DRIVE Net: An E-Science of Transportation Platform for Data

Over the past decades, transportation research has been mathematical-equation driven or relied on scarce data. Data-driven or data-based research is expected to expand in the near future with the increasing data collected from intelligent transportation system sensors. So far, most online systems are designed for handling one type of data, such as freeway or arterial sensor data. Even if transportation data are ubiquitous, data usability is difficult to improve. This study proposes a framework for region-wide web-based transportation decision system which adopts digital roadway maps as the base and provides data layers for integrating multiple data sources, including traffic sensor data, incident data, accident data, travel time data, etc. The system is named the Digital Roadway Interactive Visualization and Evaluation Network (DRIVE Net). DRIVE Net provides a practical solution to facilitate data retrieval and integration, and enhances data usability. Moreover, DRIVE Net offers a platform for optimizing transportation decisions that also serves as an ideal tool for visualizing historical observations both spatially and temporally. DRIVE Net can be used not only as a practical tool for various transportation analyses but also to help evaluate the benefit of a specific transportation solution using its onlin