Thanks to the latest advances in information technologies, transportation professionals currently operate in an extremely data-rich environment, compared to the environment of a few decades ago. The sources of these data are varied.
- First, there is the wealth of real-time traffic data resulting from the deployment of Intelligent Transportation Systems (ITS) technologies, including data from fixed sensors, probe vehicles, weigh-in-motion (WIM) stations, Automatic Vehicle Location (AVL) systems onboard buses and other fleets, and in the future from the Connected Vehicle (CV) initiative.
- Second, there are the very useful travel-related data that may be gleaned from mining publicly available social media data such Twitter, Facebook, Foursquare, and Google+, and which could provide unique insight into traveler behavior, while offering a cost-effective alternative to the traditional methods of collecting travel behavioral data.
- Third, there are data coming from large-scale transportation field tests, experiments and studies. Chief among those studies is the recent SHRP2 Naturalistic Driving Experiment which is expected to yield in excess of 1 petabyte of data regarding risky maneuvers, lane departures, near-crashes and driver behavior right before accidents’ occurrences.
- Fourth, there are data coming from remote sensing and spatial technologies, which have numerous applications for infrastructure management, environmental impact assessment, land-use modeling, regional traffic monitoring, post-disaster assessment, and safety hazard identification.
- Last, but not least, there are freight-related data in the form of trade flows, commodity flows, modal flows, logistics and supply chains, and emergency goods needs.
The volume, variety, quality and resolution of transportation-related “Big Data” currently present the transportation community with an unprecedented opportunity for improving system performance. TransInfo’s mission will be to undertake research, education, training, and technology transfer activities aimed at realizing the full potential of “Big Data” and Transportation Informatics in: (1) improving transportation system performance; and (2) guiding investments and policies.