descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Other literature type 09 May 2019Embargo end date: 01 Jan 2018 English Publisher:Springer Science and Business Media LLCJournal:Journal of Big Data Analytics in Transportation, volume 1, pages 83-94 (issn: 2523-3556, eissn: 2523-3564,

Authors: Md Johirul Islam; Anuj Sharma; Hridesh Rajan;

doi: 10.1007/s42421-019-00006-8 , 10.48550/arxiv.1805.00105

arXiv: http://arxiv.org/abs/1805.00105

handle: 20.500.12876/19875

A Cyberinfrastructure for Big Data Transportation Engineering

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Abstract

Big Data-driven transportation engineering has the potential to improve utilization of road infrastructure, decrease traffic fatalities, improve fuel consumption, 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 it's Big Data infrastructure that is aimed at decreasing this barrier to entry. Our evaluation that uses over two dozen research questions from six categories show that research is easier to realize as a BoaT computer program, an order of magnitude faster when this program is run, and exhibits 12-14x decrease in storage requirements.

Related Organizations

Iowa State University
United States

Keywords

Civil and Environmental Engineering, Big Data, FOS: Computer and information sciences, Databases and Information Systems, Computer Sciences, Other Computer Science (cs.OH), Domain-specific-language, Transportation Engineering, 004, Computer Science - Other Computer Science, Cyberinfrastructure

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