A Cyberinfrastructure for BigData Transportation Engineering

TL;DR

This paper introduces BoaT, a specialized programming language and infrastructure designed to simplify and accelerate Big Data-driven transportation engineering research, significantly reducing computational barriers and resource requirements.

Contribution

The paper presents BoaT, a novel transportation-specific programming language and infrastructure that makes Big Data transportation research more accessible, faster, and storage-efficient.

Findings

Research with BoaT is an order of magnitude faster.

BoaT reduces storage needs by 12-14 times.

Research complexity decreases with BoaT.

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.