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’
- 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
- 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.