastructure; Planning; Software packages; Transportation engineering
- Identifier Terms: BoaT (computer software)
- Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Safety and Human Factors;
Filing Info
- Accession Number: 01708264
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 24 2019 10:11AM